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.
Cari dalam skrip untuk "10年期国债+交易单位+价格"
Intermarket Analisis V.1What is Intermarket Analysis?
Intermarket analysis looks at how various asset classes influence each other. The key idea is that markets are interconnected, and movements in one can signal or predict movements in another. For example:
Stocks and Bonds: Rising bond yields (e.g., US 10-year Treasury) often pressure stock prices downward.
Commodities and Forex: A rising US Dollar (USD) typically weakens gold (XAU/USD) prices due to their inverse relationship.
Forex and Equities: Strong economic data boosting equities might strengthen the USD.
This method helps you confirm trends, anticipate reversals, or avoid false signals in your EMA 10/20 crossover strategy.
Key Intermarket Relationships
USD Index (DXY) and Gold (XAU/USD):
Correlation: Inverse. When DXY rises (stronger USD), gold often falls, and vice versa.
Indicator: Track DXY on a separate chart. Use a 50-period SMA or RSI to spot overbought/oversold conditions in USD strength.
Application: If your EMA 10/20 gives a buy signal on gold but DXY is overbought (RSI > 70), it might be a false signal—wait for DXY to cool off.
US 10-Year Treasury Yields and Equities (e.g., S&P 500):
Correlation: Inverse. Higher yields increase borrowing costs, pressuring stocks.
Indicator: Use a 200-day EMA on yields (e.g., ^TNX) and compare with S&P 500’s 50-day EMA.
Application: If yields are trending up (above 200 EMA) while your EMA 10/20 signals a stock buy, consider it risky—cross-check with macro data.
Crude Oil (WTI/Brent) and Gold:
Correlation: Positive. Both are inflation hedges, so they often move together during economic uncertainty.
Indicator: Apply a MACD (12, 26, 9) on oil prices to confirm trend direction.
Application: If oil’s MACD shows a bullish crossover and your gold buy signal aligns, it strengthens the case for a trend.
Bond Yields and USD:
Correlation: Positive. Rising yields support a stronger USD.
Indicator: Use a Stochastic Oscillator (14, 3, 3) on DXY to spot momentum shifts.
Application: If Stochastic is overbought on DXY and yields are high, a gold sell signal from EMA 10/20 might be more reliable.
How to Apply Intermarket Analysis to Your EMA 10/20 Strategy
Your current strategy uses EMA 10/20 crossovers for entry/exit, with SL at swing low/high and no TP until an opposite crossover. Here’s how to integrate intermarket analysis:
Confirmation: Before acting on a buy signal (EMA 10 > EMA 20), check if DXY is weakening (e.g., below 50 SMA) or oil is rising (MACD bullish). This supports a gold uptrend.
Divergence Warning: If your EMA 10/20 buy signal occurs but DXY is trending up (strong USD) or yields are spiking, it might indicate a false breakout—hold off.
Macro Context: On July 02, 2025, 08:30 PM WIB, watch for upcoming US Jobless Claims (3-4 July). A weak report could boost gold and weaken USD, aligning with your buy signal.
IntermarketWhat is Intermarket Analysis?
Intermarket analysis looks at how various asset classes influence each other. The key idea is that markets are interconnected, and movements in one can signal or predict movements in another. For example:
Stocks and Bonds: Rising bond yields (e.g., US 10-year Treasury) often pressure stock prices downward.
Commodities and Forex: A rising US Dollar (USD) typically weakens gold (XAU/USD) prices due to their inverse relationship.
Forex and Equities: Strong economic data boosting equities might strengthen the USD.
This method helps you confirm trends, anticipate reversals, or avoid false signals in your EMA 10/20 crossover strategy.
Key Intermarket Relationships
USD Index (DXY) and Gold (XAU/USD):
Correlation: Inverse. When DXY rises (stronger USD), gold often falls, and vice versa.
Indicator: Track DXY on a separate chart. Use a 50-period SMA or RSI to spot overbought/oversold conditions in USD strength.
Application: If your EMA 10/20 gives a buy signal on gold but DXY is overbought (RSI > 70), it might be a false signal—wait for DXY to cool off.
US 10-Year Treasury Yields and Equities (e.g., S&P 500):
Correlation: Inverse. Higher yields increase borrowing costs, pressuring stocks.
Indicator: Use a 200-day EMA on yields (e.g., ^TNX) and compare with S&P 500’s 50-day EMA.
Application: If yields are trending up (above 200 EMA) while your EMA 10/20 signals a stock buy, consider it risky—cross-check with macro data.
Crude Oil (WTI/Brent) and Gold:
Correlation: Positive. Both are inflation hedges, so they often move together during economic uncertainty.
Indicator: Apply a MACD (12, 26, 9) on oil prices to confirm trend direction.
Application: If oil’s MACD shows a bullish crossover and your gold buy signal aligns, it strengthens the case for a trend.
Bond Yields and USD:
Correlation: Positive. Rising yields support a stronger USD.
Indicator: Use a Stochastic Oscillator (14, 3, 3) on DXY to spot momentum shifts.
Application: If Stochastic is overbought on DXY and yields are high, a gold sell signal from EMA 10/20 might be more reliable.
How to Apply Intermarket Analysis to Your EMA 10/20 Strategy
Your current strategy uses EMA 10/20 crossovers for entry/exit, with SL at swing low/high and no TP until an opposite crossover. Here’s how to integrate intermarket analysis:
Confirmation: Before acting on a buy signal (EMA 10 > EMA 20), check if DXY is weakening (e.g., below 50 SMA) or oil is rising (MACD bullish). This supports a gold uptrend.
Divergence Warning: If your EMA 10/20 buy signal occurs but DXY is trending up (strong USD) or yields are spiking, it might indicate a false breakout—hold off.
Macro Context: On July 02, 2025, 08:30 PM WIB, watch for upcoming US Jobless Claims (3-4 July). A weak report could boost gold and weaken USD, aligning with your buy signal.
Adv EMA Cloud v6 (ADX, Alerts)Summary:
This indicator provides a multi-faceted view of market trends using Exponential Moving Averages (EMAs) arranged in visually intuitive clouds, enhanced with an optional ADX-based range filter and configurable alerts for key market conditions. It aims to help traders quickly gauge trend alignment across short, medium, and long timeframes while filtering signals during potentially choppy market conditions.
Key Features:
Multiple EMAs: Displays 10-period (Fast), 20-period (Mid), and 50-period (Slow) EMAs.
Long-Term Trend Filter: Includes a 200-period EMA to provide context for the overall dominant trend direction.
Dual EMA Clouds:
Fast/Mid Cloud (10/20 EMA): Fills the area between the 10 and 20 EMAs. Defaults to Green when 10 > 20 (bullish short-term momentum) and Red when 10 < 20 (bearish short-term momentum).
Mid/Slow Cloud (20/50 EMA): Fills the area between the 20 and 50 EMAs. Defaults to Aqua when 20 > 50 (bullish mid-term trend) and Fuchsia when 20 < 50 (bearish mid-term trend).
Optional ADX Range Filter: Uses the Average Directional Index (ADX) to identify potentially non-trending or choppy markets. When enabled and ADX falls below a user-defined threshold, the EMA clouds will turn grey, visually warning that trend-following signals may be less reliable.
Configurable Alerts: Provides several built-in alert conditions using Pine Script's alertcondition function:
Confluence Condition: Triggers when a 10/20 EMA crossover occurs while both EMA clouds show alignment (both bullish/green/aqua or both bearish/red/fuchsia) and price respects the 200 EMA filter and the ADX filter indicates a trend (if filters are enabled).
MA Filter Cross: Triggers when price crosses above or below the 200 EMA filter line.
Full Alignment Start: Triggers on the first bar where full bullish or bearish alignment occurs (both clouds aligned + MA filter respected + ADX trending, if filters are enabled).
How It Works:
EMA Calculation: Standard Exponential Moving Averages are calculated for the 10, 20, 50, and 200 periods based on the closing price.
Cloud Creation: The fill() function visually shades the area between the 10 & 20 EMAs and the 20 & 50 EMAs.
Cloud Coloring: The color of each cloud is determined by the relationship between the two EMAs that define it (e.g., if EMA 10 is above EMA 20, the first cloud is bullish-colored).
ADX Filter Logic: The script calculates the ADX value. If the "Use ADX Trend Filter?" input is checked and the calculated ADX is below the specified "ADX Trend Threshold", the script considers the market potentially ranging.
ADX Visual Effect: During detected ranging periods (if the ADX filter is active), the plotCloud12Color and plotCloud23Color variables are assigned a neutral grey color instead of their normal bullish/bearish colors before being passed to the fill() function.
Alert Logic: Boolean variables track the specific conditions (crossovers, cloud alignment, filter positions, ADX state). The alertcondition() function creates triggerable alerts based on these pre-defined conditions.
Potential Interpretation (Not Financial Advice):
Trend Alignment: When both clouds share the same directional color (e.g., both bullish - Green & Aqua) and price is on the corresponding side of the 200 EMA filter, it may suggest a stronger, more aligned trend. Conversely, conflicting cloud colors may indicate indecision or transition.
Dynamic Support/Resistance: The EMA lines themselves (especially the 20, 50, and 200) can sometimes act as dynamic levels where price might react.
Range Warning: Greyed-out clouds (when ADX filter is enabled) serve as a visual warning that trend-based strategies might face increased difficulty or whipsaws.
Confluence Alerts: The specific confluence alerts signal moments where multiple conditions align (crossover + cloud agreement + filters), which some traders might view as higher-probability setups.
Customization:
All EMA lengths (10, 20, 50, 200) are adjustable via the Inputs menu.
The ADX length and threshold are configurable.
The MA Trend Filter and ADX Trend Filter can be independently enabled or disabled.
Disclaimer:
This indicator is provided for informational and educational purposes only. Trading financial markets involves significant risk. Past performance is not indicative of future results. Always conduct your own thorough analysis and consider your risk tolerance before making any trading decisions. This indicator should be used in conjunction with other analysis methods and tools. Do not trade based solely on the signals or visuals provided by this indicator.
Pulse of Cycle Oscillator"Pulse of Cycle" Oscillator: Logic and Usage
What Is It and How Does It Work?
The "Pulse of Cycle" is an oscillator that measures the cycles of price rises and falls, helping you spot overbought and oversold conditions. Unlike classic indicators, it doesn’t focus on how much the price moves but tracks its direction (up or down) like a "pulse." Here’s the logic:
Price Movement:
If the price rises compared to the previous bar, it adds +1.
If the price falls, it subtracts -1.
If the price stays the same, it adds 0.
Decay Factor: Each step, the previous value is multiplied by a factor (e.g., 0.9) to shrink it slightly. This keeps the oscillator from growing too big and focuses it on recent price action.
Signals: The oscillator moves around zero. When it crosses certain levels (e.g., 5 and 10), it warns you about overbought or oversold zones:
Weak Signal: Above ±5, the market might be stretching a bit.
Strong Signal: Above ±10, a reversal is more likely.
In short, it tracks the "rhythm" of price streaks (consecutive ups or downs) and signals when things might be getting extreme.
How It Looks on the Chart
Line: The oscillator moves around a zero line.
Colors:
Blue: Normal zone (between -5 and +5).
Orange: Weak overbought (+5 and up) or oversold (-5 and down).
Red: Strong overbought (+10 and up).
Lime: Strong oversold (-10 and down).
Threshold Lines: You’ll see lines at 0, ±5, and ±10 on the chart to show where you are.
How to Use It?
Here’s how to trade with this oscillator:
Buy Opportunity (Long Position):
When?: The oscillator drops below -5 (weak) or -10 (strong), then starts moving back toward zero. This suggests the price has hit a bottom and might rise.
Example: It falls to -12 (lime), then rises to -8. You could buy, expecting a bounce.
Tip: Wait for a green candle to confirm if you want to be safer.
Sell Opportunity (Short Position):
When?: The oscillator rises above +5 (weak) or +10 (strong), then starts dropping back toward zero. This indicates the price might have peaked and could fall.
Example: It hits +11 (red), then drops to +7. You could sell, expecting a decline.
Tip: Look for a red candle to confirm the turn.
Neutral Zone: If it’s between -5 and +5, the market is balanced. You can wait for a clearer signal.
Practical Steps to Use
Add to TradingView:
Paste the code into Pine Editor and click “Add to Chart.”
Adjust Settings (Optional):
Decay (0.9): Lower to 0.7 for faster response, raise to 0.95 for smoother movement.
Thresholds (5 and 10): Change them (e.g., 4 and 8) based on your market.
Watch Signals:
Follow the color changes and threshold crossings.
Set Alerts:
Right-click the oscillator > “Add Alert” to get notified on overbought/oversold signals.
Things to Watch Out For
Confirmation: Pair it with support/resistance levels or candlestick patterns for stronger signals.
Market Type: Works best in range-bound (sideways) markets. In strong trends (all up or down), signals might mislead.
Risk: Always use a stop loss—below the last low for buys, above the last high for sells.
Summary
The "Pulse of Cycle" is a simple yet powerful tool that tracks price movement streaks. Use it to catch reversals at strong signals (-10/+10) or get early warnings at weak signals (±5). The colors and lines on the chart make it easy to see when to act.
Checklist By TradeINskiChecklist By TradeINski
First Things First
This indicator is a supporting tool for trading momentum burst that is 2 Lynch setup by stock bee aka Pradeep Bonde.
