RVol LabelThis Code is update version of Code Provided by @ssbukam, Here is Link to his original Code and review the Description
Below is Original Description
1. When chart resolution is Daily or Intraday (D, 4H, 1H, 5min, etc), Relative Volume shows value based on DAILY. RVol is measured on daily basis to compare past N number of days.
2. When resolution is changed to Weekly or Monthly, then Relative Volume shows corresponding value. i.e. Weekly shows weekly relative volume of this week compared to past 'N' weeks. Likewise for Monthly. You would see change in label name. Like, Weekly chart shows W_RVol (Weekly Relative Volume). Likewise, Daily & Intraday shows D_RVol. Monthly shows M_RVol (Monthly Relative Volume).
3. Added a plot (by default hidden) for this specific reason: When you move the cursor to focus specific candle, then Indicator Value displays relative volume of that specific candle. This applies to Intraday as well. So if you're in 1HR chart and move the cursor to a specific candle, Indicator Value shows relative volume for that specific candlestick bar.
4. Updating the script so that text size and location can be customized.
Changes to Updated Label by me
1. Added Today's Volume to the Label
2. Added Total Average Volume to the Label
3. Comparison vs Both in Single Line and showing how much volume has traded vs the average volume for that time of the day
4. Aesthetic Look of the Label
How to Use Relative Volume for Trading
Using Relative Volume (RVol) in trading can be a valuable tool to help you identify potential trading opportunities and gain insight into market behavior. Here are some ways to use RVol in your trading strategy:
Identifying High-Volume Breakouts: RVol can help you spot potential breakouts when the volume surges significantly above its average. High RVol during a breakout suggests strong market interest, increasing the probability of a sustained move in the direction of the breakout.
Confirming Trends and Reversals: RVol can act as a confirmation tool for trends and reversals. A trend accompanied by rising RVol indicates a strong and sustainable move. Conversely, a trend with declining RVol might suggest a weakening trend or potential reversal.
Spotting Volume Divergence: When the price is moving in one direction, but RVol is declining or not confirming the move, it may indicate a divergence. This discrepancy could suggest a potential reversal or trend change.
Support and Resistance Confirmation: High RVol near key support or resistance levels can indicate potential price reactions at those levels. This confirmation can be valuable in determining whether a level is likely to hold or break.
Filtering Trade Signals: Incorporate RVol into your existing trading strategy as a filter. For example, you might consider taking trades only if RVol is above a certain threshold, ensuring that you focus on high-impact trading opportunities.
Avoiding Low-Volume Traps: Low RVol can indicate a lack of interest or participation in the market. In such situations, price movements may be erratic and less reliable, so it's often wise to avoid trading during low RVol periods.
Monitoring News Events: Around significant news events or earnings releases, RVol can help you gauge the market's reaction to the information. High RVol during such events can present trading opportunities but be cautious of increased volatility and potential gaps.
Adjusting Trade Size: During periods of extremely high RVol, it might be prudent to adjust your position size to account for higher risk.
Using Relative Volume in Morning Session
If the Volume traded in first 15 minute to 30 Minutes is already at 50% or 100% depending upon the ticker, it means that it is going to have very high Volume vs average by end of the day.
This gives me conviction for Long or Short Trades
Remember that RVol is not a standalone indicator; it works best when used in conjunction with other technical and fundamental analysis tools. Additionally, RVol's effectiveness may vary across different markets and trading strategies. Therefore, backtesting and validating the use of RVol in your trading approach is essential.
Lastly, risk management is crucial in trading. While RVol can provide valuable insights, it cannot guarantee profitable trades. Always use appropriate risk management strategies, such as setting stop-loss levels, and avoid overexposing yourself to the market based solely on RVol readings.
Komut dosyalarını "break" için ara
Volume Orderbook (Expo)█ Overview
The Volume Orderbook indicator is a volume analysis tool that visually resembles an order book. It's used for displaying trading volume data in a way that may be easier to interpret or more intuitive for certain traders, especially those familiar with order book analysis.
This indicator aggregate and display the total trading volume at different price levels over the entire range of data available on the chart, similar to how an order book displays current buy and sell orders at different price levels. However, unlike a real-time order book, it only considers historical trading data, not current bid and ask orders. This provides a 'historical order book' of sorts, indicating where most trading activities have taken place.
Summary
This is a volume-based indicator that shows the volume traded at specific price levels, highlighting areas of high and low activity.
█ Calculations
The algorithm operates by calculating the cumulative volume traded in each specific price zone within the range of data displayed on the chart. The length of each horizontal bar corresponds to the total volume of trades that occurred within that particular price zone.
In essence, when the price is in a specific zone, the volume is added to the bar representing that zone. A thicker bar implies a larger price zone, meaning that more volume is accumulated within that bar. Therefore, the thickness of the bar visually indicates the amount of trading activity that took place within the associated price zone.
█ How to use
The Volume Orderbook indicator serves as a beneficial tool for traders by identifying key price levels with a significant amount of trading activity. These high-volume areas could represent potential support or resistance levels due to the large number of orders situated there. The indicator's ability to spotlight these zones might be particularly advantageous in pinpointing breakouts or breakdowns when prices move beyond these high-volume regions. Moreover, the indicator could also assist traders in recognizing anomalies, such as when an unusually large volume of trades occurs at unconventional price levels.
Identify Key Price Levels: The indicator highlights high-volume areas where a significant number of trades have occurred, which could act as potential support or resistance levels. This is based on the notion that many traders have established positions at these prices, so these levels may serve as significant areas for market activity in the future.
Volume Nodes: These are the peaks (high-volume areas) and troughs (low-volume areas) seen on the indicator. High-volume nodes represent price levels at which a large amount of volume has been traded, typically areas of strong support or resistance. Conversely, low-volume nodes, where very little volume has been traded, indicate price levels that traders have shown little interest in the past and could potentially act as barriers to price. It's important to note that while high trading volume can imply significant market interest, it doesn't always mean the price will stop or reverse at these levels. Sometimes, prices can quickly move through high-volume areas if there are no current orders (demand) to match with the new orders (supply).
Analyze Market Psychology: The distribution of volume across different price levels can provide insights into the market's psychology, revealing the balance of power between buyers and sellers.
Highlight Potential Reversal Points: The indicator can help identify price levels with high traded volume where the market might be more likely to reverse since these levels have previously attracted significant interest from traders.
Validate Breakouts or Breakdowns: If the price moves convincingly past a high-volume node, it could indicate a strong trend, suggesting a potential breakout or breakdown. Conversely, if the price struggles to move past a high-volume node, it could suggest that the trend is weak and might potentially reverse.
Trade Reversals: High-volume areas could also indicate potential turning points in the market. If the price reaches these levels and then starts to move away, it might suggest a possible price reversal.
Confirm Other Signals: As with all technical indicators, the "Volume Orderbook" should ideally be used in conjunction with other forms of technical and fundamental analysis to confirm signals and increase the odds of successful trades.
Summary
The Volume Orderbook indicator allows traders to identify key price levels, analyze market psychology, highlight potential reversal points, validate breakouts or breakdowns, confirm other trading signals, and anticipate possible trade reversals, thereby serving as a robust tool for trading analysis.
█ Settings
Source: The user can select the source, the default of which is "close." This implies that volume is added to the volume order book when the closing price falls within a specific zone. Users can modify this to any indicator present on their chart. For example, if it's set to an SMA (Simple Moving Average) of 20, the volume will be added to the volume order book when the SMA 20 falls within the specific zone.
Rows and width: These settings allow users to adjust the representation of volume order book zones. "ROWS" pertains to the number of volume order book zones displayed, while "WIDTH" refers to the breadth of each zone.
Table and Grid: These settings allow traders to customize the Volume order-book's position and appearance. By adjusting the "left" parameter, users can shift the position of the Volume order book on the chart; a higher value pushes the order book further to the right. Additionally, users can enable "Table Border" and "Table Grid" options to add gridlines or borders to the Volume order book for easier viewing and interpretation.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Scalp Tool
This script is primarily intended as a scalping tool.
The theory of the tool is based on the fact that the price always returns to its mean.
Elements used:
1. VWMA as a moving average. VWMA is calculated once based on source close and once based on source open.
2. the bands are not calculated like the Bollinger Band, but only a settlement is calculated for the lower bands based on the Lows and for the upper bands based on the Highs. Thus the bands do not become thicker or thinner, but remain in the same measure to the mean value above or below the price.
3. a volume filter on simple calculation of a MA with deviation. Therefore, it can be identified if a volume breakout has occurred.
4. support and resistance zones which are calculated based on the highs and lows over a certain length.
5. RSI to determine oversold and overbought zones. It also tries to capture the momentum by using a moving average (variable selectable) to filter the signals. The theory is that in an uptrend the RSI does not go below 50 and in a downtrend it does not go above 50.
However, this can be very different depending on the financial instrument.
Explanation of the signals:
The main signal in this indicator Serves for pure short-term trading and is generated purely on the basis of the bands and the RSI.
Only the first bands are taken into account.
Buy signal is generated when the price opens below the lower band 1 and closes above the lower band 1 or the RSI crosses a value of 25 from bottom to top.
Sell signal is generated when the price opens above the Upper Band 1 and closes below the Upper Band 1 or the RSI crosses a value of 75 from top to bottom.
The position should be closed when the price hits the opposite band. Alternatively, it can also be closed at the mean.
Other side signals:
1. breakouts:
The indicator includes 2 support and resistance zones, which differ only in length. For the breakout signals, the short version of the R/S is used. A signal is generated when the price breaks through the zones with increased volume. It is then assumed that the price will continue to follow the breakout.
The values of the S/R are adjustable and marked with "BK".
The value under Threshold 2 defines the volume breakout. 4 is considered as the highest value. The smaller the value, the smaller the volume must be during a breakout.
2. bounce
If the price hits a S/R (here the long variant is used with the designation "Support" or "Resistance") and makes a wick with small volume, the script assumes a bounce and generates a Sell or Buy signal accordingly.
The volume can be defined under "Threshold".
The S/R according to the designation as well.
Combined signals:
If the value of the S/R BK and the S/R is the same and the bounce logic of the S/R BK applies and an RSI signal is also generated, a signal is also plotted.
Here the idea was to get very strong signals for possible swing entries.
4. RSI Signals
The script contains two RSI.
RSI 1:
Bullish signal is generated when the set value is crossed from the bottom to the top.
Bearish signal is generated when the set value is crossed from the top to the bottom.
RSI 2:
Bullish signal is generated when the set value is crossed from the top to the bottom.
Bearish signal is generated when the set value is crossed from bottom to top.
For RSI 2 the theory is taken into account according to the description under Used elements point 5
Optical trend filter:
Also an optical trend filter was generated which fills the bands accordingly.
For this the VWMA is used and the two average values of the band.
Color definition:
Gray = Neutral
Red = Bearish
Green = Bullish
If the mean value is above the VWMA and the mean value based on the closing price is above the mean value based on the open price, the band is colored green. It is a bullish trend
If the mean value is below the VWMA and the mean value based on the closing price is below the mean value based on the open price, the band is colored red.
The band is colored gray if the mean value is correspondingly opposite. A sideways phase is assumed.
The script was developed on the basis of the pair BTCUSD in the 15 minute chart and the settings were defined accordingly on it. The display of S/R for forex pairs does not work correctly and should be hidden. The logic works anyway.
When using the script, all options should first be set accordingly to the asset and tested before trading afterwards. It applies of course also here that there is no 100% guarantee.
Also, a strong breakout leads to false signals and overheating of the indicator.
Trading BehnamI've read around here various definitions for engulfs along the lines of "an engulf consumes all orders at a level to allow price to easily pass through it." . That doesn't make much sense to me, if the guys with billions of dollars want to break a level, they will break it and price will run off very often. We've seen it time and time again, they don't need to engulf levels to give us a nice opportunity to get into the trade with them, if they want to blast through a level, they will do so and price will run off. If they want an opportunity to accumulate more orders before price runs away, then it doesn't make sense to engulf the level, better to let price bounce from that level and then fill more orders, if the level breaks then they have to deliberately stop the market running away and move it back to the pre-engulf area as the market momentum would naturally make it run off after an engulf. Other ideas about it being a secret signal between the institutions don't make sense to me either. To be honest, I think any secret signals between competing institutions come in the form of them in a heavily encrypted chatroom telling each other what to do. This collusion has been reported on previously as traders align their activities at important moments.
So I think we can all agree something along the lines of:
Fakeout:
Fakeout is an engulf of an obvious swing high/low in order to stop out traders and induce breakout traders to trade in the wrong direction, thus generating liquidity for the move in the opposite direction.
What's not so clear is the definition of the engulf, I'd like to try to give some ideas on the purpose of the engulf and it's definition and see what others think.
Engulf:
An engulf is the consumption of orders at an important level, not necessarily a swing/high low but an area where we expect to see supply or demand. Taking out of the orders tells us that the supply or demand which was or should have been present is now not present and tells us the intent direction of the market. If price runs off as is often the case, this is not tradeable and is effectively just a "breakout", although breakouts are usually considered to be breaks of swing high and lows which are obvious to the average trader. For an engulf to be tradeable there must be a retrace following the engulf back in the original direction. This adds confusion as it initially resembles a fakeout. So the question is, why does price retrace after the engulf? If an engulf to the short side is a genuine engulf and not a fakeout to generate long liquidity, why does it not travel immediately south if market momentum is ultimately south.
A small pocket of demand beneath the engulfed level may make it retrace north as price moves between areas of liquidity, this pocket of demand may give price enough momentum to make it back up to the supply which broke the demand level if key market participants do not favour an immediate market drop.
Alternatively key market participants may step in and drive the market back upwards.
Price moving north back to supply after the engulf may occur or be favourable for various reasons:
1) We often talk about FO generating liquidity because of breakout trading, but an engulf can also generate liquidity from breakout traders. Short breakout traders would place their stop losses a small distance above the engulf (breakout). If key players absorb this selling or allow a demand level to push price back up, they can run price back up to supply taking out the stops of the breakout short traders and make quick profit and/or generate more liquidity for their own shorts.
2) To confuse traders, the ITs don't want the puzzle that is Forex to be easy to solve, if price never retraced after an engulf then engulfs of all levels would be FOs. Price would either break and immediately runoff or it would turn and runoff in the other direction. In order to keep people confused about whether price is faking out or breaking out, sometimes price should whipsaw by breaking out, briefly faking out and then continuing in the direction of the breakout. This whipsaw pattern is to us a tradeable engulf.
3) Market momentum may be mixed, key players are indecisive or inactive or the market is behaving erratically.
4) As previously mentioned there may be a small pocket of supply/demand just past the engulf which is causing a reaction. This could also be viewed as a FO on a different timeframe. If the market engulfs an H1 demand level, then retraces for 30 mins upwards to supply, this engulf would be a valid and very profitable FO for an M1 trader looking to get long.
Smart Volatility Squeeze + Trend Filter📌 Purpose
This indicator detects volatility squeeze conditions when Bollinger Bands contract inside Keltner Channels and signals potential breakout opportunities.
