UM VIX status table and Roll Yield with EMA
Description :
This oscillator indicator gives you a quick snapshot of VIX, VIX futures prices, and the related VIX roll yield at a glance. When the roll yield is greater than 0, The front-month VX1 future contract is less than the next-month VX2 contract. This is called Contango and is typical for the majority of the time. If the roll yield falls below zero. This is considered backwardation where the front-month VX1 contract is higher than the value of the next-month VX2 contract. Contango is most common. When Backwardation occurs, there is usually high volatility present.
Features :
The red and green fill indicate the current roll yield with the gray line being zero.
An Exponential moving average is overlaid on the roll yield. It is red when trending down and green when trending up. If you right-click the indicator, you can set alerts for roll yield EMA color transitions green to red or red to green.
Suggested uses:
The author suggests a one hour chart using the 55 period EMA with a 60 minute setting in the indicator. This gives you a visual idea of whether the roll yield is rising or falling. The roll yield will often change directions at market turning points. For example if the roll yield EMA changes from red to green, this indicates a rising roll yield and volatility is subsiding. This could be considered bullish. If the roll yield begins falling, this indicates volatility is rising. This may be negative for stocks and indexes.
I look for short volatility positions (SVIX) when the roll yield is rising. I look for long volatility positions (VXX, UVXY, UVIX) when the roll yield begins falling. The indicator can be added to any chart. I suggest using the VX1, SPY, VIX, or other major stock index.
Set the time frame to your trading style. The default is 60 minutes. Note, the timeframe of the indicator does NOT utilize the current chart timeframe, it must be set to the desired timeframe. I manually input text on the chart indicator for understanding periods of Long and Short Volatility.
Settings and Defaults
The EMA is set to 55 by default and the table location is set to the lower right. The default time frame is 60 minutes. These features are all user configurable.
Other considerations
Sometimes the Tradingview data when a VX contract expires and another contract begins, may not transition cleanly and appear as a break on the chart. Tradingview is working on this as stated from my last request. This VX contract from one expiring contract to the next can be fixed on the price chart manually: ( Chart settings, Symbol, check the "Adjust for contract changes" box)
Observations
Pull up a one-hour chart of VX1 or SPY. Add this indicator. roll it back in time to see how the market and volatility reacts when the EMA changes from red to green and green to red. Adjust the EMA to your trading style and time frame. Use this for added confirmation of your long and short volatility trades with the Volatility ETFs SVIX, SVXY, VXX, UVXY, UVIX. or use it for long/short indexes such as SPY.
In den Scripts nach "one一季度财报" suchen
ATR ReadoutDisplays a readout on the bottom right corner of the screen displaying ATR average (not of the individual candlestick, but of the current rolling period, including the candlestick in question).
Due to restrictions with Pine Script (or my knowledge thereof) only the current and previous candlestick data is shown, rather than the one currently hovered over.
The data is derived via the standard calculation for ATR.
Using this, one can quickly and easily get the proper data needed to calculate one's stop loss, rather than having to analyze the line graph of the basic ATR indicator.
Settings are implemented to change certain variables to your liking.
NWOG with FVGThe New Week Opening Gap (NWOG) and Fair Value Gap (FVG) combined indicator is a trading tool designed to analyze price action and detect potential support, resistance, and trade entry opportunities based on two significant concepts:
New Week Opening Gap (NWOG): The price range between the high and low of the first candle of the new trading week.
Fair Value Gap (FVG): A price imbalance or gap between candlesticks, where price may retrace to fill the gap, indicating potential support or resistance zones.
When combined, these two concepts help traders identify key price levels (from the new week open) and price imbalances (from FVGs), which can act as powerful indicators for potential market reversals, retracements, or continuation trades.
1. New Week Opening Gap (NWOG):
Definition:
The New Week Opening Gap (NWOG) refers to the range between the high and low of the first candle in a new trading week (often, the Monday open in most markets).
Purpose:
NWOG serves as a significant reference point for market behavior throughout the week. Price action relative to this range helps traders identify:
Support and Resistance zones.
Bullish or Bearish sentiment depending on price’s relation to the opening gap levels.
Areas where the market may retrace or reverse before continuing in the primary trend.
How NWOG is Identified:
The high and low of the first candle of the new week are drawn on the chart, and these levels are used to assess the market's behavior relative to this range.
Trading Strategy Using NWOG:
Above the NWOG Range: If price is trading above the NWOG levels, it signals bullish sentiment.
Below the NWOG Range: If price is trading below the NWOG levels, it signals bearish sentiment.
Price Touching the NWOG Levels: If price approaches or breaks through the NWOG levels, it can indicate a potential retracement or reversal.
2. Fair Value Gap (FVG):
Definition:
A Fair Value Gap (FVG) occurs when there is a gap or imbalance between two consecutive candlesticks, where the high of one candle is lower than the low of the next candle (or vice versa), creating a zone that may act as a price imbalance.
Purpose:
FVGs represent an imbalance in price action, often indicating that the market moved too quickly and left behind a price region that was not fully traded.
FVGs can serve as areas where price is likely to retrace to fill the gap, as traders seek to correct the imbalance.
How FVG is Identified:
An FVG is detected if:
Bearish FVG: The high of one candle is less than the low of the next (gap up).
Bullish FVG: The low of one candle is greater than the high of the next (gap down).
The area between the gap is drawn as a shaded region, indicating the FVG zone.
Trading Strategy Using FVG:
Price Filling the FVG: Price is likely to retrace to fill the gap. A reversal candle in the FVG zone can indicate a trade setup.
Support and Resistance: FVG zones can act as support (in a bullish FVG) or resistance (in a bearish FVG) if the price retraces to them.
Combined Strategy: New Week Opening Gap (NWOG) and Fair Value Gap (FVG):
The combined use of NWOG and FVG helps traders pinpoint high-probability price action setups where:
The New Week Opening Gap (NWOG) acts as a major reference level for potential support or resistance.
Fair Value Gaps (FVG) represent market imbalances where price might retrace to, filling the gap before continuing its move.
Signal Logic:
Buy Signal:
Price touches or breaks above the NWOG range (indicating a bullish trend) and there is a bullish FVG present (gap indicating a support area).
Price retraces to fill the bullish FVG, offering a potential buy opportunity.
Sell Signal:
Price touches or breaks below the NWOG range (indicating a bearish trend) and there is a bearish FVG present (gap indicating a resistance area).
Price retraces to fill the bearish FVG, offering a potential sell opportunity.
Example:
Buy Setup:
Price breaks above the NWOG resistance level, and a bullish FVG (gap down) appears below. Traders can wait for price to pull back to fill the gap and then take a long position when confirmation occurs.
Sell Setup:
Price breaks below the NWOG support level, and a bearish FVG (gap up) appears above. Traders can wait for price to retrace and fill the gap before entering a short position.
Key Benefits of the Combined NWOG & FVG Indicator:
Combines Two Key Concepts:
NWOG provides context for the market's overall direction based on the start of the week.
FVG highlights areas where price imbalances exist and where price might retrace to, making it easier to spot entry points.
High-Probability Setups:
By combining these two strategies, the indicator helps traders spot high-probability trades based on major market levels (from NWOG) and price inefficiencies (from FVG).
Helps Identify Reversal and Continuation Opportunities:
FVGs act as potential support and resistance zones, and when combined with the context of the NWOG levels, it gives traders clearer guidance on where price might reverse or continue its trend.
Clear Visual Signals:
The indicator can plot the NWOG levels on the chart, and shade the FVG areas, providing a clean and easy-to-read chart with entry signals marked for buy and sell opportunities.
Conclusion:
The New Week Opening Gap (NWOG) and Fair Value Gap (FVG) combined indicator is a powerful tool for traders who use price action strategies. By incorporating the New Week's opening range and identifying gaps in price action, this indicator helps traders identify potential support and resistance zones, pinpoint entry opportunities, and increase the probability of successful trades.
This combined strategy enhances your analysis by adding layers of confirmation for trades based on significant market levels and price imbalances. Let me know if you'd like more details or modifications!
Turtle Soup ICT Strategy [TradingFinder] FVG + CHoCH/CSD🔵 Introduction
The ICT Turtle Soup trading setup, designed in the ICT style, operates by hunting or sweeping liquidity zones to exploit false breakouts and failed breakouts in key liquidity Zones, such as recent highs, lows, or major support and resistance levels.
This setup identifies moments when the price breaches these liquidity zones, triggering stop orders placed (Stop Hunt) by other traders, and then quickly reverses direction. These movements are often associated with liquidity sweeps that create temporary market imbalances.
The reversal is typically confirmed by one of three structural shifts : a Market Structure Shift (MSS), a Change of Character (CHoCH), or a break of the Change in State of Delivery (CISD). Each of these structural shifts provides a reliable signal to interpret market intent and align trading decisions with the expected price movement. After the structural shift, the price frequently pullback to a Fair Value Gap (FVG), offering a precise entry point for trades.
By integrating key concepts such as liquidity, liquidity sweeps, stop order activation, structural shifts (MSS, CHoCH, CISD), and price imbalances, the ICT Turtle Soup setup enables traders to identify reversal points and key entry zones with high accuracy.
This strategy is highly versatile, making it applicable across markets such as forex, stocks, cryptocurrencies, and futures. It offers traders a robust and systematic approach to understanding price movements and optimizing their trading strategies
🟣 Bullish and Bearish Setups
Bullish Setup : The price first sweeps below a Sell-Side Liquidity (SSL) zone, then reverses upward after forming an MSS or CHoCH, and finally pulls back to an FVG, creating a buying opportunity.
Bearish Setup : The price first sweeps above a Buy-Side Liquidity (BSL) zone, then reverses downward after forming an MSS or CHoCH, and finally pulls back to an FVG, creating a selling opportunity.
🔵 How to Use
To effectively utilize the ICT Turtle Soup trading setup, begin by identifying key liquidity zones, such as recent highs, lows, or support and resistance levels, in higher timeframes.
Then, monitor lower timeframes for a Liquidity Sweep and confirmation of a Market Structure Shift (MSS) or Change of Character (CHoCH).
After the structural shift, the price typically pulls back to an FVG, offering an optimal trade entry point. Below, the bullish and bearish setups are explained in detail.
🟣 Bullish Turtle Soup Setup
Identify Sell-Side Liquidity (SSL) : In a higher timeframe (e.g., 1-hour or 4-hour), identify recent price lows or support levels that serve as SSL zones, typically the location of stop-loss orders for traders.
Observe a Liquidity Sweep : On a lower timeframe (e.g., 15-minute or 30-minute), the price must move below one of these liquidity zones and then reverse. This movement indicates a liquidity sweep.
