Fair Value Gap Oscillator | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Fair Value Gap Oscillator (FVG Oscillator) indicator! This unique indicator identifies and tracks Fair Value Gaps (FVGs) in price action, presenting them in an oscillator format to reveal market momentum based on FVG strength. It highlights bullish and bearish FVGs while enabling traders to adjust detection sensitivity and apply volume and ATR-based filters for more precise setups. For more information about the process, check the "📌 HOW DOES IT WORK" section.
Features of the new FVG Oscillator:
Fully Customizable FVG Detection
An Oscillator Approach To FVGs
Divergence Markers For Potential Reversals
Alerts For Divergence Labels
Customizable Styling
📌 HOW DOES IT WORK?
Fair Value Gaps are price gaps within bars that indicate inefficiencies, often filled as the market retraces. The FVG Oscillator scans historical bars to identify these gaps, then filters them based on ATR or volume. Each FVG is marked as bullish or bearish according to the trend direction that preceded its formation.
An oscillator is calculated using recent FVGs with this formula :
1. The Oscillator starts as 0.
2. When a new FVG Appears, it contributes (FVG Width / ATR) to the oscillator of the corresponding type.
3. Each confirmed bar, the oscillator is recalculated as OSC = OSC * (1 - Decay Coefficient)
The oscillator aggregates and decays past FVGs, allowing recent FVG activity to dominate the signal. This approach emphasizes current market momentum, with oscillations moving bullish or bearish based on FVG intensity. Divergences are marked where FVG oscillations suggest potential reversals. Bullish Divergence conditions are as follows :
1. The current candlestick low must be the lowest of last 25 bars.
2. Net Oscillator (Shown in gray line by default) must be > 0.
3. The current Bullish FVG Oscillator value should be no more than 0.1 below the highest value from the last 25 bars.
Traders can use divergence signals to get an idea of potential reversals, and use the Net FVG Oscillator as a trend following marker.
🚩 UNIQUENESS
The Fair Value Gap Oscillator stands out by converting FVG activity into an oscillator format, providing a momentum-based visualization of FVGs that reveals market sentiment dynamically. Unlike traditional indicators that statically mark FVG zones, the oscillator decays older FVGs over time, showing only the most recent, relevant activity. This approach allows for real-time insight into market conditions and potential reversals based on oscillating FVG strength, making it both intuitive and powerful for momentum trading.
Another unique feature is the combination of customizable ATR and volume filters, letting traders adapt the indicator to match their strategy and market type. You can also set-up alerts for bullish & bearish divergences.
⚙️ SETTINGS
1. General Configuration
Decay Coefficient -> The decay coefficient for oscillators. Increasing this setting will result in oscillators giving the weight to recent FVGs, while decreasing it will distribute the weight equally to the past and recent FVGs.
2. Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
3. Style
Divergence Labels On -> You can switch divergence labels to show up on the chart or the oscillator plot.
Komut dosyalarını "Divergence" için ara
Kurutoga Histogram with HTF and LTF
Kurutoga Histogram:
The Kurutoga Histogram is a technical analysis indicator designed to measure price divergence from the 50% level of a recent price range. By calculating how far the current price is from the midpoint of a selected base length of candles, the histogram provides insight into the momentum, strength, and potential reversals in the market. Additionally, it can be applied across multiple timeframes to provide a comprehensive view of both short- and long-term market dynamics.
Key Components:
Base Length:
The base length is the number of candles (bars) over which the high and low prices are observed. The default base length is typically 14 periods, but it can be adjusted according to the trader's preference.
This base length defines the range from which the 50% level, or midpoint, is calculated.
50% Level (Midpoint):
The midpoint is the average of the highest high and the lowest low over the selected base length. This 50% level acts as an equilibrium point around which the price fluctuates.
Formula:
Midpoint = (Highest High + Lowest Low) / 2
The price’s distance from this midpoint is an indicator of how strong the current trend or divergence is.
Price Divergence:
The main calculation of the histogram is the difference between the current closing price and the midpoint of the price range.
Formula:
Divergence = Close Price − Midpoint
A positive divergence (price above the midpoint) indicates bullish strength, while a negative divergence (price below the midpoint) indicates bearish strength.
Multi-Timeframe Analysis:
The Kurutoga Histogram can be applied to both the current timeframe and a higher timeframe (HTF), allowing traders to gauge price movement in both short-term and long-term contexts.
By comparing the histograms of multiple timeframes, traders can determine if there is alignment (confluence) between trends, which can strengthen trade signals or provide additional confirmation.
Color-Coded Histogram:
Blue Bars (Positive Divergence): Represent that the price is above the 50% level, indicating bullish momentum. Taller blue bars suggest stronger upward momentum, while shrinking bars suggest weakening strength.
Red Bars (Negative Divergence): Represent that the price is below the 50% level, indicating bearish momentum. Taller red bars suggest stronger downward momentum, while shrinking bars suggest a potential reversal or consolidation.
The histogram’s color intensity and transparency can be adjusted to enhance the visual effect, distinguishing between current timeframe (LTF) and higher timeframe (HTF) divergence.
Interpretation:
Bullish Signals: When the histogram bars are blue and growing, the price is gaining momentum above the midpoint of its recent range. This could signal an ongoing uptrend.
Bearish Signals: When the histogram bars are red and growing, the price is gaining momentum below the midpoint, signaling an ongoing downtrend.
Momentum Shifts: When the histogram bars shrink in size (whether blue or red), it could indicate that the current trend is losing strength and may reverse or enter consolidation.
Neutral or Sideways Movement: When the histogram bars hover around zero, it means the price is trading near the midpoint of its recent range, often signaling a lack of strong momentum in either direction.
Multi-Timeframe Confluence:
When the current timeframe (LTF) histogram aligns with the higher timeframe (HTF) histogram (e.g., both are showing strong bullish or bearish divergence), it may provide stronger confirmation of the trend's strength.
Divergence between timeframes (e.g., bullish on LTF but bearish on HTF) may suggest that price movements on lower timeframes are not yet reflected in the broader trend, signaling caution.
Applications:
Trend Identification: The Kurutoga Histogram is highly useful for detecting when the price is trending away from its equilibrium point, providing insight into the strength of ongoing trends.
Momentum Analysis: By measuring the divergence from the 50% level, the histogram helps traders identify when momentum is increasing or decreasing.
Reversal Detection: Shrinking histogram bars can signal weakening momentum, which often precedes trend reversals.
Consolidation and Breakouts: When the histogram remains near zero for an extended period, it suggests consolidation, which often precedes a breakout in either direction.
Advantages:
Clear Visuals: The use of a color-coded histogram makes it easy to visually assess whether the market is gaining bullish or bearish momentum.
Multi-Timeframe Utility: The ability to compare current timeframe signals with higher timeframe signals adds an extra layer of confirmation, reducing false signals.
Dynamic Adjustment: By adjusting the base length, traders can fine-tune the sensitivity of the indicator to match different markets or trading styles.
Limitations:
Lagging Indicator: Like most divergence indicators, the Kurutoga Histogram may lag slightly behind actual price movements, especially during fast, volatile markets.
Requires Confirmation: This indicator works best when used in conjunction with other technical tools like moving averages, support/resistance levels, or volume indicators, to avoid relying on divergence alone.
Conclusion:
The Kurutoga Histogram is a versatile and visually intuitive tool for measuring price divergence from a key equilibrium point, helping traders to assess the strength of trends and identify potential reversal points. Its use across multiple timeframes provides deeper insights, making it a valuable addition to any trading strategy that emphasizes momentum and trend following.
Simple Multi-Timeframe Trends with RSI (Realtime)Simple Multi-Timeframe Trends with RSI Realtime Updates
Overview
The Simple Multi-Timeframe Trends with RSI Realtime Updates indicator is a comprehensive dashboard designed to give you an at-a-glance understanding of market trends across nine key timeframes, from one minute (M1) to one month (M).
It moves beyond simple moving average crossovers by calculating a sophisticated Trend Score for each timeframe. This score is then intelligently combined into a single, weighted Confluence Signal , which adapts to your personal trading style. With integrated RSI and divergence detection, SMTT provides a powerful, all-in-one tool to confirm your trade ideas and stay on the right side of the market.
Key Features
Automatic Trading Presets: The most powerful feature of the script. Simply select your trading style, and the indicator will automatically adjust all internal parameters for you:
Intraday: Uses shorter moving averages and higher sensitivity, focusing on lower timeframe alignment for quick moves.
Swing Trading: A balanced preset using medium-term moving averages, ideal for capturing trends that last several days or weeks.
Investment: Uses long-term moving averages and lower sensitivity, prioritizing the major trends on high timeframes.
Advanced Trend Scoring: The trend for each timeframe isn't just "up" or "down". The score is calculated based on a combination of:
Price vs. Moving Average: Is the price above or below the MA?
MA Slope: Is the trend accelerating or decelerating? A steep slope indicates a strong trend.
Price Momentum: How quickly has the price moved recently?
Volatility Adjustment: The score's quality is adjusted based on current market volatility (using ATR) to filter out choppy conditions.
Weighted Confluence Score: The script synthesizes the trend scores from all nine timeframes into a single, actionable signal. The weights are dynamically adjusted based on your selected Trading Style , ensuring the most relevant timeframes have the most impact on the final result.
Integrated RSI & Divergence: Each timeframe includes a smoothed RSI value to help you spot overbought/oversold conditions. It also flags potential bullish (price lower, RSI higher) and bearish (price higher, RSI lower) divergences, which can be early warnings of a trend reversal.
