[volfgang] Pivot Levels (Open, Close, High, Low)This script provides a clear and consistent way to track key price levels from Weekly and Daily bars, directly on your current chart interval.
The default colours are;
Today & This Week Open = White
Yesterday & Previous Week Open = Cream
Yesterday's High = Red
Yesterday's Low = Green
Weekly Pivots are 2px, and Daily Pivots are 1px.
Instead of requiring manual referencing of daily or weekly charts, these significant levels are automatically drawn and updated in real time, extending to the right as new bars form.
It adds value by helping traders quickly identify potential support/resistance zones and compare intraday price action with higher-timeframe pivots. This approach can aid in scalping, day trading, or swing trading strategies that rely on past price levels for trade entries, exits, or stop loss placement.
Daily Pivots Displayed Intraday
The script imports the previous day’s High, Low, Open, and Close and draws lines on the current chart, so you can see exactly where those levels lie on any intraday timeframe. You can easily change the colour of these lines in the menu.
Instead of switching between multiple charts for daily references, you can keep an intraday chart open and still watch how price behaves around these important daily pivots.
Weekly Pivots for Broader Context
In addition to daily levels, it also shows the previous week’s Open and Close. This feature helps traders who want to maintain a broader perspective and gauge the market’s weekly trend or bias while remaining on lower timeframes.
Automatic Line & Label Management
Each new trading day triggers a “session change” in the code, prompting the script to delete old lines and labels for daily levels. This keeps your chart from getting cluttered with outdated lines.
Weekly lines and labels follow the same approach, ensuring only the most recent weekly levels are highlighted.
Real-Time Extension
Lines are continuously extended to the right as new bars print, ensuring that you always have an updated view of your key price levels without any manual adjustments.
On the last bar, the script shifts to a time-based coordinate system for seamless visual extension.
Minimal Recalculation
This script uses security() calls in a carefully optimized way to reduce unnecessary recalculations and avoid repaint issues. By referencing open , close , etc., the lines remain fixed once the daily (or weekly) candle is confirmed.
Flexible Usage
You can apply this script to any symbol on TradingView. It’s especially beneficial for Forex pairs, indices, futures, or cryptocurrencies where you want to track significant past levels.
If you’re a scalper looking for areas of likely reaction, or a swing trader watching weekly opens for trend confirmation, these levels can be integral to your technical approach.
How to Use
Add to Chart: Click the “Add to Favorite Indicators” or “Apply to Chart” button once published.
Enable or Disable Previous Day Bars: Use the script’s input to toggle the display of previous day’s High, Low, Open, and Close lines if you only want weekly lines (or vice versa).
Customize Visuals: You can change line colors, width, and label text in the “Style” or “Inputs” tab. Adjust them to fit your preferred color scheme.
Interpretation:
Daily levels typically carry relevance for the next trading session. They can be used for intraday support/resistance, breakout checks, or gap fills.
Weekly levels help identify more prominent zones for bigger moves or for understanding overall sentiment from the prior week.
Conceptual Underpinnings
Support/Resistance: Past opens/closes often act as support or resistance because they represent important points of reference (where trading started or ended during a prior session).
Market Psychology: Many traders watch daily or weekly closes to gauge momentum and bias, which can become self-fulfilling as more participants join around those levels.
Improved Situational Awareness: By having these levels automatically drawn and updated, traders avoid missing critical areas where price may pivot.
This script is intentionally open-source to help traders study and personalize it.
By merging daily and weekly pivot concepts in a single script, it provides a convenient and efficient tool—rather than a simple mashup, it unifies two timeframes that are crucial in short-term and medium-term trading decisions.
Remember that these levels alone do not constitute a complete trading system; they are best used as part of a broader strategy involving risk management, additional technical signals, and market context.
Göstergeler ve stratejiler
SCE Price Action SuiteThis is an indicator designed to use past market data to mark key price action levels as well as provide a different kind of insight. There are 8 different features in the script that users can turn on and off. This description will go in depth on all 8 with chart examples.
#1 Absorption Zones
I defined Absorption Zones as follows.
//----------------------------------------------
//---------------Absorption---------------------
//----------------------------------------------
box absorptionBox = na
absorptionBar = ta.highest(bodySize, absorptionLkb)
bsab = ta.barssince(bool(ta.change(absorptionBar)))
if bsab == 0 and upBar and showAbsorption
absorptionBox := box.new(left = bar_index - 1, top = close, right = bar_index + az_strcuture, bottom = open, border_color = color.rgb(0, 80, 75), border_width = boxLineSize, bgcolor = color.rgb(0, 80, 75))
absorptionBox
else if bsab == 0 and downBar and showAbsorption
absorptionBox := box.new(left = bar_index - 1, top = close, right = bar_index + az_strcuture, bottom = open, border_color = color.rgb(105, 15, 15), border_width = boxLineSize, bgcolor = color.rgb(105, 15, 15))
absorptionBox
What this means is that absorption bars are defined as the bars with the largest bodies over a selected lookback period. Those large bodies represent areas where price may react. I was inspired by the concept of a Fair Value Gap for this concept. In that body price may enter to be a point of support or resistance, market participants get “absorbed” in the area so price can continue in whichever direction.
#2 Candle Wick Theory/Strategy
I defined Candle Wick Theory/Strategy as follows.
//----------------------------------------------
//---------------Candle Wick--------------------
//----------------------------------------------
highWick = upBar ? high - close : downBar ? high - open : na
lowWick = upBar ? open - low : downBar ? close - low : na
upWick = upBar ? close + highWick : downBar ? open + highWick : na
downWick = upBar ? open - lowWick : downBar ? close - lowWick : na
downDelivery = upBar and downBar and high > upWick and highWick > lowWick and totalSize > totalSize and barstate.isconfirmed and session.ismarket
upDelivery = downBar and upBar and low < downWick and highWick < lowWick and totalSize > totalSize and barstate.isconfirmed and session.ismarket
line lG = na
line lE = na
line lR = na
bodyMidpoint = math.abs(body) / 2
upWickMidpoint = math.abs(upWickSize) / 2
downWickkMidpoint = math.abs(downWickSize) / 2
if upDelivery and showCdTheory
cpE = chart.point.new(time, bar_index - 1, downWickkMidpoint)
cpE2 = chart.point.new(time, bar_index + bl, downWickkMidpoint)
cpG = chart.point.new(time, bar_index + bl, downWickkMidpoint * (1 + tp))
cpR = chart.point.new(time, bar_index + bl, downWickkMidpoint * (1 - sl))
cpG1 = chart.point.new(time, bar_index - 1, downWickkMidpoint * (1 + tp))
cpR1 = chart.point.new(time, bar_index - 1, downWickkMidpoint * (1 - sl))
lG := line.new(cpG1, cpG, xloc.bar_index, extend.none, color.green, line.style_solid, 1)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.white, line.style_solid, 1)
lR := line.new(cpR1, cpR, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
lR
else if downDelivery and showCdTheory
cpE = chart.point.new(time, bar_index - 1, upWickMidpoint)
cpE2 = chart.point.new(time, bar_index + bl, upWickMidpoint)
cpG = chart.point.new(time, bar_index + bl, upWickMidpoint * (1 - tp))
cpR = chart.point.new(time, bar_index + bl, upWickMidpoint * (1 + sl))
cpG1 = chart.point.new(time, bar_index - 1, upWickMidpoint * (1 - tp))
cpR1 = chart.point.new(time, bar_index - 1, upWickMidpoint * (1 + sl))
lG := line.new(cpG1, cpG, xloc.bar_index, extend.none, color.green, line.style_solid, 1)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.white, line.style_solid, 1)
lR := line.new(cpR1, cpR, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
lR
First I get the size of the wicks for the top and bottoms of the candles. This depends on if the bar is red or green. If the bar is green the wick is the high minus the close, if red the high minus the open, and so on. Next, the script defines the upper and lower bounds of the wicks for further comparison. If the candle is green, it's the open price minus the bottom wick. If the candle is red, it's the close price minus the bottom wick, and so on. Next we have the condition for when this strategy is present.