Confirm Market Structure Shift : After the price reversal, look for a structural shift (MSS or CHoCH) indicated by the formation of a Higher Low (HL) and Higher High (HH).
Enter the Trade : Once the structural shift is confirmed, the price typically pulls back to an FVG. Enter a buy trade in this zone, set a stop-loss slightly below the recent low, and target Buy-Side Liquidity (BSL) in the higher timeframe for profit.
🟣 Bearish Turtle Soup Setup
Identify Buy-Side Liquidity (BSL) : In a higher timeframe, identify recent price highs or resistance levels that serve as BSL zones, typically the location of stop-loss orders for traders.
Observe a Liquidity Sweep : On a lower timeframe, the price must move above one of these liquidity zones and then reverse. This movement indicates a liquidity sweep.
Confirm Market Structure Shift : After the price reversal, look for a structural shift (MSS or CHoCH) indicated by the formation of a Lower High (LH) and Lower Low (LL).
Enter the Trade : Once the structural shift is confirmed, the price typically pulls back to an FVG. Enter a sell trade in this zone, set a stop-loss slightly above the recent high, and target Sell-Side Liquidity (SSL) in the higher timeframe for profit.
🔵 Settings
Higher TimeFrame Levels : This setting allows you to specify the higher timeframe (e.g., 1-hour, 4-hour, or daily) for identifying key liquidity zones.
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
FVG Length : Default is 120 Bar.
MSS Length : Default is 80 Bar.
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filter s:
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
In the indicator settings, you can customize the visibility of various elements, including MSS, FVG, and HTF Levels. Additionally, the color of each element can be adjusted to match your preferences. This feature allows traders to tailor the chart display to their specific needs, enhancing focus on the key data relevant to their strategy.
🔵 Conclusion
The ICT Turtle Soup trading setup is a powerful tool in the ICT style, enabling traders to exploit false breakouts in key liquidity zones. By combining concepts of liquidity, liquidity sweeps, market structure shifts (MSS and CHoCH), and pullbacks to FVG, this setup helps traders identify precise reversal points and execute trades with reduced risk and increased accuracy.
With applications across various markets, including forex, stocks, crypto, and futures, and its customizable indicator settings, the ICT Turtle Soup setup is ideal for both beginner and advanced traders. By accurately identifying liquidity zones in higher timeframes and confirming structure shifts in lower timeframes, this setup provides a reliable strategy for navigating volatile market conditions.
Ultimately, success with this setup requires consistent practice, precise market analysis, and proper risk management, empowering traders to make smarter decisions and achieve their trading goals.
three Supertrend EMA Strategy by Prasanna +DhanuThe indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
Santa's Secrets | FractalystSanta’s Secrets is a visually engaging trading tool that infuses holiday cheer into your charts. Inspired by the enchanting, mysterious vibes of the holiday season, this indicator overlays price charts with dynamic, multi-colored glitches that sync with market data, delivering a festive and whimsical visual experience.
The indicator brings a magical touch to your charts, featuring characters from classic holiday themes (e.g., Santa, reindeer, snowflakes, gift boxes) to create a fun and festive “glitch effect.” Users can select a theme for their matrix characters, adding a holiday twist to their trading visuals. As the market data moves, these themed characters are randomly picked and displayed on the chart in a colorful cascade.
Underlying Calculations and Logic
1.Character Management:
The indicator uses arrays to manage different sets of holiday-themed characters, such as Santa’s sleigh, snowflakes, and reindeer. These arrays allow dynamic selection and update of characters as the market moves, mimicking a festive glitch effect.
2. Current and Previous States:
Arrays track the current and previous states of characters, ensuring smooth transitions between visual updates. This dual-state management enables the effects to look like a magical, continuous movement, just like Santa’s sleigh cruising through the winter night.
3. Transparency Control:
Transparency levels are controlled through arrays, adjusting opacity to create subtle fading effects or more intense visual appearances. The result is a festive glow that can fade or intensify depending on the market’s volatility.
4. Rain Effect Simulation:
To create the “snowfall” or “glitching lights” effect, the indicator manages arrays that simulate falling characters, like snowflakes or candy canes, continuously updating their position and visibility. As new characters enter the top of the screen, older ones disappear from the bottom, with fading transparency to simulate a seamless flow.
5. Operational Flow:
• Initialization: Arrays initialize the characters and transparency controls, readying the script for smooth and continuous updates during trading.
• Updates: During each cycle, new characters are selected and the old ones shift, with updates in both content and appearance ensuring the matrix effect is visually appealing.
• Rendering: The arrays control how the characters are rendered, ensuring the magical holiday effect stays lively and eye-catching without interrupting the trading flow.
How to Use Santa’s Secrets Indicator
1. Apply the Indicator to Your Charts:
Add the Santa’s Secrets indicator to your chart, activating the holiday-themed visual effect on your selected trading instrument or time frame.
2. Select Your Holiday Theme:
In the settings, choose the holiday theme or character set. Whether it’s Santa’s sleigh, reindeer, snowflakes, or gift boxes, pick the one that brings the most festive cheer to your charts.
3. Choose Your Visual Effect (Snowfall or Glitch Burst):
Select between the “Snowfall” effect, where characters gently drift down the chart like snowflakes, or the “Glitch Burst” effect, where characters explode outward in a burst of holiday cheer, representing bursts of market volatility.
4. Adjust the Color for Holiday Vibes:
Customize the color of the characters to match your chart’s aesthetic or reflect different market conditions. Choose from red for a downtrend, green for an uptrend, or opt for a gradient of colors to capture a true holiday spirit.
5. Fit the Matrix to Your Display:
Adjust the width and height of the matrix display to make sure it fits perfectly with your chart layout. Ensure it doesn’t obscure your view while still providing the holiday-themed magic.
What Makes Santa’s Secrets Indicator Unique?
Holiday Theme Selection:
Santa’s Secrets allows traders to choose from a variety of holiday-themed characters. Whether you prefer the traditional Santa’s sleigh, snowflakes, reindeer, or gift boxes, you can bring the festive spirit into your trading. This personalized touch adds a fun, holiday twist to your charts and keeps you engaged during the festive season.
Dynamic Effects:
Choose between two exciting visual modes – Snowfall Mode or Glitch Burst Mode. The Snowfall Mode brings a gentle, peaceful effect with characters cascading down the chart like snowflakes, while Glitch Burst Mode creates a more intense effect, radiating characters outward in an explosive, holiday-themed display.
Customizable Holiday Colors:
Traders can fully customize the color of the matrix characters to match their trading environment. Whether you want a traditional red and green for a Christmas mood or a blue and white snow effect, Santa’s Secrets allows you to create the perfect holiday atmosphere while you trade.
Universal Display Compatibility:
No matter what screen or device you’re using – whether it’s a large monitor, laptop, or mobile – Santa’s Secrets is fully adjustable to fit your screen size. The holiday effect remains visually striking without compromising the integrity of your chart data.
Wishing you a happy year filled with success, growth, and profitable trades.🎅🎁
Let's kick off the new year strong with Santa's Secrets! 🚀🎄
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
Short Term Imbalance ContinuationShort Term Imbalance Continuation
This indicator identifies short-term trading opportunities based on imbalance situations followed by consolidation.
Functionality:
The indicator looks for a specific candle formation:
1. An imbalance candle where the low is above the high of the following candle (bearish) or the high is below the low of the following candle (bullish)
2. Followed by 1-2 inside candles (close within the range of the previous candle) in the same direction
Theory:
The formation is based on two important market mechanisms:
1. Imbalance and Momentum:
- The imbalance shows a strong move with one-sided orderflow dominance
- Inside candles in the same direction confirm that the opposing side cannot take control
2. Consolidation Behavior:
- Inside candles are a classic consolidation pattern
- They show that the market is "digesting" the previous strong movement
- Consolidation within the range indicates controlled accumulation/distribution
- Particularly relevant when large market participants are building or expanding positions
- Consolidation at higher/lower levels confirms the dominance of the trend direction
Settings:
- Choice between one or two inside candles for different consolidation phases
- Option whether both inside candles must have the same direction
- Customizable colors for bullish and bearish signals
Application:
The indicator is particularly suitable for:
- Trend confirmation after strong movements
- Entry into pullbacks during trends
- Identification of continuation setups after consolidations
- Detection of accumulation/distribution phases of large market participants
Notes:
- Best used in combination with higher timeframe trend
- Particularly meaningful at important price zones
- Consolidation phases can indicate institutional interest
- The length of consolidation (one vs. two inside candles) can indicate different accumulation phases
Linear Regression Channel [TradingFinder] Existing Trend Line🔵 Introduction
The Linear Regression Channel indicator is one of the technical analysis tool, widely used to identify support, resistance, and analyze upward and downward trends.
The Linear Regression Channel comprises five main components : the midline, representing the linear regression line, and the support and resistance lines, which are calculated based on the distance from the midline using either standard deviation or ATR.
This indicator leverages linear regression to forecast price changes based on historical data and encapsulates price movements within a price channel.
The upper and lower lines of the channel, which define resistance and support levels, assist traders in pinpointing entry and exit points, ultimately aiding better trading decisions.
When prices approach these channel lines, the likelihood of interaction with support or resistance levels increases, and breaking through these lines may signal a price reversal or continuation.
Due to its precision in identifying price trends, analyzing trend reversals, and determining key price levels, the Linear Regression Channel indicator is widely regarded as a reliable tool across financial markets such as Forex, stocks, and cryptocurrencies.
🔵 How to Use
🟣 Identifying Entry Signals
One of the primary uses of this indicator is recognizing buy signals. The lower channel line acts as a support level, and when the price nears this line, the likelihood of an upward reversal increases.
In an uptrend : When the price approaches the lower channel line and signs of upward reversal (e.g., reversal candlesticks or high trading volume) are observed, it is considered a buy signal.
In a downtrend : If the price breaks the lower channel line and subsequently re-enters the channel, it may signal a trend change, offering a buying opportunity.
🟣 Identifying Exit Signals
The Linear Regression Channel is also used to identify sell signals. The upper channel line generally acts as a resistance level, and when the price approaches this line, the likelihood of a price decrease increases.
In an uptrend : Approaching the upper channel line and observing weakness in the uptrend (e.g., declining volume or reversal patterns) indicates a sell signal.
In a downtrend : When the price reaches the upper channel line and reverses downward, this is considered a signal to exit trades.
🟣 Analyzing Channel Breakouts
The Linear Regression Channel allows traders to identify price breakouts as strong signals of potential trend changes.
Breaking the upper channel line : Indicates buyer strength and the likelihood of a continued uptrend, often accompanied by increased trading volume.
