RSI SMA Crossover StrategyOverview
RSI SMA Crossover Strategy works the same way as traditional MA crossover strategies, but using RSI instead of price. When RSI crosses over the SMA, a long position is opened (buy). When RSI crosses under the SMA, the long position is closed (sell).
This strategy can be very effective when the right inputs are used (see below). Be sure to use the backtesting tool to determine the optimal parameters for a given asset/timeframe.
Inputs/Parameters
RSI Length: length for RSI calculation (default = 50)
SMA Length: length for SMA calculation (default = 25)
Strategy Properties
Initial Capital = $1000
No default properties are defined for Slippage, Commission, etc, so be sure to set these values to get accurate backtesting results. This script is being published open-source for a reason - save yourself a copy and adjust the settings as you like!
Backtesting Results
Testing on Bitcoin (all time index) 1D chart, with all default parameters.
$1,000 initial investment on 10/07/2010 turns into almost $2.5 billion as of 08/30/2022 (compared to $334 million if the initial investment was held over the same period)
Remember, results can vary greatly based on the variables mentioned above, so always be sure to backtest.
In den Scripts nach "backtesting" suchen
Short Selling EMA Cross (By Coinrule)BINANCE:AVAXUSDT
This short selling script works best in periods of downtrends and general bearish market conditions, with the ultimate goal to sell as the the price decreases further and buy back before a rebound.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to to hodl this cash, or use it to reinvest when the market reaches attractive buying levels.
Entry
The exponential moving average ( EMA ) 20 and EMA 50 have been used for the variables determining the entry to the short. EMAs can operate better than simple moving averages due to the additional weighting placed on the most recent data points, whereas simple moving averages weight all the data the same. This means that price is tracked more closely and the most recent volatile moves can be captured and exploited more efficiently using EMAs.
Our backtesting data revealed that the most profitable timeframe was the 30-minute timeframe, this also enabled a good frequency of trades and high profitability.
A fast (shorter term) exponential moving average , in this strategy the EMA 20, crossing under a slow (longer term) moving average, in this example the EMA 50, signals the price of an asset has started to trend to the downside, as the most recent data signals price is declining compared to earlier data. The entry acts on this principle and executes when the EMA 20 crosses under the EMA 50.
Enter Short: EMA 20 crosses under EMA 50.
Exit
This script utilises a take profit and stop loss for the exit. The take profit is set at -8% and the stop loss is set at +16% from the entry price. This would normally be a poor trade due to the risk:reward equalling 0.5. However, when looking at the backtesting data, the high profitability of the strategy (93.33%) leads to increased confidence and showcases the high probability of success according to historical data.
The take profit (-8%) and the stop loss (+16%) of the strategy are widely placed to ensure the move is captured without being stopped out due to relief rallies. The stop loss also plays a role of mitigating losses and minimising risk of being stuck in a short position once there has been a fundamental trend reversal and the market has become bullish .
Exit Short: -8% price decrease from entry price.
OR
Exit Short: +16% price increase from entry price.
Tip: Research what coins have consistent and large token unlocks / highly inflationary tokenomics, and target these during bear markets to short as they will most likely have substantial selling pressure that outweighs demand - leading to declining prices.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
The backtesting data was recorded from December 1st 2021, just as the market was beginning its downtrend. We therefore recommend analysing the market conditions prior to utilising this strategy as it operates best on weak coins during downtrends and bearish conditions.
Last Available Bar InfoLibrary "Last_Available_Bar_Info"
getLastBarTimeStamp()
getAvailableBars()
This simple library is built with an aim of getting the last available bar information for the chart. This returns a constant value that doesn't change on bar change.
For backtesting with accurate results on non standard charts, it will be helpful. (Especially if you are using non standard charts like Renko Chart).
Methods
getLastBarTimeStamp()
: Returns Timestamp of the last available bar (Constant)
getAvailableBars()
:Returns Number of Available Bars on the chart (Constant)
Example
import paragjyoti2012/Last_Available_Bar_Info/v1 as LastBarInfo
last_bar_timestamp=LastBarInfo.getLastBarTimeStamp()
no_of_bars=LastBarInfo.getAvailableBars()
If you are using Renko Charts, for backtesting, it's necesary to filter out the historical bars that are not of this timeframe.
In Renko charts, once the available bars of the current timeframe (based on your Tradingview active plan) are exhausted,
previous bars are filled in with historical bars of higher timeframe. Which is detrimental for backtesting, and it leads to unrealistic results.
To get the actual number of bars available of that timeframe, you should use this security function to get the timestamp for the last (real) bar available.
tf=timeframe.period
real_available_bars = request.security(syminfo.ticker, tf , LastBarInfo.getAvailableBars() , lookahead = barmerge.lookahead_off)
last_available_bar_timestamp = request.security(syminfo.ticker, tf , LastBarInfo.getLastBarTimeStamp() , lookahead = barmerge.lookahead_off)
Financial Astrology Crypto ML Daily TrendThis daily trend indicator is based on financial astrology cycles detected with advanced machine learning techniques for the crypto-currencies research portfolio: ADA, BAT, BNB, BTC, DASH, EOS, ETC, ETH, LINK, LTC, XLM, XMR, XRP, ZEC and ZRX. The daily price trend is forecasted through this planets cycles (angular aspects, speed, declination), fast ones are based on Moon, Mercury, Venus and Sun and Mid term cycles are based on Mars, Vesta and Ceres. The combination of all this cycles produce a daily price trend prediction that is encoded into a PineScript array using binary format "0 or 1" that represent sell and buy signals respectively. The indicator provides signals since 2021-01-01 to 2022-12-31, the past months signals purpose is to support backtesting of the indicator combined with other technical indicator entries like MAs, RSI or Stochastic. For future predictions besides 2022 a machine learning models re-train phase will be required.
The resolution of this indicator is 1D, you can tune a parameter where you can determine how many future bars of daily trend are plotted and adjust an hours shift to anticipate future signals into current bar in order to produce a leading indicator effect to anticipate the trend changes with some hours of anticipation. Combined with technical analysis indicators this daily trend is very powerful because can help to produce approximately 60% of profitable signals based on the backtesting results. You can look at our open source Github repositories to validate accuracy using the backtesting strategies we have implemented in Jesse Crypto Trading Framework as proof of concept of the predictive potential of this indicator. Alternatively, we have implemented a PineScript strategy that use this indicator, just consider that we are pending to do signals update to the period July 2021 to December 2022: This strategy have accumulated more than 110 likes and many traders have validated the predictive power of Financial Astrology.
DISCLAIMER: This indicator is experimental and don’t provide financial or investment advice, the main purpose is to demonstrate the predictive power of financial astrology. Any allocation of funds following the documented machine learning model prediction is a high-risk endeavour and it’s the users responsibility to practice healthy risk management according to your situation.
[laoowai]BNB_USDT_3m_3Commas_Bollinger_MACD_RSI_StrategyBNB_USDT _3m
Release Notes:
Time: 3min
Pair: BNB_USDT
Use: {{strategy.order.alert_message}}
What's the difference with 3Commas Bollinger Strategy by tedwardd:
1. Initial capital: 1210 USDT (10$ Base order / 400$*3 Safety order), if you will change, please change JUST safety order volume or number of safety orders 2-3
2. Using just 2(3) safety order (original script 4)
3. More high-performance strategy for BNB_USDT
4. Using MACD to sell order (original script take profit by scale), thanks Drun30 .
5. Using RSI to analyze the market conditions.
Need to change:
bot_id = input(title="3Commas Bot ID", defval=" YOUR DATA ")
email_token = input(title="Bot Email Token", defval=" YOUR DATA ")
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FAQ copy from tedwardd
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This strategy is intended for use as a way of backtesting various parameters available on 3commas.
The primary inputs for the strategy are:
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// USER INPUTS
Short MA Window - The length of the Short moving average
Long MA Window - The length of the Long moving average
Upper Band Offset - The offset to use for the upper bollinger offset
Lower Band Offset - The offset to use for the lower bollinger offset
Long Stop Loss % - The stop loss percentage to test
Long Take Profit % - The Take profit percentage to test
Initial SO Deviation % - The price deviation percentage required to place to first safety order
Safety Order Vol Step % - The volume scale to test
3Commas Bot ID - (self-explanatory)
Bot Email Token - Found in the deal start message for your bot (see link in the previous section for details)
3Commas Bot Trading Pair - The pair to include for composite bot start deals (should match the format of 3commas, not TradingView IE. USDT_BTC not BTCUSDT )
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Start Date, Month, Year and End Date, Month, and Year all apply to the backtesting window. By default, it will use as much data as it can give the current period select (there is less historical data available for periods below 1H) back as far as 2016 (there appears to be no historical data on Trading view much before this). If you would like to test a different period of time, just change these values accordingly.
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Composite bot using a Bollinger band type trading strategy. While its primary intention is to provide users a way of backtesting bot parameters, it can also be used to trigger a deal start by either using the {{strategy.order.alert_message}} field in your alert and providing the bot details in the configuration screen for the strategy or by including the usual deal start message provided by 3commas.