Down delivery:
Occurs when the previous candle is green, the current candle is red, and:
The high of the current candle is above the upper wick of the previous candle.
The size of the current candle's top wick is greater than its bottom wick.
The total size of the previous candle is greater than the total size of the current candle.
The current bar is confirmed (barstate.isconfirmed).
The session is during market hours (session.ismarket).
Up delivery:
Occurs when the previous candle is red, the current candle is green, and:
The low of the current candle is below the lower wick of the previous candle.
The size of the current candle's bottom wick is greater than its top wick.
The total size of the previous candle is greater than the total size of the current candle.
The current bar is confirmed.
The session is during market hours
Then risk is plotted from the percentage that users can input from an ideal entry spot.
#3 Candle Size Theory
I defined Candle Size Theory as follows.
//----------------------------------------------
//---------------Candle displacement------------
//----------------------------------------------
line lECD = na
notableDown = bodySize > bodySize * candle_size_sensitivity and downBar and session.ismarket and barstate.isconfirmed
notableUp = bodySize > bodySize * candle_size_sensitivity and upBar and session.ismarket and barstate.isconfirmed
if notableUp and showCdSizeTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lECD := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.rgb(0, 80, 75), line.style_solid, 3)
lECD
else if notableDown and showCdSizeTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lECD := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.rgb(105, 15, 15), line.style_solid, 3)
lECD
This plots candles that are “notable” or out of the ordinary. Candles that are larger than the last by a value users get to specify. These candles' highs or lows, if they are green or red, act as levels for support or resistance.
#4 Candle Structure Theory
I defined Candle Structure Theory as follows.
//----------------------------------------------
//---------------Structure----------------------
//----------------------------------------------
breakDownStructure = low < low and low < low and high > high and upBar and downBar and upBar and downBar and session.ismarket and barstate.isconfirmed
breakUpStructure = low > low and low > low and high < high and downBar and upBar and downBar and upBar and session.ismarket and barstate.isconfirmed
if breakUpStructure and showStructureTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.teal, line.style_solid, 3)
lE
else if breakDownStructure and showStructureTheory
cpE = chart.point.new(time, bar_index - 1, open)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, open)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.red, line.style_solid, 3)
lE
It is a series of candles to create a notable event. 2 lower lows in a row, a lower high, then green bar, red bar, green bar is a structure for a breakdown. 2 higher lows in a row, a higher high, red bar, green bar, red bar for a break up.
#5 Candle Swing Structure Theory
I defined Candle Swing Structure Theory as follows.
//----------------------------------------------
//---------------Swing Structure----------------
//----------------------------------------------
line htb = na
line ltb = na
if totalSize * swing_struct_sense < totalSize and upBar and downBar and high > high and showSwingSturcture and session.ismarket and barstate.isconfirmed
cpS = chart.point.new(time, bar_index - 1, high)
cpE = chart.point.new(time, bar_index + bl_strcuture, high)
htb := line.new(cpS, cpE, xloc.bar_index, color = color.red, style = line.style_dashed)
htb
else if totalSize * swing_struct_sense < totalSize and downBar and upBar and low > low and showSwingSturcture and session.ismarket and barstate.isconfirmed
cpS = chart.point.new(time, bar_index - 1, low)
cpE = chart.point.new(time, bar_index + bl_strcuture, low)
ltb := line.new(cpS, cpE, xloc.bar_index, color = color.teal, style = line.style_dashed)
ltb
A bearish swing structure is defined as the last candle’s total size, times a scalar that the user can input, is less than the current candles. Like a size imbalance. The last bar must be green and this one red. The last high should also be less than this high. For a bullish swing structure the same size imbalance must be present, but we need a red bar then a green bar, and the last low higher than the current low.
#6 Fractal Boxes
I define the Fractal Boxes as follows
//----------------------------------------------
//---------------Fractal Boxes------------------
//----------------------------------------------
box b = na
int indexx = na
if bar_index % (n * 2) == 0 and session.ismarket and showBoxes
b := box.new(left = bar_index, top = topBox, right = bar_index + n, bottom = bottomBox, border_color = color.rgb(105, 15, 15), border_width = boxLineSize, bgcolor = na)
indexx := bar_index + 1
indexx
The idea of this strategy is that the market is fractal. It is considered impossible to be able to tell apart two different time frames from just the chart. So inside the chart there are many many breakouts and breakdowns happening as price bounces around. The boxes are there to give you the view from your timeframe if the market is in a range from a time frame that would be higher than it. Like if we are inside what a larger time frame candle’s range. If we break out or down from this, we might be able to trade it. Users can specify a lookback period and the box is that period’s, as an interval, high and low. I say as an interval because it is plotted every n * 2 bars. So we get a box, price moves, then a new box.
#7 Potential Move Width
I define the Potential Move Width as follows
//----------------------------------------------
//---------------Move width---------------------
//----------------------------------------------
velocity = V(n)
line lC = na
line l = na
line l2 = na
line l3 = na
line l4 = na
line l5 = na
line l6 = na
line l7 = na
line l8 = na
line lGFractal = na
line lRFractal = na
cp2 = chart.point.new(time, bar_index + n, close + velocity)
cp3 = chart.point.new(time, bar_index + n, close - velocity)
cp4 = chart.point.new(time, bar_index + n, close + velocity * 5)
cp5 = chart.point.new(time, bar_index + n, close - velocity * 5)
cp6 = chart.point.new(time, bar_index + n, close + velocity * 10)
cp7 = chart.point.new(time, bar_index + n, close - velocity * 10)
cp8 = chart.point.new(time, bar_index + n, close + velocity * 15)
cp9 = chart.point.new(time, bar_index + n, close - velocity * 15)
cpG = chart.point.new(time, bar_index + n, close + R)
cpR = chart.point.new(time, bar_index + n, close - R)
if ((bar_index + n) * 2 - bar_index) % n == 0 and session.ismarket and barstate.isconfirmed and showPredictionWidtn
cp = chart.point.new(time, bar_index, close)
cpG1 = chart.point.new(time, bar_index, close + R)
cpR1 = chart.point.new(time, bar_index, close - R)
l := line.new(cp, cp2, xloc.bar_index, extend.none, color.aqua, line.style_solid, 1)
l2 := line.new(cp, cp3, xloc.bar_index, extend.none, color.aqua, line.style_solid, 1)
l3 := line.new(cp, cp4, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
l4 := line.new(cp, cp5, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
l5 := line.new(cp, cp6, xloc.bar_index, extend.none, color.teal, line.style_solid, 1)
l6 := line.new(cp, cp7, xloc.bar_index, extend.none, color.teal, line.style_solid, 1)
l7 := line.new(cp, cp8, xloc.bar_index, extend.none, color.blue, line.style_solid, 1)
l8 := line.new(cp, cp9, xloc.bar_index, extend.none, color.blue, line.style_solid, 1)
l8
By using the past n bar’s velocity, or directional speed, every n * 2 bars. I can use it to scale the close value and get an estimate for how wide the next moves might be.