Clean & Customizable Dashboard: The entire analysis is presented in a clean, easy-to-read table on your chart. You can choose its position and optionally display the raw numerical scores for a deeper analysis.
How to Use It
1. Add to Chart: Apply the "Simple Multi-Timeframe Trends" indicator to your chart.
2. Select Your Style: This is the most important step. Go to the indicator settings and choose the Trading Style that best fits your strategy (Intraday, Swing Trading, or Investment). All calculations will instantly adapt.
3. Analyze the Dashboard:
Look at the Trend row to see the direction and strength of the trend on individual timeframes. Strong alignment (e.g., all green or all red) indicates a powerful, market-wide move.
Check the RSI row. Is the trend overextended (RSI > 60) or is there room to run? Look for the fuchsia color, which signals a divergence and warrants caution.
Focus on the Signal row. This is your summary. A "STRONG SIGNAL" with high alignment suggests a high-probability setup. A "NEUTRAL" or "Weak" signal suggests waiting for a better opportunity.
4. Confirm Your Trades: Use the SMTT dashboard as a confirmation tool. For example, if you are looking for a long entry, wait for the dashboard to show a "BULLISH" or "STRONG SIGNAL" to confirm that the broader market structure supports your trade.
Dashboard Legend
Trend Row
This row shows the trend direction and strength for each timeframe.
⬆⬆ (Dark Green): Ultra Bullish - Very strong, established uptrend.
⬆ (Green): Strong Bullish - Confident uptrend.
▲ (Light Green): Bullish - The beginning of an uptrend or a weak uptrend.
━ (Orange): Neutral - Sideways or consolidating market.
▼ (Light Red): Bearish - The beginning of a downtrend or a weak downtrend.
⬇ (Red): Strong Bearish - Confident downtrend.
⬇⬇ (Dark Red): Ultra Bearish - Very strong, established downtrend.
RSI Row
This row displays the smoothed RSI value and its condition.
Green Text: Oversold (RSI < 40). Potential for a bounce or reversal upwards.
Red Text: Overbought (RSI > 60). Potential for a pullback or reversal downwards.
Fuchsia (Pink) Text: Divergence Detected! A potential reversal is forming.
White Text: Neutral (RSI between 40 and 60).
Signal Row
This is the final, weighted confluence of all timeframes.
Label:
🚀 STRONG SIGNAL / 💥 STRONG SIGNAL: High confluence and strong momentum.
🟢 BULLISH / 🔴 BEARISH: Clear directional bias across relevant timeframes.
🟡 Weak + / 🟠 Weak -: Minor directional bias, suggests caution.
⚪ NEUTRAL: No clear directional trend; market is likely choppy or undecided.
Numerical Score: The raw weighted confluence score. The further from zero, the stronger the signal.
Alignment %: The percentage of timeframes (out of 9) that are showing a clear bullish or bearish trend. Higher percentages indicate a more unified market.
Relative Strength Index With Range ZoneRSI (Relative Strength Index) with 45-55 Range Zone
1. Introduction and Historical Background
The Relative Strength Index (RSI) is a momentum indicator developed in 1978 by J. Welles Wilder Jr. It measures the speed and magnitude of price changes to assess overbought and oversold conditions of an asset. This widely used oscillator ranges between 0 and 100.
Historically, the RSI was mainly used to detect trend reversals by identifying extreme levels: above 70 (overbought) and below 30 (oversold). However, its application has evolved, and new approaches refine its interpretation, such as adding a 45-55 neutral zone to identify consolidation (range) periods.
2. RSI Calculation
The RSI is calculated using the following formula:
RSI=100−(1001+RS)RSI=100−(1+RS100)
Where:
RS=Average gain over N periodsAverage loss over N periodsRS=Average loss over N periodsAverage gain over N periods
• RS (Relative Strength) is the ratio between the average gains and the average losses over N periods (typically 14 periods).
• Gains and losses are calculated based on daily price variations.
Example calculation with a 14-day period:
1. Compute daily gains and losses.
2. Take an exponential or simple moving average of these values over 14 days.
3. Apply the formula to get the RSI value.
3. Classic RSI Usage
The RSI is typically interpreted as follows:
• RSI > 70: Overbought → Possible correction or bearish reversal.
• RSI < 30: Oversold → Possible rebound or bullish reversal.
• RSI between 50 and 70: Bullish momentum.
• RSI between 30 and 50: Bearish momentum.
4. Adding the 45-55 Zone to Identify Range Phases
Adding a neutral zone between 45 and 55 helps identify consolidation periods, when price moves sideways without a strong trend.
• RSI between 45 and 55: The market is in a range, meaning neither buyers nor sellers dominate.
• RSI breaking out of this zone:
o Above 55: Indicates the start of a bullish trend.
o Below 45: Indicates the start of a bearish trend.
This zone is particularly useful for:
• Avoiding false signals by waiting for trend confirmation.
• Identifying ranging markets, favoring range trading strategies (buying at support, selling at resistance).
• Filtering trend-based entries, waiting for the RSI to exit the 45-55 zone.
5. Trading Strategies Using RSI with the 45-55 Range Zone
1. Range Trading:
• When the RSI oscillates between 45 and 55, it signals a lack of strong trend.
• Strategy:
o Identify a support and resistance level.
o Buy near support when the RSI touches 45.
o Sell near resistance when the RSI touches 55.
2. Breakout Trading:
• If the RSI exits the 45-55 zone:
o Above 55 → Buy (start of a bullish trend).
o Below 45 → Sell (start of a bearish trend).
• This breakout can be used as a confirmed entry signal.
3. Confirmation with Divergences:
• A bullish divergence (price making lower lows while RSI makes higher lows) is more relevant if the RSI moves above 55.
• A bearish divergence (price making higher highs while RSI makes lower highs) is stronger if the RSI drops below 45.
6. Conclusion
The RSI is a powerful tool for analyzing price momentum. Adding a 45-55 zone enhances its usage by clearly distinguishing:
• Consolidation phases (range markets).
• Trend beginnings when RSI breaks out of this range.
This approach improves RSI reliability by filtering out false signals and allowing traders to adapt their strategy based on market conditions.
Adaptive MA-Bollinger HistogramVisualize two of your favorite moving averages in a fun new way.
This script calculates the distance (or difference) between the price and two moving averages of your choosing and then creates two histograms.
The two histograms are plotted inversely, so if the price is over both moving averages, one will be positive above the centerline while the other still positive will be below the centerline.
(In a future update you will have the option to have them both positive at the same time)
Next, what it does is apply Bollinger Bands (optional) to each of the histograms.
This creates a very interesting effect that can highlight areas of interest you may miss with other indicators.
You have plenty of options for coloring, the type of moving average, Bollinger Band length, and toggling features on and off.
Give it a few minutes of your time to study, and see what information you can learn from watching this indicator by comparing it with the chart.
Here is a full user guide:
Adaptive MA-Bollinger Histogram Indicator User Guide
Welcome to the user guide for the **Adaptive MA-Bollinger Histogram** indicator. This custom indicator is designed to help traders analyze trends and potential reversals in a financial instrument's price movements. The indicator combines two Moving Averages (MA) and Bollinger Bands to provide valuable insights into market conditions.
### Indicator Overview
The Adaptive MA-Bollinger Histogram indicator comprises the following components:
1. **Moving Averages (MA1 and MA2):** The indicator uses two moving averages, namely MA1 and MA2, to track different time periods. MA1 has a user-defined length (default: 50) and MA2 has a longer user-defined length (default: 100). These moving averages can be calculated using different methods such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), or Smoothed Moving Average (RMA).
2. **Histograms:** The indicator displays histograms based on the differences between the price source and the respective moving averages. Positive values of the histogram for MA1 are plotted in one color (default: green), while negative values are plotted in another color (default: red). Similarly, positive values of the histogram for MA2 are plotted in one color (default: blue), while negative values are plotted in another color (default: yellow). It's important to note that the histogram for MA1 is plotted positively, while the histogram for MA2 is plotted inversely.
3. **Bollinger Bands:** The indicator also features Bollinger Bands calculated based on the differences between the price source and the respective moving averages (dist1 and dist2). Bollinger Bands consist of three lines: the middle band, upper band, and lower band. These bands help visualize the potential volatility and overbought/oversold levels of the instrument's price.
### Understanding the Indicator
- **Histograms:** The histograms highlight the divergence between the price and the two moving averages. When the histogram for MA1 is positive, it indicates that the price is above the MA1. Conversely, when the histogram for MA1 is negative, it suggests that the price is below the MA1. Similarly, the histogram for MA2 is plotted inversely.
- **Bollinger Bands:** The Bollinger Bands consist of three lines. The middle band represents the moving average (MA1 or MA2), while the upper and lower bands are calculated based on the standard deviation of the differences between the price source and the moving average. The bands expand during periods of higher volatility and contract during periods of lower volatility.
### Possible Trading Ideas
1. **Trend Confirmation:** When the histograms for both MA1 and MA2 are consistently positive, it may indicate a strong bullish trend. Conversely, when both histograms are consistently negative, it may suggest a strong bearish trend.
2. **Divergence:** Divergence between price and the histograms could signal potential reversals. For example, if the price is making new highs while the histogram is declining, it might indicate a bearish divergence and a possible upcoming trend reversal.
3. **Bollinger Bands Squeeze:** A narrowing of the Bollinger Bands indicates lower volatility and often precedes a significant price movement. Traders might consider a potential breakout trade when the bands start to expand again.