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Original script:
1. 3Commas Bollinger Strategy by tedwardd
2. Momentum Strategy ( BTC /USDT; 1h) - MACD (with source code) by Drun30
3Commas Bollinger StrategyThis strategy is intended for use as a way of backtesting various parameters available on 3commas.io composite bot using a bollinger band type trading strategy. While it's primary intention is to provide users a way of backtesting bot parameters, it can also be used to trigger a deal start by either using the {{strategy.open.alert_message}} field in your alert and providing the bot details in the configuration screen for the strategy or by including the usual deal start message provided by 3commas. You can find more information about how to do this from help.3commas.io
The primary inputs for the strategy are:
// USER INPUTS
Short MA Window - The length of the Short moving average
Long MA Window - The length of the Long moving average
Upper Band Offset - The offset to use for the upper bollinger offset
Lower Band Offset - The offset to use for the lower bollinger offset
Long Stop Loss % - The stop loss percentage to test
Long Take Profit % - The Take profit percentage to test
Initial SO Deviation % - The price deviation percentage required to place to first safety order
Safety Order Vol Step % - The volume scale to test
3Commas Bot ID - (self explanatory)
Bot Email Token - Found in the deal start message for your bot (see link in previous section for details)
3Commas Bot Trading Pair - The pair to include for composite bot start deals (should match format of 3commas, not TradingView IE. USDT_BTC not BTCUSDT)
Start Date, Month, Year and End Date, Month and Year all apply to the backtesting window. By default it will use as much data as it can given the current period select (there is less historical data available for periods below 1H) back as far as 2016 (there appears to be no historical data on Trading view much before this). If you would like to test a different period of time, just change these values accordingly.
Known Issues
Currently there are a couple of issues with this strategy that you should be aware of. I may fix them at some point in the future but they don't really bug me so this is more for informational purposes than a promise that they may one day be fixed.
Does not test trailing take profit
Number of safety orders and Safety Order Step Scale are currently not user configurable (must edit source code)
Using the user configuration to generate deal start message assumes you are triggering a composite bot, not a simple bot.
Efficient Work [LucF]█ OVERVIEW
Efficient Work measures the ratio of price movement from close to close ( resulting work ) over the distance traveled to the high and low before settling down at the close ( total work ). The closer the two values are, the more Efficient Work approaches its maximum value of +1 for an up move or -1 for a down move. When price does not change, Efficient Work is zero.
Higher values of Efficient Work indicate more efficient price travel between the close of two successive bars, which I interpret to be more significant, regardless of the move's amplitude. Because it measures the direction and strength of price changes rather than their amplitude, Efficient Work may be thought of as a sentiment indicator.
█ CONCEPTS
This oscillator's design stems from a few key concepts.
Relative Levels
Other than the centerline, relative rather than absolute levels are used to identify levels of interest. Accordingly, no fixed levels correspond to overbought/oversold conditions. Relative levels of interest are identified using:
• A Donchian channel (historical highs/lows).
• The oscillator's position relative to higher timeframe values.
• Oscillator levels following points in time where a divergence is identified.
Higher timeframes
Two progressively higher timeframes are used to calculate larger-context values for the oscillator. The rationale underlying the use of timeframes higher than the chart's is that, while they change less frequently than the values calculated at the chart's resolution, they are more meaningful because more work (trader activity) is required to calculate them. Combining the immediacy of values calculated at the chart's resolution to higher timeframe values achieves a compromise between responsiveness and reliability.
Divergences as points of interest rather than directional clues
A very simple interpretation of what constitutes a divergence is used. A divergence is defined as a discrepancy between any bar's direction and the direction of the signal line on that same bar. No attempt is made to attribute a directional bias to divergences when they occur. Instead, the oscillator's level is saved and subsequent movement of the oscillator relative to the saved level is what determines the bullish/bearish state of the oscillator.
Conservative coloring scheme
Several additive coloring conditions allow the bull/bear coloring of the oscillator's main line to be restricted to specific areas meeting all the selected conditions. The concept is built on the premise that most of the time, an oscillator's value should be viewed as mere noise, and that somewhat like price, it only occasionally conveys actionable information.
█ FEATURES
Plots
• Three lines can be plotted. They are named Main line , Line 2 and Line 3 . You decide which calculation to use for each line:
• The oscillator's value at the chart's resolution.
• The oscillator's value at a medium timeframe higher than the chart's resolution.
• The oscillator's value at the highest timeframe.
• An aggregate line calculated using a weighed average of the three previous lines (see the Aggregate Weights section of Inputs to configure the weights).
• The coloring conditions, divergence levels and the Hi/Lo channel always apply to the Main line, whichever calculation you decide to use for it.
• The color of lines 2 and 3 are fixed but can be set in the "Colors" section of Inputs.
• You can change the thickness of each line.
• When the aggregate line is displayed, higher timeframe values are only used in its calculation when they become available in the chart's history,
otherwise the aggregate line would appear much later on the chart. To indicate when each higher timeframe value becomes available,
a small label appears near the centerline.
• Divergences can be shown as small dots on the centerline.
• Divergence levels can be shown. The level and fill are determined by the oscillator's position relative to the last saved divergence level.
• Bull/bear markers can be displayed. They occur whenever a new bull/bear state is determined by the "Main Line Coloring Conditions".
• The Hi/Lo (Donchian) channel can be displayed, and its period defined.
• The background can display the state of any one of 11 different conditions.
• The resolutions used for the higher timeframes can be displayed to the right of the last bar's value.
• Four key values are always displayed in the Data Window (fourth icon down to the right of your chart):
oscillator values for the chart, medium and highest timeframes, and the oscillator's instant value before it is averaged.
Main Line Coloring Conditions
• Nine different conditions can be selected to determine the bull/bear coloring of the main line. All conditions set to "ON" must be met to determine the bull/bear state.
• A volatility state can also be used to filter the conditions.
• When the coloring conditions and the filter do not allow for a bull/bear state to be determined, the neutral color is used.
Signal
• Seven different averages can be used to calculate the average of the oscillator's value.
• The average's period can be set. A period of one will show the instant value of the oscillator,
provided you don't use linear regression or the Hull MA as they do not work with a period of one.
• An external signal can be used as the oscillator's instant value. If an already averaged external value is used, set the period to one in this indicator.
• For the cases where an external signal is used, a centerline value can be set.
Higher Timeframes
• The two higher timeframes are named Medium timeframe and Highest timeframe . They can be determined using one of three methods:
• Auto-steps: the higher timeframes are determined using the chart's resolution. If the chart uses a seconds resolution, for example,
the medium and highest resolutions will be 15 and 60 minutes.
• Multiples: the timeframes are calculated using a multiple of the chart's resolution, which you can set.
• Fixed: the set timeframes do not change with the chart's resolution.
Repainting
• Repainting can be controlled separately for the chart's value and the higher timeframe values.
• The default is a repainting chart value and non-repainting higher timeframe values. The Aggregate line will thus repaint by default,
as it uses the chart's value along with the higher timeframes values.
Aggregate Weights
• The weight of each component of the Aggregate line can be set.
• The default is equal weights for the three components, meaning that the chart's value accounts for one third of the weight in the Aggregate.
High Volatility
• This provides control over the volatility filter used in the Main line's coloring conditions and the background display.
• Volatility is determined to be high when the short-term ATR is greater than the long-term ATR.
Colors
• You can define your own colors for all of the oscillator's plots.
• The default colors will perform well on both white and black chart backgrounds.
Alerts
• An alert can be defined for the script. The alert will trigger whenever a bull/bear marker appears in the indicator's display.
The particular combination of coloring conditions and the display of bull/bear markers when you create the alert will thus determine when the alert triggers.
Once the alerts are created, subsequent changes to the conditions controlling the display of markers will not affect the existing alert(s).
• You can create multiple alerts from this script, each triggering on different conditions.
Backtesting & Trading Engine Signal Line
• An invisible plot named "BTE Signal" is provided. It can be used as an entry signal when connected to the PineCoders Backtesting & Trading Engine as an external input.
It will generate an entry whenever a marker is displayed.
█ NOTES
• I do not know for sure if the calculations in Efficient Work are original. I apologize if they are not.
• Because this version of Efficient Work only has access to OHLC information, it cannot measure the total distance traveled through all of a bar's ticks, but the indicator nonetheless behaves in a manner consistent with the intentions underlying its design.
For Pine coders
This code was written using the following standards:
• The PineCoders Coding Conventions for Pine .
• A modified version of the PineCoders MTF Oscillator Framework and MTF Selection Framework .
MTF Oscillator Framework [PineCoders]This framework allows Pine coders to quickly build a complete multi-timeframe oscillator from any calculation producing values around a centerline, whether the values are bounded or not. Insert your calculation in the script and you have a ready-to-publish MTF Oscillator offering a plethora of presentation options and features.
█ HOW TO USE THE FRAMEWORK
1 — Insert your calculation in the `f_signal()` function at the top of the "Helper Functions" section of the script.
2 — Change the script's name in the `study()` declaration statement and the `alertcondition()` text in the last part of the "Plots" section.
3 — Adapt the default value used to initialize the CENTERLINE constant in the script's "Constants" section.
4 — If you want to publish the script, copy/paste the following description in your new publication's description and replace the "OVERVIEW" section with a description of your calculations.
5 — Voilà!
═════════════════════════════════════════════════════════════════════════
█ OVERVIEW
This oscillator calculates a directional value of True Range. When a bar is up, the positive value of True Range is used. A negative value is used when the bar is down. When there is no movement during the bar, a zero value is generated, even if True Range is different than zero. Because the unit of measure of True Range is price, the oscillator is unbounded (it does not have fixed upper/lower bounds).
True Range can be used as a metric for volatility, but by using a signed value, this oscillator will show the directional bias of progressively increasing/decreasing volatility, which can make it more useful than an always positive value of True Range.
The True Range calculation appeared for the first time in J. Welles Wilder's New Concepts in Technical Trading Systems book published in 1978. Wilder's objective was to provide a reliable measure of the effective movement—or range—between two bars, to measure volatility. True Range is also the building block used to calculate ATR (Average True Range), which calculates the average of True Range values over a given period using the `rma` averaging method—the same used in the calculation of another of Wilder's remarkable creations: RSI.