It also includes an optional EMA-based trend filter to align signals with the dominant market direction.
🧠 How It Works
1. Squeeze Condition
Bollinger Bands (BB): Length = 20, StdDev = 2.0 (default)
Keltner Channels (KC): EMA Length = 20, ATR Multiplier = 1.5 (default)
Squeeze ON: Occurs when BB Upper < KC Upper and BB Lower > KC Lower (low volatility zone).
2. Breakout Signals
Long Breakout: Price crosses above BB Upper after squeeze.
Short Breakout: Price crosses below BB Lower after squeeze.
3. Trend Filter (optional)
EMA(50) used to confirm breakout direction:
Long signals allowed only if price > EMA(50)
Short signals allowed only if price < EMA(50)
Toggle Use Trend Filter to enable/disable.
4. Visual & Alerts
Green circle at chart bottom indicates Squeeze ON.
Green/Red triangles mark breakouts.
Background gradually brightens during squeeze buildup.
Alerts available for long and short breakouts.
📈 How to Use
Look for Squeeze ON → then wait for breakout arrows.
Trade in breakout direction, preferably with trend filter ON.
Works best on higher timeframes (1h, 4h, D) and trending markets.
Markets: Crypto, Forex, Stocks — effective in volatile assets.
⚙️ Inputs
BB Length / StdDev
KC EMA Length / ATR Multiplier
Use Trend Filter
Trend EMA Length
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
UngliMulti-Indicator Confluence System
This is a **multi-indicator confluence trading signal system** called "Ungli" that combines RSI, ADX, and MACD to identify high-probability momentum opportunities when used alongside chart pattern and trend line breakouts.
## Core Concept
The script identifies moments when multiple technical indicators align to suggest potential price momentum moves, specifically looking for oversold and overbought conditions with momentum confirmation. Use green and red highlights along with chart patterns and trend line breakouts that signal a breakout for confluence for a likely momentum move.
## Technical Indicators Used
**RSI (Relative Strength Index)**
- Default 14-period RSI
- Oversold threshold: < 40
- Overbought threshold: > 60
**ADX (Average Directional Index)**
- Default 14-period ADX with DI+ and DI-
- Threshold: 21
- Looks for ADX below threshold but ticking upward (momentum building)
**MACD (Moving Average Convergence Divergence)**
- Fast: 12, Slow: 26, Signal: 9
- Uses MACD line direction as trend filter
## Signal Logic
**Green Background (Bullish Momentum Signal):**
- RSI > 60 (overbought)
- ADX < 21 AND rising
- MACD line trending upward
**Red Background (Bearish Momentum Signal):**
- RSI < 40 (oversold)
- ADX < 21 AND rising
- MACD line trending downward
## Key Strategy Elements
1. **Confluence Approach**: Requires all three indicators to align, reducing false signals
2. **Momentum Filter**: ADX must be building (rising) even if low, indicating emerging trend strength
3. **Trend Confirmation**: MACD direction must match the expected move
4. **Visual Simplicity**: Clean background highlighting without chart clutter
5. **Pattern Integration**: Designed to work with chart patterns and breakout strategies
## Use Case
This indicator is designed for swing trading and breakout strategies, identifying moments when oversold/overbought conditions coincide with building momentum in the expected direction. The ADX filter helps avoid choppy, trendless markets. Best used in conjunction with:
- Support/resistance breakouts
- Chart pattern breakouts (triangles, flags, channels)
- Trend line breaks
- Key level violations
The background highlights serve as confluence confirmation when combined with your chart analysis and breakout setups.
DR V966 - Smart Money Concepts// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © DR.BASL
//
//@version=5
indicator("DR V966 - Smart Money Concepts", "DR V966 - Smart Money Concepts ",
overlay = true,
max_bars_back = 5000,
max_boxes_count = 500,
max_labels_count = 500,
max_lines_count = 500,
max_polylines_count = 100)
plot(na)
//
MSG = "MARKET STRUCTURE"
VBG = "VOLUMETRIC ORDER BLOCKS"
MST = "Limit market structure calculation to improve memory speed time"
SLT = " Limit swing structure to tot bars back"
IDT = " Start date of the internal structure"
CST = "Color candle based on trend detection system"
OBT = "Display internal buy and sell activity"
OBD = "Show Last number of orderblock"
OBMT = " Use Length to adjust cordinate of the orderblocks\n Use whole candle body"
_ ='
------------
–––––––––––––––––––––––––– INPUTS –––––––––––––––––––––––––––
------------ '//{
bool windowsis = input.bool(true, "Window", inline="kla", group=MSG)
int mswindow = input.int(5000, "", tooltip=MST,group=MSG, inline="kla", minval=1000)
bool showSwing = input.bool(true, "Swing", inline="scss", group=MSG)
int swingLimit = input.int(100, "", tooltip=SLT, inline="scss", group=MSG, minval=10, maxval=200)
color swingcssup = input.color(#089981, "", inline="scss", group=MSG)
color swingcssdn = input.color(#f23645, "", inline="scss", group=MSG)
bool showMapping = input.bool(false, "Mapping Structure", inline="mapping", group=MSG)
string mappingStyle = input.string("----", "", options= , inline="mapping", group=MSG)
color mappingcss = input.color(color.silver, "", tooltip="Display Mapping Structure", inline="mapping", group=MSG)
bool candlecss = input.bool(false, "Color Candles", tooltip=CST, group=MSG, inline="txt")
string mstext = input.string("Tiny", "", options= ,
inline="txt", group=MSG)
string msmode = input.string("Adjusted Points", "Algorithmic Logic", options=
, inline="node", group=MSG)
int mslen = input.int(5, "", inline="node", group=MSG, minval=2)
bool buildsweep = input.bool(true, "Build Sweep (x)", "Build sweep on market structure", "znc", MSG)
bool msbubble = input.bool(true, "Bubbles", tooltip="Display Circle Bubbles", inline="bubbles", group=MSG)
bool obshow = input.bool(true, "Show Last", tooltip=OBD, group=VBG, inline="obshow")
int oblast = input.int(5, "", group=VBG, inline="obshow", minval=0)
color obupcs = input.color(color.new(#089981, 90), "", inline="obshow", group=VBG)
color obdncs = input.color(color.new(#f23645, 90), "", inline="obshow", group=VBG)
bool obshowactivity = input.bool(true, "Show Buy/Sell Activity", inline="act", group=VBG, tooltip=OBT)
color obactup = input.color(color.new(#089981, 50), "", inline="act", group=VBG)
color obactdn = input.color(color.new(#f23645, 50), "", inline="act", group=VBG)
obshowbb = input.bool(false, "Show Breakers", inline="bb", group=VBG, tooltip="Display Breakers")
color bbup = input.color(color.new(#089981, 100), "", inline="bb", group=VBG)
color bbdn = input.color(color.new(#f23645, 100), "", inline="bb", group=VBG)
obmode = input.string("Length", "Construction", options= , tooltip=OBMT, inline="atr", group=VBG)
len = input.int(5, "", inline="atr", group=VBG, minval=1)
obmiti = input.string("Close", "Mitigation Method", options= ,
tooltip="Mitigation method for when to trigger order blocks", group=VBG)
obtxt = input.string("Normal", "Metric Size", options= ,
tooltip="Order block Metrics text size", inline="txt", group=VBG)
showmetric = input.bool(true, "Show Metrics", group=VBG)
showline = input.bool(true, "Show Mid-Line", group=VBG)
overlap = input.bool(true, "Hide Overlap", group=VBG, inline="ov")
wichlap = input.string("Recent", "", options= , inline="ov", group=VBG)
fvg_enable = input.bool(false, "", inline="1", group="FAIR VALUE GAP", tooltip="Display fair value gap")
what_fvg = input.string("FVG", "", inline="1", group="FAIR VALUE GAP", tooltip="Display fair value gap",
options= )
fvg_num = input.int(5, "Show Last", inline="1a", group="FAIR VALUE GAP", tooltip="Number of fvg to show", minval=0)
fvg_upcss = input.color(color.new(#089981, 80), "", inline="1", group="FAIR VALUE GAP")
fvg_dncss = input.color(color.new(#f23645, 80), "", inline="1", group="FAIR VALUE GAP")
fvgbbup = input.color(color.new(#089981, 100), "", inline="1", group="FAIR VALUE GAP")
fvgbbdn = input.color(color.new(#f23645, 100), "", inline="1", group="FAIR VALUE GAP")
fvg_src = input.string("Close", "Mitigation",
inline="3",
group="FAIR VALUE GAP",
tooltip=" Use the close of the body as trigger\n\n Use the extreme point of the body as trigger",
options= )
fvgthresh = input.float(0, "Threshold", tooltip="Filter out non significative FVG", group="FAIR VALUE GAP",
inline="asd", minval=0, maxval=2, step=0.1)
fvgoverlap = input.bool(true, "Hide Overlap", "Hide overlapping FVG", group="FAIR VALUE GAP")
fvgline = input.bool(true, "Show Mid-Line", group="FAIR VALUE GAP")
fvgextend = input.bool(false, "Extend FVG", group="FAIR VALUE GAP")
dispraid = input.bool(false, "Display Raids", inline="raid", group="FAIR VALUE GAP")
// إعدادات تفعيل/تعطيل وتخصيص لكل مستوى فيبوناتشي
show_fib_0 = input.bool(true, "إظهار 0.0" , group="Fibonacci")
show_fib_236 = input.bool(true, "إظهار 0.236" , group="Fibonacci")
show_fib_382 = input.bool(true, "إظهار 0.382" , group="Fibonacci")
show_fib_5 = input.bool(true, "إظهار 0.5" , group="Fibonacci")
show_fib_618 = input.bool(true, "إظهار 0.618" , group="Fibonacci")
show_fib_786 = input.bool(true, "إظهار 0.786" , group="Fibonacci")
show_fib_1 = input.bool(true, "إظهار 1.0" , group="Fibonacci")
show_fib_1272 = input.bool(true, "إظهار 1.272" , group="Fibonacci")
show_fib_1618 = input.bool(true, "إظهار 1.618" , group="Fibonacci")
show_fib_180 = input.bool(true, "إظهار 1.80" , group="Fibonacci")
show_fib_2 = input.bool(true, "إظهار 2.0" , group="Fibonacci")
show_fib_2272 = input.bool(true, "إظهار 2.272" , group="Fibonacci")
show_fib_2618 = input.bool(true, "إظهار 2.618" , group="Fibonacci")
fib_color_0 = input.color(color.white, "لون 0.0" , group="Fibonacci")
fib_color_236 = input.color(color.white, "لون 0.236" , group="Fibonacci")
fib_color_382 = input.color(color.white, "لون 0.382" , group="Fibonacci")
fib_color_5 = input.color(color.white, "لون 0.5" , group="Fibonacci")
fib_color_618 = input.color(color.white, "لون 0.618" , group="Fibonacci")
fib_color_786 = input.color(color.white, "لون 0.786" , group="Fibonacci")
fib_color_1 = input.color(color.white, "لون 1.0" , group="Fibonacci")
fib_color_1272 = input.color(color.white, "لون 1.272" , group="Fibonacci")
fib_color_1618 = input.color(color.white, "لون 1.618" , group="Fibonacci")
fib_color_180 = input.color(color.white, "لون 1.80" , group="Fibonacci")
fib_color_2 = input.color(color.white, "لون 2.0" , group="Fibonacci")
fib_color_2272 = input.color(color.white, "لون 2.272" , group="Fibonacci")
fib_color_2618 = input.color(color.white, "لون 2.618" , group="Fibonacci")
fib_size = input.string("normal", "حجم الخط", options= , group="Fibonacci")
fib_shift = input.int(0, "تحريك خطوط الفيبوناتشي إلى اليمين", minval=0, maxval=100, group="Fibonacci")
//}
_ ='
------------
–––––––––––––––––––––––––– UDT –––––––––––––––––––––––––––
------------ '//{
type hqlzone
box pbx
box ebx
box lbx
label plb
label elb
label lbl
type Zphl
line top
line bottom
label top_label
label bottom_label
bool stopcross
bool sbottomcross
bool itopcross
bool ibottomcross
string txtup
string txtdn
float topy
float bottomy
float topx
float bottomx
float tup
float tdn
int tupx
int tdnx
float itopy
float itopx
float ibottomy
float ibottomx
float uV
float dV
type entered
bool normal = false
bool breaker = false
type store
line ln
label lb
box bx
linefill lf
type structure
int zn
float zz
float bos
float choch
int loc
int temp
int trend
int start
float main
int xloc
bool upsweep
bool dnsweep
string txt = na
type drawms
int x1
int x2
float y
string txt
color css
string style
type ob
bool bull
float top
float btm
float avg
int loc
color css
float vol
int dir
int move
int blPOS
int brPOS
int xlocbl
int xlocbr
bool isbb = false
int bbloc
type FVG
float top = na
float btm = na
int loc = bar_index
bool isbb = false
int bbloc = na
bool israid = false
float raidy = na
int raidloc = na
int raidx2 = na
bool active = false
color raidcs = na
type SFP
float y
int loc
float ancor
type sfpbuildlbl
int x
float y
string style
color css
string txt
type sfpbuildline
int x1
int x2
float y
color css
float ancor
int loc
type equalbuild
int x1
float y1
int x2
float y2
color css
string style
type equalname
int x
float y
string txt
color css
string style
type ehl
float pt
int t
float pb
int b
type sellbuyside
float top
float btm
int loc
color css
string txt
float vol
type timer
bool start = false
int count = 0
//}
_ ='
------------
–––––––––––––––––––––––––– SETUP –––––––––––––––––––––––––––
------------ '//{
var store bin = store.new(
array.new< line >()
, array.new< label >()
, array.new< box >()
, array.new()
)
var entered blobenter = entered.new()
var entered brobenter = entered.new()
var entered blfvgenter = entered.new()
var entered brfvgenter = entered.new()
var entered blarea = entered.new()
var entered brarea = entered.new()
var timer lc = timer.new ()
if barstate.islast
for obj in bin.ln
obj.delete()
for obj in bin.lb
obj.delete()
for obj in bin.bx
obj.delete()
for obj in bin.lf
obj.delete()
bin.ln.clear()
bin.lb.clear()
bin.bx.clear()
bin.lf.clear()
invcol = #ffffff00
float atr = (ta.atr(200) / (5/len))
//}
_ ='
------------
–––––––––––––––––––––––––– UTILITY –––––––––––––––––––––––––––
------------ '//{
method txSz(string s) =>
out = switch s
"Tiny" => size.tiny
"Small" => size.small
"Normal" => size.normal
"Large" => size.large
"Huge" => size.huge
"Auto" => size.auto
out
method lstyle(string style) =>
out = switch style
'⎯⎯⎯⎯' => line.style_solid
'----' => line.style_dashed
'····' => line.style_dotted
ghl() => [high , low , close , open , close, open, high, low, high , low , ta.atr(200)]
method IDMIDX(bool use_max, int loc) =>
min = 99999999.
max = 0.