Breaking the lower channel line : Suggests seller dominance and the possibility of a continued downtrend, providing a strong sell signal.
🟣 Mean Reversion Analysis
A key concept in using the Linear Regression Channel is the tendency for prices to revert to the midline of the channel, which acts as a dynamic moving average, reflecting the price's equilibrium over time.
In uptrends : Significant deviations from the midline increase the likelihood of a price retracement toward the midline.
In downtrends : When prices deviate considerably from the midline, a return toward the midline can be used to identify potential reversal points.
🔵 Settings
🟣 Time Frame
The time frame setting enables users to view higher time frame data on a lower time frame chart. This feature is especially useful for traders employing multi-time frame analysis.
🟣 Regression Type
Standard : Utilizes classical linear regression to draw the midline and channel lines.
Advanced : Produces similar results to the standard method but may provide slightly different alignment on the chart.
🟣 Scaling Type
Standard Deviation : Suitable for markets with stable volatility.
ATR (Average True Range) : Ideal for markets with higher volatility.
🟣 Scaling Coefficients
Larger coefficients create broader channels for broader trend analysis.
Smaller coefficients produce tighter channels for precision analysis.
🟣 Channel Extension
None : No extension.
Left: Extends lines to the left to analyze historical trends.
Right : Extends lines to the right for future predictions.
Both : Extends lines in both directions.
🔵 Conclusion
The Linear Regression Channel indicator is a versatile and powerful tool in technical analysis, providing traders with support, resistance, and midline insights to better understand price behavior. Its advanced settings, including time frame selection, regression type, scaling options, and customizable coefficients, allow for tailored and precise analysis.
One of its standout advantages is its ability to support multi-time frame analysis, enabling traders to view higher time frame data within a lower time frame context. The option to use scaling methods like ATR or standard deviation further enhances its adaptability to markets with varying volatility.
Designed to identify entry and exit signals, analyze mean reversion, and assess channel breakouts, this indicator is suitable for a wide range of markets, including Forex, stocks, and cryptocurrencies. By incorporating this tool into your trading strategy, you can make more informed decisions and improve the accuracy of your market predictions.
Daily Single Trade [SMRT Algo]The Daily Single Trade Indicator by SMRT Algo is a powerful yet simple tool designed for traders who value precision, discipline, and a focus on high-quality trade setups. With a unique approach, this indicator identifies just one signal daily, making it ideal for traders who prefer a structured and stress-free trading routine.
Please note that this indicator only works for timeframes below 1H.
Key Features:
Market Open & Pre-Market Analysis: The indicator focuses on the market’s opening range and identifies breakout opportunities based on price action during these critical periods.
Customizable Risk-Reward Ratio: Plan your trades with precision by setting your desired RR, ensuring that your take-profit (TP) levels are multiples of your stop-loss (SL). Stop loss is not shown with this indicator.
Price Offset for SL: Add a customizable buffer to your SL and TP levels. This offset accounts for market volatility, reducing the chances of premature stop-outs while maintaining alignment with your trading plan.
Increasing this value will lead to a greater invisible stop loss, which will increase the TP size. The opposite is occurs when decreasing this value (less than 0). If you set it as 2.5 for example for TSLA: price is 340 and SL is 330 for example, SL becomes 327.5. This calculation will then be applied to calculate the TP.
In simple terms, if the offset is positive, SL becomes larger, TP becomes larger as well.
Exit Point Visibility: Display exit points on your chart to better visualize trade targets and stop levels.
Adjustable Market Open Time: Easily modify the market open hour and minute to suit your asset’s trading session. For example, U.S. stock traders can set the market open time to 9:30 AM EST (UTC-5).
By providing a single signal each day, the indicator minimizes overtrading and keeps your focus on the best opportunities.
With predefined SL, TP, and RR settings, the indicator fosters disciplined trading, reducing the influence of emotional decision-making. Whether you’re trading stocks, indices, or forex, the customizable market open time and RR ratio make this indicator versatile and adaptable.
The combination of precise SL and TP calculations with offset pip adjustments helps protect your trades from market noise while maintaining a favorable RR.
Perfect for those who can’t monitor markets all day, the single-signal approach allows you to execute a high-quality trade and move on with your day.
How to Use:
Set the Market Open Time: Adjust the open time to align with your asset’s session. For example, set 9:30 AM EST for U.S. stocks.
Define Your Risk-Reward Ratio: Choose an RR multiple (e.g., 1:2 or 1:3) that aligns with your risk tolerance and trading goals.
Apply Pip Offset: Add a buffer to your SL and TP to account for market volatility and reduce false stops.
The Daily Single Trade Indicator simplifies trading by focusing on one high-probability setup per day. It’s perfect for traders looking to maintain consistency, improve risk management, and reduce the stress of overanalyzing the markets.
How Alerts Work:
Individual Alerts: Set separate notifications for specific actions, such as breakout signals, take-profit levels, or stop-loss activations.
Master Alert: Manage all notifications with one streamlined setting, ensuring you never miss an opportunity while keeping your setup simple and efficient.
Take control of your trading with a strategy built for clarity, precision, and success!
Top-Down Trend and Key Levels with Swing Points//by antaryaami0
Overview
The “Top-Down Trend and Key Levels with Swing Points” indicator is a comprehensive tool designed to enhance your technical analysis by integrating multiple trading concepts into a single, easy-to-use script. It combines higher timeframe trend analysis, key price levels, swing point detection, and ranging market identification to provide a holistic view of market conditions. This indicator is particularly useful for traders who employ multi-timeframe analysis, support and resistance levels, and price action strategies.
Key Features
1. Higher Timeframe Trend Background Shading:
• Purpose: Identifies the prevailing trend on a higher timeframe to align lower timeframe trading decisions with the broader market direction.
• How it Works: The indicator compares the current higher timeframe close with the previous one to determine if the trend is up, down, or ranging.
• Customization:
• Trend Timeframe: Set your preferred higher timeframe (e.g., Daily, Weekly).
• Up Trend Color & Down Trend Color: Customize the background colors for uptrends and downtrends.
• Ranging Market Color: A separate color to indicate when the market is moving sideways.
2. Key Price Levels:
• Previous Day High (PDH) and Low (PDL):
• Purpose: Identifies key support and resistance levels from the previous trading day.
• Visualization: Plots horizontal lines at PDH and PDL with labels.
• Customization: Option to show or hide these levels and customize their colors.
• Pre-Market High (PMH) and Low (PML):
• Purpose: Highlights the price range during the pre-market session, which can indicate potential breakout levels.
• Visualization: Plots horizontal lines at PMH and PML with labels.
• Customization: Option to show or hide these levels and customize their colors.
3. First 5-Minute Marker (F5H/F5L):
• Purpose: Marks the high or low of the first 5 minutes after the market opens, which is significant for intraday momentum.
• How it Works:
• If the first 5-minute high is above the Pre-Market High (PMH), an “F5H” label is placed at the first 5-minute high.
• If the first 5-minute high is below the PMH, an “F5L” label is placed at the first 5-minute low.
• Visualization: Labels are placed at the 9:35 AM candle (closing of the first 5 minutes), colored in purple by default.
• Customization: Option to show or hide the marker and adjust the marker color.
4. Swing Points Detection:
• Purpose: Identifies significant pivot points in price action to help recognize trends and reversals.
• How it Works: Uses left and right bars to detect pivot highs and lows, then determines if they are Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), or Lower Lows (LL).
• Visualization: Plots small markers (circles) with labels (HH, LH, HL, LL) at the corresponding swing points.
• Customization: Adjust the number of left and right bars for pivot detection and the size of the markers.
5. Ranging Market Detection:
• Purpose: Identifies periods when the market is consolidating (moving sideways) within a defined price range.
• How it Works: Calculates the highest high and lowest low over a specified period and determines if the price range is within a set percentage threshold.
• Visualization: Draws a gray box around the price action during the ranging period and labels the high and low prices at the end of the range.
• Customization: Adjust the range detection period and threshold, as well as the box color.
6. Trend Coloring on Chart:
• Purpose: Provides a visual cue for the short-term trend based on a moving average.
• How it Works: Colors the candles green if the price is above the moving average and red if below.
• Customization: Set the moving average length and customize the uptrend and downtrend colors.
How to Use the Indicator
1. Adding the Indicator to Your Chart:
• Copy the Pine Script code provided and paste it into the Pine Script Editor on TradingView.
• Click “Add to Chart” to apply the indicator.
2. Configuring Inputs and Settings:
• Access Inputs:
• Click on the gear icon next to the indicator’s name on your chart to open the settings.
• Customize Key Levels:
• Show Pre-Market High/Low: Toggle on/off.
• Show Previous Day High/Low: Toggle on/off.
• Show First 5-Minute Marker: Toggle on/off.
• Set Trend Parameters:
• Trend Timeframe for Background: Choose the higher timeframe for trend analysis.
• Moving Average Length for Bar Color: Set the period for the moving average used in bar coloring.
• Adjust Ranging Market Detection:
• Range Detection Period: Specify the number of bars to consider for range detection.
• Range Threshold (%): Set the maximum percentage range for the market to be considered ranging.
• Customize Visuals:
• Colors: Adjust colors for trends, levels, markers, and ranging market boxes.
• Label Font Size: Choose the size of labels displayed on the chart.
• Level Line Width: Set the thickness of the lines for key levels.
3. Interpreting the Indicator:
• Background Shading:
• Green Shade: Higher timeframe is in an uptrend.
• Red Shade: Higher timeframe is in a downtrend.
• Gray Box: Market is ranging (sideways movement).
• Key Levels and Markers:
• PDH and PDL Lines: Represent resistance and support from the previous day.
• PMH and PML Lines: Indicate potential breakout levels based on pre-market activity.
• F5H/F5L Labels: Early indication of intraday momentum after market open.
• Swing Point Markers:
• HH (Higher High): Suggests bullish momentum.
• LH (Lower High): May indicate a potential bearish reversal.
• HL (Higher Low): Supports bullish continuation.
• LL (Lower Low): Indicates bearish momentum.
• Ranging Market Box:
• Gray Box Around Price Action: Highlights consolidation periods where breakouts may occur.
• Range High and Low Labels: Provide the upper and lower bounds of the consolidation zone.
4. Applying the Indicator to Your Trading Strategy:
• Trend Alignment:
• Use the higher timeframe trend shading to align your trades with the broader market direction.
• Key Levels Trading:
• Watch for price reactions at PDH, PDL, PMH, and PML for potential entry and exit points.
• Swing Points Analysis:
• Identify trend continuations or reversals by observing the sequence of HH, HL, LH, and LL.