█ CONCEPTS
This oscillator's design stems from a few key concepts.
Relative Levels
Other than the centerline, relative rather than absolute levels are used to identify levels of interest. Accordingly, no fixed levels correspond to overbought/oversold conditions. Relative levels of interest are identified using:
• A Donchian channel (historical highs/lows).
• The oscillator's position relative to higher timeframe values.
• Oscillator levels following points in time where a divergence is identified.
Higher timeframes
Two progressively higher timeframes are used to calculate larger-context values for the oscillator. The rationale underlying the use of timeframes higher than the chart's is that, while they change less frequently than the values calculated at the chart's resolution, they are more meaningful because more work (trader activity) is required to calculate them. Combining the immediacy of values calculated at the chart's resolution to higher timeframe values achieves a compromise between responsiveness and reliability.
Divergences as points of interest rather than directional clues
A very simple interpretation of what constitutes a divergence is used. A divergence is defined as a discrepancy between any bar's direction and the direction of the signal line on that same bar. No attempt is made to attribute a directional bias to divergences when they occur. Instead, the oscillator's level is saved and subsequent movement of the oscillator relative to the saved level is what determines the bullish/bearish state of the oscillator.
Conservative coloring scheme
Several additive coloring conditions allow the bull/bear coloring of the oscillator's main line to be restricted to specific areas meeting all the selected conditions. The concept is built on the premise that most of the time, an oscillator's value should be viewed as mere noise, and that somewhat like price, it only occasionally conveys actionable information.
█ FEATURES
Plots
• Three lines can be plotted. They are named Main line , Line 2 and Line 3 . You decide which calculation to use for each line:
• The oscillator's value at the chart's resolution.
• The oscillator's value at a medium timeframe higher than the chart's resolution.
• The oscillator's value at the highest timeframe.
• An aggregate line calculated using a weighed average of the three previous lines (see the Aggregate Weights section of Inputs to configure the weights).
• The coloring conditions, divergence levels and the Hi/Lo channel always apply to the Main line, whichever calculation you decide to use for it.
• The color of lines 2 and 3 are fixed but can be set in the "Colors" section of Inputs.
• You can change the thickness of each line.
• When the aggregate line is displayed, higher timeframe values are only used in its calculation when they become available in the chart's history,
otherwise the aggregate line would appear much later on the chart. To indicate when each higher timeframe value becomes available,
a small label appears near the centerline.
• Divergences can be shown as small dots on the centerline.
• Divergence levels can be shown. The level and fill are determined by the oscillator's position relative to the last saved divergence level.
• Bull/bear markers can be displayed. They occur whenever a new bull/bear state is determined by the "Main Line Coloring Conditions".
• The Hi/Lo (Donchian) channel can be displayed, and its period defined.
• The background can display the state of any one of 11 different conditions.
• The resolutions used for the higher timeframes can be displayed to the right of the last bar's value.
• Four key values are always displayed in the Data Window (fourth icon down to the right of your chart):
oscillator values for the chart, medium and highest timeframes, and the oscillator's instant value before it is averaged.
Main Line Coloring Conditions
• Nine different conditions can be selected to determine the bull/bear coloring of the main line. All conditions set to "ON" must be met to determine the bull/bear state.
• A volatility state can also be used to filter the conditions.
• When the coloring conditions and the filter do not allow for a bull/bear state to be determined, the neutral color is used.
Signal
• Seven different averages can be used to calculate the average of the oscillator's value.
• The average's period can be set. A period of one will show the instant value of the oscillator,
provided you don't use linear regression or the Hull MA as they do not work with a period of one.
• An external signal can be used as the oscillator's instant value. If an already averaged external value is used, set the period to one in this indicator.
• For the cases where an external signal is used, a centerline value can be set.
Higher Timeframes
• The two higher timeframes are named Medium timeframe and Highest timeframe . They can be determined using one of three methods:
• Auto-steps: the higher timeframes are determined using the chart's resolution. If the chart uses a seconds resolution, for example,
the medium and highest resolutions will be 15 and 60 minutes.
• Multiples: the timeframes are calculated using a multiple of the chart's resolution, which you can set.
• Fixed: the set timeframes do not change with the chart's resolution.
Repainting
• Repainting can be controlled separately for the chart's value and the higher timeframe values.
• The default is a repainting chart value and non-repainting higher timeframe values. The Aggregate line will thus repaint by default,
as it uses the chart's value along with the higher timeframes values.
Aggregate Weights
• The weight of each component of the Aggregate line can be set.
• The default is equal weights for the three components, meaning that the chart's value accounts for one third of the weight in the Aggregate.
High Volatility
• This provides control over the volatility filter used in the Main line's coloring conditions and the background display.
• Volatility is determined to be high when the short-term ATR is greater than the long-term ATR.
Colors
• You can define your own colors for all of the oscillator's plots.
• The default colors will perform well on both white and black chart backgrounds.
Alerts
• An alert can be defined for the script. The alert will trigger whenever a bull/bear marker appears in the indicator's display.
The particular combination of coloring conditions and the display of bull/bear markers when you create the alert will thus determine when the alert triggers.
Once the alerts are created, subsequent changes to the conditions controlling the display of markers will not affect the existing alert(s).
• You can create multiple alerts from this script, each triggering on different conditions.
Backtesting & Trading Engine Signal Line
• An invisible plot named "BTE Signal" is provided. It can be used as an entry signal when connected to the PineCoders Backtesting & Trading Engine as an external input.
It will generate an entry whenever a marker is displayed.
Look first. Then leap.
Super-AO with Risk Management Alerts Template - 11-29-25Super-AO with Risk Management: ALERTS & AUTOMATION Edition
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
This is the Indicator / Alerts companion to the Super-AO Strategy.
While the Strategy version is built for backtesting (verifying profitability and checking historical performance), this Indicator version is built for Live Execution.
We understand the frustration of finding a great strategy, only to realize you can't easily hook it up to your trading bot. This script solves that. It contains the exact same "Super-AO" logic and "Risk Management Engine" as the strategy version, but it is optimized to send signals to automation platforms like Signal Lynx, 3Commas, or any Webhook listener.
2. Quick Action Guide (TL;DR)
Purpose: Live Signal Generation & Automation.
Workflow:
Use the Strategy Version to find profitable settings.
Copy those settings into this Indicator Version.
Set a TradingView Alert using the "Any Alert() function call" condition.
Best Timeframe: 4 Hours (H4) and above.
Compatibility: Works with any webhook-based automation service.
3. Why Two Scripts?
Pine Script operates in two distinct modes:
Strategy Mode: Calculates equity, drawdowns, and simulates orders. Great for research, but sometimes complex to automate.
Indicator Mode: Plots visual data on the chart. This is the preferred method for setting up robust alerts because it is lighter weight and plots specific values that automation services can read easily.
The Golden Rule: Always backtest on the Strategy, but trade on the Indicator. This ensures that what you see in your history matches what you execute in real-time.
4. How to Automate This Script
This script uses a "Visual Spike" method to trigger alerts. Instead of drawing equity curves, it plots numerical values at the bottom of your chart when a trade event occurs.
The Signal Map:
Blue Spike (2 / -2): Entry Signal (Long / Short).
Yellow Spike (1 / -1): Risk Management Close (Stop Loss / Trend Reversal).
Green Spikes (1, 2, 3): Take Profit Levels 1, 2, and 3.
Setup Instructions:
Add this indicator to your chart.
Open your TradingView "Alerts" tab.
Create a new Alert.
Condition: Select SAO - RM Alerts Template.
Trigger: Select Any Alert() function call.
Message: Paste your JSON webhook message (provided by your bot service).
5. The Logic Under the Hood
Just like the Strategy version, this indicator utilizes:
SuperTrend + Awesome Oscillator: High-probability swing trading logic.
Non-Repainting Engine: Calculates signals based on confirmed candle closes to ensure the alert you get matches the chart reality.
Advanced Adaptive Trailing Stop (AATS): Internally calculates volatility to determine when to send a "Close" signal.
6. About Signal Lynx
Automation for the Night-Shift Nation 🌙
We are providing this code open source to help traders bridge the gap between manual backtesting and live automation. This code has been in action since 2022.
If you are looking to automate your strategies, please take a look at Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
Daily % Change TableDaily % Change Table — Indicator Summary
This indicator provides a compact performance summary for daily candles, designed for backtesting and daily-session analysis. It displays a table in the top-right corner of the chart showing three key percentage-change statistics based on the current candle:
1. Prior Change
Percentage move from the close two days ago to the prior day’s close.
Useful for understanding momentum and context heading into the current session.
2. Change
Percentage move from the prior day's close to the current candle’s close.
Shows today’s full-session change.
3. Premarket
Percentage move from the prior day's close to the current day’s open.
Helps quantify overnight sentiment and gap activity.
Features
Clean, unobtrusive table display
Automatically updates on the most recent bar
Designed for use on Daily timeframe
Useful for gap analysis, backtesting, and volatility/momentum studies
LETHINH-Swing pa,smc🟦 📌 Title (English)
Swing High / Swing Low – 3-Candle Fractal (5-Bar Pivot) | Auto Alerts
⸻
🟩 📌 Short Description
A clean and reliable swing high / swing low detector based on the classic 3-candle (5-bar) fractal pivot. Automatically marks SH/SL and triggers alerts when a swing is confirmed. No repainting after confirmation.
⸻
🟧 📌 Full Description (for TradingView Publishing)
🔶 Swing High / Swing Low – 3-Candle Fractal (5-Bar Pivot)
This indicator identifies Swing Highs (SH) and Swing Lows (SL) using the classic 3-candle fractal pattern, also known as the 5-bar pivot.