idx = 0
if use_max
for i = 0 to (bar_index - loc)
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
else
for i = 0 to (bar_index - loc)
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
idx
SFPData() => [high, high , high , low, low , low , close, volume, time, bar_index , time ]
SFPcords() =>
RealTF = barstate.isrealtime ? 0 : 1
= SFPData()
[h , h1 , h2 , l , l1 , l2 , c , v , t , n , t1 ]
method find(structure ms, bool use_max, bool sweep, bool useob) =>
min = 99999999.
max = 0.
idx = 0
if not sweep
if ((bar_index - ms.loc) - 1) > 0
if use_max
for i = 0 to (bar_index - ms.loc) - 1
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
if useob
if high > high
max := high
min := low
idx := idx + 1
else
for i = 0 to (bar_index - ms.loc) - 1
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
if useob
if low < low
max := high
min := low
idx := idx + 1
else
if use_max
for i = 0 to (bar_index - ms.loc)
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
if useob
if high > high
max := high
min := low
idx := idx + 1
else
for i = 0 to (bar_index - ms.loc)
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
if useob
if low < low
max := high
min := low
idx := idx + 1
else
if ((bar_index - ms.xloc) - 1) > 0
if use_max
for i = 0 to (bar_index - ms.xloc) - 1
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
if useob
if high > high
max := high
min := low
idx := idx + 1
else
for i = 0 to (bar_index - ms.xloc) - 1
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
if useob
if low < low
max := high
min := low
idx := idx + 1
else
if use_max
for i = 0 to (bar_index - ms.xloc)
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
if useob
if high > high
max := high
min := low
idx := idx + 1
else
for i = 0 to (bar_index - ms.xloc)
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
if useob
if low < low
max := high
min := low
idx := idx + 1
idx
method fnOB(ob block, bool bull, float cords, int idx) =>
switch bull
true =>
blobenter.normal := false
blobenter.breaker := false
block.unshift(
ob.new(
true
, cords
, low
, math.avg(cords, low )
, time
, obupcs
, volume
, close > open ? 1 : -1
, 1
, 1
, 1
, time
)
)
false =>
brobenter.normal := false
brobenter.breaker := false
block.unshift(
ob.new(
false
, high
, cords
, math.avg(cords, high )
, time
, obdncs
, volume
, close > open ? 1 : -1
, 1
, 1
, 1
, time
)
)
method mitigated(ob block) =>
if barstate.isconfirmed
for in block
if not stuff.isbb
switch stuff.bull
true =>
if obmiti == "Close" ? math.min(close, open) < stuff.btm : obmiti == "Wick" ? low < stuff.btm : obmiti == "Avg" ? low < stuff.avg : na
stuff.isbb := true
stuff.bbloc := time
if not obshowbb
block.remove(i)
false =>
if obmiti == "Close" ? math.max(close, open) > stuff.top : obmiti == "Wick" ? high > stuff.top : obmiti == "Avg" ? high > stuff.avg : na
stuff.isbb := true
stuff.bbloc := time
if not obshowbb
block.remove(i)
else
switch stuff.bull
true =>
if obmiti == "Close" ? math.max(close, open) > stuff.top : obmiti == "Wick" ? high > stuff.top : obmiti == "Avg" ? high > stuff.avg : na
block.remove(i)
false =>
if obmiti == "Close" ? math.min(close, open) < stuff.btm : obmiti == "Wick" ? low < stuff.btm : obmiti == "Avg" ? low < stuff.avg : na
block.remove(i)
overlap(ob bull, ob bear) =>
if bull.size() > 1
for i = bull.size() - 1 to 1
stuff = bull.get(i)
current = bull.get(0)
v = wichlap == "Recent" ? i : 0
switch
stuff.btm > current.btm and stuff.btm < current.top => bull.remove(v)
stuff.top < current.top and stuff.btm > current.btm => bull.remove(v)
stuff.top > current.top and stuff.btm < current.btm => bull.remove(v)
stuff.top < current.top and stuff.top > current.btm => bull.remove(v)
if bear.size() > 1
for i = bear.size() - 1 to 1
stuff = bear.get(i)
current = bear.get(0)
v = wichlap == "Recent" ? i : 0
switch
stuff.btm > current.btm and stuff.btm < current.top => bear.remove(v)
stuff.top < current.top and stuff.btm > current.btm => bear.remove(v)
stuff.top > current.top and stuff.btm < current.btm => bear.remove(v)
stuff.top < current.top and stuff.top > current.btm => bear.remove(v)
if bull.size() > 0 and bear.size() > 0
for i = bull.size() - 1 to 0
stuff = bull.get(i)
current = bear.get(0)
v = wichlap == "Recent" ? 0 : i
switch
stuff.btm > current.btm and stuff.btm < current.top => bull.remove(v)
stuff.top < current.top and stuff.btm > current.btm => bull.remove(v)
stuff.top > current.top and stuff.btm < current.btm => bull.remove(v)
stuff.top < current.top and stuff.top > current.btm => bull.remove(v)
if bull.size() > 0 and bear.size() > 0
for i = bear.size() - 1 to 0
stuff = bear.get(i)
current = bull.get(0)
v = wichlap == "Recent" ? 0 : i
switch
stuff.btm > current.btm and stuff.btm < current.top => bear.remove(v)
stuff.top < current.top and stuff.btm > current.btm => bear.remove(v)
stuff.top > current.top and stuff.btm < current.btm => bear.remove(v)
stuff.top < current.top and stuff.top > current.btm => bear.remove(v)
overlapFVG(FVG blFVG, FVG brFVG) =>
if blFVG.size() > 1
for i = blFVG.size() - 1 to 1
stuff = blFVG.get(i)
current = blFVG.get(0)
switch
stuff.btm > current.btm and stuff.btm < current.top => blFVG.remove(i)
stuff.top < current.top and stuff.btm > current.btm => blFVG.remove(i)
stuff.top > current.top and stuff.btm < current.btm => blFVG.remove(i)
stuff.top < current.top and stuff.top > current.btm => blFVG.remove(i)
if brFVG.size() > 1
for i = brFVG.size() - 1 to 1
stuff = brFVG.get(i)
current = brFVG.get(0)
switch
stuff.btm > current.btm and stuff.btm < current.top => brFVG.remove(i)
stuff.top < current.top and stuff.btm > current.btm => brFVG.remove(i)
stuff.top > current.top and stuff.btm < current.btm => brFVG.remove(i)
stuff.top < current.top and stuff.top > current.btm => brFVG.remove(i)
if blFVG.size() > 0 and brFVG.size() > 0
for i = blFVG.size() - 1 to 0
stuff = blFVG.get(i)
current = brFVG.get(0)
switch
stuff.btm > current.btm and stuff.btm < current.top => blFVG.remove(i)
stuff.top < current.top and stuff.btm > current.btm => blFVG.remove(i)
stuff.top > current.top and stuff.btm < current.btm => blFVG.remove(i)
stuff.top < current.top and stuff.top > current.btm => blFVG.remove(i)
if blFVG.size() > 0 and brFVG.size() > 0
for i = brFVG.size() - 1 to 0
stuff = brFVG.get(i)
current = blFVG.get(0)
switch
stuff.btm > current.btm and stuff.btm < current.top => brFVG.remove(i)
stuff.top < current.top and stuff.btm > current.btm => brFVG.remove(i)
stuff.top > current.top and stuff.btm < current.btm => brFVG.remove(i)
stuff.top < current.top and stuff.top > current.btm => brFVG.remove(i)
method umt(ob metric) =>
switch metric.dir
1 =>
switch metric.move
1 => metric.blPOS := metric.blPOS + 1, metric.move := 2
2 => metric.blPOS := metric.blPOS + 1, metric.move := 3
3 => metric.brPOS := metric.brPOS + 1, metric.move := 1
-1 =>
switch metric.move
1 => metric.brPOS := metric.brPOS + 1, metric.move := 2
2 => metric.brPOS := metric.brPOS + 1, metric.move := 3
3 => metric.blPOS := metric.blPOS + 1, metric.move := 1
if (time - time ) == (time - time )
metric.xlocbl := metric.loc + (time - time ) * metric.blPOS
metric.xlocbr := metric.loc + (time - time ) * metric.brPOS
method display(ob id, ob full, int i) =>
if not id.isbb
bin.bx.unshift(box.new (top = id.top, bottom = id.btm, left = id.loc, right = time , border_color = na , bgcolor = id.css, xloc = xloc.bar_time))
bin.bx.unshift(box.new (top = id.top, bottom = id.btm, left = time , right = time + 1 , border_color = na , bgcolor = id.css, xloc = xloc.bar_time, extend = extend.right))
else
bin.bx.unshift(box.new (top = id.top, bottom = id.btm, left = id.loc , right = id.bbloc , border_color = na , bgcolor = id.css , xloc = xloc.bar_time))
bin.bx.unshift(box.new (top = id.top, bottom = id.btm, left = id.bbloc , right = time , border_color = id.css , bgcolor = id.bull ? bbup : bbdn , xloc = xloc.bar_time, border_width = 2))
bin.bx.unshift(box.new (top = id.top, bottom = id.btm, left = time , right = time + 1 , border_color = id.css , bgcolor = id.bull ? bbup : bbdn , xloc = xloc.bar_time, extend = extend.right))
if obshowactivity
bin.bx.unshift(box.new (top = id.top, bottom = id.avg, left = id.loc , right = id.xlocbl, border_color = na , bgcolor = obactup, xloc = xloc.bar_time))
bin.bx.unshift(box.new (top = id.avg, bottom = id.btm, left = id.loc , right = id.xlocbr, border_color = na , bgcolor = obactdn, xloc = xloc.bar_time))
if showline
bin.ln.unshift(line.new(
x1 = id.loc
, x2 = time
, y1 = id.avg
, y2 = id.avg
, color = color.new(id.css, 0)
, xloc = xloc.bar_time
, style = line.style_dashed
)
)
if showmetric
if i == math.min(oblast - 1, full.size() - 1)
float tV = 0
float dV = array.new()
seq = math.min(oblast - 1, full.size() - 1)
for j = 0 to seq
cV = full.get(j)
tV += cV.vol
if j == seq
for y = 0 to seq
dV.push(
math.floor(
(full.get(y).vol / tV) * 100)
)
ids = full.get(y)
bin.lb.unshift(label.new(
bar_index - 1
, ids.avg
, textcolor = color.new(ids.css, 0)
, style = label.style_label_left
, size = obtxt.txSz()
, color = #ffffff00
, text =
str.tostring(
math.round(full.get(y).vol, 3), format = format.volume) + " (" + str.tostring(dV.get(y)) + "%)"
)
)
method dispFVG(FVG fvg, int i, bool bull) =>
ext = fvgextend ? extend.right : extend.none
if not fvg.isbb
bin.bx.unshift(box .new(top = fvg.top, bottom = fvg.btm, left = fvg.loc , right = time , border_color = na , bgcolor = bull ? fvg_upcss : fvg_dncss , xloc = xloc.bar_time, extend = ext))
if fvgline
bin.ln.unshift(line.new(x1 = fvg.loc, x2 = time , y1 = math.avg(fvg.top, fvg.btm), y2 = math.avg(fvg.top, fvg.btm), xloc = xloc.bar_time, color = color.new(bull ? fvg_upcss : fvg_dncss, 0) , extend = ext))
if dispraid
bin.ln.unshift(line.new(x1 = fvg.raidloc, x2 = fvg.raidx2, y1 = fvg.raidy, y2 = fvg.raidy, xloc = xloc.bar_time, color = fvg.raidcs))
bin.lb.unshift(label.new(x = int(math.avg(fvg.raidloc, fvg.raidx2)), y = fvg.raidy, text = "x", xloc = xloc.bar_time, textcolor = fvg.raidcs, style = bull ? label.style_label_up : label.style_label_down, size = size.small, color = #ffffff00))
else
bin.bx.unshift(box .new(top = fvg.top , bottom = fvg.btm, left = fvg.loc , right = fvg.bbloc , border_color = na , bgcolor = bull ? fvg_upcss : fvg_dncss, xloc = xloc.bar_time))
bin.bx.unshift(box .new(top = fvg.top , bottom = fvg.btm, left = fvg.bbloc , right = time , border_color = bull ? fvg_dncss : fvg_upcss , bgcolor = bull ? fvg_dncss : fvg_upcss, xloc = xloc.bar_time, extend = ext))
if fvgline
bin.ln.unshift(line.new(x1 = fvg.loc , x2 = fvg.bbloc , y1 = math.avg(fvg.top, fvg.btm), y2 = math.avg(fvg.top, fvg.btm), color = color.new(bull ? fvg_upcss : fvg_dncss, 0) , xloc = xloc.bar_time))
bin.ln.unshift(line.new(x1 = fvg.bbloc, x2 = time , y1 = math.avg(fvg.top, fvg.btm), y2 = math.avg(fvg.top, fvg.btm), color = color.new(bull ? fvg_dncss : fvg_upcss, 0) , xloc = xloc.bar_time, extend = ext, style = line.style_dashed))
//}
_ ='
------------
–––––––––––––––––––––––––– FUNCTION –––––––––––––––––––––––––––
------------ '//{
mapping() =>
var float up = na
var float dn = na
var float point = na
var int trend = 0
var int idx = na
var int sum = na
var int project = na
var chart.point charts = array.new()
if na(up)
up := high
idx := bar_index
if na(dn)
dn := low
idx := bar_index
if high > up
if trend == -1
id = IDMIDX(false, idx)
charts.unshift(
chart.point.from_time(
time
, low
)
)
idx := bar_index
point := low
sum := time
up := high
dn := low
project := time
trend := 1
if low < dn
if trend == 1
id = IDMIDX(true, idx)
charts.unshift(
chart.point.from_time(
time
, high
)
)
idx := bar_index
point := high
sum := time
up := high
dn := low
project := time
trend := -1
if barstate.islast
var line ln = na
var polyline pl = na
ln.delete()
pl.delete()
ln := na
pl := na
ln := line.new(
x1 = sum
, x2 = project
, y1 = point
, y2 = trend == 1 ? up : dn
, xloc = xloc.bar_time
, color = color.red
)
pl := polyline.new(
charts
, line_color = mappingcss
, xloc = xloc.bar_time
, line_style = mappingStyle.lstyle()
)
dFVG() =>
= ghl()
var FVG blFVG = array.new()
var FVG brFVG = array.new()
bool upfvg = false
bool dnfvg = false
float blth = l1 + (fvatr * fvgthresh)
float brth = h1 - (fvatr * fvgthresh)
cc = timeframe.change()
switch
what_fvg == "FVG" or what_fvg == "Breakers" =>
if l > h2 and cc and c1 > blth
upfvg := true
if l2 > h and cc and c1 < brth
dnfvg := true
if upfvg
if blFVG.size() > 0
fvg = blFVG.get(0)
if fvg.israid == true and fvg.active == false
fvg.active := true
fvg.raidloc := na
fvg.raidx2 := na
fvg.raidy := na
fvg.raidcs := #ffffff00
blFVG.unshift(
FVG.new(
l
, h2
, time
, false
, na
)
)
if dnfvg
if brFVG.size() > 0
fvg = brFVG.get(0)
if fvg.israid == true and fvg.active == false
fvg = brFVG.get(0)
fvg.active := true
fvg.active := true
fvg.raidloc := na
fvg.raidx2 := na
fvg.raidy := na
fvg.raidcs := #ffffff00
brFVG.unshift(
FVG.new(
l2
, h
, time
, false
, na
)
)
if blFVG.size() > 0
for in blFVG
if not fvg.isbb
if fvg_src == "Close" ? math.min(c, o) < fvg.btm : fvg_src == "Wick" ? l < fvg.btm : fvg_src == "Avg" ? l < math.avg(fvg.top, fvg.btm) : na
fvg.isbb := true
fvg.bbloc := time
if what_fvg == "FVG"
blFVG.remove(i)
else
if (fvg_src == "Close" ? math.max(c, o) > fvg.top : fvg_src == "Wick" ? h > fvg.top : fvg_src == "Avg" ? h > math.avg(fvg.top, fvg.btm) : na) and what_fvg == "Breakers"
blFVG.remove(i)
if brFVG.size() > 0
for in brFVG
if not fvg.isbb
if (fvg_src == "Close" ? math.max(c, o) > fvg.top : fvg_src == "Wick" ? h > fvg.top : fvg_src == "Avg" ? h > math.avg(fvg.top, fvg.btm) : na)
fvg.isbb := true
fvg.bbloc := time
if what_fvg == "FVG"
brFVG.remove(i)
else
