888 BOT #backtest█ 888 BOT #backtest (open source)
This is an Expert Advisor 'EA' or Automated trading script for ‘longs’ and ‘shorts’, which uses only a Take Profit or, in the worst case, a Stop Loss to close the trade.
It's a much improved version of the previous ‘Repanocha’. It doesn`t use 'Trailing Stop' or 'security()' functions (although using a security function doesn`t mean that the script repaints) and all signals are confirmed, therefore the script doesn`t repaint in alert mode and is accurate in backtest mode.
Apart from the previous indicators, some more and other functions have been added for Stop-Loss, re-entry and leverage.
It uses 8 indicators, (many of you already know what they are, but in case there is someone new), these are the following:
1. Jurik Moving Average
It's a moving average created by Mark Jurik for professionals which eliminates the 'lag' or delay of the signal. It's better than other moving averages like EMA , DEMA , AMA or T3.
There are two ways to decrease noise using JMA . Increasing the 'LENGTH' parameter will cause JMA to move more slowly and therefore reduce noise at the expense of adding 'lag'
The 'JMA LENGTH', 'PHASE' and 'POWER' parameters offer a way to select the optimal balance between 'lag' and over boost.
Green: Bullish , Red: Bearish .
2. Range filter
Created by Donovan Wall, its function is to filter or eliminate noise and to better determine the price trend in the short term.
First, a uniform average price range 'SAMPLING PERIOD' is calculated for the filter base and multiplied by a specific quantity 'RANGE MULTIPLIER'.
The filter is then calculated by adjusting price movements that do not exceed the specified range.
Finally, the target ranges are plotted to show the prices that will trigger the filter movement.
Green: Bullish , Red: Bearish .
3. Average Directional Index ( ADX Classic) and ( ADX Masanakamura)
It's an indicator designed by Welles Wilder to measure the strength and direction of the market trend. The price movement is strong when the ADX has a positive slope and is above a certain minimum level 'ADX THRESHOLD' and for a given period 'ADX LENGTH'.
The green color of the bars indicates that the trend is bullish and that the ADX is above the level established by the threshold.
The red color of the bars indicates that the trend is down and that the ADX is above the threshold level.
The orange color of the bars indicates that the price is not strong and will surely lateralize.
You can choose between the classic option and the one created by a certain 'Masanakamura'. The main difference between the two is that in the first it uses RMA () and in the second SMA () in its calculation.
4. Parabolic SAR
This indicator, also created by Welles Wilder, places points that help define a trend. The Parabolic SAR can follow the price above or below, the peculiarity that it offers is that when the price touches the indicator, it jumps to the other side of the price (if the Parabolic SAR was below the price it jumps up and vice versa) to a distance predetermined by the indicator. At this time the indicator continues to follow the price, reducing the distance with each candle until it is finally touched again by the price and the process starts again. This procedure explains the name of the indicator: the Parabolic SAR follows the price generating a characteristic parabolic shape, when the price touches it, stops and turns ( SAR is the acronym for 'stop and reverse'), giving rise to a new cycle. When the points are below the price, the trend is up, while the points above the price indicate a downward trend.
5. RSI with Volume
This indicator was created by LazyBear from the popular RSI .
The RSI is an oscillator-type indicator used in technical analysis and also created by Welles Wilder that shows the strength of the price by comparing individual movements up or down in successive closing prices.
LazyBear added a volume parameter that makes it more accurate to the market movement.
A good way to use RSI is by considering the 50 'RSI CENTER LINE' centerline. When the oscillator is above, the trend is bullish and when it is below, the trend is bearish .
6. Moving Average Convergence Divergence ( MACD ) and ( MAC-Z )
It was created by Gerald Appel. Subsequently, the histogram was added to anticipate the crossing of MA. Broadly speaking, we can say that the MACD is an oscillator consisting of two moving averages that rotate around the zero line. The MACD line is the difference between a short moving average 'MACD FAST MA LENGTH' and a long moving average 'MACD SLOW MA LENGTH'. It's an indicator that allows us to have a reference on the trend of the asset on which it is operating, thus generating market entry and exit signals.
We can talk about a bull market when the MACD histogram is above the zero line, along with the signal line, while we are talking about a bear market when the MACD histogram is below the zero line.
There is the option of using the MAC-Z indicator created by LazyBear, which according to its author is more effective, by using the parameter VWAP ( volume weighted average price ) 'Z-VWAP LENGTH' together with a standard deviation 'STDEV LENGTH' in its calculation.