4. **Overbought/Oversold Levels:** Prices touching or exceeding the upper Bollinger Band could suggest overbought conditions, while prices touching or falling below the lower Bollinger Band could indicate oversold conditions. Traders might look for reversals or corrections in such scenarios.
### Customization
- You can adjust the parameters such as MA lengths, Bollinger Bands length, width, and colors to suit your preferences and trading strategy.
### Conclusion
The **Adaptive MA-Bollinger Histogram** indicator provides a comprehensive view of price trends, divergences, and potential reversal points. Traders can use the information from this indicator to make informed decisions in their trading strategies. However, like any technical tool, it's recommended to combine this indicator with other forms of analysis and risk management techniques for optimal results.
ProRSIProRSI is another in indicator to add to the Pro Indicator suite by DynaProTrading. This algo is made up of a few key components referenced below.
RSI: The primary function of the algo is to plot the candles of the ticker of choice on an oscillator pane to show how price compared to the various key levels. As you can see the red and blue arrows indicator oversold and overbought levels in conjunction with price.
Divergences: In addition to the RSI alerts, there is also a divergence functions where price could be making a higher high but the RSI indicator is making a lower high which is indicating a divergence in price. This is displayed by the lines in the lower window pane from one peak to another.
Trend Lines: Trend lines exist in all technical analysis but in this indicator, it shows the trend lines of the candles in the RSI pane which can help find support and resistance just like with normal price action.
Regression Model: The last key component of the indicator is a regression model which acts as a trend channel for more recent price action.
Bogdan Ciocoiu - Code runnerDescription
The Code Runner is a hybrid indicator that leverages other pre-configured, integrated open-source algorithms to help traders spot regular and continuation divergences.
The Code Runner specialises in integrating some of the most popular oscillators well known for their accuracy when scalping using divergence strategies.
Uniqueness
The Code Runner stands out as a one-stop-shop pack of oscillator algorithms that traders can further customise to spot divergences.
The indicator's uniqueness stands from its capability to recast each algorithm to apply to the same scale. This feature is achieved by manually adjusting the outputs of each algorithm to fit on a scale between +100 and -100.
Another benefit of the Code Runner comes from its standardisation of outputs, mainly consisting of lines. Showing lines enables traders to draw potential regular and continuation divergences quickly.
The indicator has been pre-configured to support scalping at 1-5 minutes.
Open-source
The Code Runner uses the following open-source scripts and algorithms:
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
These algorithms are available in the public domain either in TradingView space or outside (given their popularity in the financial markets industry).
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
OBV with MA & Bollinger Bands by Marius1032OBV with MA & Bollinger Bands by Marius1032
This script adds customizable moving averages and Bollinger Bands to the classic OBV (On Balance Volume) indicator. It helps identify volume-driven momentum and trend strength.
Features:
OBV-based trend tracking
Optional smoothing: SMA, EMA, RMA, WMA, VWMA
Optional Bollinger Bands with SMA
Potential Combinations and Trading Strategies:
Breakouts: Look for price breakouts from the Bollinger Bands, and confirm with a rising OBV for an uptrend or falling OBV for a downtrend.
Trend Reversals: When the price touches a Bollinger Band, examine the OBV for divergence. A bullish divergence (price lower low, OBV higher low) near the lower band could signal a reversal.
Volume Confirmation: Use OBV to confirm the strength of the trend indicated by Bollinger Bands. For example, if the BBs indicate an uptrend and OBV is also rising, it reinforces the bullish signal.
1. On-Balance Volume (OBV):
Purpose: OBV is a momentum indicator that uses volume flow to predict price movements.
Calculation: Volume is added on up days and subtracted on down days.
Interpretation: Rising OBV suggests potential upward price movement. Falling OBV suggests potential lower prices.
Divergence: Divergence between OBV and price can signal potential trend reversals.
2. Moving Average (MA):
Purpose: Moving Averages smooth price fluctuations and help identify trends.
Combination with OBV: Pairing OBV with MAs helps confirm trends and identify potential reversals. A crossover of the OBV line and its MA can signal a trend reversal or continuation.
3. Bollinger Bands (BB):
Purpose: BBs measure market volatility and help identify potential breakouts and trend reversals.
Structure: They consist of a moving average (typically 20-period) and two standard deviation bands.
Combination with OBV: Combining BBs with OBV allows for a multifaceted approach to market analysis. For example, a stock hitting the lower BB with a rising OBV could indicate accumulation and a potential upward reversal.
Created by: Marius1032
Risk-Adjusted Momentum Oscillator# Risk-Adjusted Momentum Oscillator (RAMO): Momentum Analysis with Integrated Risk Assessment
## 1. Introduction
Momentum indicators have been fundamental tools in technical analysis since the pioneering work of Wilder (1978) and continue to play crucial roles in systematic trading strategies (Jegadeesh & Titman, 1993). However, traditional momentum oscillators suffer from a critical limitation: they fail to account for the risk context in which momentum signals occur. This oversight can lead to significant drawdowns during periods of market stress, as documented extensively in the behavioral finance literature (Kahneman & Tversky, 1979; Shefrin & Statman, 1985).
The Risk-Adjusted Momentum Oscillator addresses this gap by incorporating real-time drawdown metrics into momentum calculations, creating a self-regulating system that automatically adjusts signal sensitivity based on current risk conditions. This approach aligns with modern portfolio theory's emphasis on risk-adjusted returns (Markowitz, 1952) and reflects the sophisticated risk management practices employed by institutional investors (Ang, 2014).
## 2. Theoretical Foundation
### 2.1 Momentum Theory and Market Anomalies
The momentum effect, first systematically documented by Jegadeesh & Titman (1993), represents one of the most robust anomalies in financial markets. Subsequent research has confirmed momentum's persistence across various asset classes, time horizons, and geographic markets (Fama & French, 1996; Asness, Moskowitz & Pedersen, 2013). However, momentum strategies are characterized by significant time-varying risk, with particularly severe drawdowns during market reversals (Barroso & Santa-Clara, 2015).
### 2.2 Drawdown Analysis and Risk Management
Maximum drawdown, defined as the peak-to-trough decline in portfolio value, serves as a critical risk metric in professional portfolio management (Calmar, 1991). Research by Chekhlov, Uryasev & Zabarankin (2005) demonstrates that drawdown-based risk measures provide superior downside protection compared to traditional volatility metrics. The integration of drawdown analysis into momentum calculations represents a natural evolution toward more sophisticated risk-aware indicators.
### 2.3 Adaptive Smoothing and Market Regimes
The concept of adaptive smoothing in technical analysis draws from the broader literature on regime-switching models in finance (Hamilton, 1989). Perry Kaufman's Adaptive Moving Average (1995) pioneered the application of efficiency ratios to adjust indicator responsiveness based on market conditions. RAMO extends this concept by incorporating volatility-based adaptive smoothing, allowing the indicator to respond more quickly during high-volatility periods while maintaining stability during quiet markets.
## 3. Methodology
### 3.1 Core Algorithm Design
The RAMO algorithm consists of several interconnected components:
#### 3.1.1 Risk-Adjusted Momentum Calculation
The fundamental innovation of RAMO lies in its risk adjustment mechanism:
Risk_Factor = 1 - (Current_Drawdown / Maximum_Drawdown × Scaling_Factor)
Risk_Adjusted_Momentum = Raw_Momentum × max(Risk_Factor, 0.05)
This formulation ensures that momentum signals are dampened during periods of high drawdown relative to historical maximums, implementing an automatic risk management overlay as advocated by modern portfolio theory (Markowitz, 1952).
#### 3.1.2 Multi-Algorithm Momentum Framework
RAMO supports three distinct momentum calculation methods:
1. Rate of Change: Traditional percentage-based momentum (Pring, 2002)
2. Price Momentum: Absolute price differences
3. Log Returns: Logarithmic returns preferred for volatile assets (Campbell, Lo & MacKinlay, 1997)
This multi-algorithm approach accommodates different asset characteristics and volatility profiles, addressing the heterogeneity documented in cross-sectional momentum studies (Asness et al., 2013).
### 3.2 Leading Indicator Components
#### 3.2.1 Momentum Acceleration Analysis
The momentum acceleration component calculates the second derivative of momentum, providing early signals of trend changes:
Momentum_Acceleration = EMA(Momentum_t - Momentum_{t-n}, n)
This approach draws from the physics concept of acceleration and has been applied successfully in financial time series analysis (Treadway, 1969).
#### 3.2.2 Linear Regression Prediction
RAMO incorporates linear regression-based prediction to project momentum values forward:
Predicted_Momentum = LinReg_Value + (LinReg_Slope × Forward_Offset)
This predictive component aligns with the literature on technical analysis forecasting (Lo, Mamaysky & Wang, 2000) and provides leading signals for trend changes.
#### 3.2.3 Volume-Based Exhaustion Detection
The exhaustion detection algorithm identifies potential reversal points by analyzing the relationship between momentum extremes and volume patterns:
Exhaustion = |Momentum| > Threshold AND Volume < SMA(Volume, 20)
This approach reflects the established principle that sustainable price movements require volume confirmation (Granville, 1963; Arms, 1989).
### 3.3 Statistical Normalization and Robustness
RAMO employs Z-score normalization with outlier protection to ensure statistical robustness:
Z_Score = (Value - Mean) / Standard_Deviation
Normalized_Value = max(-3.5, min(3.5, Z_Score))
This normalization approach follows best practices in quantitative finance for handling extreme observations (Taleb, 2007) and ensures consistent signal interpretation across different market conditions.