• Ranging Market Strategies:
• During ranging periods, consider range-bound trading strategies or prepare for breakout trades when the price exits the range.
• Intraday Momentum:
• Use the F5H/F5L marker to gauge early market sentiment and potential intraday trends.
Practical Tips
• Adjust Settings to Your Trading Style:
• Tailor the indicator’s inputs to match your preferred timeframes and trading instruments.
• Combine with Other Indicators:
• Use in conjunction with volume indicators, oscillators, or other technical tools for additional confirmation.
• Backtesting:
• Apply the indicator to historical data to observe how it performs and refine your settings accordingly.
• Stay Updated on Market Conditions:
• Be aware of news events or economic releases that may impact market behavior and the effectiveness of technical levels.
Customization Options
• Time Zone Adjustment:
• The script uses “America/New_York” time zone by default. Adjust the timezone variable in the script if your chart operates in a different time zone.
var timezone = "Your/Timezone"
• Session Times:
• Modify the Regular Trading Session and Pre-Market Session times in the indicator settings to align with the trading hours of different markets or exchanges.
• Visual Preferences:
• Colors: Personalize the indicator’s colors to suit your visual preferences or to enhance visibility.
• Label Sizes: Adjust label sizes if you find them too intrusive or not prominent enough.
• Marker Sizes: Further reduce or enlarge the swing point markers by modifying the swing_marker_size variable.
Understanding the Indicator’s Logic
1. Higher Timeframe Trend Analysis:
• The indicator retrieves the closing prices of a higher timeframe using the request.security() function.
• It compares the current higher timeframe close with the previous one to determine the trend direction.
2. Key Level Calculation:
• Previous Day High/Low: Calculated by tracking the highest and lowest prices of the previous trading day.
• Pre-Market High/Low: Calculated by monitoring price action during the pre-market session.
3. First 5-Minute Marker Logic:
• At 9:35 AM (end of the first 5 minutes after market open), the indicator evaluates whether the first 5-minute high is above or below the PMH.
• It then places the appropriate label (F5H or F5L) on the chart.
4. Swing Points Detection:
• The script uses ta.pivothigh() and ta.pivotlow() functions to detect pivot points.
• It then determines the type of swing point based on comparisons with previous swings.
5. Ranging Market Detection:
• The indicator looks back over a specified number of bars to find the highest high and lowest low.
• It calculates the percentage difference between these two points.
• If the difference is below the set threshold, the market is considered to be ranging, and a box is drawn around the price action.
Limitations and Considerations
• Indicator Limitations:
• Maximum Boxes and Labels: Due to Pine Script limitations, there is a maximum number of boxes and labels that can be displayed simultaneously.
• Performance Impact: Adding multiple visual elements (boxes, labels, markers) can affect the performance of the script on lower-end devices or with large amounts of data.
• Market Conditions:
• False Signals: Like any technical tool, the indicator may produce false signals, especially during volatile or erratic market conditions.
• Not a Standalone Solution: This indicator should be used as part of a comprehensive trading strategy, including risk management and other forms of analysis.
Conclusion
The “Top-Down Trend and Key Levels with Swing Points” indicator is a versatile tool that integrates essential aspects of technical analysis into one script. By providing insights into higher timeframe trends, highlighting key price levels, detecting swing points, and identifying ranging markets, it equips traders with valuable information to make more informed trading decisions. Whether you are a day trader looking for intraday opportunities or a swing trader aiming to align with the broader trend, this indicator can enhance your chart analysis and trading strategy.
Disclaimer
Trading involves significant risk, and it’s important to understand that past performance is not indicative of future results. This indicator is a tool to assist in analysis and should not be solely relied upon for making trading decisions. Always conduct thorough research and consider seeking advice from financial professionals before engaging in trading activities.
Prometheus Markov ChainThe Prometheus Markov Chain Indicator is a custom-built tool designed to predict potential future price movements using a Markov Chain approach. A Markov Chain is a statistical model that assumes the probability of moving to a future state depends solely on the current state. In this indicator, states represent price movement classifications—bullish, bearish, or neutral—and are determined based on historical price changes (percentage returns). The indicator builds a transition matrix to calculate probabilities of transitioning from one state to another, enabling traders to identify patterns and forecast likely price actions.
Core Functionality and Transition Matrix
The transition matrix is the backbone of the Markov Chain. It captures the frequency of transitions between states in the historical price data and normalizes these counts into probabilities. For example, if the price was in a bearish state and transitioned to a bullish state 3 out of 10 times, the probability of transitioning from bearish to bullish would be 0.3. The matrix is created dynamically using the stateFunc function to classify states, which can use either dynamic thresholds (highest and lowest returns over a lookback period) or a user-defined percent return threshold. Below is the snippet that updates the transition matrix:
transitionMatrix = matrix.new(dimension, dimension, 0.0)
for i = 0 to array.size(vec) - 2
fromState = array.get(vec, i)
toState = array.get(vec, i + 1)
transitionMatrix.set(fromState, toState, transitionMatrix.get(fromState, toState) + 1)
for i = 0 to dimension - 1
rowSum = 0.0
for j = 0 to dimension - 1
rowSum += transitionMatrix.get(i, j)
for j = 0 to dimension - 1
prob = transitionMatrix.get(i, j) / rowSum
transitionMatrix.set(i, j, prob)
This snippet iterates through historical price movements, counts state transitions, and then normalizes each row of the matrix so that the sum of probabilities for all possible transitions from a given state equals 1.
How the Indicator Predicts Future States
After constructing the transition matrix, the indicator calculates the current state of the price based on the latest percentage return and then uses the matrix to compute probabilities for transitioning to other states. The state with the highest probability is predicted as the next state, which is displayed on the chart using color-coded labels: green for bullish and red for bearish. The following snippet demonstrates how the current state and predictions are calculated:
current_chng = (close - close ) / close
var int current_state = na
if not use_custom_thresh
highest_chng = ta.highest(current_chng, int(size) * 2)
lowest_chng = ta.lowest(current_chng, int(size) * 2)
current_state := stateFunc(current_chng, highest_chng, lowest_chng)
else
current_state := stateFunc(current_chng, custom_thresh)
predicted_probs = array.new(dimension, 0.0)
for j = 0 to dimension - 1
array.set(predicted_probs, j, transitionMatrix.get(current_state, j))
The indicator evaluates which state has the highest transition probability (highest_prob) and places corresponding labels on the chart. For example, if the next state is predicted to be bullish, a green "Bullish" label is placed below the current bar. This predictive functionality helps traders anticipate potential reversals or continuations in price trends based on historical behavior patterns.
Usage:
Here we see the indicator at work on $PLTR. The states predicted are bullish then bearish. In this example we then see price move in a way that verifies those predictions.
On this 4 Hour NASDAQ:AMZN chart we see predictions play out in a short trade style. States quickly move from one to another but not without giving traders a way to take advantage.
This is the perspective we aim to provide. We encourage traders to not follow indicators blindly. No indicator is 100% accurate. This one can give you a different perspective market state. We encourage any comments about desired updates or criticism!
PSP Indicator [Elbaz]Precision Swing Point or PSP is a unique technical analysis tool designed to compare the price action of three tickers that are in sync.
It highlights moments when the price structure diverges between the markets, identifying ideal entry points for trades - We would like to enter a trade when we found PSP and one of the tickers took the wick while others didn't.
This strategy provides an edge by focusing on periods of desynchronization between the indices, where one index may be showing strength while another is lagging. The idea is to find the moments where the candle colors (bullish or bearish) differ across the markets, then wait for one of the tickers to "take" the wick of the PSP while other didn't and enter a trade.
Once a divergence is detected, the indicator plots an arrow on the chart, signaling a potential trade entry. To minimize risk, a good place to put stop loss will at the end of the wick of the PSP — the high or low wick of the candle where the divergence occurs.
The PSP Indicator allows for several custom inputs:
- Tickers: Customize the tickers to compare. The default values are S&P 500 E-mini, NASDAQ E-mini, and Dow Jones E-mini, if you trade Crypto you might want to use BTC, ETH, TOTAL3.
- Lookback Period: The lookback input defines how far back the indicator should evaluate to calculate the price structure point.
- Highlight Bar Times: Users can specify particular times during the trading day to highlight, such as the market open or significant news events. This helps traders focus on key trading windows.
Adaptive Linear Regression ChannelOverview
The Adaptive Linear Regression Channel Script is an advanced, multi-functional trading tool crafted to help traders pinpoint market trends, identify potential reversals, assess volatility, and establish dynamic levels for profit-taking and position exits. By incorporating key concepts such as linear regression , standard deviation , and other volatility measures like the ATR , the script offers a comprehensive view of market behavior beyond traditional deviation metrics.
This dynamic model continuously adapts to changing market conditions, adjusting in real-time to provide clear visualizations of trends, channels, and volatility levels. This adaptability makes the script invaluable for both trend-following and counter-trend strategies, giving traders the flexibility to respond effectively to different market environments.
Background
What is Linear Regression?
Definition : Linear regression is a statistical technique used to model the relationship between a dependent variable (target) and one or more independent variables (predictors).
In its simplest form (simple linear regression), the relationship between two variables is represented by a straight line (the regression line).
y = mx + b
where :
- y is the target variable (price)
- m is the slope
- x is the independent variable (time)
- b is the intercept
Slope of the Regression Line
Definition: The slope (m) measures the rate at which the dependent variable (y) changes as the independent variable (x) changes.
Interpretation:
- A positive slope indicates an uptrend.
- A negative slope indicates a downtrend.
Uses in Trading:
- Identifying the strength and direction of market trends.
- Assessing the momentum of price movements.
R-squared (Coefficient of Determination)
Definition: A measure of how well the regression line fits the data, ranging from 0 to 1.
Calculation :
R2 = 1− (SS tot/SS res)
where:
- SSres is the sum of squared residuals.
- SStot is the total sum of squares.
Interpretation:
- Higher R2 indicates a better fit, meaning the model explains a larger proportion of the variance in the data.
Uses in Trading:
- Higher R-squared values give traders confidence in trend-based signals.
- Low R-squared values may suggest that the market is more random or volatile.
Standard Deviation
Definition: Standard Deviation quantifies the dispersion of data points in a dataset relative to the mean. A low standard deviation indicates that data points tend to be close to the mean, while a high standard deviation indicates that the data points are spread out over a larger range of values.
Calculation
σ=√∑(xi−μ)2/N
Where
- σ is the standard deviation.
- ∑ is the summation symbol, indicating that the expression that follows should be summed over all data points.
- xi, this represents the i-th data point in the dataset.
- μ\mu, this represents the mean(average) of all the data points in the dataset.