It marks swing points only after full confirmation, making it highly reliable and suitable for structure-based trading.
⸻
🔶 📍 How It Works
A swing is confirmed when the center candle is higher (or lower) than the two candles on each side:
Swing High (SH)
high > high , high , high
Swing Low (SL)
low < low , low , low
The confirmation occurs after 2 right candles close, so the indicator does not repaint once a swing is identified.
⸻
🔶 📍 Key Features
• Detects clean and accurate swings
• Uses pure price action — no indicators, no lag
• Marks swing high (SH) and swing low (SL) directly on the chart
• Non-repainting after confirmation
• Works on all timeframes and all markets
• Extremely lightweight and fast
• Includes alert conditions for both SH and SL
Perfect for traders using:
• Market Structure (BOS / CHoCH)
• Order Blocks (OB)
• Smart Money Concepts (SMC)
• Liquidity hunts
• Wyckoff
• Support/Resistance
• Price Action entries
⸻
🔶 📍 Why This Indicator Is Useful
Swing points are the foundation of market structure.
Accurately detecting them helps traders:
• Identify trend shifts
• Spot BOS / CHoCH correctly
• Find key zones (OB, liquidity levels, supply/demand)
• Time entries more precisely
• Avoid fake structure breaks
This indicator ensures swings are plotted only when fully confirmed, reducing noise and confusion.
⸻
🔶 📍 Alerts
You can create alerts for both conditions:
• Swing High Confirmed
• Swing Low Confirmed
Recommended settings:
• Once per bar close
• Open-ended alert
With alerts enabled, TradingView will automatically notify you every time a new swing forms.
⸻
🔶 📍 No Repainting
Once a swing is confirmed and plotted, it will not change or disappear.
This makes the indicator reliable for real-time alerts and backtesting.
⸻
🔶 📍 Pine Script (v5)
Paste your indicator code here if you want it visible.
Or leave the code hidden if you are publishing as protected.
⸻
🔶 📍 Final Notes
• This indicator focuses on confirmation, not prediction
• It is designed for clean structure reading
• All markets supported: Forex, Crypto, Stocks, Indexes, Commodities
• Suitable for scalping, intraday, swing, and even higher-timeframe trading
If you find this tool helpful, feel free to give it a like and add it to your favorites ❤️
Your support helps me share more tools with the community!
able MACD Overview
Purpose: The indicator combines the traditional MACD (Moving Average Convergence Divergence) with a short-term “forecast” (projection) of MACD/histogram values to give early warning of momentum changes.
Typical outputs:
MACD line (fastEMA − slowEMA)
Signal line (EMA of MACD)
Histogram (MACD − signal)
Forecasted MACD or histogram projected N bars ahead
Optional buy/sell markers and alert conditions
Add the indicator to TradingView (Installation)
Open TradingView and the chart you want to apply the indicator to.
Click “Pine Editor” at the bottom of the chart.
Copy the contents of able_macd_forecast.pine into the Pine Editor window.
Click “Add to chart” (or Save then Add to chart). If it’s a study, it will appear on the chart below price.
If you plan to re-use the script, click Save and give it a meaningful name.
Inputs / Parameters (typical) Note: exact input names may differ in your script. Replace the names below with the script’s input labels when you inspect it.
Source: price source for calculations (close, hl2, etc.).
Fast Length: length for the fast EMA (commonly 12).
Slow Length: length for the slow EMA (commonly 26).
Signal Length: length for the MACD signal EMA (commonly 9).
Forecast Length / Horizon: how many bars ahead the script projects the MACD/histogram (e.g., 1–5).
Forecast Method / Smoothing: choice of projection method (linear regression, EMA extrapolation, simple slope * N, etc.) if available.
Histogram Thresholds: numeric thresholds to emphasize significant momentum (optional).
Show Forecast: toggle on/off the forecast plot.
Alerts On/Off toggles: enable or disable alert conditions baked into the indicator.
Visual / Style settings: colors, plot thickness, histogram style (columns/areas), show labels, show buy/sell arrows.
How the indicator is typically calculated (summary)
MACD line = EMA(source, fast) − EMA(source, slow)
Signal line = EMA(MACD line, signal length)
Histogram = MACD − Signal
Forecast = method-specific short-term projection of MACD or histogram (for example: extend the last slope forward, apply linear regression to MACD values and extrapolate N bars, or apply an additional smoothing and extend that value) Note: For exact math, I need to inspect the script; this is the typical approach.
How to read the indicator (signals & interpretation)
Bullish signal:
MACD line crossing above the signal line (MACD cross up).
Histogram turns positive (cross above zero).
Forecast shows MACD/histogram moving higher in the next N bars (if forecast is positive or trending up).
Bearish signal:
MACD line crossing below the signal line (MACD cross down).
Histogram turns negative (cross below zero).
Forecast shows MACD/histogram moving lower ahead.
Confirmations:
Use price action (higher highs/lows for bullish, lower highs/lows for bearish).
Volume or other momentum/confluence indicators (RSI, ADX).
Divergences:
Bullish divergence: price makes lower low while MACD histogram makes higher low.
Bearish divergence: price makes higher high while MACD histogram makes lower high.
Forecast behavior:
If the forecast leads the MACD cross (forecast crosses before the current MACD does), it’s an early warning.
Use caution: forecasts are prone to false signals; always confirm.
Common trading setups using this indicator
Conservative:
Wait for MACD to cross signal + histogram above zero + forecast already trending same direction.
Use stop below recent swing low (for long) or above recent swing high (for short).
Aggressive (early entry):
Enter when forecast turns positive while MACD still below signal (anticipating cross).
Use tighter stops and smaller position sizes.
Exit rules:
Opposite MACD cross, histogram flipping sign, or a target based on risk-reward.
Use trailing stop based on ATR or structure.
Example settings for different timeframes (starting points)
Scalping / 5–15 min:
Fast 8, Slow 21, Signal 5, Forecast 1–2
Intraday / 1H:
Fast 12, Slow 26, Signal 9, Forecast 2–3
Swing / 4H–Daily:
Fast 12, Slow 26, Signal 9, Forecast 3–5 Adjust based on the asset volatility and backtests.
Adding alerts (TradingView)
Click the “Alerts” button (clock icon) or press Alt + A.
In the Condition dropdown, select the indicator name (able_macd_forecast) and choose a plotted series or built-in alert condition (if the script uses alertcondition).
Common alert types:
MACD crosses Signal (Crossing)
Histogram crosses 0 (Crossing)
Forecast crosses 0 or Forecast trend change (if provided)
Message templates:
“{{ticker}}: MACD crossed above signal on {{interval}}”
“{{ticker}} Forecast positive: MACD forecast shows upward momentum”
Customize the message for your trade automation or notifications.
Configure frequency (Only once, Once per bar, or Once per bar close) — for signals like crossovers, “Once per bar close” is usually safer to avoid repainting issues. Note: If the script includes alertcondition() calls with explicit IDs/messages, use those directly — they are the most reliable for automation.
Backtesting / Strategy conversion
If this script is a study (indicator), you can:
Convert it to a strategy by adding strategy.* order calls (strategy.entry, strategy.close) using the entry/exit logic you prefer, or
Use TradingView’s “Bar Replay” to manually test signals across different markets/timeframes.
If you want, I can help convert or write a strategy wrapper that uses the indicator’s signals to place backtest trades (I’ll need the code).
Practical tips & best practices
Use higher timeframe confirmation for lower-timeframe entries (e.g., check daily MACD momentum before trading 15m signals).
Beware of choppy markets; MACD / forecast may produce whipsaws. Combine with trend filters (moving average direction, ADX).
If you rely on forecasted values, prefer alerts “on bar close” when possible to reduce false alerts from intra-bar noise.
Tune parameters for the specific asset (FX, crypto, stocks have different behavior).
Record each signal and outcome for a sample period (20–100 trades) to evaluate performance.
Troubleshooting
Indicator won’t add: verify Pine version in script header (//@version=4 or //@version=5). TradingView may reject scripts with unsupported version syntax.
Plots missing: check script inputs (Some scripts hide plots if toggles are off).
Alerts firing too often: change alert frequency to “Once per bar close” or adjust threshold values.
Forecast seems to repaint: some forecast methods can repaint (use “bar_index” or store values only on closed bars, or use non-repainting forecast methods). Ask me to inspect the script for repainting logic.
What I can do next (recommended)
If you paste the content of able_macd_forecast.pine here, I will:
Produce a precise, line-by-line usage guide mapping to the exact input names and default values.
Show the exact plotted series names and how to reference them for alerts.
Point out any repainting risks and suggest fixes.
Provide example alert messages that match the script’s alertcondition IDs (if any).
Optionally convert it into a strategy for backtesting, or add non-repainting forecast logic if needed.
Complete Harmonic PatternOverview:
The ultimate harmonic XABCD pattern identification, prediction, and backtesting system.
Harmonic patterns are among the most accurate of trading signals, yet they're widely underutilized because they can be difficult to spot and tedious to validate. If you've ever come across a pattern and struggled with questions like "are these retracement ratios close enough to the harmonic ratios?" or "what are the Potential Reversal levels and are they confluent with point D?", then this tool is your new best friend. Or, if you've never traded harmonic patterns before, maybe it's time to start. Put away your drawing tools and calculators, relax, and let this indicator do the heavy lifting for you.
- Identification -
An exhaustive search across multiple pivot lengths ensures that even the sneakiest harmonic patterns are identified. Each pattern is evaluated and assigned a score, making it easy to differentiate weak patterns from strong ones. Tooltips under the pattern labels show a detailed breakdown of the pattern's score and retracement ratios (see the Scoring section below for details).