### 3.4 Adaptive Threshold Calculation
Dynamic thresholds are calculated using Bollinger Band methodology (Bollinger, 1992):
Upper_Threshold = Mean + (Multiplier × Standard_Deviation)
Lower_Threshold = Mean - (Multiplier × Standard_Deviation)
This adaptive approach ensures that signal thresholds adjust to changing market volatility, addressing the critique of fixed thresholds in technical analysis (Taylor & Allen, 1992).
## 4. Implementation Details
### 4.1 Adaptive Smoothing Algorithm
The adaptive smoothing mechanism adjusts the exponential moving average alpha parameter based on market volatility:
Volatility_Percentile = Percentrank(Volatility, 100)
Adaptive_Alpha = Min_Alpha + ((Max_Alpha - Min_Alpha) × Volatility_Percentile / 100)
This approach ensures faster response during volatile periods while maintaining smoothness during stable conditions, implementing the adaptive efficiency concept pioneered by Kaufman (1995).
### 4.2 Risk Environment Classification
RAMO classifies market conditions into three risk environments:
- Low Risk: Current_DD < 30% × Max_DD
- Medium Risk: 30% × Max_DD ≤ Current_DD < 70% × Max_DD
- High Risk: Current_DD ≥ 70% × Max_DD
This classification system enables conditional signal generation, with long signals filtered during high-risk periods—a approach consistent with institutional risk management practices (Ang, 2014).
## 5. Signal Generation and Interpretation
### 5.1 Entry Signal Logic
RAMO generates enhanced entry signals through multiple confirmation layers:
1. Primary Signal: Crossover between indicator and signal line
2. Risk Filter: Confirmation of favorable risk environment for long positions
3. Leading Component: Early warning signals via acceleration analysis
4. Exhaustion Filter: Volume-based reversal detection
This multi-layered approach addresses the false signal problem common in traditional technical indicators (Brock, Lakonishok & LeBaron, 1992).
### 5.2 Divergence Analysis
RAMO incorporates both traditional and leading divergence detection:
- Traditional Divergence: Price and indicator divergence over 3-5 periods
- Slope Divergence: Momentum slope versus price direction
- Acceleration Divergence: Changes in momentum acceleration
This comprehensive divergence analysis framework draws from Elliott Wave theory (Prechter & Frost, 1978) and momentum divergence literature (Murphy, 1999).
## 6. Empirical Advantages and Applications
### 6.1 Risk-Adjusted Performance
The risk adjustment mechanism addresses the fundamental criticism of momentum strategies: their tendency to experience severe drawdowns during market reversals (Daniel & Moskowitz, 2016). By automatically reducing position sizing during high-drawdown periods, RAMO implements a form of dynamic hedging consistent with portfolio insurance concepts (Leland, 1980).
### 6.2 Regime Awareness
RAMO's adaptive components enable regime-aware signal generation, addressing the regime-switching behavior documented in financial markets (Hamilton, 1989; Guidolin, 2011). The indicator automatically adjusts its parameters based on market volatility and risk conditions, providing more reliable signals across different market environments.
### 6.3 Institutional Applications
The sophisticated risk management overlay makes RAMO particularly suitable for institutional applications where drawdown control is paramount. The indicator's design philosophy aligns with the risk budgeting approaches used by hedge funds and institutional investors (Roncalli, 2013).
## 7. Limitations and Future Research
### 7.1 Parameter Sensitivity
Like all technical indicators, RAMO's performance depends on parameter selection. While default parameters are optimized for broad market applications, asset-specific calibration may enhance performance. Future research should examine optimal parameter selection across different asset classes and market conditions.
### 7.2 Market Microstructure Considerations
RAMO's effectiveness may vary across different market microstructure environments. High-frequency trading and algorithmic market making have fundamentally altered market dynamics (Aldridge, 2013), potentially affecting momentum indicator performance.
### 7.3 Transaction Cost Integration
Future enhancements could incorporate transaction cost analysis to provide net-return-based signals, addressing the implementation shortfall documented in practical momentum strategy applications (Korajczyk & Sadka, 2004).
## References
Aldridge, I. (2013). *High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems*. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Ang, A. (2014). *Asset Management: A Systematic Approach to Factor Investing*. New York: Oxford University Press.
Arms, R. W. (1989). *The Arms Index (TRIN): An Introduction to the Volume Analysis of Stock and Bond Markets*. Homewood, IL: Dow Jones-Irwin.
Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. *Journal of Finance*, 68(3), 929-985.
Barroso, P., & Santa-Clara, P. (2015). Momentum has its moments. *Journal of Financial Economics*, 116(1), 111-120.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. New York: McGraw-Hill.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. *Journal of Finance*, 47(5), 1731-1764.
Calmar, T. (1991). The Calmar ratio: A smoother tool. *Futures*, 20(1), 40.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). *The Econometrics of Financial Markets*. Princeton, NJ: Princeton University Press.
Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. *International Journal of Theoretical and Applied Finance*, 8(1), 13-58.
Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. *Journal of Financial Economics*, 122(2), 221-247.
Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. *Journal of Finance*, 51(1), 55-84.
Granville, J. E. (1963). *Granville's New Key to Stock Market Profits*. Englewood Cliffs, NJ: Prentice-Hall.
Guidolin, M. (2011). Markov switching models in empirical finance. In D. N. Drukker (Ed.), *Missing Data Methods: Time-Series Methods and Applications* (pp. 1-86). Bingley: Emerald Group Publishing.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. *Econometrica*, 57(2), 357-384.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. *Journal of Finance*, 48(1), 65-91.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. *Econometrica*, 47(2), 263-291.
Kaufman, P. J. (1995). *Smarter Trading: Improving Performance in Changing Markets*. New York: McGraw-Hill.
Korajczyk, R. A., & Sadka, R. (2004). Are momentum profits robust to trading costs? *Journal of Finance*, 59(3), 1039-1082.
Leland, H. E. (1980). Who should buy portfolio insurance? *Journal of Finance*, 35(2), 581-594.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. *Journal of Finance*, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. *Journal of Finance*, 7(1), 77-91.
Murphy, J. J. (1999). *Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications*. New York: New York Institute of Finance.
Prechter, R. R., & Frost, A. J. (1978). *Elliott Wave Principle: Key to Market Behavior*. Gainesville, GA: New Classics Library.
Pring, M. J. (2002). *Technical Analysis Explained: The Successful Investor's Guide to Spotting Investment Trends and Turning Points*. 4th ed. New York: McGraw-Hill.
Roncalli, T. (2013). *Introduction to Risk Parity and Budgeting*. Boca Raton, FL: CRC Press.
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. *Journal of Finance*, 40(3), 777-790.
Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable*. New York: Random House.
Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. *Journal of International Money and Finance*, 11(3), 304-314.
Treadway, A. B. (1969). On rational entrepreneurial behavior and the demand for investment. *Review of Economic Studies*, 36(2), 227-239.
Wilder, J. W. (1978). *New Concepts in Technical Trading Systems*. Greensboro, NC: Trend Research.
Advanced Averaged Momentum Indicator (AAMI)Key Features of AAMI:
Combination of Momentum Indicators: It averages normalized values from RSI, MACD histogram, raw Momentum, and Stochastic oscillator to give a comprehensive view of momentum.
Normalization: Each component is normalized to a scale from -1 to 1 to ensure they contribute equally to the AMI calculation.
Visual Cues: The indicator includes visual levels for neutral, overbought, and oversold conditions to aid in quick decision-making.
Alerts: Basic alert conditions are included for when AMI moves into overbought or oversold territory, which traders can customize further.
Customizable: All parameters can be adjusted within TradingView to tailor the indicator to different market conditions or trading strategies.
Smoothing: Included an SMA for AMI to reduce noise and give smoother signals.
Divergence Detection: Implemented a basic divergence detection mechanism to spot potential reversals.
Usage Tips:
Overbought/Oversold: When AMI goes above 0.7, it might suggest an overbought condition, potentially signaling a sell or take profit. Below -0.7 might indicate oversold conditions, suggesting a buy opportunity.
Divergence: Watch for divergences between the AMI and price action for signals of potential trend reversals.
Crossing Zero: The AMI crossing from negative to positive might be used as a buy signal, and vice versa for a sell signal.
This script provides a new way to view momentum by consolidating multiple traditional indicators into one, potentially offering clearer signals in complex market environments.
G&S SMT### Description of the Pine Script
This Pine Script is designed to identify **Smart Money Technique (SMT)** setups between **Gold (GC1!)** and **Silver (SI1!) Futures** on a **15-minute timeframe**. It specifically looks for divergences between the price movements of Gold and Silver over the last 4 candles and compares it with the next candle's price movement. The script provides **Bullish** and **Bearish** signals for SMT during a specified time range of **8:45 AM EST to 10:30 AM EST**.
### Key Features of the Script:
1. **Futures Symbols**:
- The script uses **Gold Futures (GC1!)** and **Silver Futures (SI1!)** on a 15-minute timeframe to monitor their price movements.
2. **Time Range Filtering**:
- The signals are only active between **8:45 AM EST and 10:30 AM EST**, ensuring that the script only signals within the most relevant trading hours for your strategy.
3. **SMT Calculation (Last 4 Candles vs Next Candle)**:
- **Gold and Silver Price Change Calculation**: The script compares the price changes of **Gold** and **Silver** over the **last 4 candles** and then compares them with the price movement of the **next candle**:
- **Bullish SMT**: Occurs when Gold shows an increase in the last 4 candles while Silver shows a decrease, and both Gold and Silver show an increase in the next candle.
- **Bearish SMT**: Occurs when Gold shows a decrease in the last 4 candles while Silver shows an increase, and both Gold and Silver show a decrease in the next candle.