- (xi−μ)2, this is the squared difference between each data point and the mean.
- N is the total number of data points in the dataset.
- **Interpretation**
- A higher standard deviation indicates greater volatility.
- Useful for identifying overbought/oversold conditions in markets.
Key Features
Dynamic Linear Regression Channels:
The script automatically generates adaptive regression channels that expand or contract based on the current market volatility. This real-time adjustment ensures that traders are always working with the most relevant data, making it easier to spot key support and resistance levels.
The channel width itself serves as an indicator of market volatility, expanding during periods of heightened uncertainty and contracting during more stable phases. Additionally, the channel width is trained on previous channel widths , allowing the script to adapt and provide a more accurate view of volatility trends of the asset. Traders can also customize the script to train on less historical data , enabling a more recent view of volatility , which is particularly useful in fast-moving or changing markets.
Dynamic Profits and Stops:
What is it?
Dynamic profit levels allow traders to adjust take-profit targets based on real-time market conditions. Unlike static levels, which remain fixed regardless of market changes, these adaptive levels leverage past volatility data to create more flexible profit-taking strategies.
How does it work?
The script determines these levels using previously stored deviation values. These deviations are categorized into quantiles (like Q1, Q2, Q3, etc.) to classify current market conditions. As new deviation data is recorded, the profit levels are adjusted dynamically to reflect changes in market volatility. This approach helps to refine profit targets, especially when using regression channels with standard deviation rather than traditional ATR bands.
Why is it valuable?
By utilizing adaptive profit levels, traders can optimize their exits based on the current volatility landscape. For instance, when volatility increases, the dynamic levels expand, allowing trades to capture larger price movements. Conversely, during low volatility, profit targets tighten to lock in gains sooner, reducing exposure to market reversals. This flexibility is especially beneficial when combined with adaptive regression channels that respond to changes in standard deviation.
Slope-Based Trend Analysis:
One of the core elements of this script is the slope of the regression line , which helps define the direction and strength of the trend. Positive slopes indicate bullish momentum, while negative slopes suggest bearish conditions. The slope's steepness gives traders insight into the market's momentum, allowing them to adjust their strategies based on the strength of the trend.
Additionally, the script uses the slope to create a color gradient , which visually represents the intensity of the market's momentum. The gradient peaks at one color to show the maximum bullish momentum experienced in the past, while another color represents the maximum bearish momentum experienced in the past. This color-coded visualization makes it easier for traders to quickly assess the market's strength and direction at a glance.
Volatility Heatmap:
The integrated heatmap provides an intuitive, color-coded visualization of market volatility. The heatmap highlights areas where price action is expanding or contracting, giving traders a clear view of where volatility is rising or falling. By mapping out deviations from the regression line, the heatmap makes it easier to spot periods of high volatility that could lead to major market moves or potential reversals.
Deviation Concepts:
The script tracks price deviations from the regression line when a new range is formed, providing valuable insights when the price significantly deviates from the expected trend. These deviations are key in identifying potential breakout points or trend shifts .
This helps traders understand when the market is overextended or when a pullback may be imminent, allowing them to make more informed trading decisions.
Adaptive Model Properties:
Unlike static indicators, this script adapts over time . As the market changes, it stores historical data related to channel widths , slope dynamics , and volatility levels , adjusting its analysis accordingly to stay relevant to current market conditions.
Traders have the ability to train the model on all available data or specify a set number of bars to focus on more recent market activity. This flexibility allows for more tailored analysis , ensuring that traders can work with data that best fits their trading style and time horizon.
This continuous learning approach ensures that traders always have the most up-to-date insight into the market's structure.
Table
The table displays key metrics in real time to provide deeper insights into market behavior:
1. Deviation & Slope : Shows the current deviation if set to standard deviation or atr if set to atr(values used to calculated the channel widths) and the trend slope, helping to gauge market volatility and trend direction.
2. Rate of Change : For both deviation/atr and slope, the table also calculates the rate of change of their rates—essentially capturing the acceleration or deceleration of trends and volatility. This helps identify shifts in market momentum early.
3. R-squared : Indicates the strength and reliability of the trend fit. A higher value means the regression line better explains the price movements.
4. Quantiles : Uses historical deviation data to categorize current market conditions into quartiles (e.g., Q1, Q2, Q3). This helps classify the market's current volatility level, allowing traders to adjust strategies dynamically.
By combining these metrics, the table offers a comprehensive, real-time snapshot of market conditions, enabling more informed and adaptive trading decisions.
Settings
Here’s a breakdown of the script's settings for easy reference:
Linear Regression Settings
Show Dynamic Levels :Toggle to display dynamic profit levels on the chart.
Deviation Type :Select the method for calculating deviation—options include ATR (Average True Range) or Standard Deviation.
Timeframe :Sets the specific timeframe for the regression analysis (default is the chart’s timeframe).
Period :Defines the number of bars used for calculating the regression line (e.g., 50 bars).
Deviation Multiplier :Multiplier used to adjust the width of the deviation channel around the regression line.
Rate of Change :Sets the period for calculating the rate of change of the slope (used for momentum analysis).
Max Bars Back :Limits the number of historical bars to analyze (0 means all available data).
Slope Lookback :Number of bars used to calculate the slope gradient for trend detection.
Slope Gradient Display :Toggle to enable gradient coloring based on slope direction.
Slope Gradient Colors :Set colors for positive and negative slopes, respectively.
Slope Fill :Adjusts the transparency of the slope gradient fill.
Volatility Gradient Display :Toggle to enable gradient coloring based on volatility levels.
Volatility Gradient Colors :Set colors for low and high volatility, respectively.
Volatility Fill :Adjusts the transparency of the volatility gradient fill.
Table Settings
Show Table :Toggle to display the metrics table on the chart.
Table Position :Choose where to position the table (e.g., top-right, middle-center, etc.).
Font Size :Set the size of the text in the table. Options include Tiny, Small, Normal, Large, and Huge.
Forex Heatmap█ OVERVIEW
This indicator creates a dynamic grid display of currency pair cross rates (exchange rates) and percentage changes, emulating the Cross Rates and Heat Map widgets available on our Forex page. It provides a view of realtime exchange rates for all possible pairs derived from a user-specified list of currencies, allowing users to monitor the relative performance of several currencies directly on a TradingView chart.
█ CONCEPTS
Foreign exchange
The Foreign Exchange (Forex/FX) market is the largest, most liquid financial market globally, with an average daily trading volume of over 5 trillion USD. Open 24 hours a day, five days a week, it operates through a decentralized network of financial hubs in various major cities worldwide. In this market, participants trade currencies in pairs , where the listed price of a currency pair represents the exchange rate from a given base currency to a specific quote currency . For example, the "EURUSD" pair's price represents the amount of USD (quote currency) that equals one unit of EUR (base currency). Globally, the most traded currencies include the U.S. dollar (USD), Euro (EUR), Japanese yen (JPY), British pound (GBP), and Australian dollar (AUD), with USD involved in over 87% of all trades.
Understanding the Forex market is essential for traders and investors, even those who do not trade currency pairs directly, because exchange rates profoundly affect global markets. For instance, fluctuations in the value of USD can impact the demand for U.S. exports or the earnings of companies that handle multinational transactions, either of which can affect the prices of stocks, indices, and commodities. Additionally, since many factors influence exchange rates, including economic policies and interest rate changes, analyzing the exchange rates across currencies can provide insight into global economic health.
█ FEATURES
Requesting a list of currencies
This indicator requests data for every valid currency pair combination from the list of currencies defined by the "Currency list" input in the "Settings/Inputs" tab. The list can contain up to six unique currency codes separated by commas, resulting in a maximum of 30 requested currency pairs.
For example, if the specified "Currency list" input is "CAD, USD, EUR", the indicator requests and displays relevant data for six currency pair combinations: "CADUSD", "USDCAD", "CADEUR", "EURCAD", "USDEUR", "EURUSD". See the "Grid display" section below to understand how the script organizes the requested information.
Each item in the comma-separated list must represent a valid currency code. If the "Currency list" input contains an invalid currency code, the corresponding cells for that currency in the "Cross rates" or "Heat map" grid show "NaN" values. If the list contains empty items, e.g., "CAD, ,EUR, ", the indicator ignores them in its data requests and calculations.
NOTE: Some uncommon currency pair combinations might not have data feeds available. If no available symbols provide the exchange rates between two specified currencies, the corresponding table cells show "NaN" results.
Realtime data
The indicator retrieves realtime market prices, daily price changes, and minimum tick sizes for all the currency pairs derived from the "Currency list" input. It updates the retrieved information shown in its grid display after new ticks become available to reflect the latest known values.
NOTE: Pine scripts execute on realtime bars only when new ticks are available in the chart's data feed. If no new updates are available from the chart's realtime feed, it may cause a delay in the data the indicator receives.
Grid display
This indicator displays the requested data for each currency pair in a table with cells organized as a grid. Each row name corresponds to a pair's base currency , and each column name corresponds to a quote currency . The cell at the intersection of a specific row and column shows the value requested from the corresponding currency pair.
For example, the cell at the intersection of a "EUR" row and "USD" column shows the data retrieved for the "EURUSD" currency pair, and the cell at the "USD" row and "EUR" column shows data for the inverse pair ("USDEUR").
Note that the main diagonal cells in the table, where rows and columns with the same names intersect, are blank. The exchange rate from one currency to itself is always 1, and no Forex symbols such as "EUREUR" exist.
The dropdown input at the top of the "Settings/Inputs" tab determines the type of information displayed in the table. Two options are available: "Cross rates" and "Heat map" . Both modes color their cells for light and dark themes separately based on the inputs in the "Colors" section.
Cross rates
When a user selects the "Cross rates" display mode, the table's cells show the latest available exchange rate for each currency pair, emulating the behavior of the Cross Rates widget. Each cell's value represents the amount of the quote currency (column name) that equals one unit of the base currency (row name). This display allows users to compare cross rates across currency pairs, and their inverses.
The background color of each cell changes based on the most recent update to the exchange rate, allowing users to monitor the direction of short-term fluctuations as they occur. By default, the background turns green (positive cell color) when the cross rate increases from the last recorded update and red (negative cell color) when the rate decreases. The cell's color reverts to the chart's background color after no new updates are available for 200 milliseconds.
Heat map
When a user selects the "Heat map" display mode, the table's cells show the latest daily percentage change of each currency pair, emulating the behavior of the Heat Map widget.