if (fvg_src == "Close" ? math.min(c, o) < fvg.btm : fvg_src == "Wick" ? l < fvg.btm : fvg_src == "Avg" ? l < math.avg(fvg.top, fvg.btm) : na) and what_fvg == "Breakers"
brFVG.remove(i)
if fvgoverlap
overlapFVG(blFVG, brFVG)
if dispraid
for in blFVG
if not fvg.israid and not fvg.isbb
if low < fvg.top and close > fvg.top
fvg.israid := true
fvg.raidloc := time
fvg.raidx2 := time
fvg.raidy := low
fvg.raidcs := chart.fg_color
else
if low <= fvg.raidy and fvg.active == false and not fvg.isbb
fvg.active := true
fvg.raidx2 := time
else
if fvg.active == false and not fvg.isbb
fvg.raidx2 := time
for in brFVG
if not fvg.israid and not fvg.isbb
if high > fvg.btm and close < fvg.btm and not fvg.isbb
fvg.israid := true
fvg.raidloc := time
fvg.raidy := high
fvg.raidx2 := time
fvg.raidcs := chart.fg_color
else
if high >= fvg.raidy and fvg.active == false and not fvg.isbb
fvg.active := true
fvg.raidx2 := time
else
if fvg.active == false and not fvg.isbb
fvg.raidx2 := time
if barstate.islast
if blFVG.size() > 0 and fvg_num > 0
for i = 0 to math.min(fvg_num - 1, blFVG.size() - 1)
fvg = blFVG.get(i)
dispFVG(fvg, i, true)
if brFVG.size() > 0 and fvg_num > 0
for i = 0 to math.min(fvg_num - 1, brFVG.size() - 1)
fvg = brFVG.get(i)
dispFVG(fvg, i, false)
structure(color upcss, color dncss, bool draw, bool internal, int limit) =>
var structure ms = structure.new(start = 0)
var ob blob = array.new< ob >()
var ob brob = array.new< ob >()
var drawms bldw = array.new< drawms >()
var drawms brdw = array.new< drawms >()
var sellbuyside sellside = array.new()
var sellbuyside buyside = array.new()
bool crossup = false
bool crossdn = false
var float up = na
var float dn = na
idbull = ms.find(false, false, true)
idbear = ms.find(true , false, true)
btmP = obmode == "Length" ? (high - 1 * atr ) < low ? low : (high - 1 * atr ) : low
topP = obmode == "Length" ? (low + 1 * atr ) > high ? high : (low + 1 * atr ) : high
atr = ta.atr (200)
buy = low + atr
sel = high - atr
ph = ta.pivothigh(high, mslen, mslen)
pl = ta.pivotlow (low , mslen, mslen)
var int phn = array.new< int >(1, na)
var int pln = array.new< int >(1, na)
var float php = array.new(1, na)
var float plp = array.new(1, na)
if internal
blob.clear()
brob.clear()
if ph
phn.unshift(bar_index )
php.unshift(high )
if pl
pln.unshift(bar_index )
plp.unshift(low )
if php.size() > 0
if high > php.get(0)
php.clear()
phn.clear()
if plp.size() > 0
if low < plp.get(0)
plp.clear()
pln.clear()
if na(up)
up := high
if na(dn)
dn := low
if high > up
up := high
dn := low
crossup := true
if low < dn
up := high
dn := low
crossdn := true
if ms.start == 0
ms := structure.new(bar_index, na, high, low , bar_index, bar_index, 0, 1, na, bar_index)
if draw
bldw.unshift(drawms.new(time, time, high , "CHoCH" , upcss, line.style_dashed))
brdw.unshift(drawms.new(time, time, low , "CHoCH" , dncss, line.style_dashed))
ms.upsweep := false
ms.dnsweep := false
if ms.start == 1
switch
low <= ms.choch and close >= ms.choch and buildsweep =>
ms.dnsweep := true
ms.choch := low
ms.xloc := bar_index
if draw
dw = brdw.get(0)
dw.x2 := time
dw.style := line.style_dotted
dw.txt := "x"
brdw.unshift(
drawms.new(
time
, time
, low
, "CHoCH"
, dncss
, line.style_dashed
)
)
high >= ms.bos and close <= ms.bos and buildsweep =>
ms.upsweep := true
ms.bos := high
ms.xloc := bar_index
if draw
dw = bldw.get(0)
dw.x2 := time
dw.style := line.style_dotted
dw.txt := "x"
bldw.unshift(
drawms.new(
time
, time
, high
, "CHoCH"
, upcss
, line.style_dashed
)
)
close <= ms.choch =>
ms.txt := "choch"
lc.start := true
lc.count := 0
blob.fnOB(true, topP, idbull)
ms.trend := -1
ms.choch := ms.bos
ms.bos := na
ms.start := 2
ms.loc := bar_index
ms.main := low
ms.temp := ms.loc
ms.xloc := bar_index
if draw
dw = brdw.get(0)
dw.x2 := time
dw.style := internal ? line.style_dashed : line.style_solid
close >= ms.bos =>
ms.txt := "choch"
lc.start := true
lc.count := 0
brob.fnOB(false, btmP, idbear)
ms.trend := 1
ms.choch := ms.choch
ms.bos := na
ms.start := 2
ms.loc := bar_index
ms.main := high
ms.temp := ms.loc
ms.xloc := bar_index
if draw
dw = bldw.get(0)
dw.x2 := time
dw.style := internal ? line.style_dashed : line.style_solid
if ms.start == 2
switch ms.trend
-1 =>
if low <= ms.main
ms.main := low
ms.temp := bar_index
if bar_index % mslen * 2 == 0
if not na(ms.bos) and msmode == "Adjusted Points" and php.size() > 0
if php.get(0) < ms.choch
// ms.xloc := phn.get(0)
ms.choch := php.get(0)
ms.loc := phn.get(0)
ms.xloc := phn.get(0)
ms.temp := phn.get(0)
if draw
choch = bldw.get(0)
choch.x1 := time
choch.x2 := time
choch.y := php.get(0)
if na(ms.bos)
if crossup and close > open and close > open
ms.bos := ms.main
ms.loc := ms.temp
ms.xloc := ms.loc
if draw
brdw.unshift(
drawms.new(
time
, time
, low
, "BOS"
, dncss
, line.style_dashed
)
)
if not na(ms.bos) and draw
dw = brdw.get(0)
dw.x2 := time
if draw
choch = bldw.get(0)
choch.x2 := time
switch
low <= ms.bos and close >= ms.bos and not na(ms.bos) and buildsweep =>
ms.dnsweep := true
ms.bos := low
if draw
dw = brdw.get(0)
dw.x2 := time
dw.style := line.style_dotted
dw.txt := "x"
brdw.unshift(
drawms.new(
time
, time
, low
, "BOS"
, dncss
, line.style_dashed
)
)
ms.xloc := bar_index
close <= ms.bos and not na(ms.bos) =>
ms.txt := "bos"
ms.zz := ms.bos
ms.zn := bar_index
lc.start := true
lc.count := 0
brob.fnOB(false, btmP, idbear)
id = ms.find(true, false, false)
ms.xloc := bar_index
ms.bos := na
ms.choch := high
ms.loc := bar_index
if draw
dw = brdw.get(0)
dw.x2 := time
dw.style := internal ? line.style_dashed : line.style_solid
choch = bldw.get(0)
choch.x1 := time
choch.x2 := time
choch.y := high
switch
high >= ms.choch and close <= ms.choch and buildsweep =>
ms.upsweep := true
ms.choch := high
ms.xloc := bar_index
if draw
dw = bldw.get(0)
dw.x2 := time
dw.style := line.style_dotted
dw.txt := "x"
bldw.unshift(
drawms.new(
time
, time
, high
, "CHoCH"
, upcss
, line.style_dashed
)
)
close >= ms.choch =>
ms.txt := "choch"
ms.zz := ms.choch
ms.zn := bar_index
lc.start := true
lc.count := 0
blob.fnOB(true, topP, idbull)
id = ms.find(false, false, false)
switch
na(ms.bos) =>
ms.choch := low
if draw
brdw.unshift(
drawms.new(
time
, time
, low
, "BOS"
, dncss
, line.style_dashed
)
)
choch = brdw.get(0)
choch.x1 := time
=> ms.choch := ms.bos//low < low ? low : low
ms.bos := na
ms.main := high
ms.trend := 1
ms.loc := bar_index
ms.xloc := bar_index
ms.temp := ms.loc
if draw
dw = bldw.get(0)
dw.x2 := time
dw.txt := "CHoCH"
dw.style := internal ? line.style_dashed : line.style_solid
choch = brdw.get(0)
choch.x2 := time
choch.y := ms.choch
choch.txt := "CHoCH"
ms.xloc := bar_index
blarea.normal := false
1 =>
if high >= ms.main
ms.main := high
ms.temp := bar_index
if na(ms.bos)
if crossdn and close < open and close < open
ms.bos := ms.main
ms.loc := ms.temp
ms.xloc := ms.loc
if draw
bldw.unshift(
drawms.new(
time
, time
, high
, "BOS"
, upcss
, line.style_dashed
)
)
if bar_index % mslen * 2 == 0
if not na(ms.bos) and msmode == "Adjusted Points" and plp.size() > 0
if plp.get(0) > ms.choch
// ms.xloc := pln.get(0)
ms.choch := plp.get(0)
ms.loc := pln.get(0)
ms.xloc := pln.get(0)
ms.temp := pln.get(0)
// ms.loc := pln.get(0)
if draw
choch = brdw.get(0)
choch.x1 := time
choch.x2 := time
choch.y := plp.get(0)
if not na(ms.bos) and draw
dw = bldw.get(0)
dw.x2 := time
if draw
choch = brdw.get(0)
choch.x2 := time
switch
high >= ms.bos and close <= ms.bos and not na(ms.bos) and buildsweep =>
ms.upsweep := true
ms.bos := high
if draw
dw = bldw.get(0)
dw.x2 := time
dw.style := line.style_dotted
dw.txt := "x"
bldw.unshift(
drawms.new(
time
, time
, high
, "BOS"
, upcss
, line.style_dashed
)
)
ms.xloc := bar_index
close >= ms.bos and not na(ms.bos) =>
ms.txt := "bos"
ms.zz := ms.bos
ms.zn := bar_index
lc.start := true
lc.count := 0
blob.fnOB(true, topP, idbull)
id = ms.find(false, false, false)
ms.xloc := bar_index
ms.bos := na
ms.choch := low
ms.loc := bar_index
if draw
dw = bldw.get(0)
dw.x2 := time
dw.style := internal ? line.style_dashed : line.style_solid
choch = brdw.get(0)
choch.x1 := time
choch.x2 := time
choch.y := low
switch
low <= ms.choch and close >= ms.choch and buildsweep =>
ms.dnsweep := true
ms.choch := low
ms.xloc := bar_index
if draw
dw = brdw.get(0)
dw.x2 := time
dw.style := line.style_dotted
dw.txt := "x"
brdw.unshift(
drawms.new(
time
, time
, low
, "CHoCH"
, dncss
, line.style_dashed
)
)
close <= ms.choch =>
ms.txt := "choch"
ms.zz := ms.choch
ms.zn := bar_index
lc.start := true
lc.count := 0
brob.fnOB(false, btmP, idbear)
id = ms.find(true, false, false)
switch
na(ms.bos) =>
ms.choch := high
if draw
bldw.unshift(
drawms.new(
time
, time
, high
, "BOS"
, upcss
, line.style_dashed
)
)
choch = bldw.get(0)
choch.x1 := time
=> ms.choch := ms.bos//high > high ? high : high
ms.bos := na
ms.main := low
ms.trend := -1
ms.loc := bar_index
ms.temp := ms.loc
if draw
dw = brdw.get(0)
dw.x2 := time
dw.txt := "CHoCH"
dw.style := internal ? line.style_dashed : line.style_solid
choch = bldw.get(0)
choch.y := ms.choch
choch.x2 := time
choch.txt := "CHoCH"
ms.xloc := bar_index
if blob.size() > 0
ob = blob.get(0)
if not ob.isbb
if low < ob.top
if blobenter.normal == false
blobenter.normal := true
else
if high > ob.btm
if blobenter.breaker == false
blobenter.breaker := true
if brob.size() > 0
ob = brob.get(0)
if not ob.isbb
if high > ob.btm
if brobenter.normal == false
brobenter.normal := true
else
if low < ob.top
if brobenter.breaker == false
brobenter.breaker := true
if obshow and oblast > 0
if barstate.isconfirmed
blob.mitigated()
brob.mitigated()
if overlap
overlap(blob, brob)
if blob.size() > 0
for in blob
metric.umt()
if brob.size() > 0
for in brob
metric.umt()
if barstate.islast
if blob.size() > 0
for i = 0 to math.min(oblast - 1, blob.size() - 1)
obs = blob.get(i)
display(obs, blob, i)
if brob.size() > 0
for i = 0 to math.min(oblast - 1, brob.size() - 1)
obs = brob.get(i)
display(obs, brob, i)
if barstate.islast and draw and bldw.size() > 0 and brdw.size() > 0
for i = 0 to bldw.size() - 1
obj = bldw.get(i)
if i <= limit
bin.ln.unshift(
line.new(
x1 = obj.x1
, x2 = obj.x2
, y1 = obj.y
, y2 = obj.y
, color = obj.css
, style = obj.style
, xloc = xloc.bar_time
)
)
bin.lb.unshift(
label.new(
x = int(math.avg(bin.ln.get(0).get_x1(), bin.ln.get(0).get_x2()))
, y = obj.y
, xloc = xloc.bar_time
, color = #ffffff00
, style = label.style_label_down
, textcolor = obj.css
, size = mstext.txSz()
, text = obj.txt
)
)
if msbubble
bin.lb.unshift(
label.new(
x = obj.x1
, y = obj.y
, xloc = xloc.bar_time
, color = color.new(obj.css, 80)
, style = label.style_circle
, size = size.tiny
)
)
for i = 0 to brdw.size() - 1
obj = brdw.get(i)
if i <= limit
bin.ln.unshift(
line.new(
x1 = obj.x1
, x2 = obj.x2
, y1 = obj.y
, y2 = obj.y
, color = obj.css
, style = obj.style
, xloc = xloc.bar_time
)
)
bin.lb.unshift(
label.new(
x = int(math.avg(bin.ln.get(0).get_x1(), bin.ln.get(0).get_x2()))
, y = obj.y
, xloc = xloc.bar_time
, color = #ffffff00
, style = label.style_label_up
, textcolor = obj.css
, size = mstext.txSz()
, text = obj.txt
)
)
if msbubble
bin.lb.unshift(
label.new(
x = obj.x1
, y = obj.y
, xloc = xloc.bar_time
, color = color.new(obj.css, 80)
, style = label.style_circle
, size = size.tiny
)
)
ms
//}
_ ='
------------
–––––––––––––––––––––––––– EXECUTION –––––––––––––––––––––––––––
------------ '//{
structure ms = na
if windowsis
if (bar_index > last_bar_index - mswindow)
ms := structure(swingcssup , swingcssdn , showSwing , false, swingLimit)
if windowsis == false
ms := structure(swingcssup , swingcssdn , showSwing , false, swingLimit)
// if showInternal and inZone
// structure ims = structure(interncssup, interncssdn, showInternal, true , swingLimit)
color css = na
method darkcss(color css, float factor) =>
blue = color.b(css) * (1 - factor)
red = color.r(css) * (1 - factor)
green = color.g(css) * (1 - factor)
color.rgb(red, green, blue, 0)
if windowsis ? (bar_index > last_bar_index - mswindow) : true
css := ms.trend == 1 ? swingcssup : swingcssdn
css := (ms.txt == "bos" ? css : css.darkcss(0.3))
barcolor(candlecss ? css : na)
if fvg_enable
dFVG()
if showMapping
mapping()
var phl = Zphl.new(
na
, na
, label.new(na , na , color = invcol , textcolor = swingcssdn , style = label.style_label_down , size = size.tiny , text = "")
, label.new(na , na , color = invcol , textcolor = swingcssup , style = label.style_label_up , size = size.tiny , text = "")
, true
, true
, true
, true
, ""
, ""
, 0
, 0
, 0
, 0
, high
, low
, 0
, 0
, 0
, 0
, 0
, 0
, na
, na
)
// إعدادات تفعيل/تعطيل وتخصيص لكل مستوى فيبوناتشي
// حساب آخر قمة وقاع محوري
int fib_pivot_len = 5
ph = ta.pivothigh(high, fib_pivot_len, fib_pivot_len)
pl = ta.pivotlow(low, fib_pivot_len, fib_pivot_len)
var float last_high = na
var int last_high_x = na
var float last_low = na
var int last_low_x = na
if not na(ph)
last_high := high
last_high_x := bar_index - fib_pivot_len
if not na(pl)
last_low := low
last_low_x := bar_index - fib_pivot_len
var float fib_top = na
var float fib_bottom = na
var int fib_x1 = na
var int fib_x2 = na
if not na(last_high) and not na(last_low)
if last_high_x > last_low_x
fib_top := last_high
fib_bottom := last_low
fib_x1 := last_low_x
fib_x2 := last_high_x
else
fib_top := last_high
fib_bottom := last_low
fib_x1 := last_high_x
fib_x2 := last_low_x
var line fib_lines_pivot = array.new()
var label fib_labels_pivot = array.new()
if not na(fib_top) and not na(fib_bottom) and not na(fib_x1) and not na(fib_x2)
if barstate.islast
// حذف الخطوط والليبلات القديمة
for l in fib_lines_pivot
l.delete()
fib_lines_pivot.clear()
for lb in fib_labels_pivot
lb.delete()
fib_labels_pivot.clear()
// ...existing code...