4. **Bullish and Bearish Signals**:
- **Bullish SMT Signal**: The script will plot a **green** arrow below the bar when a Bullish SMT setup is identified.
- **Bearish SMT Signal**: A **red** arrow above the bar is plotted when a Bearish SMT setup is identified.
5. **Gold and Silver Difference Plot**:
- The difference between the prices of **Gold** and **Silver** is plotted as a **blue line**, giving a visual representation of the relationship between the two assets. When the difference line moves significantly, it can indicate a potential divergence or convergence in the prices of Gold and Silver.
### Script Logic Breakdown:
1. **Price Change for Last 4 Candles**:
- The script calculates the price change for Gold and Silver from the 4th-to-last candle to the last candle.
- `gold_change_last4` and `silver_change_last4` calculate these price differences.
2. **Price Change for Next Candle**:
- It then calculates the price change from the last candle to the next candle.
- `gold_change_next` and `silver_change_next` calculate these price differences.
3. **Bullish SMT Condition**:
- If Gold increased while Silver decreased in the last 4 candles, and both Gold and Silver show an increase in the next candle, it indicates a **Bullish SMT**.
4. **Bearish SMT Condition**:
- If Gold decreased while Silver increased in the last 4 candles, and both Gold and Silver show a decrease in the next candle, it indicates a **Bearish SMT**.
5. **Time Filter**:
- Signals are only plotted when the current time is between **8:45 AM EST and 10:30 AM EST** to match your preferred trading hours.
### Visualization:
- **Bullish Signals**: Plotted as **green arrows** below the bars when a Bullish SMT setup is identified.
- **Bearish Signals**: Plotted as **red arrows** above the bars when a Bearish SMT setup is identified.
- **Gold - Silver Difference**: A **blue line** is plotted to show the price difference between Gold and Silver, helping visualize any divergence.
### How It Helps:
- **Divergence Identification**: This script highlights potential divergences between Gold and Silver Futures, which can provide insights into market sentiment and smart money movements.
- **Focus on Relevant Time Frame**: By filtering signals between 8:45 AM EST and 10:30 AM EST, you are focusing on a timeframe that can be more beneficial for trading.
- **Visual Clarity**: The arrows and the price difference line provide clear signals and a visual representation of the relationship between Gold and Silver, helping you make informed trading decisions.
This script is an automated approach to detecting **SMT setups** and helping traders recognize when Gold and Silver might be signaling a bullish or bearish move based on their divergence patterns.
[blackcat] L1 Enveloped Oscillator█ OVERVIEW
The script is an indicator named “ L1 Enveloped Oscillator” (L1 EO) designed to plot various trend and oscillator values on a separate chart pane. It calculates multiple indicators such as trend, adjusted trend, oscillator, directional strength, and normalized oscillator, and uses these to detect potential buy and sell signals based on trend contractions, expansions, and divergences.
█ LOGICAL FRAMEWORK
Structure:
1 — Input Parameters: None are explicitly defined, but the script is parameterized within the function with fixed values for levels and periods.
2 — Calculations: The calculate_l1_enveloped_oscillator function computes multiple values including price bases, trend, oscillator, and adjusted trends. This function uses built-in Pine Script functions like ta.highest, ta.lowest, ta.ema, ta.sma, and math.max.
3 — Plotting: The calculated values are plotted on the chart using the plot function, with different colors and styles for visual distinction.
4 — Signal Detection: The script detects and labels potential buy and sell signals based on trend contractions, expansions, and divergences between the price and oscillator.
5 — Conditional Statements: Multiple if statements are used to determine when to place labels for buy and sell signals.
█ CUSTOM FUNCTIONS
• calculate_l1_enveloped_oscillator(high, low, close, open): Calculates various trend and oscillator values based on the input price data.
— Parameters: high, low, close, open (price data).
— Return Values: A tuple containing top_level, bottom_level, middle_level, adjusted_trend, trend, oscillator, directional_strength, normalized_oscillator, and adjusted_candle_trend.
█ KEY POINTS AND TECHNIQUES
• Advanced Pine Script Features: Utilizes built-in functions for technical analysis (ta.highest, ta.lowest, ta.ema, ta.sma, ta.crossover, ta.crossunder).
• Optimization Techniques: Uses fixed periods and levels for calculations, which can be adjusted for different market conditions.
• Best Practices: Clearly separates calculations and plotting, making the script modular and easier to maintain.
• Unique Approaches: Combines multiple indicators (trend, oscillator, directional strength) to detect complex market conditions like divergences and contractions/expansions.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: Users can modify the levels (top_level, bottom_level, middle_level) and periods used in calculations to better suit specific asset classes or market conditions.
• Extensions: The script can be extended to include additional indicators or signals, such as RSI or MACD, to enhance its predictive power.
• Application Scenarios: Similar techniques can be applied in other trading strategies involving trend analysis and divergence detection, such as momentum trading or mean reversion strategies.
• Related Concepts: Users can explore other Pine Script concepts like alerts, backtesting, and optimization to fine-tune strategies based on historical data.
Atareum Volume Ichimuku CandleAVIC (Atareum Volume Ichimoku Candles) is clearly an awesome indicator that is based on Ichimoku concepts by combination with volume. This is a new approach of volume candles that is combined with Ichimoku concepts and creates such a powerful tool to trace the market and assists traders to make better decisions, truly.
Concept:
Using Ichimoku leading periods and calculations on redesigning new candles in combination with volume, that makes unique reform candles on Tenkansen movement, but these new candles clearly omit noises in combination with volume, and then the new redesigned system of cloud calculations builds, new series of data for Senko Span A and Senko Span B which is so odd in first view, because they will barely ever cross each other, but they show very more informative and useful.
Parameters:
Section 1 : Candle colour setting for flourishing just as you desire !
Section 2 : Defining Periods of standard Ichimoku and source of candle data in combination with determining the smoothing type of moving averages and signal period.
Section 3 : Select using Heikin Ashi based candles alongside with redesigned cloud calculation type and three additional moving averages which can plot on each newly generated candles and standard candles on a chart with the type mode defined in the previous section.
Note: if you want to omit any or all of these moving averages, you can use 0 in period, instead of selecting "None" in the plot moving option!
Usage :
Overall:
Regardless of the additional moving averages which will lead to so many situations of market according to their types and designs, that is four different period for new redesign AVIC and three period for standard chart. You can easily select periods and type for these moving averages. Also, do not forget that signal moving averages is shown only on AVIC chart and have two different colour for upward and downward trends. Other moving averages are plot by just one single colour.
Cloud levels are so important because AVIC candles show respect to them and when they break the clouds upward or downward it's surly beginning of a trend that is may last long. Also when cloud levels flatten, it is determining a support or resistance according to up cloud or down cloud nature and as long as they will continue or repeated periodically on same level of AVIC chart, it will implement their weakness or strength.
Support and Resistance:
Any flattens of cloud up or down level means the support or resistance level due to its nature, but important thing is how long the cloud lasts flatten or how many times repeated in the same level in AVIC chart.
For plotting the support or resistance you should trace first candle of start of flattens in standard chart just like following picture.
Divergence:
All Higher high or Lower low of standard chart has its reflect in AVIC chart but there is secret in it, It is named divergence. When standard chart price candles generating lower low but the AVIC chart candles do not cross the bottom, it means we will spike high as soon as AVIC candle chart complete its divergence. You can see perfect example in following picture.
Cloud level Ends
When cloud down level become flattens and cloud up level start a bull run it means we will face a great up trend movement but as soon as cloud down level starts to move up it mean we are going to finish the bull run and maybe it goes with consolidation phase or reversal phase. This reaction is exactly happen in vice versa for bear run trend. You can see both examples in following pictures.
Note: if we face end of bull run and cloud down level make a U turn shape upside down it means we will have reversal phase even not too long but it is sharp and fast reversal. If cloud down level just turn right slightly, it means we should have consolidation phase, mostly or we can continue the last trend slightly. All these situations can happen in vice versa bear run. You can see example in following picture.
Signals:
Long but risky:
You can go long when AVIC candles are green and be in position as long as they are not change in colour.
Long and safe :
You can go long when AVIC candles cross up cloud down level and be in position as long as AVIC candles cross down cloud up level.
Long and sure:
You can go long when AVIC candles cross up cloud up level and be in position as long as AVIC candles cross down cloud down level.
Short but risky:
You can go short when AVIC candles are red and be in position as long as they are not change in colour.
Short and safe :
You can go short when AVIC candles cross down cloud up level and be in position as long as AVIC candles cross up cloud down level.
Short and sure:
You can go short when AVIC candles cross down cloud down level and be in position as long as AVIC candles cross up cloud up level.
Notice : Candles with large body are so strong but if a body candle is weak or flatten it may a signal of changing colour and direction, especially when using Heikin Ashi type.
It is the result of many years of experience in markets and there are so many details about this AVIC chart which I am in the experiment phase to publish in the future, so please help me with your ideas and do not hesitate to comment and inform me any suggestions or criticism.
Introducing the "Smart Money Trap" (SMT) IndicatorThe "Smart Money Trap" (SMT) indicator is a powerful tool designed for simultaneous analysis of multiple currency pairs and their correlations. This indicator allows you to effortlessly visualize divergences and correlations between various currency pairs on a single chart, enhancing your ability to perform in-depth technical analysis.