#8 Linear regression
//----------------------------------------------
//---------------Linear Regression--------------
//----------------------------------------------
lr = showLR ? ta.linreg(close, n, 0) : na
plot(lr, 'Linear Regression', color.blue)
I used TradingView’s built in linear regression to not reinvent the wheel. This is present to see past market strength of weakness from a different perspective.
User input
Users can control a lot about this script. For the strategy based plots you can enter what you want the risk to be in percentages. So the default 0.01 is 1%. You can also control how far forward the line goes.
Look back at where it is needed as well as line width for the Fractal Boxes are controllable. Also users can check on and off what they would like to see on the charts.
No indicator is 100% reliable, do not follow this one blindly. I encourage traders to make their own decisions and not trade solely based on technical indicators. I encourage constructive criticism in the comments below. Thank you.
Candle 1 2 3 on XAUUSD (by Veronica)Description
Discover the Candle 1 2 3 Strategy, a simple yet effective trading method tailored exclusively for XAUUSD on the 15-minute timeframe. Designed by Veronica, this strategy focuses on identifying key reversal and continuation patterns during the London and New York sessions, making it ideal for traders who prioritise high-probability entries during these active market hours.
Key Features:
1. Session-Specific Trading:
The strategy operates strictly during London (03:00–06:00 UTC) and New York (08:30–12:30 UTC) sessions, where XAUUSD tends to show higher volatility and clearer price movements.
Pattern Criteria:
- Works best if the first candle is NOT a pin bar or a doji.
- Third candle should either:
a. Be a marubozu (large body with minimal wicks).
a. Have a significant body with wicks, ensuring the close of the third candle is above Candle 2 (for Buy) or below Candle 2 (for Sell).
Callout Labels and Alerts:
Automatic Buy and Sell labels are displayed on the chart during qualifying sessions, ensuring clarity for decision-making.
Integrated alerts notify you of trading opportunities in real-time.
Risk Management:
Built-in Risk Calculator to estimate lot sizes based on your account size, risk percentage, and stop-loss levels.
Customizable Table:
Displays your calculated lot size for various stop-loss pip values, making risk management seamless and efficient.
How to Use:
1. Apply the indicator to XAUUSD (M15).
2. Focus on setups appearing within the London and New York sessions only.
3. Ensure the first candle is neither a pin bar nor a doji.
4. Validate the third candle's body placement:
For a Buy, the third candle’s close must be above the second candle.
For a Sell, the third candle’s close must be below the second candle.
5. Use the generated alerts to streamline your entry process.
Notes:
This strategy is meant to complement your existing knowledge of market structure and price action.
Always backtest thoroughly and adjust parameters to fit your personal trading style and risk tolerance.
Credit:
This strategy is the intellectual property of Veronica, developed specifically for XAUUSD (M15) traders seeking precision entries during high-volume sessions.
Price and Volume Divergence Analyzer
How to Use the Indicator
Main Purpose:
Identify divergences between price movement, the volume line, and the weighted volume line to predict potential reversals.
Volume Line Explanation:
At zero: Equal buying and selling volume.
At 1: Double the buying volume vs. selling.
At -1: Double the selling volume vs. buying.
Divergence:
Price rising, volume line falling: Sellers offloading to buyers—likely reversal downward.
Price falling, volume line rising: Buyers stepping in—likely reversal upward.
Higher/Lower Volume Movement Line:
At zero: Equal volume required for price movement.
At 1: High efficiency—half the volume needed to move price.
At -1: Low efficiency—double the volume needed to move price.
Above volume line: Movement aligns with efficient volume.
Below volume line: Inefficient price movement.
Candle Fill Colors:
Shaded based on whether the current close is higher or lower than the previous close.
Settings Overview
EMA Settings:
Timeframe Selection:
Use a lower timeframe than your chart for accuracy. Avoid selecting a timeframe higher than your chart.
EMA Length Option:
Default: Sets lengths automatically (EMA = 14, EMA of EMA = 3).
User Input: Allows custom EMA length.
Calculation Type:
EMA: Standard exponential moving average.
EMA of EMA: Applies EMA three times for smoother values.
Volume Line Settings:
Line Width: Adjust thickness.
Colors:
More Buying: Green (default).
More Selling: Red (default).
Higher/Lower Volume Movement Line:
Line Width: Adjust thickness.
Colors:
Higher Volume Movement: Indicates higher volume required.
Lower Volume Movement: Indicates lower volume required.
Up/Down Candle Fill:
Colors:
Up Candle: Green (default).
Down Candle: Red (default).
Transparency: Adjust percentage for visibility.
Balance Line Settings:
Line Width and Color: Equilibrium line showing equal buying/selling volume at zero.
Dekkapok Premium Prices and EMA360Overview:
The EMA360 Premium Levels indicator is designed to help traders identify key price levels above the EMA360 (Exponential Moving Average) on a daily timeframe. These levels, referred to as "premium levels" are calculated as multiples of the EMA360 and can act as potential resistance or support zones for price action analysis.
Features:
EMA360 Calculation:
The script calculates the EMA360 using the daily timeframe (or any user-specified timeframe).
EMA360 is plotted as a bold blue line for clear visibility.
Premium Levels:
Multiple levels above the EMA360 are plotted as horizontal green lines.
These levels are calculated by multiplying the EMA360 value by user-defined multipliers (e.g., 1.2x, 1.3x, etc.).
Premium levels can help identify overbought or extended price zones relative to EMA360.
Customizable Inputs:
EMA Length: Default is set to 360, but users can adjust the EMA length as needed.
Timeframe: EMA360 is calculated using the daily timeframe by default, but any timeframe can be selected.
Multipliers: Traders can input their desired multipliers (e.g., 1.2, 1.3, 1.5) as a comma-separated list.
Clean Visualization:
EMA360 and premium levels are plotted directly on the price chart for intuitive analysis.
Premium level lines are semi-transparent green to minimize clutter while maintaining focus on critical levels.
Use Cases:
Trend Analysis: Use the EMA360 to identify the broader market trend. Prices above the EMA360 generally indicate an uptrend, while prices below may indicate a downtrend.
Overextension Zones: Premium levels help traders identify zones where the price may be overbought or overextended relative to EMA360.
Dynamic Support/Resistance: The premium levels can act as dynamic resistance zones during uptrends and support zones during pullbacks.
How to Use:
Apply the indicator to your chart in TradingView.