In this mode, the background color of each cell depends on the corresponding currency pair's daily performance. Heat maps typically use colors that vary in intensity based on the calculated values. This indicator uses the following color coding by default:
• Green (Positive cell color): Percentage change > +0.1%
• No color: Percentage change between 0.0% and +0.1%
• Bright red (Negative cell color): Percentage change < -0.1%
• Lighter/darker red (Minor negative cell color): Percentage change between 0.0% and -0.1%
█ FOR Pine Script™ CODERS
• This script utilizes dynamic requests to iteratively fetch information from multiple contexts using a single request.security() instance in the code. Previously, `request.*()` functions were not allowed within the local scopes of loops or conditional structures, and most `request.*()` function parameters, excluding `expression`, required arguments of a simple or weaker qualified type. The new `dynamic_requests` parameter in script declaration statements enables more flexibility in how scripts can use `request.*()` calls. When its value is `true`, all `request.*()` functions can accept series arguments for the parameters that define their requested contexts, and `request.*()` functions can execute within local scopes. See the Dynamic requests section of the Pine Script™ User Manual to learn more.
• Scripts can execute up to 40 unique `request.*()` function calls. A `request.*()` call is unique only if the script does not already call the same function with the same arguments. See this section of the User Manual's Limitations page for more information.
• Typically, when requesting higher-timeframe data with request.security() using barmerge.lookahead_on as the `lookahead` argument, the `expression` argument should use the history-referencing operator to offset the series, preventing lookahead bias on historical bars. However, the request.security() call in this script uses barmerge.lookahead_on without offsetting the `expression` because the script only displays results for the latest historical bar and all realtime bars, where there is no future information to leak into the past. Instead, using this call on those bars ensures each request fetches the most recent data available from each context.
• The request.security() instance in this script includes a `calc_bars_count` argument to specify that each request retrieves only a minimal number of bars from the end of each symbol's historical data feed. The script does not need to request all the historical data for each symbol because it only shows results on the last chart bar that do not depend on the entire time series. In this case, reducing the retrieved bars in each request helps minimize resource usage without impacting the calculated results.
Look first. Then leap.
Market Stats Panel [Daveatt]█ Introduction
I've created a script that brings TradingView's watchlist stats panel functionality directly to your charts. This isn't just another performance indicator - it's a pixel-perfect (kidding) recreation of TradingView's native stats panel.
Important Notes
You might need to adjust manually the scaling the firs time you're using this script to display nicely all the elements.
█ Core Features
Performance Metrics
The panel displays key performance metrics (1W, 1M, 3M, 6M, YTD, 1Y) in real-time, with color-coded boxes (green for positive, red for negative) for instant performance assessment.
Display Modes
Switch seamlessly between absolute prices and percentage returns, making it easy to compare assets across different price scales.
Absolute mode
Percent mode
Historical Comparison
View year-over-year performance with color-coded lines, allowing for quick historical pattern recognition and analysis.
Data Structure Innovation
Let's talk about one of the most interesting challenges I faced. PineScript has this quirky limitation where request.security() can only return 127 tuples at most. £To work around this, I implemented a dual-request system. The first request handles indices 0-63, while the second one takes care of indices 64-127.
This approach lets us maintain extensive historical data without compromising script stability.
And here's the cool part: if you need to handle even more years of historical data, you can simply extend this pattern by adding more request.security() calls.
Each additional call can fetch another batch of monthly open prices and timestamps, following the same structure I've used.
Think of it as building with LEGO blocks - you can keep adding more pieces to extend your historical reach.
Flexible Date Range
Unlike many scripts that box you into specific timeframes, I've designed this one to be completely flexible with your date selection. You can set any start year, any end year, and the script will dynamically scale everything to match. The visual presentation automatically adjusts to whatever range you choose, ensuring your data is always displayed optimally.
█ Customization Options
Visual Settings
The panel's visual elements are highly customizable. You can adjust the panel width to perfectly fit your workspace, fine-tune the line thickness to match your preferences, and enjoy the pre-defined year color scheme that makes tracking historical performance intuitive and visually appealing.
Box Dimensions
Every aspect of the performance boxes can be tailored to your needs. Adjust their height and width, fine-tune the spacing between them, and position the entire panel exactly where you want it on your chart. The goal is to make this tool feel like it's truly yours.
█ Technical Challenges Solved
Polyline Precision
Creating precise polylines was perhaps the most demanding aspect of this project.
The challenge was ensuring accurate positioning across both time and price axes, while handling percentage mode scaling with precision.
The script constantly updates the current year's data in real-time, seamlessly integrating new information as it comes in.
Axis Management
Getting the axes right was like solving a complex puzzle. The Y-axis needed to scale dynamically whether you're viewing absolute prices or percentages.
The X-axis required careful month labeling that stays clean and readable regardless of your selected timeframe.
Everything needed to align perfectly while maintaining proper spacing in all conditions.
█ Final Notes
This tool transforms complex market data into clear, actionable insights. Whether you're day trading or analyzing long-term trends, it provides the information you need to make informed decisions. And remember, while we can't predict the future, we can certainly be better prepared for it with the right tools at hand.
A word of warning though - seeing those red numbers in a beautifully formatted panel doesn't make them any less painful! 😉
---
Happy Trading! May your charts be green and your stops be far away!
Daveatt
Quick scan for cycles🙏🏻
The followup for
As I told before, ML based algorading is all about detecting any kind of non-randomness & exploiting it (cuz allegedly u cant trade randomness), and cycles are legit patterns that can be leveraged
But bro would u really apply Fourier / Wavelets / 'whatever else heavy' on every update of thousands of datasets, esp in real time on HFT / nearly HFT data? That's why this metric. It works much faster & eats hell of a less electicity, will do initial rough filtering of time series that might contain any kind of cyclic behaviour. And then, only on these filtered datasets u gonna put Periodograms / Autocorrelograms and see what's going there for real. Better to do it 10x times less a day on 10x less datasets, right?
I ended up with 2 methods / formulas, I called em 'type 0' and 'type 1':
- type 0: takes sum of abs deviations from drift line, scales it by max abs deviation from the same drift line;
- type 1: takes sum of abs deviations from drift line, scales it by range of non-abs deviations from the same drift line.
Finnaly I've chosen type 0 , both logically (sum of abs dev divided by max abs dev makes more sense) and experimentally. About that actually, here are both formulas put on sine waves with uniform noise:
^^ generated sine wave with uniform noise
^^ both formulas on that wave
^^ both formulas on real data
As you can see type 0 is less affected by noise and shows higher values on synthetic data, but I decided to put type 1 inside as well, in case my analysis was not complete and on real data type 1 can actually be better since it has a lil higher info gain / info content (still not sure). But I can assure u that out of all other ways I've designed & tested for quite a time I tell you, these 2 are really the only ones who got there.
Now about dem thresholds and how to use it.
Both type 0 and type 1 can be modelled with Beta distribution, and based on it and on some obvious & tho non mainstream statistical modelling techniques, I got these thresholds, so these are not optimized overfitted values, but natural ones. Each type has 3 thresholds (from lowest to highest):
- typical value (turned off by default). aka basis ;
- typical deviation from typical value, aka deviation ;
- maximum modelled deviation from typical value (idk whow to call it properly for now, this is my own R&D), aka extension .
So when the metric is above one of these thresholds (which one is up to you, you'll read about it in a sec), it means that there might be a strong enough periodic signal inside the data, and the data got to be put through proper spectral analysis tools to confirm / deny it.
If you look at the pictures above again, you'll see gray signal, that's uniform noise. Take a look at it and see where does it sit comparing to the thresholds. Now you just undertand that picking up a threshold is all about the amount of false positives you care to withstand.
If you take basis as threshold, you'll get tons of false positives (that's why it's even turned off by default), but you'll almost never miss a true positive. If you take deviation as threshold, it's gonna be kinda balanced approach. If you take extension as threshold, you gonna miss some cycles, and gonna get only the strongest ones.
More true positives -> more false positives, less false positives -> less true positives, can't go around that mane
Just to be clear again, I am not completely sure yet, but I def lean towards type 0 as metric, and deviation as threshold.
Live Long and Prosper
P.S.: That was actually the main R&D of the last month, that script I've released earlier came out as derivative.
P.S.: These 2 are the first R&Ds made completely in " art-space", St. Petersburg. Come and see me, say wassup🤘🏻
Pine Execution MapPine Script Execution Map
Overview:
This is an educational script for Pine Script developers. The script includes data structure, functions/methods, and process to capture and print Pine Script execution map of functions called while pine script execution.
Map of execution is produced for last/latest candle execution.
The script also has example code to call execution map methods and generate Pine Execution map.
Use cases:
Pine script developers can get view of how the functions are called
This can also be used while debugging the code and know which functions are called vs what developer expect code to do
One can use this while using any of the open source published script and understand how public script is organized and how functions of the script are called.
Code components:
User defined type
type EMAP
string group
string sub_group
int level
array emap = array.new()
method called internally by other methods to generate level of function being executed
method id(string tag) =>
if(str.startswith(tag, "MAIN"))
exe_level.set(0, 0)
else if(str.startswith(tag, "END"))
exe_level.set(0, exe_level.get(0) - 1)
else
exe_level.set(0, exe_level.get(0) + 1)
exe_level.get(0)
Method called from main/global scope to record execution of main scope code. There should be only one call to this method at the start of global scope.
method main(string tag) =>
this = EMAP.new()
this.group := "MAIN"
this.sub_group := tag
this.level := "MAIN".id()
emap.push(this)
Method called from main/global scope to record end of execution of main scope code. There should be only one call to this method at the end of global scope.
method end_main(string tag) =>
this = EMAP.new()
this.group := "END_MAIN"
this.sub_group := tag
this.level := 0
emap.push(this)
Method called from start of each function to record execution of function code
method call(string tag) =>
this = EMAP.new()
this.group := "SUB"
this.sub_group := tag
this.level := "SUB".id()
emap.push(this)
Method called from end of each function to record end of execution of function code
method end_call(string tag) =>
this = EMAP.new()
this.group := "END_SUB"
this.sub_group := tag
this.level := "END_SUB".id()
emap.push(this)
Pine code which generates execution map and show it as a label tooltip.
if(barstate.islast)
for rec in emap
if(not str.startswith(rec.group, "END"))
lvl_tab = str.repeat("", rec.level+1, "\t")
txt = str.format("=> {0} {1}> {2}", lvl_tab, rec.level, rec.sub_group)
debug.log(txt)
debug.lastr()
Snapshot 1:
This is the output of the script and can be viewed by hovering mouse pointer over the blue color diamond shaped label
Snapshot 2:
How to read the Pine execution map
Value at Risk [OmegaTools]The "Value at Risk" (VaR) indicator is a powerful financial risk management tool that helps traders estimate the potential losses in a portfolio over a specified period of time, given a certain level of confidence. VaR is widely used by financial institutions, traders, and risk managers to assess the probability of portfolio losses in both normal and volatile market conditions. This TradingView script implements a comprehensive VaR calculation using several models, allowing users to visualize different risk scenarios and adjust their trading strategies accordingly.