Key Features:
Multi-Currency Comparison:
The SMT indicator enables you to view the following currency pairs simultaneously:
EUR/USD (Euro to US Dollar)
GBP/USD (British Pound to US Dollar)
USD/JPY (US Dollar to Japanese Yen)
DXY (US Dollar Index)
Correlation and Divergence Analysis:
By overlaying these currency pairs, the SMT indicator helps you identify correlations and divergences between them, which can signal potential trading opportunities.
Customizable Timeframes:
The indicator automatically adjusts to the current chart’s timeframe, ensuring that your analysis is always in sync with the selected period.
Enhanced Decision-Making:
With the ability to visualize multiple currency pairs and their relationships, you can make more informed trading decisions and better understand market dynamics.
The SMT indicator is a valuable tool for traders looking to track and analyze currency pair interactions and identify trading signals based on their correlations and divergences.
AoDivergenceLibrary_Library "AoDivergenceLibrary_"
this has functions which calculate and plot divergences which are used for ao divergences. essentially, this finds divergences by using the ao divergence logic. this logic has been used in "AO Hid & Reg Div with LC & Kernel".
regBullDivergence(swingLow, osc, colour)
Parameters:
swingLow (bool)
osc (float)
colour (color)
regBearDivergence(swingHigh, osc, colour)
Parameters:
swingHigh (bool)
osc (float)
colour (color)
hidBullDivergence(swingHigh, osc, colour)
Parameters:
swingHigh (bool)
osc (float)
colour (color)
hidBearDivergence(swingHigh, osc, colour)
Parameters:
swingHigh (bool)
osc (float)
colour (color)
Money Flow LineWhat is this? The Money Flow Line (MFL) indicator is at its core a more even-tempered version of the Price-Volume-Trend (PVT). The primary difference is the usage of `hlc3` ((high + low + close) / 3) rather than `close` to use the "typical price" that it critical to the calculation of the Money Flow Index (MFI). Other similar indicators include the Accumulation Distribution Line (ADL) and the On Balance Volume (OBV) indicators. The purpose of all of these indicators is to attempt to measure the strength of the money flow by combining price and volume into a rolling measurement that can be compared over time to look for confirmations and divergences.
The indicator also includes an optional averaging (smoothing) line that can be enabled in the display settings. Enabling this smoothing line with a desired period allows for simpler trend comparisons and also allows the user to view how far the line has diverged from the mean. This creates an indicator very similar to Elder's Force Index (EFI), which is also a `close * volume` style indicator.
Why is this important? After an extreme movement or volume spike the MFI will "snap back" sharply as that bar eventually exits the set period. This produces a result that is meaningless and skews the indicator away from the market structure. Because of this behavior, range clamping, and the loss of comparative history I prefer to shy away from oscillator style indicators. The Money Flow Line instead gives you all of the history so you may compare and see the broader trend without sharp snaps in history based on an arbitrary period setting.
Why is this better? This produces a no-lag indicator that isn't subject to the harsh skewing produced by they Money Flow Index's period calculation. It doesn't lose history like MFI or EFI, is clear about the trend direction, and prefers a "typical price" (averaging the entire range of each bar) rather than whatever happens to be the closing price for a given bar.
How can I use it? The indicator is attempting to measure supply and demand in the markets. No indicator is perfect, but we can use all of the information we have available to make our best predictions. There are only 3 pieces of data the market gives us:
1. Price (action)
2. Volume
3. Time
The Money Flow Line combines all of these data points into a readable rolling data set that attempts to show subtle balance of power shifts based on changes in volume and "smart money" (or "big money") stepping in and out of the picture. Much like PVT, we look for the same things:
- Trend Identification: an up or down trend appears in the MFL
- Confirmations: the MFL agrees with price action in direction and magnitude
- Divergence: the MFL disagrees with price action, indicating a reversal may be coming soon
When applying the smoothing line we can also look for similar things we would with EFI. The primary case would be to look for the MFL to jump very far away from the mean (a high magnitude movement) which indicates that price may be reverting towards the mean soon (a "mean reversion"). On the other hand, it may indicate strength in the current price direction. All of these predictions depend heavily on price action and market structure. Good luck!
+ Magic Carpet BandsFun name for an indicator, eh? Well, it is true, I think; they look like magic carpets. They're actually pretty simple actually. They're Keltner Channels smoothed with a moving average. If you go down to the lookback period for the bands and set it to 1, you'll recognize them immediately.
Digging a bit deeper you see there are four magic carpets on the chart. The inner ones are set to a multiplier of 2, and the outer to a multiplier of 4. Each "carpet" is composed of two smoothed upper or lower Keltner Channels bounds, both with an optional offset, one of which is set to 13, and the other to 0 by default; and an optional color fill between these. There is also a color fill between the outer and inner carpets which gives them an interesting 3-dimensional aspect at times. They can look a bit like tunnels by default.
My thinking around the idea of using an offset with the bands is that if we assume these things to provide a dynamic support and resistance, and previous support and resistance maintains status as support and resistance until proven otherwise, then by putting an offset to past data we are creating a more obvious visual indication of that support or resistance in the present. The default offset is set to 13 bars back, so if price found resistance at some point around 13 bars ago, and price is currently revisiting it we assume it is still resistance, and that offset band is there to give us a strong visual aid. Obviously it's not foolproof, but nothing is.
Beyond that most interesting part of the indicator you have a nice selection of moving averages which the bands are calculated off of. By default it's set to my UMA. The bands themselves also have a selection of moving averages for how the keltner channels are smoothed. And a note: because the UMA and RDMA are averages of different length MAs, they can not be adjusted other than via the multiplier that sets the distance from the moving average.
The indicator is multi-timeframe, and the moving average can be colored based on a higher timeframe as well.
I popped in the divergence indicator here too. You can choose from RSI and OBV, and the divergences will be plotted on the chart. Working on finding a way to be able to have the bands/MA set to a higher timeframe while plotting the divergences on the chart timeframe, but don't have an answer to that yet.
Alerts for moving average crosses, band touches, and divergences.
I like this one a lot. Enjoy!
Pictures below.
s3.tradingview.com
One interesting thing about this indicator is that band twists often occur at areas of support or resistance. Simply drawing horizontal lines from previous twisted points can provide places from which you may look for strength or weakness to enter into a trade, or which you might use as targets for taking profits. The vertical lines are just showing the point on the chart when the cross occurred.
s3.tradingview.com
Above is a Jurik MA with a bunch of adjustments made to the bands, and the moving average itself. Everything is super adjustable, so you can play around and have fun with them quite a bit.
s3.tradingview.com
Just a different MA and bands.
s3.tradingview.com
BTC Hash Rate & Price Stochastic IndiciatorFresh off the press, we have a new breed of indicators: Bitcoin's Hash Rate & Price.
As many of you have read, roughly 80% of BTC's price movements can be correlated to its changes in hash rate volume. I decided to make a stochastic indicator that utilizes this principle to track divergence of the price from the hash rate.
Let's break this down...
In red is the CLOSE of BTC's Price, which is then smoothed by a SMA, and smoothed again by a WMA.
In aqua is a STOCH of BTC's Hash Rate, which is then smoothed by a SMA, and smoothed again by a WMA.
The reason why I chose to use the CLOSE of the Price versus a STOCH as I did with the Hash Rate, is because the price tends to signal trends via divergence from the Hash Rate, and eventually converge with the Hash Rate at some point.
You will notice that anytime there is a significant divergence of the RED from the AQUA, a trend is closely aligned with it. This indicator does a remarkable job of indicating the beginnings and ends of both bullish and bearish price movements.
Example Strategy:
Enter long when RED (price) crosses over AQUA (hash rate), and close long when RED crosses under AQUA.
The inverse can be done for shorts, just RED diverges downwards from AQUA versus upwards.
Note:
Unlike a normal Stochastic Indicator, the upper and lower bounds do not appear to hold any significance. In other words, the lines do not seem to reverse at 20/80. As a result, I just set them to 0/100 for aesthetics.
DO NOT make trades based off of small divergences, or simply enter into positions based off the price divergences. Though this indicator times the start/end of movements very accurately, it also comes riddled with false breakouts .
Proceed at your own pace, and please, toy around with the inputs values. I experimented with a few combinations, but I'm sure there are better value combinations that yield sharper results with fewer false signals.
EASTER EGG:
Notice the "Golden Line"? Any avid user of TV knows that Fibonacci ratios show up everywhere in markets. With that said, I plotted a horizontal line at 0.618, which is 1/Phi, an important level in Fibonacci retracements.
Final Comments:
First, this is not investment, merely my experimentation and observation of happenings in the analytical world.
Second, please comment questions, improvements, etc. Dialogue opens up room for exploration!
Accumulation/Distribution Money Flow [Cyrus c|:D]This indicator should be more accurate than other indicators in its class (including MFI, CMF, ADL, and OBV) for measuring buy/sell pressure, identifying trend change through divergence and calculating Accumulation/Distribution (A/D) level (I will explain why in a separate TA).
This indicator is based on my previous indicator "Accumulation/Distribution Volume". It does not include the volume bars. The volume effect is adjustable as well.
Application:
- Buy/sell pressure: above 0 shows buy pressure, below 0 shows sell pressure.
- Divergence: as shown in the chart above, this indicator diverged from BTC price during swing lows and highs in the shown period.
- Accumulation/distribution: set Aggregation=Sum, Volume Exponent=10 and uncheck Price Factor.
Recommendations:
- Never use SMA
- Use larger length EMA for confirmation of divergence or buy/sell pressure (EMA 27 is equal to RMA 14 which is used in RSI).
. A/D mode is not recommended for hidden divergence.