7. Volume Condition
Volume indicates the number of participants in this war between bulls and bears, the more volume the more likely the price will move in favor of the trend. A low trading volume indicates a lower number of participants and interest in the instrument in question. Low volumes may reveal weakness behind a price movement.
With this condition, those signals whose volume is less than the volume SMA for a period 'SMA VOLUME LENGTH' multiplied by a factor 'VOLUME FACTOR' are filtered. In addition, it determines the leverage used, the more volume , the more participants, the more probability that the price will move in our favor, that is, we can use more leverage. The leverage in this script is determined by how many times the volume is above the SMA line.
The maximum leverage is 8.
8. Bollinger Bands
This indicator was created by John Bollinger and consists of three bands that are drawn superimposed on the price evolution graph.
The central band is a moving average, normally a simple moving average calculated with 20 periods is used. ('BB LENGTH' Number of periods of the moving average)
The upper band is calculated by adding the value of the simple moving average X times the standard deviation of the moving average. ('BB MULTIPLIER' Number of times the standard deviation of the moving average)
The lower band is calculated by subtracting the simple moving average X times the standard deviation of the moving average.
the band between the upper and lower bands contains, statistically, almost 90% of the possible price variations, which means that any movement of the price outside the bands has special relevance.
In practical terms, Bollinger bands behave as if they were an elastic band so that, if the price touches them, it has a high probability of bouncing.
Sometimes, after the entry order is filled, the price is returned to the opposite side. If price touch the Bollinger band in the same previous conditions, another order is filled in the same direction of the position to improve the average entry price, (% MINIMUM BETTER PRICE ': Minimum price for the re-entry to be executed and that is better than the price of the previous position in a given %) in this way we give the trade a chance that the Take Profit is executed before. The downside is that the position is doubled in size. 'ACTIVATE DIVIDE TP': Divide the size of the TP in half. More probability of the trade closing but less profit.
█ STOP LOSS and RISK MANAGEMENT.
A good risk management is what can make your equity go up or be liquidated.
The % risk is the percentage of our capital that we are willing to lose by operation. This is recommended to be between 1-5%.
% Risk: (% Stop Loss x % Equity per trade x Leverage) / 100
First the strategy is calculated with Stop Loss, then the risk per operation is determined and from there, the amount per operation is calculated and not vice versa.
In this script you can use a normal Stop Loss or one according to the ATR. Also activate the option to trigger it earlier if the risk percentage is reached. '% RISK ALLOWED'
'STOP LOSS CONFIRMED': The Stop Loss is only activated if the closing of the previous bar is in the loss limit condition. It's useful to prevent the SL from triggering when they do a ‘pump’ to sweep Stops and then return the price to the previous state.
█ BACKTEST
The objective of the Backtest is to evaluate the effectiveness of our strategy. A good Backtest is determined by some parameters such as:
- RECOVERY FACTOR: It consists of dividing the 'net profit' by the 'drawdown’. An excellent trading system has a recovery factor of 10 or more; that is, it generates 10 times more net profit than drawdown.
- PROFIT FACTOR: The ‘Profit Factor’ is another popular measure of system performance. It's as simple as dividing what win trades earn by what loser trades lose. If the strategy is profitable then by definition the 'Profit Factor' is going to be greater than 1. Strategies that are not profitable produce profit factors less than one. A good system has a profit factor of 2 or more. The good thing about the ‘Profit Factor’ is that it tells us what we are going to earn for each dollar we lose. A profit factor of 2.5 tells us that for every dollar we lose operating we will earn 2.5.
- SHARPE: (Return system - Return without risk) / Deviation of returns.
When the variations of gains and losses are very high, the deviation is very high and that leads to a very poor ‘Sharpe’ ratio. If the operations are very close to the average (little deviation) the result is a fairly high 'Sharpe' ratio. If a strategy has a 'Sharpe' ratio greater than 1 it is a good strategy. If it has a 'Sharpe' ratio greater than 2, it is excellent. If it has a ‘Sharpe’ ratio less than 1 then we don't know if it is good or bad, we have to look at other parameters.
- MATHEMATICAL EXPECTATION: (% winning trades X average profit) + (% losing trades X average loss).