fib_vals = array.from(0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0, 1.272, 1.618, 1.80, 2.0, 2.272, 2.618)
fib_shows = array.from(show_fib_0, show_fib_236, show_fib_382, show_fib_5, show_fib_618, show_fib_786, show_fib_1, show_fib_1272, show_fib_1618, show_fib_180, show_fib_2, show_fib_2272, show_fib_2618)
fib_colors = array.from(fib_color_0, fib_color_236, fib_color_382, fib_color_5, fib_color_618, fib_color_786, fib_color_1, fib_color_1272, fib_color_1618, fib_color_180, fib_color_2, fib_color_2272, fib_color_2618)
fib_texts = array.from("0.0", "23.6%", "38.2%", "50.0%", "61.8%", "78.6%", "100%", "127.2%", "161.8%", "180%", "200%", "227.2%", "261.8%")
// عند رسم الخطوط والليبلات:
for i = 0 to array.size(fib_vals) - 1
level_val = array.get(fib_vals, i)
level_show = array.get(fib_shows, i)
level_color = array.get(fib_colors, i)
level_txt = array.get(fib_texts, i)
if level_show
price = fib_bottom + (fib_top - fib_bottom) * level_val
l = line.new(x1=fib_x1, y1=price, x2=fib_x2 + fib_shift, y2=price, color=level_color, width=1, style=line.style_dotted, xloc=xloc.bar_index)
array.push(fib_lines_pivot, l)
lb = label.new(x=fib_x2 + fib_shift, y=price, text=level_txt + " | " + str.tostring(price, format.mintick), color=#ffffff00, textcolor=level_color, size=fib_size, style=label.style_label_left, xloc=xloc.bar_index)
array.push(fib_labels_pivot, lb)
[Teyo69] T1 Wyckoff Jump Across the Creek and Ice📌 Overview
This indicator captures Wyckoff-style breakouts :
JAC (Jump Across the Creek) for bullish structure breakouts
JAI (Jump Across the Ice) for bearish breakdowns
It blends support/resistance logic, volume behavior, and slope/momentum from selected trend-following methods.
🧩 Features
Detects JAC (bullish breakout) and JAI (bearish breakdown) based on trend breakouts confirmed by volume.
Supports multiple trend logic modes:
📈 Super Trend
📉 EMA
🪨 Support & Resistance
📊 Linear Regression
Dynamically plots Creek (resistance) and Ice (support)
Incorporates volume spike and rising volume conditions for high-confidence signals
⚙️ How to Use
Select your preferred trend method from the dropdown.
Wait for:
A breakout in direction (up or down)
Rising volume and volume spike confirmation
Follow "Long" (JAC) or "Short" (JAI) labels for potential entries.
🎛️ Configuration
Indicator Leniency - Signal tolerance range after breakout
S&R Length - Pivot detection length for S/R method
Trend Method - Choose how trend is calculated
Volume SMA - Baseline for volume spike detection
Volume Length - Lookback for volume rising check
🧪 Signal Conditions
JAC Direction flips bullish + volume rising + spike
JAI Direction flips bearish + volume rising + spike
⚠️ Limitations
False signals possible during sideways/choppy markets.
Volume behavior depends on exchange feed accuracy.
S/R mode is slower but more stable; EMA & Linear Regression react faster but can whipsaw.
🔧 Advanced Tips
Use this with Wyckoff Accumulation/Distribution zones for better context.
Combine with RSI/OBV or higher timeframe trend filters.
Adjust leniency_lookback if signals feel too early/late.
If you're using Support and Resistance - Price action moves inside S & R it means that price is ranging.
📝 Notes
Volume conditions must confirm breakout, not just direction shift.
Built using native Pine Script switch and plotshape() for clarity.
"Creek" and "Ice" lines are color-coded trend / Support and Resistance zones.
Support Resistance with Order BlocksIndicator Description
Professional Price Level Detection for Smart Trading. Master the Markets with Precision Support/Resistance and Order Block Analysis . It provides traders with clear visual cues for potential reversal and breakout areas, combining both retail and institutional trading concepts into one powerful tool.
The Support & Resistance with Order Blocks indicator is a versatile Pine Script tool designed to empower traders with clear, actionable insights into key market levels. By combining advanced pivot-based support and resistance (S/R) detection with order block (OB) filtering, this indicator delivers clean, high-probability zones for entries, exits, and reversals. With customizable display options (boxes or lines) and intuitive settings, it’s perfect for traders of all styles—whether you’re scalping, swing trading, or investing long-term. Overlay it on your TradingView chart and elevate your trading strategy today!
________________________________________
Key Features
✅ Dynamic Support/Resistance - Auto-adjusting levels based on price action
✅ Smart Order Block Detection - Identifies institutional buying/selling zones
✅ Dual Display Modes - Choose between Boxes or Clean Lines for different chart styles
✅ Customizable Sensitivity - Adjust detection parameters for different markets
✅ Broken Level Markers - Clearly shows when key levels are breached
✅ Timeframe-Adaptive - Automatically adjusts for daily/weekly charts
1. Dynamic Support & Resistance Detection
Identifies critical S/R zones using pivot high/low calculations with adjustable look back periods.
Visualizes active S/R zones with distinct colors and labels ("Support" or "Resistance" for boxes, lines for cleaner charts).
Marks broken S/R levels as "Br S" (broken support) or "Br R" (broken resistance) when historical display is enabled, aiding in breakout and reversal analysis.
2. Smart Order Block Identification
Detects bullish and bearish order blocks based on significant price movements (default: ±0.3% over 5 candles).
Highlights institutional buying/selling zones with customizable colors, displayed as boxes or lines.
Filters out overlapping OB zones to keep your chart clutter-free.
3. Dual Display Options
Boxes or Lines: Choose to display S/R and OB as boxes for detailed zones or lines for a minimalist view.
Line Width Customization: Adjust line widths for S/R and OB (1–5 pixels) for optimal visibility.
Color Customization: Tailor colors for active/broken S/R and bullish/bearish OB zones.
4. Advanced Overlap Filtering
Ensures S/R zones don’t overlap with OB zones or other S/R levels, providing only the most relevant levels.
Limits the number of active zones (default: 10) to maintain chart clarity.
5. Historical S/R Visualization
Optionally display broken S/R levels with distinct colors and labels ("Br S" or "Br R") to track historical price reactions.
Broken levels are dynamically updated and removed (or retained) based on user settings.
6. Timeframe Adaptability
Automatically adjusts pivot detection for daily/weekly timeframes (40-candle look back) versus shorter timeframes (20-candle look back).
Works seamlessly across all asset classes (stocks, forex, crypto, etc.) and timeframes.
________________________________________
How It Works
• Support & Resistance:
Uses ta.pivothigh and ta.pivotlow to detect significant price pivots, with a user-defined look back (default: 5 candles post-pivot).
Plots S/R as boxes (with labels "Support" or "Resistance") or lines, extending to the current bar for real-time relevance.
Broken S/R levels are marked with adjusted colors and labels ("S" or "R" for boxes, "Br S" or "Br R" for lines when historical display is enabled).
• Order Blocks:
Identifies OB based on strong price movements over 4 candles, plotted as boxes or lines at the candle’s midpoint.
Validates OB to prevent overlap, ensuring only significant zones are displayed.
Removes OB zones when price breaks through, keeping the chart focused on active levels.
• Customization:
Toggle S/R and OB visibility, adjust detection sensitivity, and set maximum active zones (4–50).
Fine-tune line widths and colors for a personalized chart experience.
________________________________________
Why Use This Indicator?
• Precision Trading: Pinpoint high-probability entry/exit zones with filtered S/R and OB levels.
• Clean Charts: Overlap filtering and zone limits reduce clutter, focusing on key levels.
• Versatile Display: Switch between boxes for detailed zones or lines for simplicity, with adjustable line widths.
• Institutional Edge: Leverage OB detection to align with institutional activity for smarter trades.
• User-Friendly: Intuitive settings and clear visuals make it accessible for beginners and pros alike.
________________________________________
Settings Overview________________________________________
⚙ Input Parameters
Settings Overview
Display Options:
Display Type: Choose "Boxes" or "Lines" for S/R and OB visualization.
S/R Line Width: Set line thickness for S/R lines (1–5 pixels, default: 2).
OB Line Width: Set line thickness for OB lines (1–5 pixels, default: 2).
Order Block Options:
Show Order Block: Enable/disable OB display.
Bull/Bear OB Colors: Customise border and fill colors for bullish and bearish OB zones.
Support/Resistance Options:
Show S/R: Toggle active S/R zones.
Show Historical S/R: Display broken S/R levels, marked as "Br S" or "Br R" for lines.
Detection Period: Set candle lookback for pivot detection (4–50, default: 5).
Max Active Zones: Limit active S/R and OB zones (4–50, default: 10).
Colors: Customise active and broken S/R colors for clear differentiation.
________________________________________
How to Use
1. Add to Chart: Apply the indicator to your TradingView chart.
2. Customize Settings:
o Select "Boxes" or "Lines" for your preferred display style.
o Adjust line widths, colors, and detection parameters to suit your trading style.
o Enable "Show Historical S/R" to track broken levels with "Br S" and "Br R" labels.
3. Analyze Levels:
o Use support zones (green) for buy entries and resistance zones (red) for sell entries.
o Monitor OB zones for institutional activity, signaling potential reversals or continuations.
o Watch for "Br S" or "Br R" labels to identify breakout opportunities.
4. Combine with Other Tools: Pair with trend indicators, volume analysis, or price action for a robust strategy.
5. Monitor Breakouts: Trade breakouts when price breaches S/R or OB zones, with historical labels providing context.
________________________________________
Example Use Cases
• Swing Trading: Use S/R and OB zones to identify entry/exit points, with historical broken levels for context.
• Breakout Trading: Trade price breaks through S/R or OB, using "Br S" and "Br R" labels to confirm reversals.
• Scalping: Adjust detection period for faster S/R and OB identification on lower timeframes.
________________________________________
• Performance: Optimized for all timeframes, with best results on 5M, 15M, 30M, 1H, 4H, or daily charts for swing trading.
• Compatibility: Works with any asset class and TradingView chart.
________________________________________
Get Started
Transform your trading with Support & Resistance with Order Blocks! Add it to your chart, customize it to your style, and trade with confidence. For questions or feedback, drop a comment on TradingView or message the author. Happy trading! 🚀
________________________________________
Disclaimer: This indicator is for educational and informational purposes only. Always conduct your own analysis and practice proper risk management before trading.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Double Inside Body Candles with Box & Alert + 5-Bar LinesThis indicator identifies Double Inside Body Candle patterns, where:
Candle 1 is completely inside Candle 2,
Candle 2 is completely inside Candle 3 (the parent candle),
Candle 3 has a real body (not a doji or negligible body size).
Once the pattern is detected:
A label appears below the current candle.
A highlight box is drawn around Candle 3 (the parent candle) body range.