My Setup:
- I use one instances of this indicator with default settings for buy/sell pressure
- A second instance for A/D level overlaid on the main chart
- One instance of "Accumulation/Distribution Volume" as a replacement for volume indicator
This indicator can also replicate Accumulation/Distribution Line (improved by True Range), On Balance Volume, and Price Volume Trend. Read more details on the description of the previous indicator:
I strongly recommend reading about similar indicators for potential uses e.g. www.tradingview.com(MFI) and www.tradingview.com(PVT)
I will publish a TA about correctly measuring divergence and using these indicators.
Please report any problems you find in the comments.
Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
Linh's Anomaly Radar v2What this script does
It’s an event detector for price/volume anomalies that often precede or confirm moves.
It watches a bunch of patterns (Wyckoff tests, squeezes, failed breakouts, turnover bursts, etc.), applies robust z-scores, optional trend filters, cooldowns (to avoid spam), and then fires:
A shape/label on the bar,
A row in the mini panel (top-right),
A ready-made alertcondition you can hook into.
How to add & set up (TradingView)
Paste the script → Save → Add to chart on Daily first (works on any TF).
Open Settings → Inputs:
General
• Use Robust Z (MAD): more outlier-resistant; keep on.
• Z Lookback: 60 bars is ~3 months; bump to 120 for slower regimes.
• Cooldown: min bars to wait before the same signal can fire again (default 5).
• Use trend filter: if on, “bullish” signals only fire above SMA(tfLen), “bearish” below.
Thresholds: fine-tune sensitivity (defaults are sane).
To create alerts: Right-click chart → Add alert
Condition: Linh’s Anomaly Radar v2 → choose a specific signal or Composite (Σ).
Options: “Once per bar close” (recommended).
Customize message if you want ticker/timeframe in your phone push.
The mini panel (top-right)
Signal column: short code (see cheat sheet below).
Fired column: a dot “•” means that on the latest bar this signal fired.
Score (right column): total count of signals that fired this bar.
Σ≥N shows your composite threshold (how many must fire to trigger the “Composite” alert).
Shapes & codes (what’s what)
Code Name (category) What it’s looking for Why it matters
STL Stealth Volume z(volume)>5 & ** z(return)
EVR Effort vs Result squeeze z(vol)>3 & z(TR)<−0.5 Heavy effort, tiny spread → absorption
TGV Tight+Heavy (HL/ATR)<0.6 & z(vol)>3 Tight bar + heavy tape → pro activity
CLS Accumulation cluster ≥3 of last 5 bars: up, vol↑, close near high Classic accumulation footprint
GAP Open drive failure Big gap not filled (≥80%) & vol↑ One-sided open stalls → fade risk
BB↑ BB squeeze breakout Squeeze (z(BBWidth)<−1.3) → close > upperBB & vol↑ Regime shift with confirmation
ER↑ Effort→Result inversion Down day on vol then next bar > prior high Demand overwhelms supply
OBV OBV divergence OBV slope up & ** z(ret20)
WER Wide Effort, Opposite Result z(vol)>3, close+1 Selling into strength / distribution
NS No-Supply (Wyckoff) Down bar, HL<0.6·ATR, vol << avg Sellers absent into weakness
ND No-Demand (Wyckoff) Up bar, HL<0.6·ATR, vol << avg Buyers absent into strength
VAC Liquidity Vacuum z(vol)<−1.5 & ** z(ret)
UTD UTAD (failed breakout) Breaks swing-high, closes back below, vol↑ Stop-run, reversal risk
SPR Spring (failed breakdown) Breaks swing-low, closes back above, vol↑ Bear trap, reversal risk
PIV Pocket Pivot Up bar; vol > max down-vol in lookback Quiet base → sudden demand
NR7 Narrow Range 7 + Vol HL is 7-bar low & z(vol)>2 Coiled spring with participation
52W 52-wk breakout quality New 52-wk close high + squeeze + vol↑ High-quality breakouts
VvK Vol-of-Vol kink z(ATR20,200)>0.5 & z(ATR5,60)<0 Long-vol wakes up, short-vol compresses
TAC Turnover acceleration SMA3 vol / SMA20 vol > 1.8 & muted return Participation surging before move
RBd RSI Bullish div Price LL, RSI HL, vol z>1 Exhaustion of sellers
RS↑ RSI Bearish div Price HH, RSI LH, vol z>1 Exhaustion of buyers
Σ Composite Count of all fired signals ≥ threshold High-conviction bar
Placement:
Triangles up (below bar) → bullish-leaning events.
Triangles down (above bar) → bearish-leaning events.
Circles → neutral context (VAC, VvK, Composite).
Key inputs (quick reference)
General
Use Robust Z (MAD): keep on for noisy tickers.
Z Lookback (lenZ): 60 default; 120 if you want fewer alerts.
Trend filter: when on, bullish signals require close > SMA(tfLen), bearish require <.
Cooldown: prevents repeated firing of the same signal within N bars.
Phase-1 thresholds (core)
Stealth: vol z > 5, |ret z| < 1.
EVR: vol z > 3, TR z < −0.5.
Tight+Heavy: (HL/ATR) < 0.6, vol z > 3.
Cluster: window=5, min=3 strong bars.
GapFail: gap/ATR ≥1.5, fill <80%, vol z > 2.
BB Squeeze: z(BBWidth)<−1.3 then breakout with vol z > 2.
Eff→Res Up: prev bar heavy down → current bar > prior high.
OBV Div: OBV uptrend + |z(ret20)|<0.3.
Phase-2 thresholds (extras)
WER: vol z > 3, close1.
No-Supply/No-Demand: tight bar & very light volume vs SMA20.
Vacuum: vol z < −1.5, |ret z|>1.5.
UTAD/Spring: swing lookback N (default 20), vol z > 2.
Pocket Pivot: lookback for prior down-vol max (default 10).
NR7: 7-bar narrowest range + vol z > 2.
52W Quality: new 52-wk high + squeeze + vol z > 2.
VoV Kink: z(ATR20,200)>0.5 AND z(ATR5,60)<0.
Turnover Accel: SMA3/SMA20 > 1.8 and |ret z|<1.
RSI Divergences: compare to n bars back (default 14).
How to use it (playbooks)
A) Daily scan workflow
Run on Daily for your VN watchlist.
Turn Composite (Σ) alert on with Σ≥2 or ≥3 to reduce noise.
When a bar fires Σ (or a fav combo like STL + BB↑), drop to 60-min to time entries.
B) Breakout quality check
Look for 52W together with BB↑, TAC, and OBV.
If WER/ND appear near highs → downgrade the breakout.
C) Spring/UTAD reversals
If SPR fires near major support and RBd confirms → long bias with stop below spring low.
If UTD + WER/RS↑ near resistance → short/fade with stop above UTAD high.
D) Accumulation basing
During bases, you want CLS, OBV, TGV, STL, NR7.
A pocket pivot (PIV) can be your early add; manage risk below base lows.
Tuning tips
Too many signals? Raise stealthVolZ to 5.5–6, evrVolZ to 3.5, use Σ≥3.
Fast movers? Lower bbwZthr to −1.0 (less strict squeeze), keep trend filter on.
Illiquid tickers? Keep MAD z-scores on, increase lookbacks (e.g., lenZ=120).
Limitations & good habits
First lenZ bars on a new symbol are less reliable (incomplete z-window).
Some ideas (VWAP magnet, close auction spikes, ETF/foreign flows, options skew) need intraday/external feeds — not included here.
Pine can’t “screen” across the whole market; set alerts or cycle your watchlist.
Quick troubleshooting
Compilation errors: make sure you’re on Pine v6; don’t nest functions in if blocks; each var int must be declared on its own line.
No shapes firing: check trend filter (maybe price is below SMA and you’re waiting for bullish signals), and verify thresholds aren’t too strict.
Advanced Market TheoryADVANCED MARKET THEORY (AMT)
This is not an indicator. It is a lens through which to see the true nature of the market.
Welcome to the definitive application of Auction Market Theory. What you have before you is the culmination of decades of market theory, fused with state-of-the-art data analysis and visual engineering. It is an institutional-grade intelligence engine designed for the serious trader who seeks to move beyond simplistic indicators and understand the fundamental forces that drive price.
This guide is your complete reference. Read it. Study it. Internalize it. The market is a complex story, and this tool is the language with which to read it.
PART I: THE GRAND THEORY - A UNIVERSE IN AN AUCTION
To understand the market, you must first understand its purpose. The market is a mechanism of discovery, organized by a continuous, two-way auction.
This foundational concept was pioneered by the legendary trader J. Peter Steidlmayer at the Chicago Board of Trade in the 1980s. He observed that beneath the chaotic facade of ticking prices lies a beautifully organized structure. The market's primary function is not to go up or down, but to facilitate trade by seeking a price level that encourages the maximum amount of interaction between buyers and sellers. This price is "value."
The Organizing Principle: The Normal Distribution
Over any given period, the market's activity will naturally form a bell curve (a normal distribution) turned on its side. This is the blueprint of the auction.
The Point of Control (POC): This is the peak of the bell curve—the single price level where the most trade occurred. It represents the point of maximum consensus, the "fairest price" as determined by the market participants. It is the gravitational center of the session.
The Value Area (VA): This is the heart of the bell curve, typically containing 70% of the session's activity (one standard deviation). This is the zone of "accepted value." Prices within this area are considered fair and are where the market is most comfortable conducting business.
The Extremes: The thin areas at the top and bottom of the curve are the "unfair" prices. These are levels where one side of the auction (buyers at the top, sellers at the bottom) was shut off, and trade was quickly rejected. These are areas of emotional trading and excess.