Observe the EMA360 line to understand the market trend.
Use the green premium level lines to identify potential resistance zones as the price moves above the EMA360.
Customization Options:
Adjust the EMA Length and Timeframe to match your trading style.
Modify the Premium Multipliers to suit your market analysis needs (e.g., add or reduce levels like 1.1x, 1.8x, etc.).
This indicator is especially useful for trend-following traders who want to leverage EMA-based levels for strategic decision-making.
- Dekkapok
Dekkapok Premium Prices and EMA360 [Clean Ver.]Overview:
The EMA360 Premium Levels indicator is designed to help traders identify key price levels above the EMA360 (Exponential Moving Average) on a daily timeframe. These levels, referred to as "premium levels" are calculated as multiples of the EMA360 and can act as potential resistance or support zones for price action analysis.
Features:
EMA360 Calculation:
The script calculates the EMA360 using the daily timeframe (or any user-specified timeframe).
EMA360 is plotted as a bold blue line for clear visibility.
Premium Levels:
Multiple levels above the EMA360 are plotted as horizontal green lines.
These levels are calculated by multiplying the EMA360 value by user-defined multipliers (e.g., 1.2x, 1.3x, etc.).
Premium levels can help identify overbought or extended price zones relative to EMA360.
Customizable Inputs:
EMA Length: Default is set to 360, but users can adjust the EMA length as needed.
Timeframe: EMA360 is calculated using the daily timeframe by default, but any timeframe can be selected.
Multipliers: Traders can input their desired multipliers (e.g., 1.2, 1.3, 1.5) as a comma-separated list.
Clean Visualization:
EMA360 and premium levels are plotted directly on the price chart for intuitive analysis.
Premium level lines are semi-transparent green to minimize clutter while maintaining focus on critical levels.
Use Cases:
Trend Analysis: Use the EMA360 to identify the broader market trend. Prices above the EMA360 generally indicate an uptrend, while prices below may indicate a downtrend.
Overextension Zones: Premium levels help traders identify zones where the price may be overbought or overextended relative to EMA360.
Dynamic Support/Resistance: The premium levels can act as dynamic resistance zones during uptrends and support zones during pullbacks.
How to Use:
Apply the indicator to your chart in TradingView.
Observe the EMA360 line to understand the market trend.
Use the green premium level lines to identify potential resistance zones as the price moves above the EMA360.
Customization Options:
Adjust the EMA Length and Timeframe to match your trading style.
Modify the Premium Multipliers to suit your market analysis needs (e.g., add or reduce levels like 1.1x, 1.8x, etc.).
This indicator is especially useful for trend-following traders who want to leverage EMA-based levels for strategic decision-making.
- Dekkapok
Flow-Weighted Volume Oscillator (FWVO)Volume Dynamics Oscillator (VDO)
Description
The Volume Dynamics Oscillator (VDO) is a powerful and innovative tool designed to analyze volume trends and provide traders with actionable insights into market dynamics. This indicator goes beyond simple volume analysis by incorporating a smoothed oscillator that visualizes the flow and momentum of trading activity, giving traders a clearer understanding of volume behavior over time.
What It Does
The VDO calculates the flow of volume by scaling raw volume data relative to its highest and lowest values over a user-defined period. This scaled volume is then smoothed using an exponential moving average (EMA) to eliminate noise and highlight significant trends. The oscillator dynamically shifts above or below a zero line, providing clear visual cues for bullish or bearish volume pressure.
Key features include:
Smoothed Oscillator: Displays the direction and momentum of volume using gradient colors.
Threshold Markers: Highlights overbought or oversold zones based on upper and lower bounds of the oscillator.
Visual Fill Zones: Uses color-filled areas to emphasize positive and negative volume flow, making it easy to interpret market sentiment.
How It Works
The calculation consists of several steps:
Smoothing with EMA: An EMA of the scaled volume is applied to reduce noise and enhance trends. A separate EMA period can be adjusted by the user (Volume EMA Period).
Dynamic Thresholds: The script determines upper and lower bounds around the smoothed oscillator, derived from its recent highest and lowest values. These thresholds indicate critical zones of volume momentum.
How to Use It
Bullish Signals: When the oscillator is above zero and green, it suggests strong buying pressure. A crossover from negative to positive can signal the start of an uptrend.
Bearish Signals: When the oscillator is below zero and blue, it indicates selling pressure. A crossover from positive to negative signals potential bearish momentum.
Overbought/Oversold Zones: Use the upper and lower threshold levels as indicators of extreme volume momentum. These can act as early warnings for trend reversals.
Traders can adjust the following inputs to customize the indicator:
High/Low Period: Defines the period for volume scaling.
Volume EMA Period: Adjusts the smoothing factor for the oscillator.
Smooth Factor: Controls the responsiveness of the smoothed oscillator.
Originality and Usefulness
The VDO stands out by combining dynamic volume scaling, EMA smoothing, and gradient-based visualization into a single, cohesive tool. Unlike traditional volume indicators, which often display raw or cumulative data, the VDO emphasizes relative volume strength and flow, making it particularly useful for spotting reversals, confirming trends, and identifying breakout opportunities.
The integration of color-coded fills and thresholds enhances usability, allowing traders to quickly interpret market conditions without requiring deep technical expertise.
Chart Recommendations
To maximize the effectiveness of the VDO, use it on a clean chart without additional indicators. The gradient coloring and filled zones make it self-explanatory, but traders can overlay basic trendlines or support/resistance levels for additional context.
For advanced users, the VDO can be paired with price action strategies, candlestick patterns, or other trend-following indicators to improve accuracy and timing.
00 Averaging Down Backtest Strategy by RPAlawyer v21FOR EDUCATIONAL PURPOSES ONLY! THE CODE IS NOT YET FULLY DEVELOPED, BUT IT CAN PROVIDE INTERESTING DATA AND INSIGHTS IN ITS CURRENT STATE.
This strategy is an 'averaging down' backtester strategy. The goal of averaging/doubling down is to buy more of an asset at a lower price to reduce your average entry price.
This backtester code proves why you shouldn't do averaging down, but the code can be developed (and will be developed) further, and there might be settings even in its current form that prove that averaging down can be done effectively.
Different averaging down strategies exist:
- Linear/Fixed Amount: buy $1000 every time price drops 5%
- Grid Trading: Placing orders at price levels, often with increasing size, like $1000 at -5%, $2000 at -10%
- Martingale: doubling the position size with each new entry
- Reverse Martingale: decreasing position size as price falls: $4000, then $2000, then $1000
- Percentage-Based: position size based on % of remaining capital, like 10% of available funds at each level
- Dynamic/Adaptive: larger entries during high volatility, smaller during low
- Logarithmic: position sizes increase logarithmically as price drops
Unlike the above average costing strategies, it applies averaging down (I use DCA as a synonym) at a very strong trend reversal. So not at a certain predetermined percentage negative PNL % but at a trend reversal signaled by an indicator - hence it most closely resembles a dynamically moving grid DCA strategy.
Both entering the trade and averaging down assume a strong trend. The signals for trend detection are provided by an indicator that I published under the name '00 Parabolic SAR Trend Following Signals by RPAlawyer', but any indicator that generates numeric signals of 1 and -1 for buy and sell signals can be used.