- Prediction -
After a pattern is identified, paths to potential targets are drawn, and Potential Reversal Zone (PRZ) levels are plotted based on the retracement ratios of the harmonic pattern. Targets are customizable by pattern type (e.g. you can specify one set of targets for a Gartley and another for a Bat, etc).
- Backtesting -
A table shows the results of all the patterns found in the chart. Change your target, stop-loss, and % error inputs and observe how it affects your success rate.
//------------------------------------------------------
// Scoring
//------------------------------------------------------
A percentage-based score is calculated from four components:
(1) Retracement % Accuracy - this measures how closely the pattern's retracement ratios match the theoretical values (fibs) defined for a given harmonic pattern. You can change the "Allowed fib ratio error %" in Settings to be more or less inclusive.
(2) PRZ Level Confluence - Potential Reversal Zone levels are projected from retracements of the XA and BC legs. The PRZ Level Confluence component measures the closeness of the closest XA and BC retracement levels, relative to the total height of the PRZ.
(3) Point D / PRZ Confluence - this measures the closeness of point D to either of the closest two PRZ levels (identified in the PRZ Level Confluence component above), relative to the total height of the PRZ. In theory, the closer together these levels are, the higher the probability of a reversal.
(4) Leg Length Symmetry - this measures the ΔX symmetry of each leg. You can change the "Allowed leg length asymmetry %" in settings to be more or less inclusive.
So, a score of 100% would mean that (1) all leg retracements match the theoretical fib ratios exactly (to 16 decimal places), (2) the closest XA and BC PRZ levels are exactly the same, (3) point D is exactly at the confluent PRZ level, and (4) all legs are exactly the same number of bars. While this is theoretically possible, you have better odds of getting struck by lightning twice on a sunny day.
Calculation weights of all four components can be changed in Settings.
//------------------------------------------------------
// Targets
//------------------------------------------------------
A hard-coded set of targets are available to choose from, and can be applied to each pattern type individually:
(1) .618 XA = .618 retracement of leg XA, measured from point D
(2) 1.272 XA = 1.272 retracement of leg XA, measured from point D
(3) 1.618 XA = 1.618 retracement of leg XA, measured from point D
(4) .618 CD = .618 retracement of leg CD, measured from point D
(5) 1.272 CD = 1.272 retracement of leg CD, measured from point D
(6) 1.618 CD = 1.618 retracement of leg CD, measured from point D
(7) A = point A
(8) B = point B
(9) C = point C
Static K-means Clustering | InvestorUnknownStatic K-Means Clustering is a machine-learning-driven market regime classifier designed for traders who want a data-driven structure instead of subjective indicators or manually drawn zones.
This script performs offline (static) K-means training on your chosen historical window. Using four engineered features:
RSI (Momentum)
CCI (Price deviation / Mean reversion)
CMF (Money flow / Strength)
MACD Histogram (Trend acceleration)
It groups past market conditions into K distinct clusters (regimes). After training, every new bar is assigned to the nearest cluster via Euclidean distance in 4-dimensional standardized feature space.
This allows you to create models like:
Regime-based long/short filters
Volatility phase detectors
Trend vs. chop separation
Mean-reversion vs. breakout classification
Volume-enhanced money-flow regime shifts
Full machine-learning trading systems based solely on regimes
Note:
This script is not a universal ML strategy out of the box.
The user must engineer the feature set to match their trading style and target market.
K-means is a tool, not a ready made system, this script provides the framework.
Core Idea
K-means clustering takes raw, unlabeled market observations and attempts to discover structure by grouping similar bars together.
// STEP 1 — DATA POINTS ON A COORDINATE PLANE
// We start with raw, unlabeled data scattered in 2D space (x/y).
// At this point, nothing is grouped—these are just observations.
// K-means will try to discover structure by grouping nearby points.
//
// y ↑
// |
// 12 | •
// | •
// 10 | •
// | •
// 8 | • •
// |
// 6 | •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 2 — RANDOMLY PLACE INITIAL CENTROIDS
// The algorithm begins by placing K centroids at random positions.
// These centroids act as the temporary “representatives” of clusters.
// Their starting positions heavily influence the first assignment step.
//
// y ↑
// |
// 12 | •
// | •
// 10 | • C2 ×
// | •
// 8 | • •
// |
// 6 | C1 × •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 3 — ASSIGN POINTS TO NEAREST CENTROID
// Each point is compared to all centroids.
// Using simple Euclidean distance, each point joins the cluster
// of the centroid it is closest to.
// This creates a temporary grouping of the data.
//
// (Coloring concept shown using labels)
//
// - Points closer to C1 → Cluster 1
// - Points closer to C2 → Cluster 2
//
// y ↑
// |
// 12 | 2
// | 1
// 10 | 1 C2 ×
// | 2
// 8 | 1 2
// |
// 6 | C1 × 2
// |
// 4 | 1
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
// (1 = assigned to Cluster 1, 2 = assigned to Cluster 2)
// At this stage, clusters are formed purely by distance.
Your chosen historical window becomes the static training dataset , and after fitting, the centroids never change again.
This makes the model:
Predictable
Repeatable
Consistent across backtests
Fast for live use (no recalculation of centroids every bar)
Static Training Window
You select a period with:
Training Start
Training End
Only bars inside this range are used to fit the K-means model. This window defines:
the market regime examples
the statistical distributions (means/std) for each feature
how the centroids will be positioned post-trainin
Bars before training = fully transparent
Training bars = gray
Post-training bars = full colored regimes
Feature Engineering (4D Input Vector)
Every bar during training becomes a 4-dimensional point:
This combination balances: momentum, volatility, mean-reversion, trend acceleration giving the algorithm a richer "market fingerprint" per bar.
Standardization
To prevent any feature from dominating due to scale differences (e.g., CMF near zero vs CCI ±200), all features are standardized:
standardize(value, mean, std) =>
(value - mean) / std
Centroid Initialization
Centroids start at diverse coordinates using various curves:
linear
sinusoidal
sign-preserving quadratic
tanh compression
init_centroids() =>
// Spread centroids across using different shapes per feature
for c = 0 to k_clusters - 1
frac = k_clusters == 1 ? 0.0 : c / (k_clusters - 1.0) // 0 → 1
v = frac * 2 - 1 // -1 → +1
array.set(cent_rsi, c, v) // linear
array.set(cent_cci, c, math.sin(v)) // sinusoidal
array.set(cent_cmf, c, v * v * (v < 0 ? -1 : 1)) // quadratic sign-preserving
array.set(cent_mac, c, tanh(v)) // compressed
This makes initial cluster spread “random” even though true randomness is hardly achieved in pinescript.
K-Means Iterative Refinement
The algorithm repeats these steps:
(A) Assignment Step, Each bar is assigned to the nearest centroid via Euclidean distance in 4D:
distance = sqrt(dx² + dy² + dz² + dw²)
(B) Update Step, Centroids update to the mean of points assigned to them. This repeats iterations times (configurable).
LIVE REGIME CLASSIFICATION
After training, each new bar is:
Standardized using the training mean/std
Compared to all centroids
Assigned to the nearest cluster
Bar color updates based on cluster
No re-training occurs. This ensures:
No lookahead bias
Clean historical testing
Stable regimes over time
CLUSTER BEHAVIOR & TRADING LOGIC
Clusters (0, 1, 2, 3…) hold no inherent meaning. The user defines what each cluster does.
Example of custom actions:
Cluster 0 → Cash
Cluster 1 → Long
Cluster 2 → Short
Cluster 3+ → Cash (noise regime)
This flexibility means:
One trader might have cluster 0 as consolidation.
Another might repurpose it as a breakout-loading zone.
A third might ignore 3 clusters entirely.
Example on ETHUSD
Important Note:
Any change of parameters or chart timeframe or ticker can cause the “order” of clusters to change
The script does NOT assume any cluster equals any actionable bias, user decides.
PERFORMANCE METRICS & ROC TABLE
The indicator computes average 1-bar ROC for each cluster in:
Training set
Test (live) set
This helps measure:
Cluster profitability consistency
Regime forward predictability
Whether a regime is noise, trend, or reversion-biased
EQUITY SIMULATION & FEES
Designed for close-to-close realistic backtesting.
Position = cluster of previous bar
Fees applied only on regime switches. Meaning:
Staying long → no fee
Switching long→short → fee applied
Switching any→cash → fee applied
Fee input is percentage, but script already converts internally.
Disclaimers
⚠️ This indicator uses machine-learning but does not predict the future. It classifies similarity to past regimes, nothing more.
⚠️ Backtest results are not indicative of future performance.
⚠️ Clusters have no inherent “bullish” or “bearish” meaning. You must interpret them based on your testing and your own feature engineering.
ParabolicSAR+EMA[TS_Indie]🚀 EMA + Parabolic SAR Reversal Trading Strategy
This trading system effectively combines the use of Exponential Moving Averages (EMA) with the Parabolic SAR to identify both price trends and key reversal points. The EMA Fast is used to signal the primary short-term trend, while the EMA Slow acts as a filter for the long-term trend direction. The Parabolic SAR then helps to confirm the reversal signals.
🛠️ Tools Used
1. EMA Fast – Primary Short-Term Trend
2. EMA Slow – Long-Term Trend Filter
3. Parabolic SAR – Reversal Confirmation
🎯 Entry Rules
📈 Buy Setup
1. Trend Filter: EMA Fast > EMA Slow → Uptrend
2. Pullback: Price pulls back and closes below the EMA Fast line.
3. Reversal: Price reverses/pulls back up and closes above the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is above the high, and the dot in the current candle is below the low → Reversal signal confirmed.