Concept of Value at Risk
Value at Risk (VaR) is a statistical technique used to measure the likelihood of losses in a portfolio or financial asset due to market risks. In essence, it answers the question: "What is the maximum potential loss that could occur in a given portfolio over a specific time horizon, with a certain confidence level?" For instance, if a portfolio has a one-day 95% VaR of $10,000, it means that there is a 95% chance the portfolio will not lose more than $10,000 in a single day. Conversely, there is a 5% chance of losing more than $10,000. VaR is a key risk management tool for portfolio managers and traders because it quantifies potential losses in monetary terms, allowing for better-informed decision-making.
There are several ways to calculate VaR, and this indicator script incorporates three of the most commonly used models:
Historical VaR: This approach uses historical returns to estimate potential losses. It is based purely on past price data, assuming that the past distribution of returns is indicative of future risks.
Variance-Covariance VaR: This model assumes that asset returns follow a normal distribution and that the risk can be summarized using the mean and standard deviation of past returns. It is a parametric method that is widely used in financial risk management.
Exponentially Weighted Moving Average (EWMA) VaR: In this model, recent data points are given more weight than older data. This dynamic approach allows the VaR estimation to react more quickly to changes in market volatility, which is particularly useful during periods of market stress. This model uses the Exponential Weighted Moving Average Volatility Model.
How the Script Works
The script starts by offering users a set of customizable input settings. The first input allows the user to choose between two main calculation modes: "All" or "OCT" (Only Current Timeframe). In the "All" mode, the script calculates VaR using all available methodologies—Historical, Variance-Covariance, and EWMA—providing a comprehensive risk overview. The "OCT" mode narrows the calculation to the current timeframe, which can be particularly useful for intraday traders who need a more focused view of risk.
The next input is the lookback window, which defines the number of historical periods used to calculate VaR. Commonly used lookback periods include 21 days (approximately one month), 63 days (about three months), and 252 days (roughly one year), with the script supporting up to 504 days for more extended historical analysis. A longer lookback period provides a more comprehensive picture of risk but may be less responsive to recent market conditions.
The confidence level is another important setting in the script. This represents the probability that the loss will not exceed the VaR estimate. Standard confidence levels are 90%, 95%, and 99%. A higher confidence level results in a more conservative risk estimate, meaning that the calculated VaR will reflect a more extreme loss scenario.
In addition to these core settings, the script allows users to customize the visual appearance of the indicator. For example, traders can choose different colors for "Bullish" (Risk On), "Bearish" (Risk Off), and "Neutral" phases, as well as colors for highlighting "Breaks" in the data, where returns exceed the calculated VaR. These visual cues make it easy to identify periods of heightened risk at a glance.
The actual VaR calculation is broken down into several models, starting with the Historical VaR calculation. This is done by computing the logarithmic returns of the asset's closing prices and then using linear interpolation to determine the percentile corresponding to the desired confidence level. This percentile represents the potential loss in the asset over the lookback period.
Next, the script calculates Variance-Covariance VaR using the mean and standard deviation of the historical returns. The standard deviation is multiplied by a z-score corresponding to the chosen confidence level (e.g., 1.645 for 95% confidence), and the resulting value is subtracted from the mean return to arrive at the VaR estimate.
The EWMA VaR model uses the EWMA for the sigma parameter, the standard deviation, obtaining a specific dynamic in the volatility. It is particularly useful in volatile markets where recent price behavior is more indicative of future risk than older data.
For traders interested in intraday risk management, the script provides several methods to adjust VaR calculations for lower timeframes. By using intraday returns and scaling them according to the chosen timeframe, the script provides a dynamic view of risk throughout the trading day. This is especially important for short-term traders who need to manage their exposure during high-volatility periods within the same day. The script also incorporates an EWMA model for intraday data, which gives greater weight to the most recent intraday price movements.
In addition to calculating VaR, the script also attempts to detect periods where the asset's returns exceed the estimated VaR threshold, referred to as "Breaks." When the returns breach the VaR limit, the script highlights these instances on the chart, allowing traders to quickly identify periods of extreme risk. The script also calculates the average of these breaks and displays it for comparison, helping traders understand how frequently these high-risk periods occur.
The script further visualizes the risk scenario using a risk phase classification system. Depending on the level of risk, the script categorizes the market as either "Risk On," "Risk Off," or "Risk Neutral." In "Risk On" mode, the market is considered bullish, and the indicator displays a green background. In "Risk Off" mode, the market is bearish, and the background turns red. If the market is neither strongly bullish nor bearish, the background turns neutral, signaling a balanced risk environment.
Traders can customize whether they want to see this risk phase background, along with toggling the display of the various VaR models, the intraday methods, and the break signals. This flexibility allows traders to tailor the indicator to their specific needs, whether they are day traders looking for quick intraday insights or longer-term investors focused on historical risk analysis.
The "Risk On" and "Risk Off" phases calculated by this Value at Risk (VaR) script introduce a novel approach to market risk assessment, offering traders an advanced toolset to gauge market sentiment and potential risk levels dynamically. These risk phases are built on a combination of traditional VaR methodologies and proprietary logic to create a more responsive and intuitive way to manage exposure in both normal and volatile market conditions. This method of classifying market conditions into "Risk On," "Risk Off," or "Risk Neutral" is not something that has been traditionally associated with VaR, making it a groundbreaking addition to this indicator.
How the "Risk On" and "Risk Off" Phases Are Calculated
In typical VaR implementations, the focus is on calculating the potential losses at a given confidence level without providing an overall market outlook. This script, however, introduces a unique risk classification system that takes the output of various VaR models and translates it into actionable signals for traders, marking whether the market is in a Risk On, Risk Off, or Risk Neutral phase.
The Risk On and Risk Off phases are primarily determined by comparing the current returns of the asset to the average VaR calculated across several different methods, including Historical VaR, Variance-Covariance VaR, and EWMA VaR. Here's how the process works:
1. Threshold Setting and Effect Calculation: The script first computes the average VaR using the selected models. It then checks whether the current returns (expressed as a negative value to signify loss) exceed the average VaR value. If the current returns surpass the calculated VaR threshold, this indicates that the actual market risk is higher than expected, signaling a potential shift in market conditions.
2. Break Analysis: In addition to monitoring whether returns exceed the average VaR, the script counts the number of instances within the lookback period where this breach occurs. This is referred to as the "break effect." For each period in the lookback window, the script checks whether the returns surpass the calculated VaR threshold and increments a counter. The percentage of periods where this breach occurs is then calculated as the "effect" or break percentage.
3. Dual Effect Check (if "Double" Risk Scenario is selected): When the user chooses the "Double" risk scenario mode, the script performs two layers of analysis. First, it calculates the effect of returns exceeding the VaR threshold for the current timeframe. Then, it calculates the effect for the lower intraday timeframe as well. Both effects are compared to the user-defined confidence level (e.g., 95%). If both effects exceed the confidence level, the market is deemed to be in a high-risk situation, thus triggering a Risk Off phase. If both effects fall below the confidence level, the market is classified as Risk On.
4. Risk Phases Determination: The final risk phase is determined by analyzing these effects in relation to the confidence level:
- Risk On: If the calculated effect of breaks is lower than the confidence level (e.g., fewer than 5% of periods show returns exceeding the VaR threshold for a 95% confidence level), the market is considered to be in a relatively safe state, and the script signals a "Risk On" phase. This is indicative of bullish conditions where the potential for extreme loss is minimal.
- Risk Off: If the break effect exceeds the confidence level (e.g., more than 5% of periods show returns breaching the VaR threshold), the market is deemed to be in a high-risk state, and the script signals a "Risk Off" phase. This indicates bearish market conditions where the likelihood of significant losses is higher.
- Risk Neutral: If the break effect hovers near the confidence level or if there is no clear trend indicating a shift toward either extreme, the market is classified as "Risk Neutral." In this phase, neither bulls nor bears are dominant, and traders should remain cautious.
The phase color that the script uses helps visualize these risk phases. The background will turn green in Risk On conditions, red in Risk Off conditions, and gray in Risk Neutral phases, providing immediate visual feedback on market risk. In addition to this, when the "Double" risk scenario is selected, the background will only turn green or red if both the current and intraday timeframes confirm the respective risk phase. This double-checking process ensures that traders are only given a strong signal when both longer-term and short-term risks align, reducing the likelihood of false signals.
A New Way of Using Value at Risk
This innovative Risk On/Risk Off classification, based on the interaction between VaR thresholds and market returns, represents a significant departure from the traditional use of Value at Risk as a pure risk measurement tool. Typically, VaR is employed as a backward-looking measure of risk, providing a static estimate of potential losses over a given timeframe with no immediate actionable feedback on current market conditions. This script, however, dynamically interprets VaR results to create a forward-looking, real-time signal that informs traders whether they are operating in a favorable (Risk On) or unfavorable (Risk Off) environment.
By incorporating the "break effect" analysis and allowing users to view the VaR breaches as a percentage of past occurrences, the script adds a predictive element that can be used to time market entries and exits more effectively. This **dual-layer risk analysis**, particularly when using the "Double" scenario mode, adds further granularity by considering both current timeframe and intraday risks. Traders can therefore make more informed decisions not just based on historical risk data, but on how the market is behaving in real-time relative to those risk benchmarks.
This approach transforms the VaR indicator from a risk monitoring tool into a decision-making system that helps identify favorable trading opportunities while alerting users to potential market downturns. It provides a more holistic view of market conditions by combining both statistical risk measurement and intuitive phase-based market analysis. This level of integration between VaR methodologies and real-time signal generation has not been widely seen in the world of trading indicators, marking this script as a cutting-edge tool for risk management and market sentiment analysis.
I would like to express my sincere gratitude to @skewedzeta for his invaluable contribution to the final script. From generating fresh ideas to applying his expertise in reviewing the formula, his support has been instrumental in refining the outcome.
Macros ICT KillZones [TradingFinder] Times & Price Trading Setup🔵 Introduction
ICT Macros, developed by Michael Huddleston, also known as ICT (Inner Circle Trader), is a powerful trading tool designed to help traders identify the best trading opportunities during key time intervals like the London and New York trading sessions.
For traders aiming to capitalize on market volatility, liquidity shifts, and Fair Value Gaps (FVG), understanding and using these critical time zones can significantly improve trading outcomes.