The indicator must be connected to the strategy: in the strategy settings under 'External Source' you need to select '00 Parabolic SAR Trend Following Signals by RPAlawyer: Connector'. From this point, the strategy detects when the indicator generates buy and sell signals.
The strategy considers a strong trend when a buy signal appears above a very conservative ATR band, or a sell signal below the ATR band. The conservative ATR is chosen to filter ranging markets. This very conservative ATR setting has a default multiplier of 8 and length of 40. The multiplier can be increased up to 10, but there will be very few buy and sell signals at that level and DCA requirements will be very high. Trade entry and DCA occur at these strong trends. In the settings, the 'ATR Filter' setting determines the entry condition (e.g., ATR Filter multiplier of 9), and the 'DCA ATR' determines when DCA will happen (e.g., DCA ATR multiplier of 6).
The DCA levels and DCA amounts are determined as follows:
The first DCA occurs below the DCA Base Deviation% level (see settings, default 3%) which acts as a threshold. The thick green line indicates the long position avg price, and the thin red line below the green line indicates the 3% DCA threshold for long positions. The thick red line indicates the short position avg price, and the thin red line above the thick red line indicates the short position 3% DCA threshold. DCA size multiplier defines the DCA amount invested.
If the loss exceeds 3% AND a buy signal arrives below the lower ATR band for longs, or a sell signal arrives above the upper ATR band for shorts, then the first DCA will be executed. So the first DCA won't happen at 3%, rather 3% is a threshold where the additional condition is that the price must close above or below the ATR band (let's say the first DCA occured at 8%) – this is why the code resembles a dynamic grid strategy, where the grid moves such that alongside the first 3% threshold, a strong trend must also appear for DCA. At this point, the thick green/red line moves because the avg price is modified as a result of the DCA, and the thin red line indicating the next DCA level also moves. The next DCA level is determined by the first DCA level, meaning modified avg price plus an additional +8% + (3% * the Step Scale Multiplier in the settings). This next DCA level will be indicated by the modified thin red line, and the price must break through this level and again break through the ATR band for the second DCA to occur.
Since all this wasn't complicated enough, and I was always obsessed by the idea that when we're sitting in an underwater position for days, doing DCA and waiting for the price to correct, we can actually enter a short position on the other side, on which we can realize profit (if the broker allows taking hedge positions, Binance allows this in Europe).
This opposite position in this strategy can open from the point AFTER THE FIRST DCA OF THE BASE POSITION OCCURS. This base position first DCA actually indicates that the price has already moved against us significantly so time to earn some money on the other side. Breaking through the ATR band is also a condition for entry here, so the hedge position entry is not automatic, and the condition for further DCA is breaking through the DCA Base Deviation (default 3%) and breaking through the ATR band. So for the 'hedge' or rather opposite position, the entry and further DCA conditions are the same as for the base position. The hedge position avg price is indicated by a thick black line and the Next Hedge DCA Level is indicated by a thin black line.
The TPs are indicated by green labels for base positions and red labels for hedge positions.
No SL built into the strategy at this point but you are free to do your coding.
Summary data can be found in the upper right corner.
The fantastic trend reversal indicator Machine learning: Lorentzian Classification by jdehorty can be used as an external indicator, choose 'backtest stream' for the external source. The ATR Band multiplicators need to be reduced to 5-6 when using Lorentz.
The code can be further developed in several aspects, and as I write this, I already have a few ideas 😊
Dynamic S/R Levels: Edge FinderOverview
The Dynamic S/R Levels: Edge Finder indicator is designed to identify dynamic support and resistance levels based on historical price action. It uses a combination of price extremes (highs and lows) over user-defined lookback periods, weighted moving averages (WMAs), and touch-count analysis to provide actionable insights into key market levels.
This tool is ideal for traders who want to:
Identify dynamic support and resistance zones.
Understand the strength of these levels based on price touches.
Make informed decisions using clear, adaptive levels.
How It Works
Dynamic Levels Calculation:
The indicator calculates dynamic support levels using the lowest lows and dynamic resistance levels using the highest highs over user-defined lookback periods (e.g., 20, 40, 60 bars, etc.).
These levels are updated dynamically as new price data becomes available.
Touch Count Analysis:
The indicator counts how many times the price has touched or come close to each support/resistance level within the lookback period.
Levels with more touches are considered stronger and are highlighted accordingly.
Weighted Moving Averages (WMAs):
The indicator uses 50-period and 100-period WMAs to identify the closest support/resistance levels to the current trend.
Levels near these WMAs are given additional weight, as they are more likely to act as significant barriers.
Level Merging:
If two support or resistance levels are too close to each other (based on the minimum distance percentage), the weaker level (with fewer touches) is removed to avoid clutter.
Visualization:
Support levels are displayed as dashed red lines, and resistance levels are displayed as dashed blue lines.
Each level is labeled with its corresponding touch count, allowing traders to quickly assess its strength.
How to Interpret the Indicator
Strong Support/Resistance Levels:
Levels with higher touch counts (e.g., 5, 10, or more) are considered stronger and are more likely to hold in the future.
Use these levels to plan entries, exits, or stop-loss placements.
Proximity to WMAs:
Levels closest to the 50-period or 100-period WMA are more significant, especially in trending markets.
These levels often act as dynamic barriers where price reactions are more likely.
Breakouts and Rejections:
If the price breaks through a strong resistance level, it may indicate a potential bullish trend.
If the price rejects a strong support level, it may indicate a potential bearish trend.
Always confirm breakouts or rejections with additional analysis (e.g., volume, candlestick patterns).
Level Merging:
Merged levels indicate areas of high confluence, where multiple support/resistance zones overlap.
These areas are particularly important for decision-making, as they represent stronger market reactions.
Key Features
Customizable Lookback Periods: Adjust the lookback periods for each dynamic level to suit your trading style.
Touch Count Labels: Quickly identify the strength of each level based on the number of price touches.
Adaptive Levels: The indicator dynamically updates levels based on recent price action.
Clean Visualization: Levels are automatically merged to avoid clutter and provide a clear view of the market structure.
Usage Tips
Trend Identification: Combine the indicator with trend-following tools (e.g., moving averages, trendlines) to confirm the overall market direction.
Risk Management: Use the identified levels to set stop-loss orders or take-profit targets.
Timeframe Flexibility: The indicator works on all timeframes, but it is particularly effective on higher timeframes (e.g., 1H, 4H, Daily) for more reliable levels.
Example Scenarios
Bounce Trade:
If the price approaches a strong support level (high touch count) and shows signs of rejection (e.g., bullish candlestick patterns), consider a long position with a stop-loss below the support level.
Breakout Trade:
If the price breaks above a strong resistance level with high volume, consider a long position with a target at the next resistance level.
Range-Bound Market:
In a sideways market, use the support and resistance levels to identify range boundaries and trade bounces between them.