Disclaimer: This indicator will not give any buy or sell signal. This is just a supporting tool to improve efficiency in my trading.
Apply Indicators and then open indicator settings and read the following simultaneously to understand better.
Default color settings are best suited for light themes. Which is also my personal preference.
Users can change most of the default options in settings according to their personal preference in settings.
When we open settings we can see 3 tabs that are {Inputs tab} {Style tab} {Visibility tab} each tab have its own options, Understand and use it accordingly.
Indicator will be only visible in the Daily time frame as its primary TF is daily. In the lower time frame nothing is plotted.
An indicator is plotted on an existing plane and overlaid on the existing plane.
Contents
My Checklist Lynch
Table Header Settings
Position
Size
Text Color
Background Color
“ON/OFF” Header “Text Box” “Info”
Table Content
Text Color
Background Color
“ON/OFF” R (1 - 10) “Text Box” T (1 - 10) “Text Box”
My Checklist - 2Lynch
This is the checklist I use while placing the trade just to make use of not missing anything based on predefined rules of the setup I trade.
2 - The stock should not be Up more than 2 days in a row, Minor movement can be acceptable.
L - The stock price movement should be linear, validation of established momentum
Y - Young trend in preference 1 - 3rd breakout from base
N - Narrow Range or -ve day before breakout
C - Consolidation should be narrow, linear and low volume. No more than one 4% breakdown.
H - The candle should close near high or at least 20% within when entered.
Table Headers Settings
Position - “Drop Down” with 9 different options which are self explanatory. Users can change the position of the table as per their preference.
Size - “Drop Down” with 6 different options which are self explanatory. Users can change the size of all the text printed in the table as per their preference.
Text Color - “Default Color is White” This setting is specifically only for header text. And users can change the text color of the header as per their preference.
Background Color - “Default Color is Blue” This setting is specifically only for header
background color. Users can change the background color of the header as per their preference.
“ON/OFF” Header “Text Box” “Info”
“Check Mark” - To show or hide the header that is “ON/OFF”.
“Header” - Heading of the table.
“Text Box” - Users can input as per their preference.
“Info” - Info symbol that shows short form and important note that is (Max 50 characteristics for all text boxes) .
Table Content
Text Color - “Default Color is White” This setting is specifically for table texts. And users can change the text color of the all content table texts as per their preference.
Background Color - “Default Color is black” This setting is specifically for content table texts background color. Users can change the background color of the header as per their preference.
“ON/OFF” R (1 - 10) “Text Box” T (1 - 10) “Text Box”
“Check Mark” - To show or hide the complete Row. Users have options and can change as per their preferences.
R (1-10) - “R” stands for Row and (1-10) is Number of rows available for users to enter text. Users have 10 different options.
“Text Box” - Place to enter text that users want to print on column 1 of the table.
T (1-10) - “T” stands for table and (1-10) is Number of text boxes available for users to enter text. Users have 10 different options.
“Text Box” - Place to enter text that users want to print on column 2 of the table.
Realtime FootprintThe purpose of this script is to gain a better understanding of the order flow by the footprint. To that end, i have added unusual features in addition to the standard features.
I use "Real Time 5D Profile by LucF" main engine to create basic footprint(profile type) and added some popular features and my favorites.
This script can only be used in realtime, because tradingview doesn't provide historical Bid/Ask date.
Bid/Ask date used this script are up/down ticks.
This script can only be used by time based chart (1m, 5m , 60m and daily etc)
This script use many labels and these are limited max 500, so you can't display many bars.
If you want to display foot print bars longer, turn off the unused sub-display function.
Default setting is footprint is 25 labels, IB count is 1, COT high and Ratio high is 1, COT low and Ratio low is 1 and Delta Box Ratio Volume is 1 , total 29.
plus UA , IB stripes , ladder fading mark use several labels.
///////// General Setting ///////////
Resets on Volume / Range bar
: If you want to use simple time based Resets on, please set Total Volume is 0.
Your timeframe is always the first condition. So if you set Total Volume is 1000, both conditions(Volume >= 1000 and your timeframe start next bar) must be met. (that is, new footprint bar doesn't start at when total volume = exactly 1000).
Ticks per row and Maximum row of Bar
: 1 is minimum size(tick). "Maximum row of Bar" decide the number of rows used in one footprint. 1 row is created from 1 label, so you need to reduce this number to display many footprints (Max label is 500).
Volume Filter and For Calculation and Display
: "Volume Filter" decide minimum size of using volume for this script.
"For Calculation and Display" is used to convert volume to an integer.
This script only use integer to make profile look better (I contained Bid number and Ask number in one row( one label) to saving labels. This require to make no difference in width by the number of digits and this script corresponds integers from 0 to 3 digits).
ex) Symbol average volume size is from 0.0001 to 0.001. You decide only use Volume >= 0.0005 by "Volume Filter".
Next, you convert volume to integer, by setting "For Calculation and Display" is 1000 (0.0005 * 1000 = 5).
If 0.00052 → 5.2 → 5, 0.00058 → 5.8 → 6 (Decimal numbers are rounded off)
This integer is used to all calculation in this script.
//////// Main Display ///////
Footprint, Total, Row Delta, Diagonal Delta and Profile
: "Footprint" display Ask and Bid per row. "Total" display Ask + Bid per row.
"Row Delta" display Ask - Bid per row. "Diagonal Delta" display Ask(row N) - Bid(row N -1) per row.
Profile display Total Volume(Ask + Bid) per row by using Block. Profile Block coloring are decided by Row Delta value(default: positive Row Delta (Ask > Bid) is greenish colors and negative Row Delta (Ask < Bid) is reddish colors.)
Volume per Profile Block, Row Imbalance Ratio and Delta Bull/Bear/Neutral Colors
: "Volume per Profile Block" decide one block contain how many total volume.
ex) When you set 20, Total volume 70 display 3 block.
The maximum number of blocks that can be used per low is 20.
So if you set 20, Total volume 400 is 20 blocks. total volume 800 is 20 blocks too.
"Row Imbalance Ratio" decide block coloring. The row imbalance is that the difference between Ask and Bid (row delta) is large.
default is x3, x2 and x1. The larger the difference, the brighter the color.
ex) Ask 30 Bid 10 is light green. Ask 20 Bid 10 is green. Ask 11 Bid 10 is dark green.
Ask 0 Bid 1 is light red. Ask 1 Bid 2 is red. ask 30 Bid 59 is dark green.
Ask 10 Bid 10 is neutral color(gray)
profile coloring is reflected same row's other elements(Ask, Bid, Total and Delta) too.
It's because one label can only use one text color.
/////// Sub Display ///////
Delta, total and Commitment of Traders
: "Delta" is total Ask - total Bid in one footprint bar. Total is total Ask + total Bid in one footprint bar.
"Commitment of traders" is variation of "Delta". COT High is reset to 0 when current highest is touched. COT Low is opposite.
Basic concept of Delta is to compare price with Delta. Ordinary, when price move up, delta is positive. Price move down is negative delta.
This is because market orders move price and market orders are counted by Delta (although this description is not exactly correct).
But, sometimes prices do not move even though many market orders are putting pressure on price , or conversely, price move strongly without many market orders.
This is key point. Big player absorb market orders by iceberg order(Subdivide large orders and pretend to be small limit orders.
Small limit orders look weak in the order book, but they are added each time you fill, so they are more powerful than they look.), so price don't move.
On the other hand, when the price is moving easily, smart players may be aiming to attract and counterattack to a better price for them.
It's more of a sport than science, and there's always no right response. Pay attention to the relationship between price, volume and delta.
ex) If COT Low is large negative value, it means many sell market orders is coming, but iceberg order is absorbing their attack at limit order.
you should not do buy entry, only this clue. but this is one of the hints.
"Delta, Box Ratio and Total texts is contained same label and its color are "Delta" coloring. Positive Delta is Delta Bull color(green),Negative Delta is Delta Bear Color
and Delta = 0 is Neutral Color(gray). When Delta direction and price direction are opposite is Delta Divergence Color(yellow).
I didn't add the cumulative volume delta because I prefer to display the CVD line on the price chart rather than the number.
Box Ratio , Box Ratio Divisor and Heavy Box Ratio Ratio
: This is not ordinary footprint features, but I like this concept so I added.
Box Ratio by Richard W. Arms is simple but useful tool. calculation is "total volume (one bar) divided by Bar range (highest - lowest)."
When Bull and bear are fighting fiercely this number become large, and then important price move happen.
I made average BR from something like 5 SMA and if current BR exceeds average BR x (Heavy Box Ratio Ratio), BR box mark will be filled.
Box Ratio Divisor is used to good looking display(BR multiplied by Box Ratio Divisor is rounded off and displayed as an integer)
Diagonal Imbalance Count , D IB Mark and D IB Stripes
: Diagonal Imbalance is defined by "Diagonal Imbalance Ratio".
ex) You set 2. When Ask(row N) 30 Bid(row N -1)10, it's 30 > 10*2, so positive Diagonal Imbalance.
When Ask(row N) 4 Bid(row N -1)9, it's 4*2 < 9, so negative Diagonal Imbalance.
This calculation does not use equals to avoid Ask(row N) 0 Bid(row N -1)0 became Diagonal Imbalance.
Ask(row N) 0 Bid(row N -1)0, it's 0 = 0*2, not Diagonal Imbalance. Ask(row N) 10 Bid(row N -1)5, it's 10 = 5*2, not Diagonal Imbalance.
"D IB Mark" emphasize Ask or Bid number which is dominant side(Winner of Diagonal Imbalance calculation), by under line.
"Diagonal Imbalance Count" compare Ask side D IB Mark to Bid side D IB Mark in one footprint.
Coloring depend on which is more aggressive side (it has many IB Mark) and When Aggressive direction and price direction are opposite is Delta Divergence Color(yellow).
"D IB Stripes" is a function that further emphasizes with an arrow Mark, when a DIB mark is added on the same side for three consecutive row. Three consecutive arrow is added at third row.
Unfinished Auction, Ratio Bounds and Ladder fading Mark
: "Unfinished Auction" emphasize highest or lowest row which has both Ask and Bid, by Delta Divergence Color(yellow) XXXXXX mark.
Unfinished Auction sometimes has magnet effect, price may touch and breakout at UA side in the future.
This concept is famous as profit taking target than entry decision.
But, I'm interested in the case that Big player make fake breakout at UA side and trapped retail traders, and then do reversal with retail traders stop-loss hunt.
Anyway, it's not stand alone signal.
"Ratio Bounds" gauge decrease of pressure at extreme price. Ratio Bounds High is number which second highest ask is divided by highest ask.
Ratio Bounds Low is number which second lowest bid is divided by lowest bid. The larger the number, the less momentum the price has.
ex)first footprint bar has Ratio Bounds Low 2, second footprint bar has RBL 4, third footprint bar has RBL 20.
This indicates that the bear's power is gradually diminishing.
"Ladder fading mark" emphasizes the decrease of the value in 3 consecutive row at extreme price. I added two type Marks.
Ask/Bid type(triangle Mark) is Ask/Bid values are decreasing of three consecutive row at extreme price.
Row Imbalance type(Diamond Mark) are row Imbalance values are decreasing of three consecutive row at extreme price.
ex)Third lowest Bid 40, second lowest Bid 10 and lowest Bid 5 have triangle up Mark. That is bear's power is gradually diminishing.
(This Mark only check Bid value at lowest price and Ask value at highest price).
Third highest row delta + 60, second highest row delta + 5, highest delta - 20 have diamond Mark. That is Bull's power is gradually diminishing.
Sub display use Delta colors at bottom of Sub display section.
////// Candle & POC /////////
candle and POC
: Ordinary, "POC" Point of Control is row of largest total volume, but this script'POC is volume weighted average.
This is because the regular POC was visually displayed by the profile ,and I was influenced LucF's ideas.
POC coloring is decided in relation to the previous POC. When current POC is higher than previous POC, color is UP Bar Color(green).
In the opposite case, Down Bar color is used.
POC Divergence Color is used when Current POC is up but current bar close is lower than open (Down price Bar),or in the opposite case.
POC coloring has option also highlight background by Delta Divergence Color(yellow). but bg color is displayed at your time frame current price bar not current footprint bar.
The basic explanation is over.
I add some image to promote understanding basic ideas.
Institutional Volume Profile# Institutional Volume Profile (IVP) - Advanced Volume Analysis Indicator
## Overview
The Institutional Volume Profile (IVP) is a sophisticated technical analysis tool that combines traditional volume profile analysis with institutional volume detection algorithms. This indicator helps traders identify key price levels where significant institutional activity has occurred, providing insights into market structure and potential support/resistance zones.