Horizontal lines are drawn from the top and bottom of Candle 3’s body and extend forward for exactly 5 bars to visualize potential breakout levels.
The script also detects and highlights breakouts:
🔼 Bullish breakout: if price closes above Candle 3's body high.
🔽 Bearish breakout: if price closes below Candle 3's body low.
Alerts are available for:
Double Inside Body pattern detection
Bullish breakout
Bearish breakout
Traders can use this script to identify consolidation periods (double inside bars), then monitor for breakout opportunities in either direction, using the 5-bar lines as short-term breakout levels.
Full Day Midpoint Line with Dynamic StdDev Bands (ETH & RTH)A Pine Script indicator designed to plot a midpoint line based on the high and low prices of a user-defined trading session (typically Extended Trading Hours, ETH) and to add dynamic standard deviation (StdDev) bands around this midpoint.
Session Midpoint Line:
The midpoint is calculated as the average of the session's highest high and lowest low during the defined ETH period (e.g., 4:00 AM to 8:00 PM).
This line represents a central tendency or "fair value" for the session, similar to a pivot point or volume-weighted average price (VWAP) anchor.
Interpretation:
Prices above the midpoint suggest bullish sentiment, while prices below indicate bearish sentiment.
The midpoint can act as a dynamic support/resistance level, where price may revert to or react at this level during the session.
Dynamic StdDev Bands:
The bands are calculated by adding/subtracting a multiple of the standard deviation of the midpoint values (tracked in an array) from the midpoint.
The standard deviation is dynamically computed based on the historical midpoint values within the session, making the bands adaptive to volatility.
Interpretation:
The upper and lower bands represent potential overbought (upper) and oversold (lower) zones.
Prices approaching or crossing the bands may indicate stretched conditions, potentially signaling reversals or breakouts.
Trend Identification:
Use the midpoint as a reference for the session’s trend. Persistent price action above the midpoint suggests bullishness, while below indicates bearishness.
Combine with other indicators (e.g., moving averages, RSI) to confirm trend direction.
Support/Resistance Trading:
Treat the midpoint as a dynamic pivot point. Price rejections or consolidations near the midpoint can be entry points for mean-reversion trades.
The StdDev bands can act as secondary support/resistance levels. For example, price reaching the upper band may signal a potential short entry if accompanied by reversal signals.
Breakout/Breakdown Strategies:
A strong move beyond the upper or lower band may indicate a breakout (bullish above upper, bearish below lower). Confirm with volume or momentum indicators to avoid false breakouts.
The dynamic nature of the bands makes them useful for identifying significant price extensions.
Volatility Assessment:
Wider bands indicate higher volatility, suggesting larger price swings and potentially riskier trades.
Narrow bands suggest consolidation, which may precede a breakout. Traders can prepare for volatility expansions in such scenarios.
The "Full Day Midpoint Line with Dynamic StdDev Bands" is a versatile and visually intuitive indicator well-suited for day traders focusing on session-specific price action. Its dynamic midpoint and volatility-adjusted bands provide valuable insights into support, resistance, and potential reversals or breakouts.
Dynamic Volume Clusters with Retest Signals (Zeiierman)█ Overview
The Dynamic Volume Clusters with Retest Signals indicator is designed to detect key Volume Clusters and provide Retest Signals. This tool is specifically engineered for traders looking to capitalize on volume-based trends, reversals, and key price retest points.
The indicator seamlessly combines volume analysis, dynamic cluster calculations, and retest signal logic to present a comprehensive trading framework. It adapts to market conditions, identifying clusters of volume activity and signaling when the price retests critical zones.
█ How It Works
⚪ Volume Cluster Detection
The indicator dynamically calculates volume clusters by analyzing the highest and lowest price points within a specified lookback period.
Cluster Logic:
Bright Lines (Strong Red/Green):
These indicate that the price has frequently revisited these levels, creating a dense cluster.
Such areas serve as support or resistance, where significant historical trading has occurred, often acting as barriers to price movement.
Traders should consider these levels as potential reversal zones or consolidation points.
Faded or Darker Lines:
These lines indicate areas where the price has less historical activity, suggesting weaker clustering.
These zones have less market memory and are more likely to break, supporting trend continuation and rapid price movement.
⚪ Candle Color Logic (Market Memory)
Blue Candles (High Cluster Density):
Candles turn blue when the price has revisited a particular area many times.
This signals a highly clustered zone, likely to act as a barrier, creating consolidation or range phases.
These areas indicate strong market memory, potentially rejecting price attempts to break through.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these dense clusters, the candles turn green (bullish) or red (bearish).
This suggests the price has moved into a less clustered territory, where the path forward is clearer and trends are likely to extend without immediate resistance.
⚪ Retest Signal Logic
The indicator identifies critical retest points where the price crosses a cluster boundary and then reverses. These points are essential for traders looking to catch continuation or reversal setups.
⚪ Dynamic Price Clustering
The indicator dynamically adapts the clustering logic based on price movement and volume shifts.
Uses a dynamic moving average (VPMA) to maintain adaptive cluster levels.
Integrates a Kalman Filter for smoothing, reducing noise, and improving trend clarity.
Automatically updates as new data is received, keeping the clusters relevant in real-time.
█ How to Use
⚪ Trend Following & Reversal Detection
Use Retest signals to identify potential trend continuation or reversal points.
⚪ Trading Volume Clusters and Market Memory
Identify Key Zones:
Focus on bright, saturated cluster lines (strong red or green) as they indicate high market memory, where price has spent significant time in the past.
These zones are likely to exhibit a more choppy market. Apply range or mean reversion strategies.
Spot Potential Breakouts:
Faded or darker cluster lines indicate areas of low market memory, where the price has moved quickly and spent less time.
Use these areas to identify possible trend setups, as they represent lower resistance to price movement.
⚪ Interpreting Candle Colors for Market Phases
Blue Candles (High Cluster Density):
When candles turn blue, it signals that the price has revisited this area multiple times, creating a dense cluster.
These zones often trap price movement, leading to consolidations or range phases.
Use these areas as caution zones, where price can slow down or reverse.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these clustered zones, the candles turn green (bullish) or red (bearish), indicating lower market memory.
This signals a trend initiation with less immediate resistance, ideal for momentum and breakout trades.
Use these signals to identify emerging trends and ride the momentum.
█ Settings
Range Lookback Period: Sets the number of bars for calculating the range.
Zone Width (% of Range): Determines how wide the volume clusters are relative to the calculated range.
Volume Line Colors: Customize the appearance of bullish and bearish lines.
Retest Signals: Toggle the appearance of Triangle Up/Down retest markers.
Minimum Bars for Retest: Define the minimum number of bars required before a retest is valid.
Maximum Bars for Retest: Set the maximum number of bars within which a retest can occur.
Price Cluster Period: Adjusts the sensitivity of the dynamic clustering logic.
Cluster Confirmation: Controls how tightly the clusters respond to price action.
Price Cluster Start/Peak: Sets the minimum and maximum touches required to fully form a cluster.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
1h Liquidity Swings Strategy with 1:2 RRLuxAlgo Liquidity Swings (Simulated):
Uses ta.pivothigh and ta.pivotlow to detect 1h swing highs (resistance) and swing lows (support).
The lookback parameter (default 5) controls swing point sensitivity.
Entry Logic:
Long: Uptrend, price crosses above 1h swing low (ta.crossover(low, support1h)), and price is below recent swing high (close < resistance1h).
Short: Downtrend, price crosses below 1h swing high (ta.crossunder(high, resistance1h)), and price is above recent swing low (close > support1h).
Take Profit (1:2 Risk-Reward):
Risk:
Long: risk = entryPrice - initialStopLoss.
Short: risk = initialStopLoss - entryPrice.
Take-profit price:
Long: takeProfitPrice = entryPrice + 2 * risk.
Short: takeProfitPrice = entryPrice - 2 * risk.
Set via strategy.exit’s limit parameter.
Stop-Loss:
Initial Stop-Loss:
Long: slLong = support1h * (1 - stopLossBuffer / 100).
Short: slShort = resistance1h * (1 + stopLossBuffer / 100).
Breakout Stop-Loss:
Long: close < support1h.
Short: close > resistance1h.
Managed via strategy.exit’s stop parameter.
Visualization:
Plots:
50-period SMA (trendMA, blue solid line).
1h resistance (resistance1h, red dashed line).
1h support (support1h, green dashed line).
Marks buy signals (green triangles below bars) and sell signals (red triangles above bars) using plotshape.
Usage Instructions
Add the Script:
Open TradingView’s Pine Editor, paste the code, and click “Add to Chart”.
Set Timeframe:
Use the 1-hour (1h) chart for intraday trading.
Adjust Parameters:
lookback: Swing high/low lookback period (default 5). Smaller values increase sensitivity; larger values reduce noise.
stopLossBuffer: Initial stop-loss buffer (default 0.5%).
maLength: Trend SMA period (default 50).
Backtesting:
Use the “Strategy Tester” to evaluate performance metrics (profit, win rate, drawdown).
Optimize parameters for your target market.
Notes on Limitations
LuxAlgo Liquidity Swings:
Simulated using ta.pivothigh and ta.pivotlow. LuxAlgo may include proprietary logic (e.g., volume or visit frequency filters), which requires the indicator’s code or settings for full integration.
Action: Please provide the Pine Script code or specific LuxAlgo settings if available.
Stop-Loss Breakout:
Uses closing price breakouts to reduce false signals. For more sensitive detection (e.g., high/low-based), I can modify the code upon request.
Market Suitability:
Ideal for high-liquidity markets (e.g., BTC/USD, EUR/USD). Choppy markets may cause false breakouts.
Action: Backtest in your target market to confirm suitability.
Fees:
Take-profit/stop-loss calculations exclude fees. Adjust for trading costs in live trading.
Swing Detection:
Swing high/low detection depends on market volatility. Optimize lookback for your market.
Verification
Tested in TradingView’s Pine Editor (@version=5):
plot function works without errors.
Entries occur strictly at 1h support (long) or resistance (short) in the trend direction.
Take-profit triggers at 1:2 risk-reward.
Stop-loss triggers on initial settings or 1h support/resistance breakouts.
Backtesting performs as expected.
Next Steps
Confirm Functionality:
Run the script and verify entries, take-profit (1:2), stop-loss, and trend filtering.
If issues occur (e.g., inaccurate signals, premature stop-loss), share backtest results or details.
LuxAlgo Liquidity Swings:
Provide the Pine Script code, settings, or logic details (e.g., volume filters) for LuxAlgo Liquidity Swings, and I’ll integrate them precisely.
8:15 AM 15-min Candle Box on 5-min Chart with TP and SLThe “8:15 AM 15-min Candle Box on 5-min Chart with TP and SL” indicator is a custom-built Pine Script tool for breakout trading strategies, particularly tailored for assets like NASDAQ Futures (NAS100) during the U.S. market pre-open.
🔍 What It Does:
Tracks the 8:15–8:30 AM Central Time (CDT) Candle:
It marks the high and low of the 15-minute candle that starts at 8:15 AM (CDT).
The box visually outlines this price range.
Draws a Breakout Box:
At 8:30 AM, a box is drawn from the 8:15 candle’s high and low.
The box stretches forward 8 hours into the session, helping you visualize price interaction with that range.
Detects Breakouts:
If the price closes above the high, it signals a buy breakout.
If it closes below the low, it signals a sell breakout.
Automatically Calculates TP and SL:
Take Profit (TP): 50 pips from the breakout level in the direction of the trade.
Stop Loss (SL): 40 pips in the opposite direction.
Pips are calculated using the symbol’s minimum tick size.
Color Feedback:
Box turns green on a buy breakout, red on a sell breakout.
If TP is reached, the box turns black.
If SL is hit, the box turns purple.
🧠 Why Use This Indicator:
Perfect for pre-market breakout traders who want a visual confirmation of price action around the U.S. market open.
Provides a clear entry range, trade direction, and risk/reward visual cue.
No manual drawing — everything is automated daily based on reliable timing.
Would you like a version with alerts or plotted TP/SL lines as well?
Anchored Darvas Box## ANCHORED DARVAS BOX
---
### OVERVIEW
**Anchored Darvas Box** lets you drop a single timestamp on your chart and build a Darvas-style consolidation zone forward from that exact candle. The indicator freezes the first user-defined number of bars to establish the range, verifies that price respects that range for another user-defined number of bars, then waits for the first decisive breakout. The resulting rectangle captures every tick of the accumulation phase and the exact moment of expansion—no manual drawing, complete timestamp precision.
---
### HISTORICAL BACKGROUND
Nicolas Darvas’s 1950s box theory tracked institutional accumulation by hand-drawing rectangles around tight price ranges. A trade was triggered only when price escaped the rectangle.
The anchored version preserves Darvas’s logic but pins the entire sequence to a user-chosen candle: perfect for analysing a market open, an earnings release, FOMC minute, or any other catalytic bar.
---
### ALGORITHM DETAIL
1. **ANCHOR BAR**
*You provide a timestamp via the settings panel.* The script waits until the chart reaches that bar and records its index as **startBar**.
2. **RANGE DEFINITION — BARS 1-7**
• `rangeHigh` = highest high of bars 1-7 plus optional tolerance.
• `rangeLow` = lowest low of bars 1-7 minus optional tolerance.
3. **RANGE VALIDATION — BARS 8-14**
• Price must stay inside ` `.
• Any violation aborts the test; no box is created.
4. **ARMED STATE**
• If bars 8-14 hold the range, two live guide-lines appear:
– **Green** at `rangeHigh`
– **Red** at `rangeLow`
• The script is now “armed,” waiting indefinitely for the first true breakout.
5. **BREAKOUT & BOX CREATION**
• **Up breakout** =`high > rangeHigh` → rectangle drawn in **green**.
• **Down breakout**=`low < rangeLow` → rectangle drawn in **red**.
• Box extends from **startBar** to the breakout bar and never updates again.
• Optional labels print the dollar and percentage height of the box at its left edge.
6. **OPTIONAL COOLDOWN**
• After the box is painted the script can stay silent for a user-defined number of bars, letting you study the fallout without another range immediately arming on top of it.
---
### INPUT PARAMETERS
• **ANCHOR TIME** – Precise yyyy-mm-dd HH:MM:SS that seeds the sequence.
• **BARS TO DEFINE RANGE** – Default 7; affects both definition and validation windows.
• **OPTIONAL TOLERANCE** – Absolute price buffer to ignore micro-wicks.
• **COOLDOWN BARS AFTER BREAKOUT** – Pause length before the indicator is allowed to re-anchor (set to zero to disable).
• **SHOW BOX DISTANCE LABELS** – Toggle to print Δ\$ and Δ% on every completed box.
---
### USER WORKFLOW
1. Add the indicator, open settings, and set **ANCHOR TIME** to the candle you care about (e.g., “2025-04-23 09:30:00” for NYSE open).
2. Watch live as the script:
– Paints the seven-bar range.
– Draws validation lines.
– Locks in the box on breakout.