Disclaimer
Dynamic S/R Levels: Edge Finder is a technical analysis tool designed to identify dynamic support and resistance levels based on historical price action. It is intended for informational and educational purposes only. This indicator does not provide financial, investment, or trading advice. Users are solely responsible for their trading decisions and should conduct their own research and analysis before making any trades. The developer of this tool is not liable for any financial losses or damages resulting from the use of this indicator. Trading in financial markets involves risk, and you should only trade with capital you can afford to lose.
Machine Learning Price Target Prediction Signals [AlgoAlpha]Introducing the Machine Learning Price Target Predictions, a cutting-edge trading tool that leverages kernel regression to provide accurate price targets and enhance your trading strategy. This indicator combines trend-based signals with advanced machine learning techniques, offering predictive insights into potential price movements. Perfect for traders looking to make data-driven decisions with confidence.
What is Kernel Regression and How It Works
Kernel regression is a non-parametric machine learning technique that estimates the relationship between variables by weighting data points based on their similarity to a given input. The similarity is determined using a kernel function, such as the Gaussian (RBF) kernel, which assigns higher weights to closer data points and progressively lower weights to farther ones. This allows the model to make smooth and adaptive predictions, balancing recent data and historical trends.
Key Features
🎯 Predictive Price Targets : Uses kernel regression to estimate the magnitude of price movements.
📈 Dynamic Trend Analysis : Multiple trend detection methods, including EMA crossovers, Hull Moving Average, and SuperTrend.
🔧 Customizable Settings : Adjust bandwidth for kernel regression and tweak trend indicator parameters to suit your strategy.
📊 Visual Trade Levels : Displays take-profit and stop-loss levels directly on the chart with customizable colors.
📋 Performance Metrics : Real-time win rate, recommended risk-reward ratio, and training data size displayed in an on-chart table.
🔔 Alerts : Get notified for new trends, take-profit hits, and stop-loss triggers.
How to Use
🛠 Add the Indicator : Add it to your favorites and apply it to your chart. Configure the trend detection method (SuperTrend, HMA, or EMA crossover) and other parameters based on your preferences.
📊 Analyze Predictions : Observe the predicted move size, recommended risk-reward ratio, and trend direction. Use the displayed levels for trade planning.
🔔 Set Alerts : Enable alerts for trend signals, take-profit hits, or stop-loss triggers to stay informed without constant monitoring.
How It Works
The indicator calculates features such as price volatility, relative strength, and trend signals, which are stored during training periods. When a trend change is detected, the kernel regression model predicts the likely price move based on these features. Predictions are smoothed using the specified bandwidth to avoid overfitting while ensuring timely responses to feature changes. Visualized take-profit and stop-loss levels help traders optimize risk management. Real-time metrics like win rate and recommended risk-reward ratios provide actionable insights for decision-making.
ADX-DMIThis script manually calculates the Directional Movement Index (DMI) and the Average Directional Index (ADX) using Wilder’s smoothing technique. The DMI indicators are used to assess the strength and direction of a market trend. It includes three main lines: ADX (yellow), DI+ (green), and DI− (red). Traders use these indicators to determine whether a trend is strong and in which direction it is moving.
The process begins by defining the length parameter, which determines how many periods are considered in the calculation. It then calculates the True Range (TR), which is the greatest of three values: the difference between the current high and low, the difference between the current high and the previous close, and the difference between the current low and the previous close. This TR is used to compute the Average True Range (ATR), which smooths out price fluctuations to get a clearer picture of the market’s volatility. Next, the script calculates the +DM (positive directional movement) and -DM (negative directional movement) based on the changes in the highs and lows from one period to the next.
Finally, the script computes the DI+ and DI− values by dividing the smoothed +DM and -DM by the ATR and multiplying by 100 to express them as percentages. The DX value is calculated as the absolute difference between DI+ and DI−, normalized by the sum of both values. The ADX is then derived by smoothing the DX value over the specified length. The three indicators — ADX, DI+, and DI− — are plotted in the lower chart panel, providing traders with visual cues about the trend’s direction (DI+ and DI−) and strength (ADX).
Important Notice:
The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data before applying them in live trading scenarios.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research before making any trading decisions.
MB 3ST+EMA+StochRSI Martin Buecker 16.01.2025Short Description of the Indicator "MB 3ST+EMA+StochRSI Martin Buecker 16.01.2025"
This trend-following and momentum-based indicator combines Supertrend, EMA 200, and Stochastic RSI to generate buy and sell signals with improved accuracy.
1. Key Components
Supertrend (3 variations):
Uses three Supertrend indicators with different periods to confirm trend direction.
Buy signal when at least 2 Supertrends are bearish.
Sell signal when at least 2 Supertrends are bullish.
EMA 200 (Exponential Moving Average):
Buy signals only when the price is above EMA 200 (uptrend confirmation).
Sell signals only when the price is below EMA 200 (downtrend confirmation).
Multi-Timeframe Stochastic RSI:
Uses a higher timeframe Stoch RSI (default: 15 minutes) to filter signals.
Buy signal when %K crosses above %D (bullish momentum).
Sell signal when %K crosses below %D (bearish momentum).
2. Signal Generation
📈 Buy Signal Conditions:
✅ At least 2 of 3 Supertrends are bearish
✅ Price is above EMA 200
✅ Stoch RSI shows a bullish crossover (%K > %D)
📉 Sell Signal Conditions:
✅ At least 2 of 3 Supertrends are bullish
✅ Price is below EMA 200
✅ Stoch RSI shows a bearish crossover (%K < %D)
3. Visual Representation & Alerts
Supertrend Lines:
Green = Bullish, Red = Bearish
EMA 200: White Line
Buy/Sell Signals:
Green triangle (below bar) = Buy
Red triangle (above bar) = Sell
Alerts:
Notifies users when a buy or sell signal is triggered.
Background Coloring:
Green for Buy signals, Red for Sell signals
4. Purpose & Benefits
🔥 Combines trend (EMA 200, Supertrend) and momentum analysis (Stoch RSI) for better signal accuracy.
🔥 Works best in trending markets, filtering out false signals in sideways movements.
🔥 Suitable for scalping and day trading, providing clear and structured trade entries.
Best of Option Indicator - Manoj WadekarPlot this indicator for both CALL and PUT options and buy only when color of candle is YELLOW and above BLACK line.
VWMACD-MFI-OBV Composite# MACD-MFI-OBV Composite
A dynamic volume-based technical indicator combining Volume-Weighted MACD, Money Flow Index (MFI), and normalized On Balance Volume (OBV). This composite indicator excels at identifying breakouts and strong trend movements through multiple volume confirmations, making it particularly effective for momentum and high-volatility trading environments.
## Overview
The indicator integrates trend, momentum, and cumulative volume analysis into a unified visualization system. Each component is carefully normalized to enable direct comparison, while the background color system provides instant trend recognition. This version is specifically optimized for breakout detection and strong trend confirmation.
## Core Components
### Volume-Weighted MACD
Visualized through the background color system, this enhanced MACD implementation uses Volume-Weighted Moving Averages (VWMA) instead of traditional EMAs. This modification ensures greater sensitivity to volume-supported price movements while filtering out less significant low-volume price changes. The background alternates between green (bullish) and red (bearish) to provide immediate trend feedback.