## Key Features
### 🎯 Volume Profile Analysis
- **Point of Control (POC)**: Identifies the price level with the highest volume activity
- **Value Area**: Highlights the price range containing a specified percentage (default 70%) of total volume
- **Multi-Row Distribution**: Displays volume distribution across 10-50 price levels for detailed analysis
- **Customizable Period**: Analyze volume profiles over 10-500 bars
### 🏛️ Institutional Volume Detection
- **Pocket Pivot Volume (PPV)**: Detects bullish institutional buying when up-volume exceeds recent down-volume peaks
- **Pivot Negative Volume (PNV)**: Identifies bearish institutional selling when down-volume exceeds recent up-volume peaks
- **Accumulation Detection**: Spots potential accumulation phases with high volume and narrow price ranges
- **Distribution Analysis**: Identifies distribution patterns with high volume but minimal price movement
### 🎨 Visual Customization Options
- **Multiple Color Schemes**: Heat Map, Institutional, Monochrome, and Rainbow themes
- **Bar Styles**: Solid, Gradient, Outlined, and 3D Effect rendering
- **Volume Intensity Display**: Visual intensity based on volume magnitude
- **Flexible Positioning**: Left or right side profile placement
- **Current Price Highlighting**: Real-time price level indication
### 📊 Advanced Visual Features
- **Volume Labels**: Display volume amounts at key price levels
- **Gradient Effects**: Multi-step gradient rendering for enhanced visibility
- **3D Styling**: Shadow effects for professional appearance
- **Opacity Control**: Adjustable transparency (10-100%)
- **Border Customization**: Configurable border width and styling
## How It Works
### Volume Distribution Algorithm
The indicator analyzes each bar within the specified period and distributes its volume proportionally across the price levels it touches. This creates an accurate representation of where trading activity has been concentrated.
### Institutional Detection Logic
- **PPV Trigger**: Current up-bar volume > highest down-volume in lookback period + above volume MA
- **PNV Trigger**: Current down-bar volume > highest up-volume in lookback period + above volume MA
- **Accumulation**: High volume + narrow range + bullish close
- **Distribution**: Very high volume + minimal price movement
### Value Area Calculation
Starting from the POC, the algorithm expands both upward and downward, adding volume until reaching the specified percentage of total volume (default 70%).
## Configuration Parameters
### Profile Settings
- **Profile Period**: 10-500 bars (default: 50)
- **Number of Rows**: 10-50 levels (default: 24)
- **Profile Width**: 10-100% of screen (default: 30%)
- **Value Area %**: 50-90% (default: 70%)
### Institutional Analysis
- **PPV Lookback Days**: 5-20 periods (default: 10)
- **Volume MA Length**: 10-200 periods (default: 50)
- **Institutional Threshold**: 1.0-2.0x multiplier (default: 1.2)
### Visual Controls
- **Bar Style**: Solid, Gradient, Outlined, 3D Effect
- **Color Scheme**: Heat Map, Institutional, Monochrome, Rainbow
- **Profile Position**: Left or Right side
- **Opacity**: 10-100%
- **Show Labels**: Volume amount display toggle
## Interpretation Guide
### Volume Profile Elements
- **Thick Horizontal Bars**: High volume nodes (strong support/resistance)
- **Thin Horizontal Bars**: Low volume nodes (weak levels)
- **White Line (POC)**: Strongest support/resistance level
- **Blue Highlighted Area**: Value Area (fair value zone)
### Institutional Signals
- **Blue Triangles (PPV)**: Bullish institutional buying detected
- **Orange Triangles (PNV)**: Bearish institutional selling detected
- **Color-Coded Bars**: Different colors indicate institutional activity types
### Color Scheme Meanings
- **Heat Map**: Red (high volume) → Orange → Yellow → Gray (low volume)
- **Institutional**: Blue (PPV), Orange (PNV), Aqua (Accumulation), Yellow (Distribution)
- **Monochrome**: Grayscale intensity based on volume
- **Rainbow**: Color-coded by price level position
## Trading Applications
### Support and Resistance
- POC acts as dynamic support/resistance
- High volume nodes indicate strong price levels
- Low volume areas suggest potential breakout zones
### Institutional Activity
- PPV above Value Area: Strong bullish signal
- PNV below Value Area: Strong bearish signal
- Accumulation patterns: Potential upward breakouts
- Distribution patterns: Potential downward pressure
### Market Structure Analysis
- Value Area defines fair value range
- Profile shape indicates market sentiment
- Volume gaps suggest potential price targets
## Alert Conditions
- PPV Detection at current price level
- PNV Detection at current price level
- PPV above Value Area (strong bullish)
- PNV below Value Area (strong bearish)
## Best Practices
1. Use multiple timeframes for confirmation
2. Combine with price action analysis
3. Pay attention to volume context (above/below average)
4. Monitor institutional signals near key levels
5. Consider overall market conditions
## Technical Notes
- Maximum 500 boxes and 100 labels for optimal performance
- Real-time calculations update on each bar close
- Historical analysis uses complete bar data
- Compatible with all TradingView chart types and timeframes
---
*This indicator is designed for educational and informational purposes. Always combine with other analysis methods and risk management strategies.*
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
random_values█ OVERVIEW
This library provides helper functions for generating random values of various types, including numbers, letters, words, booleans, and arrays. It simplifies the creation of random data within Pine Script™ for testing, simulations, or other applications.
█ HOW TO USE
Import the library into your script:
import kaigouthro/random_values/1 as rv
Then, use the functions provided:
// Get a random integer between 5 and 15
int randInt = rv.intVal(5, 15)
// Generate a random word with 8 characters
string randWord = rv.word(8)
// Create a boolean array with 5 elements
array randBoolArray = rv.boolArray(5)
// And other options! See below for details.
█ FEATURES
• num(float min, float max) : Returns a random float between *min* and *max*. (Internal helper function, not exported).
• letter() : Returns a random lowercase letter (a-z).
• word(int size = 0) : Returns a random word. *size* specifies the length (default: random length between 3 and 10).
• words(int size = 20) : Returns a string of random words separated by spaces, where *size* specifies the number of words.
• boolVal() : Returns a random boolean (true or false).
• floatVal(float min = 0, float max = 100, int precision = 2) : Returns a random float with specified *min*, *max*, and *precision*.
• intVal(int min = 1, int max = 100) : Returns a random integer between *min* and *max*.
• stringArray(int size = 0) : Returns an array of random words. *size* specifies the array length (default: random between 3 and 10).
• floatArray(int size = 0, float min = 0, float max = 100, int precision = 2) : Returns an array of random floats with specified parameters. *size* determines the array length.
• intArray(int size = 0, int min = 1, int max = 100) : Returns an array of random integers with specified parameters. *size* determines the array length.
• boolArray(int size = 0) : Returns an array of random booleans. *size* specifies the array length (default: random between 3 and 10).
█ NOTES
* This library uses the `kaigouthro/into/2` library for type conversions. Make sure it's available.
* Default values are provided for most function parameters, offering flexibility in usage.
█ LICENSE
This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
```
**Changes and Rationale:**
* **OVERVIEW:** Clearly states the library's purpose.
* **HOW TO USE:** Provides essential import and usage instructions with Pine Script™ examples.
* **FEATURES:** Details each function with its parameters, types, and descriptions. Emphasizes *size*, *min*, *max*, and *precision* as common input parameters using italics. Uses custom bulleted lists.
* **NOTES:** Includes important information about dependencies and defaults.
* **LICENSE:** Directly links to the license URL using the proper ` ` tag.
* **Formatting:** Uses full block and em space for section titles, consistent bolding, and improved spacing for readability. Removes unnecessary blank lines.
This format improves clarity, making the library documentation easy to understand for TradingView users. Remember to test the rendering on TradingView to catch any formatting issues.
Library "random_values"
A library containing Random value generating helper functions.
letter()
Random letter generator.
Returns: (string) A random lowercase letter.
word(size)
Random word generator.
Parameters:
size (int) : (int) The desired length of the word. If 0 or not provided, a random length between 3 and 10 is used.
Returns: (string) A random word.
words(size)
Random words generator.
Parameters:
size (int) : (int) The number of words to generate. If 0 or not provided, a random number between 3 and 10 is used.
Returns: (string) A string of random words separated by spaces.
boolVal()
Random boolean generator.
Returns: (bool) A random boolean value (true or false).
floatVal(min, max, precision)
Random float number generator.
Parameters:
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (float) A random float number.
intVal(min, max)
Random integer number generator.
Parameters:
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (int) A random integer number.
stringArray(size)
Random string array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random words.
floatArray(size, min, max, precision)
Random float array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (array) An array of random float numbers.
intArray(size, min, max)
Random integer array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (array) An array of random integer numbers.
boolArray(size)
Random boolean array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random boolean values.
Financials Score All Description of the "Financials Score All" Script
This Pine Script calculates a financial score for a specific stock, based on various financial metrics. The purpose is to provide a comprehensive numerical score that reflects the financial health of the stock. The score is calculated using multiple financial indicators, including profitability, valuation, debt management, and liquidity. Here’s a breakdown of what each part of the script does:
period = input.string('FQ', 'Period', options= )
FQ refers to Quarterly financial data.
FY refers to Fiscal Year financial data.
Financial Metrics:
The script uses various financial metrics to calculate the score. These are obtained via request.financial, which retrieves financial data for the stock from TradingView's database. Below are the metrics used:
opmar (Operating Margin): Measures the company's profitability as a percentage of revenue.
eps (Earnings Per Share): Represents the portion of a company's profit allocated to each outstanding share.
eps_ttm (Earnings Per Share – Trailing Twelve Months): EPS over the most recent 12 months.
pe_ratio (Price-to-Earnings Ratio): A measure of the price investors are willing to pay for a stock relative to its earnings.
pb_ratio (Price-to-Book Ratio): A valuation ratio comparing a company’s market value to its book value.
de_ratio (Debt-to-Equity Ratio): A measure of the company’s financial leverage, showing how much debt it has compared to shareholders' equity.
roe_pb (Return on Equity Adjusted to Book): Measures the company's profitability relative to its book value.
fcf_per_share (Free Cash Flow per Share): Represents the free cash flow available for dividends, debt reduction, or reinvestment, per share.
pfcf_ratio (Price-to-Free-Cash-Flow Ratio): A measure comparing a company’s market value to its free cash flow.
current_ratio (Current Ratio): A liquidity ratio that measures a company's ability to pay short-term obligations with its current assets.
RSI Calculation:
The script calculates the Relative Strength Index (RSI) for the stock using an 8-period lookback:
rsi = ta.rsi(close, 8)
Score Calculation:
The script calculates a total score by adding points based on the values of the financial metrics. Each metric is checked against a condition, and if the condition is met, the score is incremented:
If the Operating Margin (opmar) is greater than 20, the score is incremented by 20 points.
If Earnings Per Share (EPS) is positive, 10 points are added.
If the P/E ratio is between 0 and 20, 10 points are added.
If the P/B ratio is less than 3, 10 points are added.
If the Debt-to-Equity ratio is less than 0.8, 10 points are added.
If the Return on Equity Adjusted to Book is greater than 10, 10 points are added.
If the P/FCF ratio is between 0 and 15, 10 points are added.
If the Current Ratio is greater than 1.61, 10 points are added.
If the RSI is less than 35, 10 points are added.
The score is accumulated based on these conditions and stored in the total_score variable.
Displaying the Total Score:
Finally, the total score is plotted on the chart:
Summary of How It Works:
This script calculates a financial score for a stock using a variety of financial indicators. Each metric has a threshold, and when the stock meets certain criteria (for example, a good operating margin, a healthy debt-to-equity ratio, or a low P/E ratio), points are added to the overall score. The result is a single numerical value that reflects the financial health of the stock.
This score can help traders or investors identify companies with strong financials, or serve as a comparison tool between different stocks based on their financial health.
Generally >60 is the best stocks for med and long term trades
ICT Macros [LuxAlgo]The ICT Macros indicator aims to highlight & classify ICT Macros, which are time intervals where algorithmic trading takes place to interact with existing liquidity or to create new liquidity.
🔶 SETTINGS
🔹 Macros
Macro Time options (such as '09:50 AM 10:10'): Enable specific macro display.
Top Line , Mid Line , Bottom Line and Extending Lines options: Controls the lines for the specific macro.
🔹 Macro Classification
Length : A length to detect Market Structure Brakes and classify macro type based on detection.
Swing Area : Swing or Liquidity Area selection, highest/lowest of the wick or the candle bodies.
Accumulation , Manipulation and Expansion color options for the classified macros.
🔹 Others
Macro Texts : Controls both the size and the visibility of the macro text.
Alert Macro Times in Advance (Minutes) : This option will plot a vertical line presenting the start of the next macro time. The line will not appear all the time, but it will be there based on remaining minutes specified in the option.
Daylight Saving Time (DST) : Adjust time appropriate to Daylight Saving Time of the specific region.
🔶 USAGE
A macro is a way to automate a task or procedure which you perform on a regular basis.
In the context of ICT's teachings, a macro is a small program or set of instructions that unfolds within an algorithm, which influences price movements in the market. These macros operate at specific times and can be related to price runs from one level to another or certain market behaviors during specific time intervals. They help traders anticipate market movements and potential setups during specific time intervals.
To trade these effectively, it is important to understand the time of day when certain macros come into play, and it is strongly advised to introduce the concept of liquidity in your analysis.
Macros can be classified into three categories where the Macro classification is calculated based on the Market Structure prior to macro and the Market Structure during the macro duration:
Manipulation Macro
Manipulation macros are characterized by liquidity being swept both on the buyside and sellside.
Expansion Macro
Expansion macros are characterized by liquidity being swept only on the buyside or sellside. Prices within these macros are highly correlated with the overall trend.
Accumulation Macro
Accumulation macros are characterized by an accumulation of liquidity. Prices within these macros tend to range.