In today’s highly competitive financial markets, identifying the moments when the market is seeking buy-side or sell-side liquidity, or filling price imbalances, is essential for maximizing profitability.
The ICT Macros indicator is built on the renowned ICT time and price theory, which enables traders to track and leverage key market dynamics such as breaks of highs and lows, imbalances, and liquidity hunts.
This indicator automatically detects crucial market times and optimizes strategies for traders by highlighting the specific moments when price movements are most likely to occur. A standout feature of ICT Macros is its automatic adjustment for Daylight Saving Time (DST), ensuring that traders remain synced with the correct session times.
This means you can rely on accurate market timing without the need for manual updates, allowing you to focus on capturing profitable trades during critical timeframes.
🔵 How to Use
The ICT Macros indicator helps you capitalize on trading opportunities during key market moments, particularly when the market is breaking highs or lows, filling Fair Value Gaps (FVG), or addressing imbalances. This indicator is particularly beneficial for traders who seek to identify liquidity, market volatility, and price imbalances.
🟣 Sessions
London Sessions
London Macro 1 :
UTC Time : 06:33 to 07:00
New York Time : 02:33 to 03:00
London Macro 2 :
UTC Time : 08:03 to 08:30
New York Time : 04:03 to 04:30
New York Sessions
New York Macro AM 1 :
UTC Time : 12:50 to 13:10
New York Time : 08:50 to 09:10
New York Macro AM 2 :
UTC Time : 13:50 to 14:10
New York Time : 09:50 to 10:10
New York Macro AM 3 :
UTC Time : 14:50 to 15:10
New York Time : 10:50 to 11:10
New York Lunch Macro :
UTC Time : 15:50 to 16:10
New York Time : 11:50 to 12:10
New York PM Macro :
UTC Time : 17:10 to 17:40
New York Time : 13:10 to 13:40
New York Last Hour Macro :
UTC Time : 19:15 to 19:45
New York Time : 15:15 to 15:45
These time intervals adjust automatically based on Daylight Saving Time (DST), helping traders to enter or exit trades during key market moments when price volatility is high.
Below are the main applications of this tool and how to incorporate it into your trading strategies :
🟣 Combining ICT Macros with Trading Strategies
The ICT Macros indicator can easily be used in conjunction with various trading strategies. Two well-known strategies that can be combined with this indicator include:
ICT 2022 Trading Model : This model is designed based on identifying market liquidity, structural price changes, and Fair Value Gaps (FVG). By using ICT Macros, you can identify the key time intervals when the market is seeking liquidity, filling imbalances, or breaking through important highs and lows, allowing you to enter or exit trades at the right moment.
Silver Bullet Strategy : This strategy, which is built around liquidity hunting and rapid price movements, can work more accurately with the help of ICT Macros. The indicator pinpoints precise liquidity times, helping traders take advantage of market shifts caused by filling Fair Value Gaps or correcting imbalances.
🟣 Capitalizing on Price Volatility During Key Times
Large market algorithms often seek liquidity or fill Fair Value Gaps (FVG) during the intervals marked by ICT Macros. These periods are when price volatility increases, and traders can use these moments to enter or exit trades.
For example, if sell-side liquidity is drained and the market fills an imbalance, the price might move toward buy-side liquidity. By identifying these moments, which may also involve breaking a previous high or low, you can leverage rapid market fluctuations to your advantage.
🟣 Identifying Liquidity and Price Imbalances
One of the important uses of ICT Macros is identifying points where the market is seeking liquidity and correcting imbalances. You can determine high or low liquidity levels in the market before each ICT Macro, as well as Fair Value Gaps (FVG) and price imbalances that need to be filled, using them to adjust your trading strategy. This capability allows you to manage trades based on liquidity shifts or imbalance corrections without needing a bias toward a specific direction.
🔵 Settings
The ICT Macros indicator offers various customization options, allowing users to tailor it to their specific needs. Below are the main settings:
Time Zone Mode : You can select one of the following options to define how time is displayed:
UTC : For traders who need to work with Universal Time.
Session Local Time : The local time corresponding to the London or New York markets.
Your Time Zone : You can specify your own time zone (e.g., "UTC-4:00").
Your Time Zone : If you choose "Your Time Zone," you can set your specific time zone. By default, this is set to UTC-4:00.
Show Range Time : This option allows you to display the time range of each session on the chart. If enabled, the exact start and end times of each interval are shown.
Show or Hide Time Ranges : Toggle on/off for visual clarity depending on user preference.
Custom Colors : Set distinct colors for each session, allowing users to personalize their chart based on their trading style.These settings allow you to adjust the key time intervals of each trading session to your preference and customize the time format according to your own needs.
🔵 Conclusion
The ICT Macros indicator is a powerful tool for traders, helping them to identify key time intervals where the market seeks liquidity or fills Fair Value Gaps (FVG), corrects imbalances, and breaks highs or lows. This tool is especially valuable for traders using liquidity-based strategies such as ICT 2022 or Silver Bullet.
One of the key features of this indicator is its support for Daylight Saving Time (DST), ensuring you are always in sync with the correct trading session timings without manual adjustments. This is particularly beneficial for traders operating across different time zones.
With ICT Macros, you can capitalize on crucial market opportunities during sensitive times, take advantage of imbalances, and enhance your trading strategies based on market volatility, liquidity shifts, and Fair Value Gaps.
RSI Fakeout Filter with SMA Confirmation [CHE] Introducing: RSI Fakeout Detection
Are you tired of being caught in fakeouts that can lead to frustrating losses? The RSI Fakeout Detection is here to enhance your trading strategy by filtering out false signals and providing you with more reliable entries. This innovative indicator is designed to help traders identify when market momentum, as indicated by the RSI, does not align with price movement – a key indicator of potential fakeouts!
What Does It Do?
The RSI Fakeout Detection focuses on one key goal: avoiding false signals. By monitoring when the RSI exceeds a customizable threshold (indicating strength) but the price remains below a moving average like the SMA, this indicator highlights situations where the market may seem strong, but the price action doesn't support that momentum. In other words, it saves you from those tricky fake breakouts.
Key Benefits:
1. Reduce Risk, Increase Confidence: Get an extra layer of protection against fakeouts by receiving signals only when both RSI and price confirm the market's true direction. Avoid entering false breakouts and trade with more confidence.
2. Dynamic Analysis of SMA Lengths: It doesn’t just rely on one SMA. The indicator automatically analyzes and sorts through different SMA lengths to find the most reliable one for your specific market condition, ensuring that you get the best possible signal.
3. Tailored for You: With customizable RSI thresholds, a choice of multiple moving average types (SMA, EMA, Bollinger Bands, and more), and vibrant color-coded visuals, this tool is built to fit your unique trading style and preferences.
4. Spot Fakeouts with Ease: Visual cues make it easy to see when the market might be tricking you. Labels, plotted lines, and a toggleable disclaimer keep everything transparent and easy to understand.
5. Friendly and Intuitive: Whether you’re new to trading or a seasoned pro, the RSI Fakeout Detection is designed to be simple and effective. The labels and plots are clear, the alerts are timely, and it seamlessly integrates into your chart without cluttering it.
Why Choose RSI Fakeout Detection?
- Accuracy and Precision: By combining RSI and SMA analysis, this indicator minimizes the risk of following false trends and entering trades too early.
- Save Time and Reduce Guesswork: No more spending hours trying to figure out which SMA length works best – the RSI Fakeout Detection does it for you!
- Peace of Mind: Avoiding fakeouts means fewer bad trades, which can lead to more consistent performance and less stress.
Transform the way you trade, and step into a more confident trading future with RSI Fakeout Detection . Whether you’re day trading or swing trading, this tool will give you an edge by helping you filter out the noise and make more informed decisions.
Best regards,
Chervolino
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Custom Pattern DetectionOverview
Chart Patterns is a major tool for many traders. Pattern formation at specific location on the chart is used for investment/trading decisions.
This indicator is designed in a way to allow investors/traders to define patterns of their choice based on certain input parameters and then detect defined pattern on the chart.
Investors/traders can use their own creativity to create and detect patterns.
This indicator works in 2 modes
Create Pattern: One can define a pattern and verify sample pattern formation visually
Detect Pattern: Detect and mark patterns on the chart
Settings
Create Custom Pattern:
Show Custom Pattern – This will mark the pattern lines on the chart so that one can verify how pattern appears based on the input’s parameters provided for lines XA, AB, BC, CD, DE, EF
Offset – Used while pattern creation. Offset is horizonal distance between 2 lines.
XA Points – Used to draw XA line when sample pattern is drawn. XA points can be a negative or position number.
XA line is drawn based on Offset and XA Points. E.g. Offset = 5 and XA Points = -20. In this line would be drawn from last candle high to high – 20 (these are y1 and y2 points of a line). While drawing line distance of 5 candles would be placed between 2 line points (these are x1 and x2 points of a line). In XA line X forms start point and A forms end point of the line.
Line AB – Line AB is drawn from point X. To derive the end point of AB, average Fib% is derived based on From Fib% and To Fib% parameters. Finally end point is derived by applying Fib Retracement on Line XA based on average Fib%.
Line AB to Line EF – These points are derived as explained in Line AB.
The indicator can be used to define/create patterns up to 6 legs/lines. The line would be named as XA -> AB -> BC -> CD -> DE -> EF.
If one wish to create pattern consisting 3 legs then it can be achieved by unchecking/deselecting Line CD, DE and EF or by checking only Line AB and BC.
Based on the parameters above indicator draws a sample pattern after last candle/bar on the chart. Sample pattern helps to visually see how pattern will appear on the chart.
Pattern Identification
Indicator derive the swing high/low points based on the Pivot lookback and use as reference points while detecting patterns.
Use of From Fib% and To Fib% - While detecting pattern, retracement price points are derived for From Fib% and To Fib%. Price points between from Fib% and To Fib% are treated as valid retracement points.
How to configure and use indicator for detecting patterns
Sample Pattern 1
Sample Pattern 2
Sample Pattern 3
Sample Pattern 4
Shifted Symbol Overlay with OffsetThe Shifted Symbol Overlay Indicator is a custom TradingView indicator designed to overlay the price data of one stock or asset over another, allowing for direct visual comparison. This is particularly useful for comparing the performance of two assets over different time periods. The indicator enables you to shift the data from one asset either forward or backward in time, making it easier to compare historical data from one stock with more recent data from another. The indicator supports shifting both to the right (future periods) and to the left (earlier periods), helping traders and analysts explore correlations or divergences between two financial instruments.
The indicator also includes a normalization option that adjusts the scale of the two assets, so you can compare them even if they have vastly different price levels. This is useful when you're interested in relative performance rather than the absolute price values.