### Money Flow Index (MFI)
Displayed as the purple line, the MFI functions as a volume-weighted momentum oscillator. Operating within a natural 0-100 range, it helps identify potential overbought and oversold conditions while confirming volume support for price movements. The MFI is particularly effective at validating breakout momentum.
### Normalized On Balance Volume (OBV)
The white line represents normalized OBV, providing insight into cumulative buying and selling pressure. The normalization process scales OBV to match other components while maintaining its ability to confirm price trends through volume analysis. This component excels at identifying strong breakout movements and volume surges.
## Signal Integration
The indicator generates its most powerful signals when all three components align, particularly during breakout conditions:
Strong Bullish Signals develop when:
- Background shifts to green (VWMACD bullish)
- MFI shows strong upward momentum
- OBV demonstrates sharp volume accumulation
Strong Bearish Signals emerge when:
- Background turns red (VWMACD bearish)
- MFI exhibits downward momentum
- OBV shows significant volume distribution
## Market Application
This indicator variant is specifically designed for:
Breakout Trading:
The OBV component provides excellent sensitivity to volume surges, making it ideal for breakout confirmation and momentum validation.
Trend Following:
Sharp OBV movements combined with MFI momentum help identify and confirm strong trending conditions.
High Volatility Markets:
The indicator's design excels in active, volatile markets where clear signal generation is crucial for decision-making.
## Technical Implementation
Default Parameters:
Volume-Weighted MACD maintains traditional periods (12/26/9) while leveraging volume weighting. MFI uses standard 14-period calculation with 80/20 overbought/oversold thresholds. All components undergo normalization over a 100-period lookback for stable comparison.
Visual Elements:
- Background: VWMACD trend indication (green/red)
- Purple Line: Money Flow Index
- White Line: Normalized OBV
- Yellow Line: Combined signal (arithmetic mean of normalized components)
- Reference Lines: Key levels at 20, 50, and 80
## Trading Methodology
The indicator supports a systematic approach to breakout and momentum trading:
1. Breakout Identification
Monitor for background color changes accompanied by significant OBV movement, indicating potential breakout conditions.
2. Volume Surge Confirmation
Examine OBV slope and magnitude to confirm genuine breakout scenarios versus false moves.
3. Momentum Validation
Use MFI to confirm breakout strength and identify potential exhaustion points.
4. Combined Signal Analysis
The yellow line provides a unified view of all components, helping identify high-probability breakout opportunities.
## Interpretation Guidelines
Breakout Confirmation:
Strong breakouts typically show alignment of all three components with notable OBV surge. This configuration often precedes significant price movements.
Trend Strength:
Continuous OBV expansion during trends, supported by steady MFI readings, suggests sustained momentum.
## Market Selection
Optimal Markets Include:
- High-beta growth stocks
- Momentum-driven securities
- Stocks with significant volatility
- Active trading instruments
- Examples: TSLA, NVDA, growth stocks
## Version Information
Current Version: 2.0.0
This indicator represents a specialized adaptation of volume-based analysis, optimized for breakout trading and momentum strategies in high-volatility environments.
metaconnectorLibrary "metaconnector"
metaconnector
buy_market_order(License_ID, symbol, lot)
Places a buy market order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
Returns: String syntax for the buy market order
sell_market_order(License_ID, symbol, lot)
Places a sell market order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
Returns: String syntax for the sell market order
buy_limit_order(License_ID, symbol, lot, price)
Places a buy limit order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
price (float) : Limit price for the order
Returns: String syntax for the buy limit order
sell_limit_order(License_ID, symbol, lot, price)
Places a sell limit order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
price (float) : Limit price for the order
Returns: String syntax for the sell limit order
stoploss_for_buy_order(License_ID, symbol, lot, stoploss_price)
Places a stop-loss order for a buy position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
stoploss_price (float)
Returns: String syntax for the buy stop-loss order
stoploss_for_sell_order(License_ID, symbol, lot, stoploss_price)
Places a stop-loss order for a sell position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
stoploss_price (float)
Returns: String syntax for the sell stop-loss order
takeprofit_for_buy_order(License_ID, symbol, lot, target_price)
Places a take-profit order for a buy position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
target_price (float)
Returns: String syntax for the buy take-profit order
takeprofit_for_sell_order(License_ID, symbol, lot, target_price)
Places a take-profit order for a sell position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
target_price (float)
Returns: String syntax for the sell take-profit order
buy_stop_order(License_ID, symbol, lot, price)
Places a buy stop order above the current market price
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
price (float) : Stop order price
Returns: String syntax for the buy stop order
sell_stop_order(License_ID, symbol, lot, price)
Places a sell stop order below the current market price
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
price (float) : Stop order price
Returns: String syntax for the sell stop order
close_all_positions(License_ID, symbol)
Closes all positions for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
Returns: String syntax for closing all positions
close_buy_positions(License_ID, symbol)
Closes all buy positions for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
Returns: String syntax for closing all buy positions
close_sell_positions(License_ID, symbol)
Closes all sell positions for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
Returns: String syntax for closing all sell positions
close_partial_buy_position(License_ID, symbol, lot)
Closes a partial buy position for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to close
Returns: String syntax for closing a partial buy position
close_partial_sell_position(License_ID, symbol, lot)
Closes a partial sell position for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to close
Returns: String syntax for closing a partial sell position
Price Projection by Linear RegressionPurpose:
This is a TradingView Pine Script indicator that performs a linear regression on historical price data to project potential future price levels. It's designed to help traders visualize long-term price trends and potential future price targets.
Key Components:
User Inputs:
Historical Data Points (default 1000 bars) - The amount of historical data used to calculate the trend
Years to Project (default 10 years) - How far into the future to project the price
Technical Implementation:
Uses linear regression (ta.linreg) to calculate the trend slope
Converts years to trading days using 252 trading days per year
Limits visible projection to 500 bars due to TradingView's drawing limitations
Projects prices using the formula: current_price + (slope × number_of_bars)
Visual Elements:
Blue line showing actual historical prices
Red projection line showing the expected price path
Label showing the projected price at the visible end of the line
Information table in the top-right corner showing:
Current price
Final projected price after the full time period
Limitations:
Can only display projections up to 500 bars into the future (about 2 years) due to TradingView limitations
The full projection value is still calculated and shown in the table
Past performance doesn't guarantee future results - this is a mathematical projection based on historical trends
Usage:
Traders can use this to:
Visualize potential long-term price trends
Set long-term price targets
Understand the historical trend's trajectory
Compare current prices with projected future values
Day Break LinesDay Break Lines Indicator
The Day Break Lines Indicator is a simple tool designed to enhance your chart analysis by visually marking the start of a new trading day with vertical lines. This is particularly useful for intraday traders and those analyzing time-based price movements.
Key Features:
Automatically detects the start of a new trading day.
Draws customizable vertical lines that span the entire visible chart height.
Fully customizable line attributes, including:
Color: Choose a transparent or solid color.
Width: Adjust line thickness (1-5).
Style: Select solid, dotted, or dashed lines.
4EMAs+OpenHrs+FOMC+CPIThis script displays 4 custom EMAs of your choice based on the Pine script standard ema function.