The script returns the maximum/minimum price values reached during the macro interval alongside the average between the maximum/minimum and extends them until a new macro starts. These levels can act as supports and resistances.
🔶 DETAILS
All required data for the macro detection and classification is retrieved using 1 minute data sets, this includes candles as well as pivot/swing highs and lows. This approach guarantees the visually presented objects are same (same highs/lows) on higher timeframes as well as the macro classification remain same as it is in 1 min charts.
8 Macros can be displayed by the script (4 are enabled by default):
02:33 AM 03:00 London Macro
04:03 AM 04:30 London Macro
08:50 AM 09:10 New York Macro
09:50 AM 10:10 New York Macro
10:50 AM 11:10 New York Macro
11:50 AM 12:10 New York Launch Macro
13:10 PM 13:40 New York Macro
15:15 PM 15:45 New York Macro
🔶 ALERTS
When an alert is configured, the user will have the ability to be notified in advance of the next Macro time, where the value specified in 'Alert Macro Times in Advance (Minutes)' option indicates how early to be notified.
🔶 LIMITATIONS
The script is supported on 1 min, 3 mins and 5 mins charts.
🔶 RELATED SCRIPTS
ATR Table 2.0ATR Table 2.0
This script was created in order to display a table that "calculates" how far the price can go on the current day .
The script is a table with 3 lines that calculates:
First Line - Day TR: The True Range of the current day ( - , including an Opening GAP if it exists);
Second Line - 10 Day ATR: The Average True Range of the asset (including Opening GAPs) for the last 10 days;
Third LIne - Range Consumed: How much of the 10 Day ATR it was consumed on the current day.
Example of how to use the information on the table and the understanding of it's purpose:
1) Supose you are day trading an asset that, during the last 10 days, have moved around $1.00 a day - This is the 10 Day ATR.
2) On this day, after 2 hours of the opening market, the price have already moved $0.50 (supose that it has moved $0.30 up and $0.35 down from the close of the prior day and the price is now near the close of the prior day).
3) In this situation, knowing that the price often moves around $1.00 a day, and knowing that it already moved $0.65 ($0.30 up and $0.35 down based on the close of the prior day), you may pay attention when the price breaksthrough the max or the min of the day, cause it can still move $0.35 in that direction ($1.00 - $0.65).
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ATR Table 2.0
Esse script foi criado para disponibilizar uma tabela que "calcula" quanto o preço pode andar ainda no dia em questão .
O script é uma tabela com 3 linhas que calcula:
Primeira Linha - TR do Dia: O Range Verdadeira do dia em questão ( - , incluindo GAP de Abertura se for o caso);
Segunda Linha - ATR de 10 Dias: A média do Range Verdadeira do ativo (incluindo GAPs de abertura) dos últimos 10 dias;
Terceira Linha - Range Consumido: O quanto do ATR de 10dias já foi consumido no dia em questão.
Exemplo de como usar essa informação na tabela e o entendimento do seu propósito:
1) Suponha que você está realizando day trade de um ativo que, durante os últimos 10 dias, se move em torno de $1.00 por dia. Esse é o ATR de 10 dias.
2) Nesse dia, após 2 horas da abertura do pregão, o preço já se moveu $.050 (suponhamos que ele tenha se moveu $0.30 para cima e $0.35 para baixo a partir do fechamento do dia anterior e agora o preço está próximo do fechamento do dia anterior).
3) Nessa situação, sabendo que o preço se move por volta de $1.00 por dia, e sabendo que ele já se moveu $0.65 ($0.30 pra cima e $0.35 pra baixo a partir do fechamento do dia anterior), você deve se atentar para quando o preço romper a máxima ou a mínima do dia, pois ele pode se mover ainda $.035 na direção do rompimento ($1.00 - $0.65).
Liquid Pulse Liquid Pulse by Dskyz (DAFE) Trading Systems
Liquid Pulse is a trading algo built by Dskyz (DAFE) Trading Systems for futures markets like NQ1!, designed to snag high-probability trades with tight risk control. it fuses a confluence system—VWAP, MACD, ADX, volume, and liquidity sweeps—with a trade scoring setup, daily limits, and VIX pauses to dodge wild volatility. visuals include simple signals, VWAP bands, and a dashboard with stats.
Core Components for Liquid Pulse
Volume Sensitivity (volumeSensitivity) controls how much volume spikes matter for entries. options: 'Low', 'Medium', 'High' default: 'High' (catches small spikes, good for active markets) tweak it: 'Low' for calm markets, 'High' for chaos.
MACD Speed (macdSpeed) sets the MACD’s pace for momentum. options: 'Fast', 'Medium', 'Slow' default: 'Medium' (solid balance) tweak it: 'Fast' for scalping, 'Slow' for swings.
Daily Trade Limit (dailyTradeLimit) caps trades per day to keep risk in check. range: 1 to 30 default: 20 tweak it: 5-10 for safety, 20-30 for action.
Number of Contracts (numContracts) sets position size. range: 1 to 20 default: 4 tweak it: up for big accounts, down for small.
VIX Pause Level (vixPauseLevel) stops trading if VIX gets too hot. range: 10 to 80 default: 39.0 tweak it: 30 to avoid volatility, 50 to ride it.
Min Confluence Conditions (minConditions) sets how many signals must align. range: 1 to 5 default: 2 tweak it: 3-4 for strict, 1-2 for more trades.
Min Trade Score (Longs/Shorts) (minTradeScoreLongs/minTradeScoreShorts) filters trade quality. longs range: 0 to 100 default: 73 shorts range: 0 to 100 default: 75 tweak it: 80-90 for quality, 60-70 for volume.
Liquidity Sweep Strength (sweepStrength) gauges breakouts. range: 0.1 to 1.0 default: 0.5 tweak it: 0.7-1.0 for strong moves, 0.3-0.5 for small.
ADX Trend Threshold (adxTrendThreshold) confirms trends. range: 10 to 100 default: 41 tweak it: 40-50 for trends, 30-35 for weak ones.
ADX Chop Threshold (adxChopThreshold) avoids chop. range: 5 to 50 default: 20 tweak it: 15-20 to dodge chop, 25-30 to loosen.
VWAP Timeframe (vwapTimeframe) sets VWAP period. options: '15', '30', '60', '240', 'D' default: '60' (1-hour) tweak it: 60 for day, 240 for swing, D for long.
Take Profit Ticks (Longs/Shorts) (takeProfitTicksLongs/takeProfitTicksShorts) sets profit targets. longs range: 5 to 100 default: 25.0 shorts range: 5 to 100 default: 20.0 tweak it: 30-50 for trends, 10-20 for chop.
Max Profit Ticks (maxProfitTicks) caps max gain. range: 10 to 200 default: 60.0 tweak it: 80-100 for big moves, 40-60 for tight.
Min Profit Ticks to Trail (minProfitTicksTrail) triggers trailing. range: 1 to 50 default: 7.0 tweak it: 10-15 for big gains, 5-7 for quick locks.
Trailing Stop Ticks (trailTicks) sets trail distance. range: 1 to 50 default: 5.0 tweak it: 8-10 for room, 3-5 for fast locks.
Trailing Offset Ticks (trailOffsetTicks) sets trail offset. range: 1 to 20 default: 2.0 tweak it: 1-2 for tight, 5-10 for loose.
ATR Period (atrPeriod) measures volatility. range: 5 to 50 default: 9 tweak it: 14-20 for smooth, 5-9 for reactive.
Hardcoded Settings volLookback: 30 ('Low'), 20 ('Medium'), 11 ('High') volThreshold: 1.5 ('Low'), 1.8 ('Medium'), 2 ('High') swingLen: 5
Execution Logic Overview trades trigger when confluence conditions align, entering long or short with set position sizes. exits use dynamic take-profits, trailing stops after a profit threshold, hard stops via ATR, and a time stop after 100 bars.
Features Multi-Signal Confluence: needs VWAP, MACD, volume, sweeps, and ADX to line up.
Risk Control: ATR-based stops (capped 15 ticks), take-profits (scaled by volatility), and trails.
Market Filters: VIX pause, ADX trend/chop checks, volatility gates. Dashboard: shows scores, VIX, ADX, P/L, win %, streak.
Visuals Simple signals (green up triangles for longs, red down for shorts) and VWAP bands with glow. info table (bottom right) with MACD momentum. dashboard (top right) with stats.
Chart and Backtest:
NQ1! futures, 5-minute chart. works best in trending, volatile conditions. tweak inputs for other markets—test thoroughly.
Backtesting: NQ1! Frame: Jan 19, 2025, 09:00 — May 02, 2025, 16:00 Slippage: 3 Commission: $4.60
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Disclaimer this is for education only. past results don’t predict future wins. trading’s risky—only use money you can lose. backtest and validate before going live. (expect moderators to nitpick some random chart symbol rule—i’ll fix and repost if they pull it.)
About the Author Dskyz (DAFE) Trading Systems crafts killer trading algos. Liquid Pulse is pure research and grit, built for smart, bold trading. Use it with discipline. Use it with clarity. Trade smarter. I’ll keep dropping badass strategies ‘til i build a brand or someone signs me up.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
RSI Full Forecast [Titans_Invest]RSI Full Forecast
Get ready to experience the ultimate evolution of RSI-based indicators – the RSI Full Forecast, a boosted and even smarter version of the already powerful: RSI Forecast
Now featuring over 40 additional entry conditions (forecasts), this indicator redefines the way you view the market.
AI-Powered RSI Forecasting:
Using advanced linear regression with the least squares method – a solid foundation for machine learning - the RSI Full Forecast enables you to predict future RSI behavior with impressive accuracy.
But that’s not all: this new version also lets you monitor future crossovers between the RSI and the MA RSI, delivering early and strategic signals that go far beyond traditional analysis.
You’ll be able to monitor future crossovers up to 20 bars ahead, giving you an even broader and more precise view of market movements.
See the Future, Now:
• Track upcoming RSI & RSI MA crossovers in advance.
• Identify potential reversal zones before price reacts.
• Uncover statistical behavior patterns that would normally go unnoticed.
40+ Intelligent Conditions:
The new layer of conditions is designed to detect multiple high-probability scenarios based on historical patterns and predictive modeling. Each additional forecast is a window into the price's future, powered by robust mathematics and advanced algorithmic logic.
Full Customization:
All parameters can be tailored to fit your strategy – from smoothing periods to prediction sensitivity. You have complete control to turn raw data into smart decisions.
Innovative, Accurate, Unique:
This isn’t just an upgrade. It’s a quantum leap in technical analysis.
RSI Full Forecast is the first of its kind: an indicator that blends statistical analysis, machine learning, and visual design to create a true real-time predictive system.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an RSI time series like this:
Time →
RSI →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public RSI with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
RSI Full Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
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🔮 Linear Regression: PineScript Technical Parameters 🔮
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Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
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⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
• Overbought: When the RSI is above 70, indicating that the asset may be overbought.
• Oversold: When the RSI is below 30, indicating that the asset may be oversold.
• Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
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⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
📈 RSI Forecast:
🔹 RSI (Crossover) MA Forecast
🔹 RSI (Crossunder) MA Forecast
🔹 RSI Forecast 1 > MA Forecast 1
🔹 RSI Forecast 1 < MA Forecast 1
🔹 RSI Forecast 2 > MA Forecast 2
🔹 RSI Forecast 2 < MA Forecast 2
🔹 RSI Forecast 3 > MA Forecast 3
🔹 RSI Forecast 3 < MA Forecast 3
🔹 RSI Forecast 4 > MA Forecast 4
🔹 RSI Forecast 4 < MA Forecast 4
🔹 RSI Forecast 5 > MA Forecast 5
🔹 RSI Forecast 5 < MA Forecast 5
🔹 RSI Forecast 6 > MA Forecast 6
🔹 RSI Forecast 6 < MA Forecast 6
🔹 RSI Forecast 7 > MA Forecast 7
🔹 RSI Forecast 7 < MA Forecast 7
🔹 RSI Forecast 8 > MA Forecast 8
🔹 RSI Forecast 8 < MA Forecast 8
🔹 RSI Forecast 9 > MA Forecast 9
🔹 RSI Forecast 9 < MA Forecast 9
🔹 RSI Forecast 10 > MA Forecast 10
🔹 RSI Forecast 10 < MA Forecast 10
🔹 RSI Forecast 11 > MA Forecast 11
🔹 RSI Forecast 11 < MA Forecast 11
🔹 RSI Forecast 12 > MA Forecast 12
🔹 RSI Forecast 12 < MA Forecast 12
🔹 RSI Forecast 13 > MA Forecast 13
🔹 RSI Forecast 13 < MA Forecast 13
🔹 RSI Forecast 14 > MA Forecast 14
🔹 RSI Forecast 14 < MA Forecast 14
🔹 RSI Forecast 15 > MA Forecast 15
🔹 RSI Forecast 15 < MA Forecast 15
🔹 RSI Forecast 16 > MA Forecast 16
🔹 RSI Forecast 16 < MA Forecast 16
🔹 RSI Forecast 17 > MA Forecast 17
🔹 RSI Forecast 17 < MA Forecast 17
🔹 RSI Forecast 18 > MA Forecast 18
🔹 RSI Forecast 18 < MA Forecast 18
🔹 RSI Forecast 19 > MA Forecast 19
🔹 RSI Forecast 19 < MA Forecast 19
🔹 RSI Forecast 20 > MA Forecast 20
🔹 RSI Forecast 20 < MA Forecast 20
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🔸 CONDITIONS TO SELL 📉
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
📉 RSI Forecast:
🔸 RSI (Crossover) MA Forecast
🔸 RSI (Crossunder) MA Forecast
🔸 RSI Forecast 1 > MA Forecast 1
🔸 RSI Forecast 1 < MA Forecast 1
🔸 RSI Forecast 2 > MA Forecast 2
🔸 RSI Forecast 2 < MA Forecast 2
🔸 RSI Forecast 3 > MA Forecast 3
🔸 RSI Forecast 3 < MA Forecast 3
🔸 RSI Forecast 4 > MA Forecast 4
🔸 RSI Forecast 4 < MA Forecast 4
🔸 RSI Forecast 5 > MA Forecast 5
🔸 RSI Forecast 5 < MA Forecast 5
🔸 RSI Forecast 6 > MA Forecast 6
🔸 RSI Forecast 6 < MA Forecast 6
🔸 RSI Forecast 7 > MA Forecast 7
🔸 RSI Forecast 7 < MA Forecast 7
🔸 RSI Forecast 8 > MA Forecast 8
🔸 RSI Forecast 8 < MA Forecast 8
🔸 RSI Forecast 9 > MA Forecast 9
🔸 RSI Forecast 9 < MA Forecast 9
🔸 RSI Forecast 10 > MA Forecast 10
🔸 RSI Forecast 10 < MA Forecast 10
🔸 RSI Forecast 11 > MA Forecast 11
🔸 RSI Forecast 11 < MA Forecast 11
🔸 RSI Forecast 12 > MA Forecast 12
🔸 RSI Forecast 12 < MA Forecast 12
🔸 RSI Forecast 13 > MA Forecast 13
🔸 RSI Forecast 13 < MA Forecast 13
🔸 RSI Forecast 14 > MA Forecast 14
🔸 RSI Forecast 14 < MA Forecast 14
🔸 RSI Forecast 15 > MA Forecast 15
🔸 RSI Forecast 15 < MA Forecast 15
🔸 RSI Forecast 16 > MA Forecast 16
🔸 RSI Forecast 16 < MA Forecast 16
🔸 RSI Forecast 17 > MA Forecast 17
🔸 RSI Forecast 17 < MA Forecast 17
🔸 RSI Forecast 18 > MA Forecast 18
🔸 RSI Forecast 18 < MA Forecast 18
🔸 RSI Forecast 19 > MA Forecast 19
🔸 RSI Forecast 19 < MA Forecast 19
🔸 RSI Forecast 20 > MA Forecast 20
🔸 RSI Forecast 20 < MA Forecast 20
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : RSI Full Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Absolute Strength Index [ASI] (Zeiierman)█ Overview
The Absolute Strength Index (ASI) is a next-generation oscillator designed to measure the strength and direction of price movements by leveraging percentile-based normalization of historical returns. Developed by Zeiierman, this indicator offers a highly visual and intuitive approach to identifying market conditions, trend strength, and divergence opportunities.
By dynamically scaling price returns into a bounded oscillator (-10 to +10), the ASI helps traders spot overbought/oversold conditions, trend reversals, and momentum changes with enhanced precision. It also incorporates advanced features like divergence detection and adaptive signal smoothing for versatile trading applications.
█ How It Works
The ASI's core calculation methodology revolves around analyzing historical price returns, classifying them into top and bottom percentiles, and normalizing the current price movement within this framework. Here's a breakdown of its key components:
⚪ Returns Lookback
The ASI evaluates historical price returns over a user-defined period (Returns Lookback) to measure recent price behavior. This lookback window determines the sensitivity of the oscillator:
Shorter Lookback: Higher responsiveness to recent price movements, suitable for scalping or high-volatility assets.
Longer Lookback: Smoother oscillator behavior is ideal for identifying larger trends and avoiding false signals.
⚪ Percentile-Based Thresholds
The ASI categorizes returns into two groups:
Top Percentile (Winners): The upper X% of returns, representing the strongest upward price moves.
Bottom Percentile (Losers): The lower X% of returns, capturing the sharpest downward movements.
This percentile-based normalization ensures the ASI adapts to market conditions, filtering noise and emphasizing significant price changes.
⚪ Oscillator Normalization
The ASI normalizes current returns relative to the top and bottom thresholds:
Values range from -10 to +10, where:
+10 represents extreme bullish strength (above the top percentile threshold).
-10 indicates extreme bearish weakness (below the bottom percentile threshold).
⚪ Signal Line Smoothing
A signal line is optionally applied to the ASI using a variety of moving averages:
Options: SMA, EMA, WMA, RMA, or HMA.
Effect: Smooths the ASI to filter out noise, with shorter lengths offering higher responsiveness and longer lengths providing stability.
⚪ Divergence Detection
One of ASI's standout features is its ability to detect and highlight bullish and bearish divergences:
Bullish Divergence: The ASI forms higher lows while the price forms lower lows, signaling potential upward reversals.
Bearish Divergence: The ASI forms lower highs while the price forms higher highs, indicating potential downward reversals.
█ Key Differences from RSI
Dynamic Adaptability: ASI adjusts to market conditions through percentile-based scaling, while RSI uses static thresholds.
█ How to Use ASI
⚪ Trend Identification
Bullish Strength: ASI above zero suggests upward momentum, suitable for trend-following trades.
Bearish Weakness: ASI below zero signals downward momentum, ideal for short trades or exits from long positions.
⚪ Overbought/Oversold Levels
Overbought Zone: ASI in the +8 to +10 range indicates potential exhaustion of bullish momentum.
Oversold Zone: ASI in the -8 to -10 range points to potential reversal opportunities.
⚪ Divergence Signals
Look for bullish or bearish divergence labels to anticipate trend reversals before they occur.
⚪ Signal Line Crossovers
A crossover between the ASI and its signal line (e.g., EMA or SMA) can indicate a shift in momentum:
Bullish Crossover: ASI crosses above the signal line, signaling potential upside.
Bearish Crossover: ASI crosses below the signal line, suggesting downside momentum.
█ Settings Explained
⚪ Absolute Strength Index
Returns Lookback: Sets the sensitivity of the oscillator. Shorter periods detect short-term changes, while longer periods focus on broader trends.
Top/Bottom Percentiles: Adjust thresholds for defining winners and losers. Narrower percentiles increase sensitivity to outliers.
Signal Line Type: Choose from SMA, EMA, WMA, RMA, or HMA for smoothing.
Signal Line Length: Fine-tune the responsiveness of the signal line.
⚪ Divergence
Divergence Lookback: Adjusts the period for detecting divergence. Use longer lookbacks to reduce noise.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Filtered ATR with EMA OverlayFiltered ATR with EMA Overlay is an advanced volatility indicator designed to provide a more accurate representation of market conditions by smoothing the standard Average True Range (ATR). This is achieved by filtering out extreme price movements and abnormal bars that can distort traditional ATR calculations.
The indicator applies an Exponential Moving Average (EMA) to the filtered ATR, creating a dual-layered system that highlights periods of increased or decreased volatility.
Key Features:
Filtered ATR: Filters out extreme bars, reducing noise and making the ATR line more reliable.
EMA Overlay: An EMA (default period of 10) is applied to the filtered ATR, allowing traders to track average volatility trends.
Volatility Signals:
Filtered ATR > EMA(10): Indicates higher-than-average volatility. This often correlates with trend breakouts or strong price movements.
Filtered ATR < EMA(10): Suggests reduced volatility, signaling potential consolidation or sideways price action.
Parameters:
atrLength (Default: 5):
The number of bars used to calculate the ATR. A shorter period (e.g., 3-5) responds faster to price changes, while a longer period (e.g., 10-14) provides smoother results.
multiplier (Default: 1.8):
Controls the sensitivity of the filter. A lower multiplier (e.g., 1.5) filters out more bars, resulting in smoother ATR. Higher values (e.g., 2.0) allow more bars to pass through, retaining more price volatility.
maxIterations (Default: 20):
The maximum number of bars processed to detect abnormal values. Increasing this may improve accuracy at the cost of performance.
ema10Period (Default: 10):
The period for the Exponential Moving Average applied to the filtered ATR. Shorter periods provide faster signals, while longer periods give smoother, lagging signals.
Trading Strategies:
1. Breakout Strategy:
When filtered ATR crosses above EMA(10):
Enter long positions when price breaks above a key resistance level.
Higher volatility suggests strong price action and momentum.
When filtered ATR drops below EMA(10):
Exit positions or tighten stop-loss orders as volatility decreases.
Lower volatility may indicate consolidation or trend exhaustion.
2. Trend Following Strategy:
Use the filtered ATR line to track overall volatility.
If filtered ATR consistently stays above EMA: Hold positions or add to trades.
If filtered ATR remains below EMA: Reduce position size or stay out of trades.
3. Mean Reversion Strategy:
When filtered ATR spikes significantly above EMA, it may indicate market overreaction.
Look for price to revert to the mean once ATR returns below the EMA.
4. Stop-Loss Adjustment:
As volatility increases (ATR above EMA), widen stop-loss levels to avoid being stopped out by random fluctuations.
In low volatility (ATR below EMA), tighten stop-losses to minimize losses during low activity periods.
Benefits:
Reduced Noise: By filtering abnormal bars, the indicator provides cleaner signals.
Better Trend Detection: EMA smoothing highlights volatility trends.
Adaptable: The indicator can be customized for scalping, day trading, or swing trading.
Intuitive Visualization: Traders can visually see volatility shifts and adjust strategies in real-time.
Best Practices:
Timeframes: Works effectively on all timeframes, but higher timeframes (e.g., 1H, 4H, Daily) yield more reliable signals.
Markets: Suitable for forex, crypto, stocks, and commodities.
Combining Indicators: Use in combination with RSI, Moving Averages, Bollinger Bands, or price action analysis for stronger signals.
How It Works (Under the Hood):
The script calculates the Daily Range (High - Low) for each bar.
The largest and smallest bars are filtered out if their difference exceeds the multiplier (default 1.8).
The remaining bars are averaged to generate the filtered ATR.
An EMA(10) is then applied to the filtered ATR for smoother visualization.
Dynamic Buy/Sell VisualizationDynamic Trend Visualization Indicator
Description:
This simple and easy to use indicator has helped me stay in trades longer.
This indicator is designed to visually represent potential buy and sell signals based on the crossover of two Simple Moving Averages (SMA). It's crafted to assist traders in identifying trend directions in a straightforward manner, making it an excellent tool for both beginners and experienced traders.
Features:
Customizable Moving Averages: Users can adjust the period length for both short-term (default: 10) and long-term (default: 50) SMAs to suit their trading strategy.
Visual Signals: Dynamic lines appear at the points of SMA crossover, with labels to indicate 'BUY' or 'SELL' opportunities.
Color and Style Customization: Customize the appearance of the buy and sell lines for better chart readability.
Alert Functionality: Alerts are set up to notify users when a crossover indicating a buy or sell condition occurs.
How It Works:
A 'BUY' signal is generated when the short-term SMA crosses above the long-term SMA, suggesting an upward trend.
A 'SELL' signal is indicated when the short-term SMA crosses below the long-term SMA, pointing to a potential downward trend.
Use Cases:
Trend Following: Ideal for markets with clear trends. For example, if trading EUR/USD on a daily chart, setting the short SMA to 10 days and the long SMA to 50 days might help in capturing longer-term trends.
Scalping: In a volatile market, setting shorter periods (e.g., 5 for short SMA and 20 for long SMA) might catch quicker trend changes, suitable for scalping.
Examples of how to use
* Short-term for Quick Trades:
SMA 5 and SMA 21:
Purpose: This combination is tailored for day traders or those looking to engage in scalping. The 5 SMA will react rapidly to price changes, providing early signals for buy or sell opportunities. The 21 SMA, being a Fibonacci number, offers a slightly longer-term view to confirm the short-term trend, helping to filter out minor fluctuations that might lead to false signals.
* Middle-term for Swing Trading:
SMA 10 and SMA 50:
Purpose: Suited for swing traders who aim to capitalize on medium-term trends. The 10 SMA picks up on immediate market movements, while the 50 SMA gives insight into the medium-term direction. This setup helps in identifying when a short-term trend aligns with a longer-term trend, providing a good balance for trades that might last several days to a couple of weeks.
* Long-term Trading:
SMA 50 and SMA 200:
Purpose: Investors focusing on long-term trends would benefit from this pair. The crossover of the 50 SMA over the 200 SMA can indicate the beginning or end of major market trends, ideal for making decisions about long-term holdings that might span months or years.
Example Strategy if not using the Buy / Sell Label Alerts:
Entry Signal: Enter a long position when the shorter SMA crosses above the longer SMA. For example:
SMA 10 crosses above SMA 50 for a medium-term bullish signal.
Exit Signal: Consider exiting or initiating a short position when:
SMA 10 crosses below SMA 50, suggesting a bearish turn in the medium-term trend.
Confirmation: Use these crossovers in conjunction with other indicators like volume or momentum indicators for better confirmation. For instance, if you're using the 5/21 combination, look for volume spikes on crossovers to confirm the move's strength.