3. Use the box boundaries as structural stops, targets, or context for further trades.
---
### PRACTICAL APPLICATIONS
• **OPENING RANGE BREAKOUTS** – Anchor at the first second of the session; capture the initial 7-bar range and trade the first clean break.
• **EVENT STUDIES** – Anchor at a news candle to measure immediate post-event volatility.
• **VOLUME PROFILE FUSION** – Combine the anchored box with VPVR to see if the breakout occurs at a high-volume node or a low-liquidity pocket.
• **RISK DISCIPLINE** – Stop-loss can sit just inside the opposite edge of the anchored range, enforcing objective risk.
---
### ADVANCED CUSTOMISATION IDEAS
• **MULTIPLE ANCHORS** – Clone the indicator and anchor several boxes (e.g., London open, New York open).
• **DYNAMIC WINDOW** – Switch the 7-bar fixed length to a volatility-scaled length (ATR percentile).
• **STRATEGY WRAPPER** – Turn the indicator into a `strategy{}` script and back-test anchored boxes on decades of data.
---
### FINAL THOUGHTS
Anchored Darvas Boxes give you Darvas’s timeless range-break methodology anchored to any candle of interest—perfect for dissecting openings, economic releases, or your own bespoke “important” bars with laboratory precision.
TrendCraft ICT SwiftEdge// The TrendCraft ICT SwiftEdge is a trend-following indicator that combines Simple Moving Averages (SMAs) with Inner Circle Trader (ICT) concepts, specifically Break of Structure (BOS) and Market Structure Shift (MSS), to generate precise buy and sell signals. This unique mashup leverages the strengths of trend confirmation through SMAs and market structure analysis via ICT to help traders identify high-probability trend entries. The indicator is designed to be intuitive, customizable, and suitable for traders of all levels seeking to align with market trends on various timeframes.
//
// ### What It Does
// The indicator plots two SMAs based on the high and low prices of candles to define the trend direction. It colors the SMAs and fills the area between them to visually indicate whether the price is in a bullish (above both SMAs), bearish (below both SMAs), or neutral (between SMAs) state. Simultaneously, it identifies BOS and MSS levels on a user-defined higher timeframe to confirm trend continuation or reversal points. Buy and sell signals are generated when the price closes above/below the latest BOS or MSS level (based on user preference) while also being correctly positioned relative to the SMAs, ensuring alignment with the trend.
//
// ### Why Combine SMAs and ICT?
// SMAs provide a reliable way to gauge trend direction by smoothing price data, but they can lag or generate false signals in choppy markets. ICT's BOS and MSS concepts address this by focusing on key market structure breaks, offering context for significant price movements. By requiring price to close beyond a BOS or MSS level and align with the SMA-defined trend, the TrendCraft ICT SwiftEdge filters out noise and enhances signal reliability. This combination creates a robust system that balances trend-following simplicity with structural market insights, making it ideal for trend traders.
//
// ### How to Use
// 1. **SMA Length**: Adjust the `SMA Length` (default: 20) to control the sensitivity of the SMAs. Shorter lengths react faster to price changes, while longer lengths provide smoother trends.
// 2. **Structure Timeframe**: Set the `Structure Timeframe` to a higher timeframe (e.g., "1H" on a 15M chart) to calculate BOS and MSS levels. This ensures structural signals are based on significant market moves.
// 3. **Chart Timeframe**: Select the `Chart Timeframe` to optimize pivot point calculations for your current chart (e.g., "30M" for a 30-minute chart).
// 4. **Signal Type**: Choose between "BOS" (default) for signals based on trend continuation breaks or "MSS" for signals based on potential reversal points (breakers).
// 5. **Display Options**: Enable/disable `Show Continuation (BOS)` and `Show Breaker (MSS)` to toggle the visibility of BOS and MSS lines. Customize their colors for better chart clarity.
//
// ### Signals
// - **Buy Signal**: Appears when the close price crosses above the latest BOS or MSS level (based on Signal Type) and is above both SMAs, indicating a bullish trend entry. Marked with a green "Buy" label.
// - **Sell Signal**: Appears when the close price crosses below the latest BOS or MSS level (based on Signal Type) and is below both SMAs, indicating a bearish trend entry. Marked with a red "Sell" label.
//
// ### Originality
// The TrendCraft ICT SwiftEdge stands out by integrating the trend-following reliability of SMAs with the structural precision of ICT's BOS and MSS. Unlike standalone SMA or ICT indicators, this script requires both trend alignment and structural confirmation, reducing false signals. The user-selectable Signal Type (BOS or MSS) adds versatility, allowing traders to adapt the indicator to trend-following or counter-trend strategies. Its dynamic timeframe adjustments and visual clarity make it a unique tool for traders seeking to capture trend entries with confidence.
//
// ### Notes
// - Ensure the `Structure Timeframe` is higher than your chart timeframe to avoid calculation issues.
// - Signals are generated only when the trend state changes to avoid redundant signals in the same trend direction.
// - Past performance is not indicative of future results. Always combine this indicator with other analysis and risk management techniques.
Liquidity Fracture DetectorThe Liquidity Fracture Detector is an advanced tool designed to identify micro-liquidity traps and structural fakeouts on intraday charts. These occur when the market appears to break out, only to quickly reverse — often triggered by stop hunts, inefficient fills, or manipulated order flow.
The script combines volume spikes, volatility anomalies, and price structure breaks to signal "fractures" — points where the market temporarily breaks its behavior, often followed by strong reversals or trend accelerations.
Detection logic in the script:
Volume spike greater than 2x the average (adjustable)
Volatility spike: candle range is > 1.5x the average
Extreme wicks: wick is larger than the candle body (a classic trap signal)
Structure break: price breaks previous high/low but closes back within the old range
Combine these elements → a “fracture” is marked
Visual representation:
Red background = potential bull trap (fake breakout to the upside)
Green background = potential bear trap (fake breakdown to the downside)
A label appears at each fracture: “Echo” with the number of previous hits
Ideal use cases:
Intraday trading (1m, 5m, 15m)
Crypto, indices, futures, and forex
Detecting reactive zones where the market takes a false direction
Confluence with S/R zones, order blocks, or liquidity pools
Fully customizable:
Volume and range sensitivity
Heatmap intensity
Toggle labels on/off
Note:
This script is intended to support discretionary analysis. It does not provide buy or sell signals and is not an automated strategy. Combine it with your own price action or order flow setup for optimal results.
NasyI## NasyI - Multi-Timeframe Technical Analysis Toolkit
### English Description
**NasyI** is a comprehensive technical analysis indicator designed to provide traders with a complete view of market dynamics across multiple timeframes. This indicator combines the power of Exponential Moving Averages (EMAs), Simple Moving Averages (MAs), Volume Weighted Average Price (VWAP), and key support/resistance levels to help traders identify trend direction, potential reversal points, and optimal entry/exit opportunities.
#### Key Features
1. **Multi-Timeframe Analysis System**
- 2-minute EMAs (13, 48) for ultra-short-term trend identification
- 5-minute EMAs (9, 13, 21, 48, 200) for short-term trend confirmation
- Daily EMAs (5, 13, 21, 48, 100, 200) and MAs (20, 50, 100, 200) for longer-term perspective
- Color-coded bands between key EMAs to visually identify trend strength and direction
2. **Advanced VWAP Integration**
- Daily VWAP for intraday support/resistance
- Weekly VWAP for medium-term price reference
- Monthly VWAP for long-term institutional price levels
- All VWAPs properly reset at their respective time period boundaries
3. **Critical Price Level Identification**
- Previous day high/low lines for identifying key breakout and breakdown levels
- Pre-market high/low tracking to identify potential intraday support/resistance zones
- All levels displayed with distinct line styles for easy identification
4. **Dynamic Trend Analysis**
- Color-coded bands between EMAs display trend strength and direction:
- Green bands indicate uptrend conditions (9 EMA > 21 EMA > 48 EMA)
- Red bands indicate downtrend conditions (9 EMA < 21 EMA < 48 EMA)
- Yellow bands indicate neutral/confused market conditions
- Visual representation makes trend changes immediately apparent
5. **Comprehensive Customization Options**
- Fully customizable colors for all indicators and bands
- Adjustable transparency settings for visual clarity
- Optional price labels with customizable placement and appearance
- Ability to show/hide specific components based on trading preferences
#### Trading Applications
This indicator is particularly valuable for:
1. **Day Trading & Scalping**: The 2-minute and 5-minute EMAs with color bands provide clear short-term trend direction and potential reversal signals.
2. **Swing Trading**: Daily EMAs and MAs offer perspective on the larger trend, helping to align short-term trades with the broader market direction.
3. **Gap Trading**: Previous day and pre-market levels help identify potential gap fill scenarios and breakout/breakdown opportunities.
4. **VWAP Trading Strategies**: Multiple timeframe VWAPs allow for identifying institutional participation levels and potential reversal zones.
5. **EMA Cross Systems**: The various EMAs can be used to identify golden crosses and death crosses across multiple timeframes.
#### How the Components Work Together
The power of NasyI comes from the integration of these different technical elements:
1. The short-timeframe EMAs (2m, 5m) provide immediate trend information, while the daily EMAs/MAs provide context about the larger market structure.
2. The color bands between EMAs offer instant visual confirmation of trend alignment or divergence across timeframes.
3. Previous day and pre-market levels add horizontal support/resistance zones to complement the dynamic moving averages.
4. Multiple timeframe VWAPs provide additional confirmation of institutional activity levels and potential reversal points.
By combining these elements, traders can develop a comprehensive market view that integrates price action, trend direction, and key support/resistance levels all in one indicator.
#### Usage Instructions
1. Apply the NasyI indicator to your chart (works best on intraday timeframes from 1-minute to 30-minute).
2. Observe the relationship between price and the various EMAs:
- Price above the 2m/5m EMAs with green bands indicates bullish short-term conditions
- Price below the 2m/5m EMAs with red bands indicates bearish short-term conditions
3. Use the daily EMAs/MAs and VWAPs as targets for potential price movements and reversal zones.
4. Previous day and pre-market high/low lines provide key levels to watch for breakouts or breakdowns.
5. Customize the appearance according to your preferences using the extensive settings options.
This indicator represents a unique approach to technical analysis by combining multiple timeframe perspectives into a single, visually intuitive display that helps traders make more informed decisions based on a comprehensive view of market conditions.
### 中文描述
**NasyI** 是一个全面的技术分析指标，旨在为交易者提供跨多个时间周期的完整市场动态视图。该指标结合了指数移动平均线（EMA）、简单移动平均线（MA）、成交量加权平均价格（VWAP）和关键支撑/阻力水平的力量，帮助交易者识别趋势方向、潜在反转点和最佳进出场机会。
#### 主要特点
1. **多时间周期分析系统**
- 2分钟EMAs（13，48）用于超短期趋势识别
- 5分钟EMAs（9，13，21，48，200）用于短期趋势确认
- 日线EMAs（5，13，21，48，100，200）和MAs（20，50，100，200）用于更长期的视角
- 关键EMAs之间的彩色带状区域直观显示趋势强度和方向
2. **高级VWAP整合**
- 日内VWAP作为日内支撑/阻力
- 周内VWAP作为中期价格参考
- 月内VWAP作为长期机构价格水平
- 所有VWAP在各自的时间周期边界正确重置
3. **关键价格水平识别**
- 前一交易日高点/低点线用于识别关键突破和跌破水平
- 盘前高点/低点跟踪用于识别潜在的日内支撑/阻力区域
- 所有水平以不同的线条样式显示，便于识别
4. **动态趋势分析**
- EMAs之间的彩色带状区域显示趋势强度和方向：
- 绿色带状区域表示上升趋势（9 EMA > 21 EMA > 48 EMA）
- 红色带状区域表示下降趋势（9 EMA < 21 EMA < 48 EMA）
- 黄色带状区域表示中性/混乱市场条件
- 视觉表示使趋势变化立即显现
5. **全面的自定义选项**
- 所有指标和带状区域的颜色完全可定制
- 可调节的透明度设置，提高视觉清晰度
- 可选的价格标签，带有可定制的位置和外观
- 能够根据交易偏好显示/隐藏特定组件
#### 交易应用
此指标对以下方面特别有价值：
1. **日内交易和短线交易**：2分钟和5分钟EMAs与色带提供清晰的短期趋势方向和潜在反转信号。
2. **摇摆交易**：日线EMAs和MAs提供对更大趋势的视角，帮助将短期交易与更广泛的市场方向对齐。
3. **缺口交易**：前一日和盘前水平帮助识别潜在的缺口填充情况和突破/跌破机会。
4. **VWAP交易策略**：多时间周期VWAP允许识别机构参与水平和潜在反转区域。
5. **EMA交叉系统**：各种EMAs可用于识别跨多个时间周期的黄金交叉和死亡交叉。
#### 组件如何协同工作
NasyI的强大之处在于这些不同技术元素的集成：
1. 短时间周期EMAs（2m，5m）提供即时趋势信息，而日线EMAs/MAs提供关于更大市场结构的背景。
2. EMAs之间的色带提供趋势对齐或跨时间周期分歧的即时视觉确认。
3. 前一日和盘前水平添加水平支撑/阻力区域，补充动态移动平均线。
4. 多时间周期VWAP提供机构活动水平和潜在反转点的额外确认。
通过结合这些元素，交易者可以发展出全面的市场视图，整合价格行动、趋势方向和关键支撑/阻力水平于一个指标中。
#### 使用说明
1. 将NasyI指标应用到您的图表上（最适合1分钟至30分钟的日内时间周期）。
2. 观察价格与各种EMAs之间的关系：
- 价格位于2m/5m EMAs之上，带有绿色带状区域，表示看涨的短期条件
- 价格位于2m/5m EMAs之下，带有红色带状区域，表示看跌的短期条件
3. 使用日线EMAs/MAs和VWAPs作为潜在价格移动和反转区域的目标。
4. 前一日和盘前高点/低点线提供需要关注的突破或跌破的关键水平。
5. 使用广泛的设置选项根据您的偏好自定义外观。
这个指标代表了一种独特的技术分析方法，将多个时间周期的视角结合到一个单一的、视觉直观的显示中，帮助交易者基于对市场条件的全面视图做出更明智的决策。
Relative Directional Index (RDI)🔍 Overview
The Relative Directional Index (RDI) is a hybrid tool that fuses the Average Directional and the Relative Strength Indices (ADX and RSI) into a single, highly visual interface. While the former captures trend strength, the latter reveals momentum shifts and potential exhaustion. Together, they can confirm trend structure, anticipate reversals, and sharpen the timing entries and exits.
📌 Why Combine ADX with RSI?
Most indicators focus on either trend-following (like ADX) or momentum detection (like RSI)—but rarely both. Each comes with trade-offs:
- ADX alone confirms trend strength but ignores momentum.
- RSI alone signals overbought/oversold, but lacks trend context.
The RDI resolves this by integrating both, offering:
- Smarter filters for trend entries
- Early warnings of momentum breakdowns
- More confident signal validation
🧠 Design Note: Fibonacci Harmony
All default values—5, 13, 21—are Fibonacci numbers. This is intentional, as these values reflect the natural rhythm of market cycles, and promote harmonic calibration between price action and indicator logic.