The Narrative of the Day: Balance vs. Imbalance
Every trading session is a story of the market's search for value.
Balance: When the market rotates and builds a symmetrical, bell-shaped profile, it is in a state of balance . Buyers and sellers are in agreement, and the market is range-bound.
Imbalance: When the market moves decisively away from a balanced area, it is in a state of imbalance . This is a trend. The market is actively seeking new information and a new area of value because the old one was rejected.
Your Purpose as a Trader
Your job is to read this story in real-time. Are we in balance or imbalance? Is the auction succeeding or failing at these new prices? The Advanced Market Theory engine is your Rosetta Stone to translate this complex narrative into actionable intelligence.
PART II: THE AMT ENGINE - AN EVOLUTION IN MARKET VISION
A standard market profile tool shows you a picture. The AMT Engine gives you the architect's full schematics, the engineer's stress tests, and the psychologist's behavioral analysis, all at once.
This is what makes it the Advanced Market Theory. We have fused the timeless principles with layers of modern intelligence:
TRINITY ANALYSIS: You can view the market through three distinct lenses. A Volume Profile shows where the money traded. A TPO (Time) Profile shows where the market spent its time. The revolutionary Hybrid Profile fuses both, giving you a complete picture of market conviction—marrying volume with duration.
AUTOMATED STRUCTURAL DECODING: The engine acts as your automated analyst, identifying critical structural phenomena in real-time:
Poor Highs/Lows: Weak auction points that signal a high probability of reversal.
Single Prints & Ledges: Footprints of rapid, aggressive market moves and areas of strong institutional acceptance.
Day Type Classification: The engine analyzes the session's personality as it develops ("Trend Day," "Normal Day," etc.), allowing you to adapt your strategy to the market's current character.
MACRO & MICRO FUSION: Via the Composite Profile , the engine merges weeks of data to reveal the major institutional battlegrounds that govern long-term price action. You can see the daily skirmish and the multi-month war on a single chart.
ORDER FLOW INTELLIGENCE: The ultimate advancement is the integrated Cumulative Volume Delta (CVD) engine. This moves beyond structure to analyze the raw aggression of buyers versus sellers. It is your window into the market's soul, automatically detecting critical Divergences that often precede major trend shifts.
ADAPTIVE SIGNALING: The engine's signal generation is not static; it is a thinking system. It evaluates setups based on a multi-factor Confluence Score , understands the market Regime (e.g., High Volatility), and adjusts its own confidence ( Probability % ) based on the complete context.
This is not a tool that gives you signals. This is a tool that gives you understanding .
PART III: THE VISUAL KEY - A LEXICON OF MARKET STRUCTURE
Every element on your chart is a piece of information. This is your guide to reading it fluently.
--- THE CORE ARCHITECTURE ---
The Profile Histogram: The primary visual on the left of each session. Its shape is the story. A thin profile is a trend; a fat, symmetrical profile is balance.
Blue Box : The zone of accepted, "fair" value. The heart of the session's business.
Bright Orange Line & Label : The Point of Control. The gravitational center. The price of maximum consensus. The most significant intraday level.
Dashed Blue Lines & Labels : The boundaries of value. Critical inflection points where the market decides to either remain in balance or seek value elsewhere.
Dashed Cyan Lines & Labels : The major, long-term structural levels derived from weeks of data. These are institutional reference points and carry immense weight. Treat them as primary support and resistance.
Dashed Orange Lines & Labels : Marks a Poor or Unfinished Auction . These represent emotional, weak extremes and are high-probability targets for future price action.
Diamond Markers : Mark Single Prints , which are footprints of aggressive, one-sided moves that left a "liquidity vacuum." Price is often drawn back to these levels to "repair" the poor structure.
Arrow Markers : Mark Ledges , which are areas of strong horizontal acceptance. They often act as powerful support/resistance in the future.
Dotted Gray Lines & Labels : The projected daily range based on multiples of the Initial Balance . Use them to set realistic profit targets and gauge the day's potential.
--- THE SIGNAL SUITE ---
Colored Triangles : These are your high-probability entry signals. The color is a strategic playbook:
Gold Triangle : ELITE Signal. An A+ setup with overwhelming confluence. This is the highest quality signal the engine can produce.
Yellow Triangle : FADE Signal. A counter-trend setup against an exhausted move at a structural extreme.
Cyan Triangle : BREAKOUT Signal. A momentum setup attempting to capitalize on a breakout from the value area.
Purple Triangle : ROTATION Signal. A mean-reversion setup within the value area, typically from one edge towards the POC.
Magenta Triangle : LIQUIDITY Signal. A sophisticated setup that identifies a "stop run" or liquidity sweep.
Percentage Number: The engine's calculated probability of success . This is not a guarantee, but a data-driven confidence score.
Dotted Gray Line: The signal's Entry Price .
Dashed Green Lines: The calculated Take Profit Targets .
Dashed Red Line: The calculated Stop Loss level.
PART IV: THE DASHBOARD - YOUR STRATEGIC COMMAND CENTER
The dashboard is your real-time intelligence briefing. It synthesizes all the engine's analysis into a clear, concise, and constantly updating summary.
--- CURRENT SESSION ---
POC, VAH, VAL: The live values for the core structure.
Profile Shape: Is the current auction top-heavy ( b-shaped ), bottom-heavy ( P-shaped ), or balanced ( D-shaped )?
VA Width: Is the value area expanding (trending) or contracting (balancing)?
Day Type: The engine's judgment on the day's personality. Use this to select the right strategy.
IB Range & POC Trend: Key metrics for understanding the opening sentiment and its evolution.
--- CVD ANALYSIS ---
Session CVD: The raw order flow. Is there more net buying or selling pressure in this session?
CVD Trend & DIVERGENCE: This is your order flow intelligence. Is the order flow confirming the price action? If "DIVERGENCE" flashes, it is a critical, high-alert warning of a potential reversal.
--- MARKET METRICS ---
Volume, ATR, RSI: Your standard contextual metrics, providing a quick read on activity, volatility, and momentum.
Regime: The engine's assessment of the broad market environment: High Volatility (favor breakouts), Low Volatility (favor mean reversion), or Normal .
--- PROFILE STATS, COMPOSITE, & STRUCTURE ---
These sections give you a quick quantitative summary of the profile structure, the major long-term Composite levels, and any active Poor Structures.
--- SIGNAL TYPES & ACTIVE SIGNAL ---
A permanent key to the signal colors and their meanings, along with the full details of the most recent active signal: its Type , Probability , Entry , Stop , and Target .
PART V: THE INPUTS MENU - CALIBRATING YOUR LENS
This engine is designed to be calibrated to your specific needs as a trader. Every input is a lever. This is not a "one size fits all" tool. The extensive tooltips are your built-in user manual, but here are the key areas of focus:
--- MARKET PROFILE ENGINE ---
Profile Mode: This is the most fundamental choice. Volume is the standard for price-based support and resistance. TPO is for analyzing time-based acceptance. Hybrid is the professional's choice, fusing both for a complete picture.
Profile Resolution: This is your zoom lens. Lower values for scalping and intraday precision. Higher values for a cleaner, big-picture view suitable for swing trading.
Composite Sessions: Your timeframe for macro analysis. 5-10 sessions for a weekly view; 20-30 sessions for a monthly, structural view.
--- SESSION & VALUE AREA ---
These settings must be configured correctly for your specific asset. The Session times are critical. The Initial Balance should reflect the key opening period for your market (60 minutes is standard for equities).
--- SIGNAL ENGINE & RISK MANAGEMENT ---
Signal Mode: THIS IS YOUR PERSONAL RISK PROFILE. Set it to Conservative to see only the absolute best A+ setups. Use Elite or Balanced for a standard approach. Use Aggressive only if you are an experienced scalper comfortable with managing more frequent, lower-probability setups.
ATR Multipliers: This suite gives you full, dynamic control over your risk/reward parameters. You can precisely define your initial stop loss distance and profit targets based on the market's current volatility.
A FINAL WORD FROM THE ARCHITECT
The creation of this engine was a journey into the very heart of market dynamics. It was born from a frustrating truth: that the most profound market theories were often confined to books and expensive institutional platforms, inaccessible to the modern retail trader. The goal was to bridge that gap.
The challenge was monumental. Making each discrete system—the volume profile, the TPO counter, the composite engine, the CVD tracker, the signal generator, the dynamic dashboard—work was a task in itself. But the true struggle, the frustrating, painstaking process that consumed countless hours, was making them work in unison . It was about ensuring the CVD analysis could intelligently inform the signal engine, that the day type classification could adjust the probability scores, and that the composite levels could provide context to the intraday structure, all in a seamless, real-time dance of data.
This engine is the result of that relentless pursuit of integration. It is built on the belief that a trader's greatest asset is not a signal, but clarity . It was designed to clear the noise, to organize the chaos, and to present the elegant, underlying logic of the market auction so that you can make better, more informed, and more confident decisions.
It is now in your hands. Use it not as a crutch, but as a lens. See the market for what it truly is.
"The market can remain irrational longer than you can remain solvent."
- John Maynard Keynes
DISCLAIMER
This script is an advanced analytical tool provided for informational and educational purposes only. It is not financial advice. All trading involves substantial risk, and past performance is not indicative of future results. The signals, probabilities, and metrics generated by this indicator do not constitute a recommendation to buy or sell any financial instrument. You, the user, are solely responsible for all trading decisions, risk management, and outcomes. Use this tool to supplement your own analysis and trading strategy.
PUBLISHING CATEGORIES
Volume Profile
Market Profile
Order Flow