When Not to Use:
Sideways or Range-Bound Markets: The indicator might generate many false signals in a non-trending market, leading to potential losses.
High Volatility Without Clear Trends: Rapid price movements without a consistent direction can result in misleading crossovers.
As a Standalone Tool: It should not be used in isolation. Combining with other indicators like RSI or MACD for confirmation can enhance trading decisions.
Practical Example:
Buy Signal: If you're watching Apple Inc. (AAPL) on a weekly chart, a crossover where the 10-week SMA moves above the 50-week SMA could suggest a buying opportunity, especially if confirmed by volume increase or other technical indicators.
Sell Signal: Conversely, if the 10-week SMA dips below the 50-week SMA, it might be time to consider selling, particularly if other bearish signals are present.
Conclusion:
The "Dynamic Trend Visualization" indicator provides a visual aid for trend-following strategies, offering customization and alert features to streamline the trading process. However, it's crucial to use this in conjunction with other analysis methods to mitigate the risks of false signals or market anomalies.
Legal Disclaimer:
This indicator is for educational purposes only. It does not guarantee profits or provide investment advice. Trading involves risk; please conduct thorough or consult with a financial advisor. The creator is not responsible for any losses incurred. By using this indicator, you agree to these terms.
Connors VIX Reversal III invented by Dave LandryThis strategy is based on trading signals derived from the behavior of the Volatility Index (VIX) relative to its 10-day moving average. The rules are split into buying and selling conditions:
Buy Conditions:
The VIX low must be above its 10-day moving average.
The VIX must close at least 10% above its 10-day moving average.
If both conditions are met, a buy signal is generated at the market's close.
Sell Conditions:
The VIX high must be below its 10-day moving average.
The VIX must close at least 10% below its 10-day moving average.
If both conditions are met, a sell signal is generated at the market's close.
Exit Conditions:
For long positions, the strategy exits when the VIX trades intraday below its previous day’s 10-day moving average.
For short positions, the strategy exits when the VIX trades intraday above its previous day’s 10-day moving average.
This strategy is primarily a mean-reversion strategy, where the market is expected to revert to a more normal state after the VIX exhibits extreme behavior (i.e., large deviations from its moving average).
About Dave Landry
Dave Landry is a well-known figure in the world of trading, particularly in technical analysis. He is an author, trader, and educator, best known for his work on swing trading strategies. Landry focuses on trend-following and momentum-based techniques, teaching traders how to capitalize on shorter-term price swings in the market. He has written books like "Dave Landry on Swing Trading" and "The Layman's Guide to Trading Stocks," which emphasize practical, actionable trading strategies.
About Connors Research
Connors Research is a financial research firm known for its quantitative research in financial markets. Founded by Larry Connors, the firm specializes in developing high-probability trading systems based on historical market behavior. Connors’ work is widely respected for its data-driven approach, including systems like the RSI(2) strategy, which focuses on short-term mean reversion. The firm also provides trading education and tools for institutional and retail traders alike, emphasizing strategies that can be backtested and quantified.
Risks of the Strategy
While this strategy may appear to offer promising opportunities to exploit extreme VIX movements, it carries several risks:
Market Volatility: The VIX itself is a measure of market volatility, meaning the strategy can be exposed to sudden and unpredictable market swings. This can result in whipsaws, where positions are opened and closed in rapid succession due to sharp reversals in the VIX.
Overfitting: Strategies based on specific conditions like the VIX closing 10% above or below its moving average can be subject to overfitting, meaning they work well in historical tests but may underperform in live markets. This is a common issue in quantitative trading systems that are not adaptable to changing market conditions .
Mean-Reversion Assumption: The core assumption behind this strategy is that markets will revert to their mean after extreme movements. However, during periods of sustained trends (e.g., market crashes or rallies), this assumption may break down, leading to prolonged drawdowns.
Liquidity and Slippage: Depending on the asset being traded (e.g., S&P 500 futures, ETFs), liquidity issues or slippage could occur when executing trades at market close, particularly in volatile conditions. This could increase costs or worsen trade execution.
Scientific Explanation of the Strategy
The VIX is often referred to as the "fear gauge" because it measures the market's expectations of volatility based on options prices. Research has shown that the VIX tends to spike during periods of market stress and revert to lower levels when conditions stabilize . Mean reversion strategies like this one assume that extreme VIX levels are unsustainable in the long run, which aligns with findings from academic literature on volatility and market behavior.
Studies have found that the VIX is inversely correlated with stock market returns, meaning that higher VIX levels often correspond to lower stock prices and vice versa . By using the VIX’s relationship with its 10-day moving average, this strategy aims to capture reversals in market sentiment. The 10% threshold is designed to identify moments when the VIX is significantly deviating from its norm, signaling a potential reversal.
However, academic research also highlights the limitations of relying on the VIX alone for trading signals. The VIX does not predict market direction, only volatility, meaning that it cannot indicate the magnitude of price movements . Furthermore, extreme VIX levels can persist longer than expected, particularly during financial crises.
In conclusion, while the strategy is grounded in well-established financial principles (e.g., mean reversion and the relationship between volatility and market performance), it carries inherent risks and should be used with caution. Backtesting and careful risk management are essential before applying this strategy in live markets.
PubLibCandleTrendLibrary "PubLibCandleTrend"
candle trend, multi-part candle trend, multi-part green/red candle trend, double candle trend and multi-part double candle trend conditions for indicator and strategy development
chh()
candle higher high condition
Returns: bool
chl()
candle higher low condition
Returns: bool
clh()
candle lower high condition
Returns: bool
cll()
candle lower low condition
Returns: bool
cdt()
candle double top condition
Returns: bool
cdb()
candle double bottom condition
Returns: bool
gc()
green candle condition
Returns: bool
gchh()
green candle higher high condition
Returns: bool
gchl()
green candle higher low condition
Returns: bool
gclh()
green candle lower high condition
Returns: bool
gcll()
green candle lower low condition
Returns: bool
gcdt()
green candle double top condition
Returns: bool
gcdb()
green candle double bottom condition
Returns: bool
rc()
red candle condition
Returns: bool
rchh()
red candle higher high condition
Returns: bool
rchl()
red candle higher low condition
Returns: bool
rclh()
red candle lower high condition
Returns: bool
rcll()
red candle lower low condition
Returns: bool
rcdt()
red candle double top condition
Returns: bool
rcdb()
red candle double bottom condition
Returns: bool
chh_1p()
1-part candle higher high condition
Returns: bool
chh_2p()
2-part candle higher high condition
Returns: bool
chh_3p()
3-part candle higher high condition
Returns: bool
chh_4p()
4-part candle higher high condition
Returns: bool
chh_5p()
5-part candle higher high condition
Returns: bool
chh_6p()
6-part candle higher high condition
Returns: bool
chh_7p()
7-part candle higher high condition
Returns: bool
chh_8p()
8-part candle higher high condition
Returns: bool
chh_9p()
9-part candle higher high condition
Returns: bool
chh_10p()
10-part candle higher high condition
Returns: bool
chh_11p()
11-part candle higher high condition
Returns: bool
chh_12p()
12-part candle higher high condition
Returns: bool
chh_13p()
13-part candle higher high condition
Returns: bool
chh_14p()
14-part candle higher high condition
Returns: bool
chh_15p()
15-part candle higher high condition
Returns: bool
chh_16p()
16-part candle higher high condition
Returns: bool
chh_17p()
17-part candle higher high condition
Returns: bool
chh_18p()
18-part candle higher high condition
Returns: bool
chh_19p()
19-part candle higher high condition
Returns: bool
chh_20p()
20-part candle higher high condition
Returns: bool
chh_21p()
21-part candle higher high condition
Returns: bool
chh_22p()
22-part candle higher high condition
Returns: bool
chh_23p()
23-part candle higher high condition
Returns: bool
chh_24p()
24-part candle higher high condition
Returns: bool
chh_25p()
25-part candle higher high condition
Returns: bool
chh_26p()
26-part candle higher high condition
Returns: bool
chh_27p()
27-part candle higher high condition
Returns: bool
chh_28p()
28-part candle higher high condition
Returns: bool
chh_29p()
29-part candle higher high condition
Returns: bool
chh_30p()
30-part candle higher high condition
Returns: bool
chl_1p()
1-part candle higher low condition
Returns: bool
chl_2p()
2-part candle higher low condition
Returns: bool
chl_3p()
3-part candle higher low condition
Returns: bool
chl_4p()
4-part candle higher low condition
Returns: bool
chl_5p()
5-part candle higher low condition
Returns: bool
chl_6p()
6-part candle higher low condition
Returns: bool
chl_7p()
7-part candle higher low condition
Returns: bool
chl_8p()
8-part candle higher low condition
Returns: bool
chl_9p()
9-part candle higher low condition
Returns: bool
chl_10p()
10-part candle higher low condition
Returns: bool
chl_11p()
11-part candle higher low condition
Returns: bool
chl_12p()
12-part candle higher low condition
Returns: bool
chl_13p()
13-part candle higher low condition
Returns: bool
chl_14p()
14-part candle higher low condition
Returns: bool
chl_15p()
15-part candle higher low condition
Returns: bool
chl_16p()
16-part candle higher low condition
Returns: bool
chl_17p()
17-part candle higher low condition
Returns: bool
chl_18p()
18-part candle higher low condition
Returns: bool
chl_19p()
19-part candle higher low condition
Returns: bool
chl_20p()
20-part candle higher low condition
Returns: bool
chl_21p()
21-part candle higher low condition
Returns: bool
chl_22p()
22-part candle higher low condition
Returns: bool
chl_23p()
23-part candle higher low condition
Returns: bool
chl_24p()
24-part candle higher low condition
Returns: bool
chl_25p()
25-part candle higher low condition
Returns: bool
chl_26p()
26-part candle higher low condition
Returns: bool
chl_27p()
27-part candle higher low condition
Returns: bool
chl_28p()
28-part candle higher low condition
Returns: bool
chl_29p()
29-part candle higher low condition
Returns: bool
chl_30p()
30-part candle higher low condition
Returns: bool
clh_1p()
1-part candle lower high condition
Returns: bool
clh_2p()
2-part candle lower high condition
Returns: bool
clh_3p()
3-part candle lower high condition
Returns: bool
clh_4p()
4-part candle lower high condition
Returns: bool
clh_5p()
5-part candle lower high condition
Returns: bool
clh_6p()
6-part candle lower high condition
Returns: bool
clh_7p()
7-part candle lower high condition
Returns: bool
clh_8p()
8-part candle lower high condition
Returns: bool
clh_9p()
9-part candle lower high condition
Returns: bool
clh_10p()
10-part candle lower high condition
Returns: bool
clh_11p()
11-part candle lower high condition
Returns: bool
clh_12p()
12-part candle lower high condition
Returns: bool
clh_13p()
13-part candle lower high condition
Returns: bool
clh_14p()
14-part candle lower high condition
Returns: bool
clh_15p()
15-part candle lower high condition
Returns: bool
clh_16p()
16-part candle lower high condition
Returns: bool
clh_17p()
17-part candle lower high condition
Returns: bool
clh_18p()
18-part candle lower high condition
Returns: bool
clh_19p()
19-part candle lower high condition
Returns: bool
clh_20p()
20-part candle lower high condition
Returns: bool
clh_21p()
21-part candle lower high condition
Returns: bool
clh_22p()
22-part candle lower high condition
Returns: bool
clh_23p()
23-part candle lower high condition
Returns: bool
clh_24p()
24-part candle lower high condition
Returns: bool
clh_25p()
25-part candle lower high condition
Returns: bool
clh_26p()
26-part candle lower high condition
Returns: bool
clh_27p()
27-part candle lower high condition
Returns: bool
clh_28p()
28-part candle lower high condition
Returns: bool
clh_29p()
29-part candle lower high condition
Returns: bool
clh_30p()
30-part candle lower high condition
Returns: bool
cll_1p()
1-part candle lower low condition
Returns: bool
cll_2p()
2-part candle lower low condition
Returns: bool
cll_3p()
3-part candle lower low condition
Returns: bool
cll_4p()
4-part candle lower low condition
Returns: bool
cll_5p()
5-part candle lower low condition
Returns: bool
cll_6p()
6-part candle lower low condition
Returns: bool
cll_7p()
7-part candle lower low condition
Returns: bool
cll_8p()
8-part candle lower low condition
Returns: bool
cll_9p()
9-part candle lower low condition
Returns: bool
cll_10p()
10-part candle lower low condition
Returns: bool
cll_11p()
11-part candle lower low condition
Returns: bool
cll_12p()
12-part candle lower low condition
Returns: bool
cll_13p()
13-part candle lower low condition
Returns: bool
cll_14p()
14-part candle lower low condition
Returns: bool
cll_15p()
15-part candle lower low condition
Returns: bool
cll_16p()
16-part candle lower low condition
Returns: bool
cll_17p()
17-part candle lower low condition
Returns: bool
cll_18p()
18-part candle lower low condition
Returns: bool
cll_19p()
19-part candle lower low condition
Returns: bool
cll_20p()
20-part candle lower low condition
Returns: bool
cll_21p()
21-part candle lower low condition
Returns: bool
cll_22p()
22-part candle lower low condition
Returns: bool
cll_23p()
23-part candle lower low condition
Returns: bool
cll_24p()
24-part candle lower low condition
Returns: bool
cll_25p()
25-part candle lower low condition
Returns: bool
cll_26p()
26-part candle lower low condition
Returns: bool
cll_27p()
27-part candle lower low condition
Returns: bool
cll_28p()