Additionally the following events are shown
1. Opening hours for New York Stock exchange
2. Opening Time for London Stock exchange
3. US CPI Release Dates
4. FOMC press conference dates
5. FOMC meeting minutes release dates
I have currently added FOMC and CPI Dates for 2025 but will keep updating in January of every year (at least as long as I stay in the game :D)
Red Pill VWAP/RSI DivergenceI created this indicator to identify moments in time VWAP and RSI are diverging.
Ideally useful in strong trend, bullish or bearish, as a potential entry point on a pull back for continuation. Not to be used as a stand alone signal, but rather in conjunction with any possible trend/momentum strategy.
VWAP is identified as the blue line. Green label(blue pill) is your potential entry on a pull back when price is above, stacked EMAS & VWAP for a long position. Red label(red pill) is your potential entry on a pull back when price is below inversely stacked EMAS & VWAP for a short position. These are the 2 ideal scenarios I have found. Please back test for yourself
I have had great results but must emphasis this is not a stand alone buy/sell. I use it in confluence to add conviction to my current A+ setups.
***Pivot ribbon in chart created by Saty Mahajan set to 3/10 time warp works ideal in conjunction.
***please note false positive and false negative signals can occur, particularly in chop
I hope you find this helpful . TRADE SAFE!
Adaptive Fourier Transform Supertrend [QuantAlgo]Discover a brand new way to analyze trend with Adaptive Fourier Transform Supertrend by QuantAlgo , an innovative technical indicator that combines the power of Fourier analysis with dynamic Supertrend methodology. In essence, it utilizes the frequency domain mathematics and the adaptive volatility control technique to transform complex wave patterns into clear and high probability signals—ideal for both sophisticated traders seeking mathematical precision and investors who appreciate robust trend confirmation!
🟢 Core Architecture
At its core, this indicator employs an adaptive Fourier Transform framework with dynamic volatility-controlled Supertrend bands. It utilizes multiple harmonic components that let you fine-tune how market frequencies influence trend detection. By combining wave analysis with adaptive volatility bands, the indicator creates a sophisticated yet clear framework for trend identification that dynamically adjusts to changing market conditions.
🟢 Technical Foundation
The indicator builds on three innovative components:
Fourier Wave Analysis: Decomposes price action into primary and harmonic components for precise trend detection
Adaptive Volatility Control: Dynamically adjusts Supertrend bands using combined ATR and standard deviation
Harmonic Integration: Merges multiple frequency components with decreasing weights for comprehensive trend analysis
🟢 Key Features & Signals
The Adaptive Fourier Transform Supertrend transforms complex wave calculations into clear visual signals with:
Dynamic trend bands that adapt to market volatility
Sophisticated cloud-fill visualization system
Strategic L/S markers at key trend reversals
Customizable bar coloring based on trend direction
Comprehensive alert system for trend shifts
🟢 Practical Usage Tips
Here's how you can get the most out of the Adaptive Fourier Transform Supertrend :
1/ Setup:
Add the indicator to your favorites, then apply it to your chart ⭐️
Start with close price as your base source
Use standard Fourier period (14) for balanced wave detection
Begin with default harmonic weight (0.5) for balanced sensitivity
Start with standard Supertrend multiplier (2.0) for reliable band width
2/ Signal Interpretation:
Monitor trend band crossovers for potential signals
Watch for convergence of price with Fourier trend
Use L/S markers for trade entry points
Monitor bar colors for trend confirmation
Configure alerts for significant trend reversals
🟢 Pro Tips
Fine-tune Fourier parameters for optimal sensitivity:
→ Lower Base Period (8-12) for more reactive analysis
→ Higher Base Period (15-30) to filter out noise
→ Adjust Harmonic Weight (0.3-0.7) to control shorter trend influence
Customize Supertrend settings:
→ Lower multiplier (1.5-2.0) for tighter bands
→ Higher multiplier (2.0-3.0) for wider bands
→ Adjust ATR length based on market volatility
Strategy Enhancement:
→ Compare signals across multiple timeframes
→ Combine with volume analysis
→ Use with support/resistance levels
→ Integrate with other momentum indicators
FACTOR MONITORThe Factor Monitor is a comprehensive designed to track relative strength and standard deviation movements across multiple market segments and investment factors. The indicator calculates and displays normalized percentage moves and their statistical significance (measured in standard deviations) across daily, 5-day, and 20-day periods, providing a multi-timeframe view of market dynamics.
Key Features:
Real-time tracking of relative performance between various ETF pairs (e.g., QQQ vs SPY, IWM vs SPY)
Standard deviation scoring system that identifies statistically significant moves
Color-coded visualization (green/red) for quick interpretation of relative strength
Multiple timeframe analysis (1-day, 5-day, and 20-day moves)
Monitoring of key market segments:
Style factors (Value, Growth, Momentum)
Market cap segments (Large, Mid, Small)
Sector relative strength
Risk factors (High Beta vs Low Volatility)
Credit conditions (High Yield vs Investment Grade)
The tool is particularly valuable for:
Identifying significant factor rotations in the market
Assessing market breadth through relative strength comparisons
Spotting potential trend changes through statistical deviation analysis
Monitoring sector leadership and market regime shifts
Quantifying the magnitude of market moves relative to historical norms
India VIXThe VIX chart represents the Volatility Index, commonly referred to as the "Fear Gauge" of the stock market. It measures the market's expectations of future volatility over the next 30 days, based on the implied volatility of NSE index options. The VIX is often used as an indicator of investor sentiment, reflecting the level of fear or uncertainty in the market.
Here’s a breakdown of what you might observe on a typical VIX chart:
VIX Value: The y-axis typically represents the VIX index value, with higher values indicating higher levels of expected market volatility (more fear or uncertainty), and lower values signaling calm or stable market conditions.
VIX Spikes: Large spikes in the VIX often correspond to market downturns or periods of heightened uncertainty, such as during financial crises or major geopolitical events. A high VIX is often associated with a drop in the stock market.
VIX Drops: A decline in the VIX indicates a reduction in expected market volatility, usually linked with periods of market calm or rising stock prices.
Trend Analysis: Technical traders might use moving averages or other indicators on the VIX chart to assess the potential for future market movements.
Inverse Relationship with the Stock Market: Typically, there is an inverse correlation between the VIX and the stock market. When stocks fall sharply, volatility increases, and the VIX tends to rise. Conversely, when the stock market rallies or remains stable, the VIX tends to fall.
A typical interpretation would be that when the VIX is low, the market is relatively stable, and when the VIX is high, the market is perceived to be uncertain or volatile.
Accumulated Funding RateAccumulated Funding Rate
for future contract -ve/+ve funding fees that indicate long and short opening so that price differance between Spot and Future is balance buy exchange funding between long and short holder
-ve rate means Short is high so short holder has to pay fees to Long to correction in Price and vise versa
so over the periode of time accumulated rate its indicates the Bubble which can be explode any time to Liquidation of inbalance Long/Short Ratio some time its take longer period but its indicated bubbles direction
maximum -ve rates indicate Short opened from long period of time so when its liquidate/exit
then price will be correct to its original price that was struck due Short holder over the time and then now market will liquidate/exit those unstable Short like 50X/25X leverage and correct the price