5. Entry: Enter Buy immediately.
📉 Sell Setup
1. Trend Filter: EMA Fast < EMA Slow → Downtrend
2. Pullback: Price pulls back and closes above the EMA Fast line.
3. Reversal: Price reverses/pulls back down and closes below the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is below the low, and the dot in the current candle is above the high → Reversal signal confirmed.
5. Entry: Enter Sell immediately.
💰 Exit Management (Entry, Stop Loss, Take Profit)
1. Entry: Enter the order at the closing price of the signal candle.
2. Stop Loss (SL): Set the Stop Loss at the Parabolic SAR dot.
3. Take Profit (TP): Calculated from the Entry and Stop Loss points, multiplied by the Risk Reward Ratio.
⚙️ Optional Parameters
➭ Custom Risk/Reward Ratio for Take Profit.
➭ Option to add an ATR buffer to the Stop Loss.
➭ Adjustable EMA Fast period.
➭ Adjustable EMA Slow period.
➭ Adjustable Parabolic SAR parameters.
➭ Option to enable Long-only / Short-only positions.
➭ Customizable Backtest start and end date.
➭ Customizable trading session time.
🔔 Alert Function
Alerts display:
➭ Entry Price
➭ Stop Loss Price
➭ Take Profit Price
💡 This strategy allows for many parameter adjustments, such as the MA type, adding/subtracting from the Stop Loss using ATR, and selecting specific sessions for backtesting. If you find interesting or profitable results after adjusting the parameters, please share your comments with other traders!
⚠️ Disclaimer
This indicator is designed for educational and research purposes only. It does not guarantee profits and should not be considered financial advice. Trading in financial markets involves significant risk , including the potential loss of capital.
Mirror Blocks: StrategyMirror Blocks is an educational structural-wave model built around a unique concept:
the interaction of mirrored weighted moving averages (“blocks”) that reflect shifts in market structure as price transitions between layered symmetry zones.
Rather than attempting to “predict” markets, the Mirror Blocks framework visualizes how price behaves when it expands away from, contracts toward, or flips across stacked WMA structures. These mirrored layers form a wave-like block system that highlights transitional zones in a clean, mechanical way.
This strategy version allows you to study how these structural transitions behave in different environments and on different timeframes.
The goal is understanding wave structure, not generating signals.
How It Works
Mirror Blocks builds three mirrored layers:
Top Block (Structural High Symmetry)
Base Block (Neutral Wave)
Bottom Block (Structural Low Symmetry)
The relative position of these blocks — and how price interacts with them — helps visualize:
Compression and expansion
Reversal zones
Wave stability
Momentum transitions
Structure flips
A structure is considered bullish-stack aligned when:
Top > Base > Bottom
and bearish-stack aligned when:
Bottom > Base > Top
These formations create the core of the Mirror Blocks wave engine.
What the Strategy Version Adds
This version includes:
Long Only, Short Only, or Long & Short modes
Adjustable symmetry distance (Mirror Distance)
Configurable WMA smoothing length
Optional trend filter using fast/slow MA comparison
ENTER / EXIT / LONG / SHORT labels for structural transitions
Fixed stop-loss controls for research
A clean, transparent structure with no hidden components
It is optimized for educational chart study, not automated signals.
Intended Purpose
Mirror Blocks is meant to help traders:
Study structural transitions
Understand symmetry-based wave models
Explore how price interacts with mirrored layers
Examine reversals and expansions from a mechanical perspective
Conduct long and short backtesting for research
Develop a deeper sense of market rhythm
This is not a prediction model.
It is a visual and structural framework for understanding movement.
Backtesting Disclaimer
Backtest results can vary depending on:
Slippage settings
Commission settings
Timeframe
Asset volatility
Structural sensitivity parameters
Past performance does not guarantee future results.
Use this as a research tool only.
Warnings & Compliance
This script is educational.
It is not financial advice.
It does not provide signals.
It does not promise profitability.
The purpose is to help visualize structure, not predict price.
The strategy features are simply here to help users study how structural transitions behave under various conditions.
License
Released under the Michael Culpepper Gratitude License (2025).
Use and modify freely for education and research with attribution.
No resale.
No promises of profitability.
Purpose is understanding, not signals.
Forever ModelForever Model is a comprehensive trading framework that visualizes market structure through Fair Value Gaps (FVGs), Smart Money Technique (SMT) divergences, and order block confirmations. The indicator identifies potential price rotations by tracking internal liquidity zones, correlation breaks between assets, and confirmation signals across multiple timeframes.
Designed for clarity and repeatability, the model presents a structured visual logic that supports manual analysis while maintaining flexibility across different assets and timeframes. All components are non-repainting, ensuring historical accuracy and reliable backtesting.
Description
The model operates through a three-part sequence that forms the visual foundation for identifying potential market rotations:
Fair Value Gaps (FVGs)
FVGs are price imbalances detected on higher timeframes—areas where price moved rapidly between candles, leaving an inefficiency that may be revisited. The indicator identifies both bullish and bearish FVGs, displaying them with color-coded levels that extend until mitigated.
: Chart showing FVG detection with colored lines indicating bullish (green) and bearish (red) gaps
Smart Money Technique (SMT)
SMT detects divergence between the current chart asset and a correlated pair. When one asset makes a higher high while the other forms a lower high (or vice versa), it indicates a potential shift in delivery. The indicator draws visual lines connecting these divergence points and can filter SMTs to only display those occurring within FVG ranges.
: Chart showing SMT divergence lines between two correlated assets with labels indicating the pair name]
Order Block Confirmations (OB)
When price confirms a signal by crossing a pivot level, an Order Block is created. The confirmation line extends from the pivot point, labeled as "OB+" for bullish signals or "OB-" for bearish signals. The latest OB extends to the current bar, while previous OBs remain fixed at their confirmation points.
: Chart showing OB confirmation lines with OB+ and OB- labels at confirmation points]
Key Features
Higher Timeframe (HTF) Detection
FVGs are detected on a higher timeframe than the current chart, with automatic HTF selection based on the current timeframe or manual override options. This ensures that internal liquidity zones are identified from the appropriate structural context.
External Range Liquidity (ERL)
Tracks the latest higher timeframe pivot highs and lows, marking external liquidity levels that may be revisited. ERL levels are displayed as horizontal lines with optional labels, providing context for potential continuation targets.
: Chart showing ERL lines at recent HTF pivot points
Signal Creation and Confirmation System
The model creates pending signals when FVG levels are mitigated. Signals confirm when price closes beyond a pivot level, creating the OB confirmation line. Stop levels are automatically calculated from the maximum (bearish) or minimum (bullish) price between signal creation and confirmation.
SMT Filtering Options
Display all SMTs or only those within FVG ranges
Require SMT for signal confirmation (optional filter)
Automatic or manual SMT pair selection
Support for both correlated and inverse correlated pairs
Directional Bias Filter
Filter FVG detection to show only bullish bias, bearish bias, or both. This allows analysts to align with higher timeframe structure or focus on unidirectional setups.
Confirmation Line Management
Toggle to extend only the latest confirmation line or all confirmation lines
Transparent label backgrounds with colored text (red for bearish, green for bullish)
Automatic cleanup of old confirmation lines (keeps last 50)
Labels positioned at line end (latest) or middle (older lines)
Position Sizing Calculator
Optional position sizing based on account balance, risk percentage or fixed amount, and instrument-specific contract sizes. Supports prop firm calculations and can display position size, entry, and stop levels in the dashboard.
Information Dashboard
A customizable floating table displays:
Current timeframe and HTF
Remaining time in current bar
Current bias direction
Latest confirmed signal details (type, size, entry, stop)
Pending signal status
The dashboard can be repositioned, resized, and styled to match your preferences.
Special Range Creation
When signals confirm, the model can automatically create special range levels from stop prices. These levels persist on the chart as important reference points, even after mitigation, serving as potential reversal zones for future signals.
Label and Visualization Controls
Toggle FVG labels on/off
Toggle confirmation lines on/off
Customizable colors for bullish and bearish FVGs
ERL color customization
SMT line width adjustment
Order Flow Integration (Optional)
The indicator includes optional Open Interest (OI) based special range detection, allowing integration with order flow analysis for enhanced context.
Technical Notes
All components are non-repainting—once formed, they remain on the chart
FVGs cannot be mitigated on their creation bar
Signal-based special ranges persist even after mitigation (important stop levels)
SMT detection supports both HTF and chart timeframe modes
Maximum 50 confirmation lines are maintained for performance
The model is designed to work across all asset classes and timeframes, providing a consistent framework for identifying potential market rotations through the interaction of internal liquidity, correlation breaks, and confirmation signals, this does not constitute as trading advice, past performance is no indication of future performance , this is entirely done for entertainment and educational purposes
Time ColorsTime Colors – Custom Trading Sessions Visualizer
Time Colors is a simple visual helper for backtesting and intraday trading.
It lets you define up to 10 custom time blocks and highlights the chart background during those periods.
Use it to:
Mark the exact times when you are realistically able to trade
Visually separate different sessions (e.g. London, New York, Asia)
Filter out “dream trades” that happened while you were sleeping or at work
Features
Up to 10 fully customizable time blocks
Individual on/off toggle for each block
Custom color for every block
Works on any intraday timeframe
Session resolution input for flexible time handling
How to use
Add the Time Colors indicator to your chart.
Set each Time Block to your personal trading hours (based on your TradingView timezone).
Disable blocks you don’t need with “Enable Block X”.
When backtesting, only count trades that occur inside the colored areas – those are the times you could have actually taken trades.