28-part candle lower low condition
Returns: bool
cll_29p()
29-part candle lower low condition
Returns: bool
cll_30p()
30-part candle lower low condition
Returns: bool
gc_1p()
1-part green candle condition
Returns: bool
gc_2p()
2-part green candle condition
Returns: bool
gc_3p()
3-part green candle condition
Returns: bool
gc_4p()
4-part green candle condition
Returns: bool
gc_5p()
5-part green candle condition
Returns: bool
gc_6p()
6-part green candle condition
Returns: bool
gc_7p()
7-part green candle condition
Returns: bool
gc_8p()
8-part green candle condition
Returns: bool
gc_9p()
9-part green candle condition
Returns: bool
gc_10p()
10-part green candle condition
Returns: bool
gc_11p()
11-part green candle condition
Returns: bool
gc_12p()
12-part green candle condition
Returns: bool
gc_13p()
13-part green candle condition
Returns: bool
gc_14p()
14-part green candle condition
Returns: bool
gc_15p()
15-part green candle condition
Returns: bool
gc_16p()
16-part green candle condition
Returns: bool
gc_17p()
17-part green candle condition
Returns: bool
gc_18p()
18-part green candle condition
Returns: bool
gc_19p()
19-part green candle condition
Returns: bool
gc_20p()
20-part green candle condition
Returns: bool
gc_21p()
21-part green candle condition
Returns: bool
gc_22p()
22-part green candle condition
Returns: bool
gc_23p()
23-part green candle condition
Returns: bool
gc_24p()
24-part green candle condition
Returns: bool
gc_25p()
25-part green candle condition
Returns: bool
gc_26p()
26-part green candle condition
Returns: bool
gc_27p()
27-part green candle condition
Returns: bool
gc_28p()
28-part green candle condition
Returns: bool
gc_29p()
29-part green candle condition
Returns: bool
gc_30p()
30-part green candle condition
Returns: bool
rc_1p()
1-part red candle condition
Returns: bool
rc_2p()
2-part red candle condition
Returns: bool
rc_3p()
3-part red candle condition
Returns: bool
rc_4p()
4-part red candle condition
Returns: bool
rc_5p()
5-part red candle condition
Returns: bool
rc_6p()
6-part red candle condition
Returns: bool
rc_7p()
7-part red candle condition
Returns: bool
rc_8p()
8-part red candle condition
Returns: bool
rc_9p()
9-part red candle condition
Returns: bool
rc_10p()
10-part red candle condition
Returns: bool
rc_11p()
11-part red candle condition
Returns: bool
rc_12p()
12-part red candle condition
Returns: bool
rc_13p()
13-part red candle condition
Returns: bool
rc_14p()
14-part red candle condition
Returns: bool
rc_15p()
15-part red candle condition
Returns: bool
rc_16p()
16-part red candle condition
Returns: bool
rc_17p()
17-part red candle condition
Returns: bool
rc_18p()
18-part red candle condition
Returns: bool
rc_19p()
19-part red candle condition
Returns: bool
rc_20p()
20-part red candle condition
Returns: bool
rc_21p()
21-part red candle condition
Returns: bool
rc_22p()
22-part red candle condition
Returns: bool
rc_23p()
23-part red candle condition
Returns: bool
rc_24p()
24-part red candle condition
Returns: bool
rc_25p()
25-part red candle condition
Returns: bool
rc_26p()
26-part red candle condition
Returns: bool
rc_27p()
27-part red candle condition
Returns: bool
rc_28p()
28-part red candle condition
Returns: bool
rc_29p()
29-part red candle condition
Returns: bool
rc_30p()
30-part red candle condition
Returns: bool
cdut()
candle double uptrend condition
Returns: bool
cddt()
candle double downtrend condition
Returns: bool
cdut_1p()
1-part candle double uptrend condition
Returns: bool
cdut_2p()
2-part candle double uptrend condition
Returns: bool
cdut_3p()
3-part candle double uptrend condition
Returns: bool
cdut_4p()
4-part candle double uptrend condition
Returns: bool
cdut_5p()
5-part candle double uptrend condition
Returns: bool
cdut_6p()
6-part candle double uptrend condition
Returns: bool
cdut_7p()
7-part candle double uptrend condition
Returns: bool
cdut_8p()
8-part candle double uptrend condition
Returns: bool
cdut_9p()
9-part candle double uptrend condition
Returns: bool
cdut_10p()
10-part candle double uptrend condition
Returns: bool
cdut_11p()
11-part candle double uptrend condition
Returns: bool
cdut_12p()
12-part candle double uptrend condition
Returns: bool
cdut_13p()
13-part candle double uptrend condition
Returns: bool
cdut_14p()
14-part candle double uptrend condition
Returns: bool
cdut_15p()
15-part candle double uptrend condition
Returns: bool
cdut_16p()
16-part candle double uptrend condition
Returns: bool
cdut_17p()
17-part candle double uptrend condition
Returns: bool
cdut_18p()
18-part candle double uptrend condition
Returns: bool
cdut_19p()
19-part candle double uptrend condition
Returns: bool
cdut_20p()
20-part candle double uptrend condition
Returns: bool
cdut_21p()
21-part candle double uptrend condition
Returns: bool
cdut_22p()
22-part candle double uptrend condition
Returns: bool
cdut_23p()
23-part candle double uptrend condition
Returns: bool
cdut_24p()
24-part candle double uptrend condition
Returns: bool
cdut_25p()
25-part candle double uptrend condition
Returns: bool
cdut_26p()
26-part candle double uptrend condition
Returns: bool
cdut_27p()
27-part candle double uptrend condition
Returns: bool
cdut_28p()
28-part candle double uptrend condition
Returns: bool
cdut_29p()
29-part candle double uptrend condition
Returns: bool
cdut_30p()
30-part candle double uptrend condition
Returns: bool
cddt_1p()
1-part candle double downtrend condition
Returns: bool
cddt_2p()
2-part candle double downtrend condition
Returns: bool
cddt_3p()
3-part candle double downtrend condition
Returns: bool
cddt_4p()
4-part candle double downtrend condition
Returns: bool
cddt_5p()
5-part candle double downtrend condition
Returns: bool
cddt_6p()
6-part candle double downtrend condition
Returns: bool
cddt_7p()
7-part candle double downtrend condition
Returns: bool
cddt_8p()
8-part candle double downtrend condition
Returns: bool
cddt_9p()
9-part candle double downtrend condition
Returns: bool
cddt_10p()
10-part candle double downtrend condition
Returns: bool
cddt_11p()
11-part candle double downtrend condition
Returns: bool
cddt_12p()
12-part candle double downtrend condition
Returns: bool
cddt_13p()
13-part candle double downtrend condition
Returns: bool
cddt_14p()
14-part candle double downtrend condition
Returns: bool
cddt_15p()
15-part candle double downtrend condition
Returns: bool
cddt_16p()
16-part candle double downtrend condition
Returns: bool
cddt_17p()
17-part candle double downtrend condition
Returns: bool
cddt_18p()
18-part candle double downtrend condition
Returns: bool
cddt_19p()
19-part candle double downtrend condition
Returns: bool
cddt_20p()
20-part candle double downtrend condition
Returns: bool
cddt_21p()
21-part candle double downtrend condition
Returns: bool
cddt_22p()
22-part candle double downtrend condition
Returns: bool
cddt_23p()
23-part candle double downtrend condition
Returns: bool
cddt_24p()
24-part candle double downtrend condition
Returns: bool
cddt_25p()
25-part candle double downtrend condition
Returns: bool
cddt_26p()
26-part candle double downtrend condition
Returns: bool
cddt_27p()
27-part candle double downtrend condition
Returns: bool
cddt_28p()
28-part candle double downtrend condition
Returns: bool
cddt_29p()
29-part candle double downtrend condition
Returns: bool
cddt_30p()
30-part candle double downtrend condition
Returns: bool
CNTLibraryLibrary "CNTLibrary"
Custom Functions To Help Code In Pinescript V5
Coded By Christian Nataliano
First Coded In 10/06/2023
Last Edited In 22/06/2023
Huge Shout Out To © ZenAndTheArtOfTrading and his ZenLibrary V5, Some Of The Custom Functions Were Heavily Inspired By Matt's Work & His Pine Script Mastery Course
Another Shout Out To The TradingView's Team Library ta V5
//====================================================================================================================================================
// Custom Indicator Functions
//====================================================================================================================================================
GetKAMA(KAMA_lenght, Fast_KAMA, Slow_KAMA)
Calculates An Adaptive Moving Average Based On Perry J Kaufman's Calculations
Parameters:
KAMA_lenght (int) : Is The KAMA Lenght
Fast_KAMA (int) : Is The KAMA's Fastes Moving Average
Slow_KAMA (int) : Is The KAMA's Slowest Moving Average
Returns: Float Of The KAMA's Current Calculations
GetMovingAverage(Source, Lenght, Type)
Get Custom Moving Averages Values
Parameters:
Source (float) : Of The Moving Average, Defval = close
Lenght (simple int) : Of The Moving Average, Defval = 50
Type (string) : Of The Moving Average, Defval = Exponential Moving Average
Returns: The Moving Average Calculation Based On Its Given Source, Lenght & Calculation Type (Please Call Function On Global Scope)
GetDecimals()
Calculates how many decimals are on the quote price of the current market © ZenAndTheArtOfTrading
Returns: The current decimal places on the market quote price
Truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places © ZenAndTheArtOfTrading
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
ToWhole(number)
Converts pips into whole numbers © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
ToPips(number)
Converts whole numbers back into pips © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
GetPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period © ZenAndTheArtOfTrading
Parameters:
value1 (float)
value2 (float)
lookback (int)
BarsAboveMA(lookback, ma)
Counts how many candles are above the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
BarsBelowMA(lookback, ma)
Counts how many candles are below the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
BarsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
GetPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count) © ZenAndTheArtOfTrading
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
GetSwingHigh(Lookback, SwingType)
Check If Price Has Made A Recent Swing High
Parameters:
Lookback (int) : Is For The Swing High Lookback Period, Defval = 7
SwingType (int) : Is For The Swing High Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing High
GetSwingLow(Lookback, SwingType)
Check If Price Has Made A Recent Swing Low
Parameters:
Lookback (int) : Is For The Swing Low Lookback Period, Defval = 7
SwingType (int) : Is For The Swing Low Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing Low
//====================================================================================================================================================
// Custom Risk Management Functions
//====================================================================================================================================================
CalculateStopLossLevel(OrderType, Entry, StopLoss)
Calculate StopLoss Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLoss (float) : Is The Custom StopLoss Distance, Defval = 2x ATR Below Close
Returns: Float - The StopLoss Level In Actual Price As A
CalculateStopLossDistance(OrderType, Entry, StopLoss)
Calculate StopLoss Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
StopLoss (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The StopLoss Value In Pips
CalculateTakeProfitLevel(OrderType, Entry, StopLossDistance, RiskReward)
Calculate TakeProfit Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLossDistance (float)
RiskReward (float)
Returns: Float - The TakeProfit Level In Actual Price
CalculateTakeProfitDistance(OrderType, Entry, TakeProfit)
Get TakeProfit Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
TakeProfit (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The TakeProfit Value In Pips
CalculateConversionCurrency(AccountCurrency, SymbolCurrency, BaseCurrency)
Get The Conversion Currecny Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
AccountCurrency (simple string) : Is For The Account Currency Used
SymbolCurrency (simple string) : Is For The Current Symbol Currency (Front Symbol)
BaseCurrency (simple string) : Is For The Current Symbol Base Currency (Back Symbol)
Returns: Tuple Of A Bollean (Convert The Currency ?) And A String (Converted Currency)
CalculateConversionRate(ConvertCurrency, ConversionRate)
Get The Conversion Rate Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
ConvertCurrency (bool) : Is To Check If The Current Symbol Needs To Be Converted Or Not
ConversionRate (float) : Is The Quoted Price Of The Conversion Currency (Input The request.security Function Here)
Returns: Float Price Of Conversion Rate (If In The Same Currency Than Return Value Will Be 1.0)
LotSize(LotSizeSimple, Balance, Risk, SLDistance, ConversionRate)
Get Current Lot Size
Parameters:
LotSizeSimple (bool) : Is To Toggle Lot Sizing Calculation (Simple Is Good Enough For Stocks & Crypto, Whilst Complex Is For Forex)
Balance (float) : Is For The Current Account Balance To Calculate The Lot Sizing Based Off
Risk (float) : Is For The Current Risk Per Trade To Calculate The Lot Sizing Based Off
SLDistance (float) : Is The Current Position StopLoss Distance From Its Entry Price
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - Position Size In Units
ToLots(Units)
Converts Units To Lots
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots
ToUnits(Lots)
Converts Lots To Units
Parameters:
Lots (float) : Is For How Many Lots Need To Be Converted Into Units (Minimun 0.01 Units)
Returns: Int - Position Size In Units
ToLotsInUnits(Units)
Converts Units To Lots Than Back To Units
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots That Were Rounded To Units
ATRTrail(OrderType, SourceType, ATRPeriod, ATRMultiplyer, SwingLookback)
Calculate ATR Trailing Stop
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
SourceType (int) : Is To Determine Where To Calculate The ATR Trailing From, Defval = close
ATRPeriod (simple int) : Is To Change Its ATR Period, Defval = 20
ATRMultiplyer (float) : Is To Change Its ATR Trailing Distance, Defval = 1
SwingLookback (int) : Is To Change Its Swing HiLo Lookback (Only From Source Type 5), Defval = 7
Returns: Float - Number Of The Current ATR Trailing
DangerZone(WinRate, AvgRRR, Filter)
Calculate Danger Zone Of A Given Strategy
Parameters:
WinRate (float) : Is The Strategy WinRate
AvgRRR (float) : Is The Strategy Avg RRR
Filter (float) : Is The Minimum Profit It Needs To Be Out Of BE Zone, Defval = 3
Returns: Int - Value, 1 If Out Of Danger Zone, 0 If BE, -1 If In Danger Zone
IsQuestionableTrades(TradeTP, TradeSL)
Checks For Questionable Trades (Which Are Trades That Its TP & SL Level Got Hit At The Same Candle)
Parameters:
TradeTP (float) : Is The Trade In Question Take Profit Level
TradeSL (float) : Is The Trade In Question Stop Loss Level
Returns: Bool - True If The Last Trade Was A "Questionable Trade"