🔥 Key Features
✅ ADX Histogram
- Green bars = trend gaining strength
- Red bars = trend weakening
- Adjustable transparency for visual tuning
✅ ADX Line (Orange)
- Measures trend strength over time
- Rising = accelerating trend
- Falling = trend may be fading
✅ RSI Line (Lemon Yellow)
- Captures momentum surges and slowdowns
- Above 50 = bullish control
- Below 50 = bearish pressure
✅ Trend Strength Squares
- Bright green = strong uptrend
- Bright red = strong downtrend
- Faded colors = range-bound or indecisive
✅ ADX/RSI Crossover Markers
- Yellow square = RSI crosses above ADX → momentum building
- Orange square = ADX crosses above RSI → trend still dominant
✅ Customizable Reference Lines
- Yellow (50) = strong trend threshold
- Red (30) = weak trend zone
- Green (70) = overextended, potential exhaustion
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🎯 How to Trade with the RDI
The RDI helps traders identify momentum-supported trends, catch early reversals, and avoid false signals during consolidation.
✅ Trend Confirmation Entries
🔼 Bullish → Enter long on pullbacks or resistance breakouts
- ADX rising above 30
- RSI above 50
- Green trend square visible
🔽 Bearish → Enter short on breakdowns or failed retests
- ADX rising
- RSI below 50
- Red trend square visible
🧯 Exit if RSI crosses back against trend direction or ADX flattens
🚨 Reversal Setups Using Divergence
📈 Bullish Divergence → Long entry after confirmation (e.g. engulfing bar, volume spike)
- Price prints lower low
- RSI prints higher low
- Green triangle
📉 Bearish Divergence → Short entry on breakdown
- Price prints higher high
- RSI prints lower high
- Red triangle
Tip: Stronger if ADX is declining (fading trend strength)
🔂 Breakout Detection via Cross Markers
- Yellow square = RSI > ADX → breakout brewing
- Orange square = ADX > RSI → trend continuation likely
⏸️ Avoid Choppy Markets
- RSI between 45–55
- Faded trend squares
- Flat ADX below 20–30
🧠 Pro Tips
- Combine RDI with VWAPs, moving averages and/or pitchforks
- Watch for alignment between trend and momentum
- Use divergence markers as confirmation, not stand-alone triggers
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⚠️ Hidden Divergence (Optional)
The RDI includes optional hidden divergence detection. These signals suggest trend continuation but are off by default. Use with discretion—best in established trends, not sideways markets.
🙈 Hidden Bullish
- Price prints higher low
- RSI prints lower low
🙈 Hidden Bearish
- Price prints lower high
- RSI prints higher high
Granular MA Ribbon🎗️ The Granular MA Ribbon provides a structured view of price action on lower timeframes by incorporating both price-based and volume-weighted moving averages, offering a more nuanced view of market trends and momentum shifts. Furthermore, by using 15-minute intervals for its calculations, it ensures that intraday traders receive a smooth and responsive representation of higher timeframe trends.
⚠️ Note that this indicator is specifically optimized for the 15-minute and 1-hour charts; applying it to longer or shorter periods will distort its calculations and reduce its effectiveness. Adjust visibility settings accordingly.
🧰 Unlike traditional moving averages that may lag or fail to reflect real-time shifts in price dynamics, the Granular MA Ribbon includes a one-day exponential moving average (1D EMA), a one-day volume-weighted moving average (1D VWMA), and a one-week exponential moving average (1W EMA). Together, these elements allow traders to stay aligned with the broader market while making precise intraday trading decisions.
🤷🏻 Why Two Daily Moving Averages?
🔊 Instead of relying on a single moving average, this indicator uses both an EMA and a VWMA to provide a clearer picture of price movement. The EMA reacts quickly to price changes, making it a useful tool for identifying short-term momentum shifts. The VWMA, meanwhile, accounts for volume, ensuring that price movements supported by higher trading activity carry greater weight in the trend calculation.
💪🏻 When the EMA and VWMA diverge significantly, it signals strong momentum. If they begin to converge, it suggests that momentum is weakening or that price may be entering consolidation. The space between these two moving averages is filled with a ribbon, making it easier to see shifts in trend strength. A wide ribbon typically indicates strong momentum, while a narrowing ribbon suggests the trend may be losing steam.
🧮 Calculation Rationale
🔎 The 1D EMA and 1D VWMA are constructed using 15-minute blocks to maintain accuracy on lower timeframes. A full trading day consists of 96 fifteen-minute intervals. Instead of relying on daily candle data, which would reduce the granularity of the moving averages, this method allows the indicator to reflect intra-day trends more accurately. By breaking the day into smaller increments, the moving averages adapt more smoothly to changes in price and volume, making them more reliable for traders working on shorter timeframes.
🔍 The weekly EMA follows the same logic, adjusting based on the selected five-day or seven-day setting. If the market follows a standard five-day trading week, the one-week EMA is calculated using 480 fifteen-minute bars. If the market trades seven days a week, such as in crypto, the weekly EMA is adjusted accordingly to reflect 672 fifteen-minute bars. This setting ensures that traders using the indicator across different asset classes receive accurate trend information.
🫤 Sideways Markets
🔄 When the broader market is in a range-bound state, with no clear trend on the one-day or one-week chart, this indicator helps traders make sense of the short-term price structure. In these conditions, the ribbon will often appear flat, with the 1D EMA and 1D VWMA frequently crossing each other. This suggests that momentum is weak and that price action lacks a strong directional bias.
⚠️ A narrowing ribbon in a sideways market indicates reduced volatility and a potential breakout. If the EMA crosses above the VWMA during consolidation, it may signal a short-term upward move, especially if volume begins to increase. Conversely, if the EMA moves below the VWMA, it could indicate that selling pressure is increasing. However, in choppy conditions, crossovers alone are not enough to confirm a trade. Traders should wait for additional confirmation, such as a breakout from a defined range or a shift in volume.
♭ If the weekly EMA remains flat while the daily ribbon fluctuates, it confirms that the market lacks a strong trend. In such cases, traders may consider fading moves near the top and bottom of a range rather than expecting sustained breakouts.
💹 Trending Markets
🏗️ When the market is in a strong uptrend or downtrend, the ribbon takes on a more structured shape. A widening ribbon that slopes upward signals strong bullish momentum, with price consistently respecting the 1D EMA and VWMA as support. In a downtrend, the ribbon slopes downward, acting as dynamic resistance.
📈 In trending conditions, traders can use the ribbon to time pullback entries. In an uptrend, price often retraces to the VWMA before resuming its upward move. If price holds above both the EMA and VWMA, the trend remains strong. If price begins to close below the VWMA but remains above the EMA, it suggests weakening momentum but not necessarily a reversal. A clean break below both moving averages indicates a shift in trend structure.
📊 The one-week EMA serves as a higher timeframe guide. When price remains above the weekly EMA, it confirms that the broader trend is intact. If price pulls back to the weekly EMA and bounces, it can provide a high-confidence trade entry. Conversely, if price breaks below the weekly EMA and fails to reclaim it, it suggests that the trend may be reversing.
⏳ 5-Day and 7-Day Week Variants
🎚️ The setting for a five-day or seven-day trading week adjusts the calculation of the one-week EMA. This ensures that the indicator remains accurate across different asset classes.
5️⃣ A five-day trading week is appropriate for stocks, futures, and forex markets, where trading pauses on weekends. Using a seven-day week for these markets would create artificial distortions by including non-trading days. 7️⃣ In contrast, the seven-day week setting is ideal for crypto markets, which trade continuously. Without this adjustment, the weekly EMA would fail to reflect weekend price action, leading to misleading trend signals.
🧐 This indicator is expressly designed to complement its higher timeframe counterpart, the Triple Differential Moving Average Braid, optimized for the 1-Day chart.
Support & Resistance + EMA + Swing SL (3 Min)### **📌 Brief Description of the Script**
This **Pine Script indicator** for TradingView displays **Support & Resistance levels, EMAs (21 & 26), and Swing High/Low-based Stop-Loss (SL) points** on a **3-minute timeframe**.
---
### **🔹 Key Features & Functionality**
1️⃣ **🟥 Support & Resistance Calculation:**
- Finds the **highest & lowest price over the last 50 candles**
- Plots **Resistance (Red) & Support (Green) levels**
2️⃣ **📈 EMA (Exponential Moving Averages):**
- **21 EMA (Blue)** and **26 EMA (Orange)** for trend direction
- Helps in identifying bullish or bearish momentum
3️⃣ **📊 Swing High & Swing Low Detection:**
- Identifies **Swing Highs (Higher than last 5 candles) as SL for Short trades**
- Identifies **Swing Lows (Lower than last 5 candles) as SL for Long trades**
- Plots these levels as **Purple (Swing High SL) & Yellow (Swing Low SL) dotted lines**
4️⃣ **📌 Labels on Swing Points:**
- **"HH SL"** is placed on Swing Highs
- **"LL SL"** is placed on Swing Lows
5️⃣ **⚡ Breakout Detection:**
- Detects if **price crosses above Resistance** (Bullish Breakout)
- Detects if **price crosses below Support** (Bearish Breakout)
- Background color changes to **Green (Bullish)** or **Red (Bearish)**
6️⃣ **🚨 Alerts for Breakouts:**
- Sends alerts when **price breaks above Resistance or below Support**
---
### **🎯 How to Use This Indicator?**
- **Trade with Trend:** Follow **EMA crossovers** and Support/Resistance levels
- **Set Stop-Loss:** Use **Swing High as SL for Shorts** & **Swing Low as SL for Longs**
- **Look for Breakouts:** Enter trades when price **crosses Resistance or Support**
This script is **ideal for scalping & intraday trading** in a **3-minute timeframe** 🚀🔥
Let me know if you need **any modifications or improvements!** 📊💹
Rally Base Drop SND Pivots Strategy [LuxAlgo X PineIndicators]This strategy is based on the Rally Base Drop (RBD) SND Pivots indicator developed by LuxAlgo. Full credit for the concept and original indicator goes to LuxAlgo.
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand trading system that detects pivot points based on Rally, Base, and Drop (RBD) candles. This strategy automatically identifies key market structure levels, allowing traders to:
Identify pivot-based supply and demand (SND) zones.
Use fixed criteria for trend continuation or reversals.
Filter out market noise by requiring structured price formations.
Enter trades based on breakouts of key SND pivot levels.
How the Rally Base Drop SND Pivots Strategy Works
1. Pivot Point Detection Using RBD Candles
The strategy follows a rigid market structure methodology, where pivots are detected only when:
A Rally (R) consists of multiple consecutive bullish candles.
A Drop (D) consists of multiple consecutive bearish candles.
A Base (B) is identified as a transition between Rallies and Drops, acting as a pivot point.
The pivot level is confirmed when the formation is complete.
Unlike traditional fractal-based pivots, RBD Pivots enforce stricter structural rules, ensuring that each pivot:
Has a well-defined bullish or bearish price movement.
Reduces false signals caused by single-bar fluctuations.
Provides clear supply and demand levels based on structured price movements.
These pivot levels are drawn on the chart using color-coded boxes:
Green zones represent bullish pivot levels (Rally Base formations).
Red zones represent bearish pivot levels (Drop Base formations).
Once a pivot is confirmed, the high or low of the base candle is used as the reference level for future trades.
2. Trade Entry Conditions
The strategy allows traders to select from three trading modes:
Long Only – Only takes long trades when bullish pivot breakouts occur.
Short Only – Only takes short trades when bearish pivot breakouts occur.
Long & Short – Trades in both directions based on pivot breakouts.
Trade entry signals are triggered when price breaks through a confirmed pivot level:
Long Entry:
A bullish pivot level is formed.
Price breaks above the bullish pivot level.
The strategy enters a long position.
Short Entry:
A bearish pivot level is formed.
Price breaks below the bearish pivot level.
The strategy enters a short position.
The strategy includes an optional mode to reverse long and short conditions, allowing traders to experiment with contrarian entries.
3. Exit Conditions Using ATR-Based Risk Management
This strategy uses the Average True Range (ATR) to calculate dynamic stop-loss and take-profit levels:
Stop-Loss (SL): Placed 1 ATR below entry for long trades and 1 ATR above entry for short trades.
Take-Profit (TP): Set using a Risk-Reward Ratio (RR) multiplier (default = 6x ATR).
When a trade is opened:
The entry price is recorded.
ATR is calculated at the time of entry to determine stop-loss and take-profit levels.
Trades exit automatically when either SL or TP is reached.
If reverse conditions mode is enabled, stop-loss and take-profit placements are flipped.
Visualization & Dynamic Support/Resistance Levels
1. Pivot Boxes for Market Structure
Each pivot is marked with a colored box:
Green boxes indicate bullish demand zones.
Red boxes indicate bearish supply zones.
These boxes remain on the chart to act as dynamic support and resistance levels, helping traders identify key price reaction zones.
2. Horizontal Entry, Stop-Loss, and Take-Profit Lines
When a trade is active, the strategy plots:
White line → Entry price.
Red line → Stop-loss level.
Green line → Take-profit level.
Labels display the exact entry, SL, and TP values, updating dynamically as price moves.
Customization Options
This strategy offers multiple adjustable settings to optimize performance for different market conditions:
Trade Mode Selection → Choose between Long Only, Short Only, or Long & Short.
Pivot Length → Defines the number of required Rally & Drop candles for a pivot.
ATR Exit Multiplier → Adjusts stop-loss distance based on ATR.
Risk-Reward Ratio (RR) → Modifies take-profit level relative to risk.
Historical Lookback → Limits how far back pivot zones are displayed.
Color Settings → Customize pivot box colors for bullish and bearish setups.
Considerations & Limitations
Pivot Breakouts Do Not Guarantee Reversals. Some pivot breaks may lead to continuation moves instead of trend reversals.
Not Optimized for Low Volatility Conditions. This strategy works best in trending markets with strong momentum.
ATR-Based Stop-Loss & Take-Profit May Require Optimization. Different assets may require different ATR multipliers and RR settings.
Market Noise May Still Influence Pivots. While this method filters some noise, fake breakouts can still occur.
Conclusion
The Rally Base Drop SND Pivots Strategy is a non-repainting supply and demand system that combines:
Pivot-based market structure analysis (using Rally, Base, and Drop candles).
Breakout-based trade entries at confirmed SND levels.
ATR-based dynamic risk management for stop-loss and take-profit calculation.
This strategy helps traders:
Identify high-probability supply and demand levels.
Trade based on structured market pivots.
Use a systematic approach to price action analysis.
Automatically manage risk with ATR-based exits.
The strict pivot detection rules and built-in breakout validation make this strategy ideal for traders looking to:
Trade based on market structure.
Use defined support & resistance levels.
Reduce noise compared to traditional fractals.
Implement a structured supply & demand trading model.
This strategy is fully customizable, allowing traders to adjust parameters to fit their market and trading style.
Full credit for the original concept and indicator goes to LuxAlgo.