LapseBacktestingTableLibrary "LapseBacktestingMetrics"
This library provides a robust set of quantitative backtesting and performance evaluation functions for Pine Script strategies. It’s designed to help traders, quants, and developers assess risk, return, and robustness through detailed statistical metrics — including Sharpe, Sortino, Omega, drawdowns, and trade efficiency.
Built to enhance any trading strategy’s evaluation framework, this library allows you to visualize performance with the quantlapseTable() function, producing an interactive on-chart performance table.
Credit to EliCobra and BikeLife76 for original concept inspiration.
curve(disp_ind)
Retrieves a selected performance curve of your strategy.
Parameters:
disp_ind (simple string): Type of curve to plot. Options include "Equity", "Open Profit", "Net Profit", "Gross Profit".
Returns: (float) Corresponding performance curve value.
cleaner(disp_ind, plot)
Filters and displays selected strategy plots for clean visualization.
Parameters:
disp_ind (simple string): Type of display.
plot (simple float): Strategy plot variable.
Returns: (float) Filtered plot value.
maxEquityDrawDown()
Calculates the maximum equity drawdown during the strategy’s lifecycle.
Returns: (float) Maximum equity drawdown percentage.
maxTradeDrawDown()
Computes the worst intra-trade drawdown among all closed trades.
Returns: (float) Maximum intra-trade drawdown percentage.
consecutive_wins()
Finds the highest number of consecutive winning trades.
Returns: (int) Maximum consecutive wins.
consecutive_losses()
Finds the highest number of consecutive losing trades.
Returns: (int) Maximum consecutive losses.
no_position()
Counts the maximum consecutive bars where no position was held.
Returns: (int) Maximum flat days count.
long_profit()
Calculates total profit generated by long positions as a percentage of initial capital.
Returns: (float) Total long profit %.
short_profit()
Calculates total profit generated by short positions as a percentage of initial capital.
Returns: (float) Total short profit %.
prev_month()
Measures the previous month’s profit or loss based on equity change.
Returns: (float) Monthly equity delta.
w_months()
Counts the number of profitable months in the backtest.
Returns: (int) Total winning months.
l_months()
Counts the number of losing months in the backtest.
Returns: (int) Total losing months.
checktf()
Returns the time-adjusted scaling factor used in Sharpe and Sortino ratio calculations based on chart timeframe.
Returns: (float) Annualization multiplier.
stat_calc()
Performs complete statistical computation including drawdowns, Sharpe, Sortino, Omega, trade stats, and profit ratios.
Returns: (array)
.
f_colors(x, nv)
Generates a color gradient for performance values, supporting dynamic table visualization.
Parameters:
x (simple string): Metric label name.
nv (simple float): Metric numerical value.
Returns: (color) Gradient color value for table background.
quantlapseTable(option, position)
Displays an interactive Performance Table summarizing all major backtesting metrics.
Includes Sharpe, Sortino, Omega, Profit Factor, drawdowns, profitability %, and trade statistics.
Parameters:
option (simple string): Table type — "Full", "Simple", or "None".
position (simple string): Table position — "Top Left", "Middle Right", "Bottom Left", etc.
Returns: (table) On-chart performance visualization table.
This library empowers advanced quantitative evaluation directly within Pine Script®, ideal for strategy developers seeking deeper performance diagnostics and intuitive on-chart metrics.
Complete DashboardPA+AI PRE/GO Trading Dashboard v0.1.2 - Publication Summary
Overview
A comprehensive multi-component trading system that combines technical analysis with an intelligent probability scoring framework to identify high-quality trade setups. The indicator features TTM Squeeze integration, volatility regime adaptation, and professional risk management tools—all presented in an intuitive 4-dashboard interface.
Key Features
🎯 8-Component Probability Scoring System (0-100%)
VWAP Position & Momentum - Price location and directional bias
MACD Alignment - Trend confirmation and momentum strength
EMA Trend Analysis - Multi-timeframe trend validation
Volume Surge Detection - Relative volume analysis (RVOL)
Price Extension Analysis - Distance from VWAP in ATR multiples
TTM Squeeze Status - Volatility compression/expansion cycles
Squeeze Momentum - Directional thrust measurement
Confluence Scoring - Multi-indicator alignment bonus
🔥 TTM Squeeze Integration
Squeeze Detection - Identifies consolidation phases (BB inside KC)
Strength Classification - Distinguishes tight vs. loose squeezes
Fire Signals - Premium entry alerts when squeeze releases
Building Alerts - Early warnings when tight squeezes are coiling
📊 Volatility Regime Adaptation
Dynamic Thresholds - Auto-adjusts based on ATR percentile (100-bar)
Three Regimes - LOW VOL, NORMAL, HIGH VOL classification
Adaptive Parameters - RVOL requirements and distance limits adjust automatically
Context-Aware Scoring - Volume expectations scale with market volatility
💰 Professional Risk Management
Position Sizing Calculator - Risk-based share calculation (% of account)
ATR Trailing Stops - Dynamic stop-loss that tightens with profits
Multiple Entry Strategies - VWAP reversion and pullback entries
Complete Trade Info - Entry, stop, target, and size for every signal
📈 Multi-Timeframe Analysis Dashboard
4 Timeframes - Daily, 4H, 15m, 5m (customizable)
6 Metrics per TF - Price change, MACD, RSI, RVOL, EMA trend
Alignment Visualization - Color-coded bull/bear indicators
HTF Context - Understand broader market structure
🛡️ Reliability Features
Confirm-on-Close - Eliminates intrabar repainting
Minimum Bars Filter - Prevents premature signals on chart load
NA-Safe Calculations - Works reliably on all symbols/timeframes
Zero Division Protection - Bulletproof math across all market conditions
What Makes This Indicator Unique
Intelligent Probability Weighting
Unlike binary "buy/sell" indicators, this system quantifies setup quality from 0-100%, allowing traders to:
Filter by confidence - Only take 70%+ probability setups
Size accordingly - Larger positions on higher probability signals
Understand context - Know exactly why a signal fired
Squeeze-Enhanced Entries
The integration of TTM Squeeze analysis adds a powerful timing dimension:
Premium Signals - 🔥 when squeeze fires + high probability (75%+)
Regular Signals - Standard entries during trending conditions
Avoid Chop - No entries during squeeze consolidation
Strength Matters - Tight squeezes (BB width <20th percentile) get bonus points
Adaptive Intelligence
The volatility regime system ensures the indicator performs across all market conditions:
Dead markets - Tighter thresholds prevent false signals
Volatile markets - Loosened requirements catch real moves
Automatic adjustment - No manual intervention needed
Dashboard-Centric Design
All critical information visible at a glance:
Top-right - Probability breakdown & regime status
Middle-right - Multi-timeframe alignment matrix
Middle-left - RVOL status (volume confirmation)
Bottom-right - Entry strategies with exact prices & sizes
Ideal For
✅ Day Traders - Intraday setups with clear entry/exit
✅ Swing Traders - Multi-timeframe confirmation for position trades
✅ Options Traders - Squeeze timing for volatility expansion plays
✅ Systematic Traders - Quantified probabilities for rule-based systems
✅ Risk Managers - Built-in position sizing & stop placement
Technical Specifications
Indicator Type: Overlay (draws on price chart)
Pine Script Version: v6
Calculation Method: Real-time, confirm-on-close option
Alerts: 8 different alert types (premium entries, exits, squeeze warnings)
Customization: 30+ input parameters
Performance: Optimized for real-time updates
Entry Strategies Included
1. VWAP Reversion
Enter when price bounces off VWAP ± 0.7 ATR
Targets mean reversion moves
Best for range-bound or choppy markets
2. Pullback to Structure
Enter on 50% retracement from swing high/low
Targets trend continuation after healthy pullback
Best for strong trending markets
Both strategies include:
Precise entry levels
ATR-based stop placement
Risk/reward targets
Position size calculation
Alert System
8 Alert Types:
🔥 Premium Long - Squeeze firing + bullish + high probability
🔥 Premium Short - Squeeze firing + bearish + high probability
🟢 High Probability Long - Standard bullish setup (70%+)
🔴 High Probability Short - Standard bearish setup (70%+)
⚡ Squeeze Coiling Long - Tight squeeze building, bullish bias
⚡ Squeeze Coiling Short - Tight squeeze building, bearish bias
Exit Long - Long position exit signal
Exit Short - Short position exit signal
Settings & Customization
Basic Settings
ATR Length (default: 14)
Confirm on Close (default: ON)
Minimum Bars Required (default: 50)
Squeeze Settings
Bollinger Band Length & Multiplier
Keltner Channel Length & Multiplier
Momentum Length
Squeeze strength classification
Probability Settings
MACD Parameters (12, 26, 9)
Volume Surge Multiplier (1.5x)
High/Medium Probability Thresholds (70%/50%)
Volatility Regime Adaptation (ON/OFF)
Risk Management
Account Equity
Risk % per Trade (default: 1%)
ATR Trailing Stop (ON/OFF)
Trail Multiplier (default: 2.0x)
Visual Settings
RVOL Period (20 bars)
Fast/Slow EMA (9/21)
Show/Hide each timeframe
Dashboard positioning
Use Cases
Conservative Trading
Set High Probability Threshold to 75%+
Enable Confirm-on-Close
Only take Premium (🔥) entries
Use 0.5% risk per trade
Aggressive Trading
Set Medium Probability Threshold to 50%
Disable Confirm-on-Close (live signals)
Take all High Probability entries
Use 1.5-2% risk per trade
Squeeze Specialist
Focus exclusively on Premium entries (squeeze firing)
Wait for "TIGHT SQUEEZE" status
Monitor squeeze building alerts
Enter immediately on fire signal
Range Trading
Use VWAP reversion entries only
Lower probability threshold to 60%
Tighter trailing stops (1.5x ATR)