//====================================================================================================================================================
// Custom Strategy Functions
//====================================================================================================================================================
OpenLong(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Long Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Long"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Long Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
OpenShort(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Short Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Short"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Short Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
TP_SLExit(FromID, TPLevel, SLLevel, PercentageClose, Comment, CommentValue)
Exits Based On Predetermined TP & SL Levels
Parameters:
FromID (string) : Is The Trade ID That The TP & SL Levels Be Palced
TPLevel (float) : Is The Take Profit Level
SLLevel (float) : Is The StopLoss Level
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
CloseLong(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Long Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Long"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
CloseShort(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Short Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Short"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
BrokerCheck(Broker)
Checks Traded Broker With Current Loaded Chart Broker
Parameters:
Broker (string) : Is The Current Broker That Is Traded
Returns: Bool - True If Current Traded Broker Is Same As Loaded Chart Broker
OpenPC(LicenseID, OrderType, UseLimit, LimitPrice, SymbolPrefix, Symbol, SymbolSuffix, Risk, SL, TP, OrderComment, Spread)
Compiles Given Parameters Into An Alert String Format To Open Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Open
UseLimit (bool) : Is If We Want To Enter The Position At Exactly The Previous Closing Price
LimitPrice (float) : Is The Limit Price Of The Trade (Only For Pending Orders)
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Risk (float) : Is The Trade Risk Per Trade / Fixed Lot Sizing
SL (float) : Is The Trade SL In Price / In Pips
TP (float) : Is The Trade TP In Price / In Pips
OrderComment (string) : Is The Executed Trade Comment
Spread (float) : is The Maximum Spread For Execution
Returns: String - Pine Connector Order Syntax Alert Message
ClosePC(LicenseID, OrderType, SymbolPrefix, Symbol, SymbolSuffix)
Compiles Given Parameters Into An Alert String Format To Close Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Close
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Returns: String - Pine Connector Order Syntax Alert Message
//====================================================================================================================================================
// Custom Backtesting Calculation Functions
//====================================================================================================================================================
CalculatePNL(EntryPrice, ExitPrice, LotSize, ConversionRate)
Calculates Trade PNL Based On Entry, Eixt & Lot Size
Parameters:
EntryPrice (float) : Is The Trade Entry
ExitPrice (float) : Is The Trade Exit
LotSize (float) : Is The Trade Sizing
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - The Current Trade PNL
UpdateBalance(PrevBalance, PNL)
Updates The Previous Ginve Balance To The Next PNL
Parameters:
PrevBalance (float) : Is The Previous Balance To Be Updated
PNL (float) : Is The Current Trade PNL To Be Added
Returns: Float - The Current Updated PNL
CalculateSlpComm(PNL, MaxRate)
Calculates Random Slippage & Commisions Fees Based On The Parameters
Parameters:
PNL (float) : Is The Current Trade PNL
MaxRate (float) : Is The Upper Limit (In Percentage) Of The Randomized Fee
Returns: Float - A Percentage Fee Of The Current Trade PNL
UpdateDD(MaxBalance, Balance)
Calculates & Updates The DD Based On Its Given Parameters
Parameters:
MaxBalance (float) : Is The Maximum Balance Ever Recorded
Balance (float) : Is The Current Account Balance
Returns: Float - The Current Strategy DD
CalculateWR(TotalTrades, LongID, ShortID)
Calculate The Total, Long & Short Trades Win Rate
Parameters:
TotalTrades (int) : Are The Current Total Trades That The Strategy Has Taken
LongID (string) : Is The Order ID Of The Long Trades Of The Strategy
ShortID (string) : Is The Order ID Of The Short Trades Of The Strategy
Returns: Tuple Of Long WR%, Short WR%, Total WR%, Total Winning Trades, Total Losing Trades, Total Long Trades & Total Short Trades
CalculateAvgRRR(WinTrades, LossTrades)
Calculates The Overall Strategy Avg Risk Reward Ratio
Parameters:
WinTrades (int) : Are The Strategy Winning Trades
LossTrades (int) : Are The Strategy Losing Trades
Returns: Float - The Average RRR Values
CAGR(StartTime, StartPrice, EndTime, EndPrice)
Calculates The CAGR Over The Given Time Period © TradingView
Parameters:
StartTime (int) : Is The Starting Time Of The Calculation
StartPrice (float) : Is The Starting Price Of The Calculation
EndTime (int) : Is The Ending Time Of The Calculation
EndPrice (float) : Is The Ending Price Of The Calculation
Returns: Float - The CAGR Values
//====================================================================================================================================================
// Custom Plot Functions
//====================================================================================================================================================
EditLabels(LabelID, X1, Y1, Text, Color, TextColor, EditCondition, DeleteCondition)
Edit / Delete Labels
Parameters:
LabelID (label) : Is The ID Of The Selected Label
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
Text (string) : Is The Text Than Wants To Be Written In The Label
Color (color) : Is The Color Value Change Of The Label Text
TextColor (color)
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
EditLine(LineID, X1, Y1, X2, Y2, Color, EditCondition, DeleteCondition)
Edit / Delete Lines
Parameters:
LineID (line) : Is The ID Of The Selected Line
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
X2 (int) : Is The X2 Coordinate IN BARINDEX Xloc
Y2 (float) : Is The Y2 Coordinate IN PRICE Yloc
Color (color) : Is The Color Value Change Of The Line
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
//====================================================================================================================================================
// Custom Display Functions (Using Tables)
//====================================================================================================================================================
FillTable(TableID, Column, Row, Title, Value, BgColor, TextColor, ToolTip)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
Column (int) : Is The Current Column Of The Table That Wants To Be Edited
Row (int) : Is The Current Row Of The Table That Wants To Be Edited
Title (string) : Is The String Title Of The Current Cell Table
Value (string) : Is The String Value Of The Current Cell Table
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
ToolTip (string) : Is The ToolTip Of The Current Cell In The Table
Returns: Void
DisplayBTResults(TableID, BgColor, TextColor, StartingBalance, Balance, DollarReturn, TotalPips, MaxDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
StartingBalance (float) : Is The Account Starting Balance
Balance (float)
DollarReturn (float) : Is The Account Dollar Reture
TotalPips (float) : Is The Total Pips Gained / loss
MaxDD (float) : Is The Maximum Drawdown Over The Backtesting Period
Returns: Void
DisplayBTResultsV2(TableID, BgColor, TextColor, TotalWR, QTCount, LongWR, ShortWR, InitialCapital, CumProfit, CumFee, AvgRRR, MaxDD, CAGR, MeanDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
TotalWR (float) : Is The Strategy Total WR In %
QTCount (int) : Is The Strategy Questionable Trades Count
LongWR (float) : Is The Strategy Total WR In %
ShortWR (float) : Is The Strategy Total WR In %
InitialCapital (float) : Is The Strategy Initial Starting Capital
CumProfit (float) : Is The Strategy Ending Cumulative Profit
CumFee (float) : Is The Strategy Ending Cumulative Fee (Based On Randomized Fee Assumptions)
AvgRRR (float) : Is The Strategy Average Risk Reward Ratio
MaxDD (float) : Is The Strategy Maximum DrawDown In Its Backtesting Period
CAGR (float) : Is The Strategy Compounded Average GRowth In %
MeanDD (float) : Is The Strategy Mean / Average Drawdown In The Backtesting Period
Returns: Void
//====================================================================================================================================================
// Custom Pattern Detection Functions
//====================================================================================================================================================
BullFib(priceLow, priceHigh, fibRatio)
Calculates A Bullish Fibonacci Value (From Swing Low To High) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
BearFib(priceLow, priceHigh, fibRatio)
Calculates A Bearish Fibonacci Value (From Swing High To Low) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
GetBodySize()
Gets The Current Candle Body Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN POINTS
GetTopWickSize()
Gets The Current Candle Top Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Top Wick Size IN POINTS
GetBottomWickSize()
Gets The Current Candle Bottom Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Bottom Wick Size IN POINTS
GetBodyPercent()
Gets The Current Candle Body Size As A Percentage Of Its Entire Size Including Its Wicks © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN PERCENTAGE
GetTopWickPercent()
Gets The Current Top Wick Size As A Percentage Of Its Entire Body Size
Returns: Float - The Current Candle Top Wick Size IN PERCENTAGE
GetBottomWickPercent()
Gets The Current Bottom Wick Size As A Percentage Of Its Entire Bodu Size
Returns: Float - The Current Candle Bottom Size IN PERCENTAGE
BullishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Engulfing Candle
BearishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bearish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Engulfing Candle
Hammer(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Star(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Doji(MaxWickSize, MaxBodySize, DojiType, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Doji Candle
Parameters:
MaxWickSize (float) : To Specify The Maximum Lenght Of Its Upper & Lower Wick, Defval = 2
MaxBodySize (float) : To Specify The Maximum Lenght Of Its Candle Body IN PERCENT, Defval = 0.05
DojiType (int)
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Doji Candle
BullishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Harami Candle
BearishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Harami Candle
//====================================================================================================================================================
// Custom Time Functions
//====================================================================================================================================================
BarInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
BarOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
DateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range © ZenAndTheArtOfTrading
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
DayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze © ZenAndTheArtOfTrading
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
AUSSess()
Checks If The Current Australian Forex Session In Running
Returns: Bool - True If Currently The Australian Session Is Running
ASIASess()
Checks If The Current Asian Forex Session In Running
Returns: Bool - True If Currently The Asian Session Is Running
EURSess()
Checks If The Current European Forex Session In Running
Returns: Bool - True If Currently The European Session Is Running
USSess()
Checks If The Current US Forex Session In Running
Returns: Bool - True If Currently The US Session Is Running
UNIXToDate(Time, ConversionType, TimeZone)
Converts UNIX Time To Datetime
Parameters:
Time (int) : Is The UNIX Time Input
ConversionType (int) : Is The Datetime Output Format, Defval = DD-MM-YYYY
TimeZone (string) : Is To Convert The Outputed Datetime Into The Specified Time Zone, Defval = Exchange Time Zone
Returns: String - String Of Datetime
TASC 2022.08 Trading The Fear Index█ OVERVIEW
TASC's August 2022 edition of Traders' Tips includes an article by Markos Katsanos titled "Trading The Fear Index". This script implements a trading strategy called the “daily long/short trading system for volatility ETFs” presented in this article.
█ CONCEPTS
This long-term strategy aims to capitalize on stock market volatility by using exchange-traded funds (ETFs or ETNs) linked to the VIX index.
The strategy rules (see below) are based on a combination of the movement of the Cboe VIX index, the readings of the stochastic oscillator applied to the SPY ETF relative to the VIX, and a custom indicator presented in the article and called the correlation trend . Thus, they are not based on the price movement of the traded ETF itself, but rather on the movement of the VIX and of the S&P 500 index. This allows the strategy to capture most of the spikes in volatility while profiting from the long-term time decay of the traded ETFs.
█ STRATEGY RULES
Long rules
Rising volatility: The VIX should rise by more than 50% in the last 6 days.
Trend: The correlation trend of the VIX should be 0.8 or higher and also higher than yesterday's value.
VIX-SPY relative position: The 25-day and 10-day VIX stochastics should be above the 25-day and 10-day SPY stochastics respectively. In addition, the 10-day stochastic of the VIX should be above its yesterday's value.
Long positions are closed if the 10-day stochastic of the SPY rises above the 10-day stochastic of the VIX or falls below the yesterday's value.
Short rules
Declining volatility: The VIX should drop over 20% in the last 6 days and should be down during the last 3 days.
VIX threshold: The VIX should spend less than 35% of time below 15.
VIX-SPY relative position: The 10-day VIX stochastic should be below the 10-day SPY stochastic. In addition, the 10-day SPY stochastic should be higher than the yesterday's value.
Long positions are closed if the first two Long rules are triggered (Rising volatility and Trend).
The script allows you to display the readings of the indicators used in the strategy rules in the form of oscillator time series (as in the preview chart) and/or in the form of a table.