Focus on low volatility regime periods
Performance Expectations
Based on backtesting and design principles:
Signal Quality:
False signals reduced ~20-30% vs. single-indicator systems
Win rate improvement ~5-10% from regime adaptation
Average win size +15-20% from trailing stops
Execution:
Clear entry signals with exact prices
Defined risk on every trade (stop loss)
Consistent position sizing (% of account)
Professional trade management
Adaptability:
Works across stocks, futures, forex, crypto
Performs in trending and ranging markets
Adjusts to changing volatility automatically
Version History
v0.1.2 (Current)
Added squeeze momentum scoring (was calculated but unused)
Implemented volatility regime adaptation
Added confluence scoring (multi-indicator alignment)
Enhanced squeeze strength classification (tight vs. loose)
Improved reliability (confirm-on-close, NA-safe calculations)
Added ATR trailing stops
Added position sizing calculator
Consolidated alert system
v0.1.1
Initial release with 6-component probability system
Basic TTM Squeeze integration
Multi-timeframe analysis
Entry strategy frameworks
Limitations & Disclaimers
⚠️ Not a Holy Grail - No indicator is 100% accurate; losses will occur
⚠️ Requires Judgment - Use probability scores to guide, not replace, decision-making
⚠️ Backtesting Recommended - Test on paper/demo before live trading
⚠️ Market Dependent - Performance varies by asset class and market conditions
⚠️ Risk Management Essential - Always use stops; never risk more than you can afford to lose
Installation & Setup
Copy the Pine Script code
Open TradingView chart
Pine Editor → Paste code → "Add to Chart"
Configure inputs for your trading style
Set up alerts via TradingView alert menu
Paper trade for 20+ signals before going live
Future Development Roadmap
Phase 3 (Planned)
HTF alignment filter (require Daily + 4H confirmation)
Session filters (avoid low-liquidity periods)
Probability decay (signals lose value over time)
Squeeze pre-alert enhancements
Phase 4 (AI Integration)
Feature vector export via webhooks
ML-based parameter optimization
Neural network regime classification
Reinforcement learning for exits
Support & Documentation
Included Documentation:
Complete changelog with implementation details
Technical guide explaining all components
Risk management best practices
Alert configuration guide
Best Practices:
Start with default settings
Enable Confirm-on-Close initially
Use 1% risk per trade or less
Focus on Premium (🔥) entries first
Keep a trade journal to track performance
Credits & Methodology
Indicators Used:
TTM Squeeze (John Carter)
VWAP (Volume-Weighted Average Price)
MACD (Gerald Appel)
Exponential Moving Averages
Average True Range (Wilder)
Relative Volume
Original Contributions:
Multi-component probability weighting system
Volatility regime adaptation framework
Confluence scoring methodology
Integrated risk management calculator
Dashboard-centric visualization
License & Terms
Usage: Free for personal trading
Modification: Open source, modify as needed
Distribution: Credit original author if sharing modified versions
Commercial Use: Contact author for licensing
No Warranty: This indicator is provided "as-is" without guarantees of profitability. Trading involves substantial risk. Past performance does not guarantee future results.
Quick Stats
📊 Components: 8
🎯 Probability Range: 0-100%
📈 Timeframes: 4 (customizable)
🔔 Alert Types: 8
⚙️ Input Parameters: 30+
📱 Dashboards: 4
💰 Entry Strategies: 2 (VWAP + Pullback)
🛡️ Risk Management: Integrated
Status: Production Ready ✅
Version: 0.1.2
Last Updated: November 2025
Pine Script: v6
File Name: PA_AI_PRE_GO_v0.1.2_FIXED.pine
One-Line Summary
A professional-grade trading dashboard combining 8 technical components with TTM Squeeze analysis, volatility-adaptive thresholds, and integrated risk management—delivering quantified probability scores (0-100%) for every trade setup.
Dual Harmonic-based AHR DCA (Default :BTC-ETH)A panel indicator designed for dual-asset BTC/ETH DCA (Dollar Cost Averaging) decisions.
It is inspired by the Chinese community indicator "AHR999" proposed by “Jiushen”.
How to use:
Lower HM-based AHR → cheaper (potential buy zone).
Higher HM-based AHR → more expensive (potential risk zone).
Higher than Risk Threshold → consider to sell, but not suitable for DCA.
When both AHR lines are below the Risk threshold → buy the cheaper one (or split if similar).
If one AHR is above Risk → buy the other asset.
If both are above Risk → simulation shows “STOP (both risk)”.
Not limited to BTC/ETH — you can freely change symbols in the input panel
to build any dual-asset DCA pair you want (e.g., BTC/BNB, ETH/SOL, etc.).
What you’ll see:
Two lines: AHR BTC (HM) and AHR ETH (HM)
Two dashed lines: OppThreshold (green) and RiskThreshold (red)
Colored fill showing which asset is cheaper (BTC or ETH)
Buy markers:
- B = Buy BTC
- E = Buy ETH
- D = Dual (split budget)
Top-right table: prices, AHRs, thresholds, qOpp/qRisk%, simulation, P&L
Labels showing last-bar AHR values
Core idea:
Use an AHR based on Harmonic Moving Average (HM) — a ratio that measures how “cheap or expensive” price is relative to both its short-term mean and long-term trend.
The original AHR999 used SMA and was designed for BTC only.
This indicator extends it with cross-exchange percentile mapping, allowing the empirical “opportunity/risk” zones of the AHR999 (on Bitstamp) to adapt automatically to the current market pair.
The indicator derives two adaptive thresholds:
OppThreshold – opportunity zone
RiskThreshold – risk zone
These thresholds are compared with the current HM-based AHR of BTC and ETH to decide which asset is cheaper, and whether it is good to DCA or not, or considering to sell(When it in risk area).
This version uses
Display base: Binance (default: perpetual) with HM-based AHR
Percentile base: Bitstamp spot SMA-AHR (complete, stable history)
Rolling window: 2920 daily bars (~8 years) for percentile tracking
Concept summary
AHR measures the ratio of price to its long-term regression and short-term mean.
HM replaces SMA to better reflect equal-fiat-cost DCA behavior.
Cross-exchange percentile mapping (Bitstamp → Binance) keeps thresholds consistent with the original AHR999 interpretation.
Recommended settings (1D):
DCA length (harmonic): 200
Log-regression lookback: 1825 (≈5 years)
Rolling window: 2920 (≈8 years)
Reference thresholds: 0.45 / 1.20 (AHR999 empirical priors)
Tie split tolerance (ΔAHR): 0.05
Daily budget: 15 USDT (simulation)
All display options can be toggled: table, markers, labels, etc.
Notes:
When the rolling window is filled (2920 bars by default), thresholds are first calculated and then visually backfilled as left-extended lines.
The “buy markers” and “decision table” are light simulations without fees or funding costs — for rhythm and relative analysis, not backtesting.
Crypto Futures Basis Tracker (Annualized)🧩 What is Basis Arbitrage
Basis arbitrage is a market-neutral trading strategy that exploits the price difference between a cryptocurrency’s spot and its futures markets.
When futures trade above spot (called contango), traders can buy spot and short futures, locking in a potential yield.
When futures trade below spot (backwardation), the reverse applies — short spot and go long futures.
The yield earned (or cost paid) by holding this position until expiry is called the basis. Expressing it as an annualized percentage allows comparison across different contract maturities.
⚙️ How the Indicator Works
This tool calculates the annualized basis for up to 10 cryptocurrency futures against a chosen spot price.
You select one spot symbol (e.g., BITSTAMP:BTCUSD) and up to 10 futures symbols (e.g., DERIBIT:BTCUSD07X2025, DERIBIT:BTCUSD14X2025, etc.).
The script automatically computes the days-to-expiry (DTE) and the annualized basis for each future.
A table displays for each contract: symbol, expiry date, DTE, last price, and annualized basis (%) — making it easy to compare the forward curve across maturities.
⚠️ Risks and Limitations
While basis arbitrage is often considered low-risk, it’s not risk-free:
Funding and financing costs can erode returns, especially when borrowing or using leverage.
Exchange or counterparty risk — if one leg of the trade fails (e.g., exchange default, margin liquidation), the hedge breaks.
Execution and timing risk — the basis can tighten or invert before both legs are opened.
Liquidity differences — thin futures may have large bid-ask spreads or slippage.
Use this indicator for analysis and monitoring, not as an automated trading signal.
Disclaimer: Please remember that past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script don't provide any financial advice.
Pivots High Low Live DetectionPivots High Low Live Detection
Identifies and visualizes swing highs and lows on the chart in real time.
Helps to observe evolving market structure by connecting confirmed or developing pivot points with lines and labels.
Using a configurable lookback, minimum deviation, and confirmation bar system, the indicator highlights new Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL) as they form.
When “Live (repainting)” mode is enabled, the current swing leg updates dynamically with each candle, giving immediate feedback as price develops.
When disabled, only confirmed pivots are plotted, ideal for historical validation and backtesting.
+ Key Features
Detects and labels major swing points (HH, HL, LH, LL).
Works in live or confirmed (non-repainting) mode.
Adjustable parameters for lookback, deviation (in ticks), and confirmation bars.
Lightweight and compatible with any timeframe or symbol.
Includes runtime alerts for new structural pivots and direction shifts.
+ How to Use
Adjust the inputs under the “Pivots” group to control sensitivity.
Enable “Live (repainting)” to see developing swing legs, or disable it for confirmed structure only.
Use alerts to track structural changes or potential trend reversals.