To earn money with a Trading system, it is not necessary to win all the operations, what is really important is the final result of the operation. A Trading system has to have positive mathematical expectation as is the case with this script: ME = (0.87 x 30.74$) - (0.13 x 56.16$) = (26.74 - 7.30) = 19.44$ > 0
The game of roulette, for example, has negative mathematical expectation for the player, it can have positive winning streaks, but in the long term, if you continue playing you will end up losing, and casinos know this very well.
PARAMETERS
'BACKTEST DAYS': Number of days back of historical data for the calculation of the Backtest.
'ENTRY TYPE': For '% EQUITY' if you have $ 10,000 of capital and select 7.5%, for example, your entry would be $ 750 without leverage. If you select CONTRACTS for the 'BTCUSDT' pair, for example, it would be the amount in 'Bitcoins' and if you select 'CASH' it would be the amount in $ dollars.
'QUANTITY (LEVERAGE 1X)': The amount for an entry with X1 leverage according to the previous section.
'MAXIMUM LEVERAGE': It's the maximum allowed multiplier of the quantity entered in the previous section according to the volume condition.
The settings are for Bitcoin at Binance Futures (BTC: USDTPERP) in 15 minutes.
For other pairs and other timeframes, the settings have to be adjusted again. And within a month, the settings will be different because we all know the market and the trend are changing.
Cerca negli script per "backtest"
LANZ Strategy 2.0 [Backtest]🔷 LANZ Strategy 2.0 — Structural Breakout Logic with Dynamic Swing Protection
LANZ Strategy 2.0 is a precision-focused backtesting system built for intraday traders who rely on structural confirmations before the London session to guide directional bias. This tool uses smart swing detection, risk-defined position sizing, and strict time-based execution to simulate real trading conditions with clarity and control.
🧠 Core Components:
Structural Confirmation (Trend & BoS): Detects trend direction and break of structure (BoS) using a three-swing logic, aligning trade entries with valid structural movement.
Time-Based Execution: Trades are triggered exclusively at 02:00 a.m. New York time, ensuring disciplined and repeatable intraday testing.
Swing-Based SL Models: Traders can select between three stop-loss protection types:
First Swing: Most recent structural level
Second Swing: Prior level
Full Coverage: All recent swing levels + configurable pip buffer
Dynamic TP Calculation: Take-Profit is projected as a risk-based multiple (RR), fully adjustable via input.
Capital-Based Risk Management: Risk is defined as a percentage of a fixed account size (e.g., $100 per trade from $10,000), and lot size is automatically calculated based on SL distance.
Fallback Entry Logic: If structural breakout is present but trend is not confirmed, a secondary entry is triggered.
End-of-Session Management: Any open trades are automatically closed at 11:45 a.m. NY time, with optional manual labeling or review.
📊 Visual Features (Optional in Indicator Version):
(Note: Visuals apply to the indicator version of LANZ 2.0, not this backtest script)
Swing level labels (1st, 2nd) and dynamic SL/TP lines.
Real-time session coloring for clarity: Pre-London, Entry Window, and NY Close.
Outcome labels: +RR, -RR, or net % at close.
Auto-cleanup of previous drawings for a clean chart per session.
⚙️ How It Works:
Detects last trend and BoS using swing logic before 02:00 a.m. NY.
At 02:00 a.m., evaluates directional bias and executes BUY or SELL if confirmed.
Applies selected SL logic (1st, 2nd, or full swing protection).
Sets TP based on the RR multiplier.
Closes the trade either on SL, TP, or at 11:45 a.m. NY manually.
🔔 Alerts:
Time-of-day alert at 02:00 a.m. NY to monitor execution.
Can be extended to cover SL/TP triggers or new BoS events.
📝 Notes:
Designed for backtesting precision and discretionary decision-making.
Ideal for Forex pairs, indices, or assets active during the London session.
Fully customizable: session timing, swing logic, SL buffer, and RR.
👤 Credits:
Strategy built by @rau_u_lanz using Pine Script v6, combining structural logic, capital-based risk control, and London-session timing in a backtest-ready framework for traders who demand accuracy and structure.
LSMA Z-Score [BackQuant]LSMA Z-Score
Main Features and Use in the Trading Strategy
- The indicator normalizes the LSMA into a detrended Z-Score, creating an oscillator with standard deviation levels to indicate trend strength.
- Adaptive coloring highlights the rate of change and potential reversals, with different colors for positive and negative changes above and below the midline.
- Extreme levels with adaptive coloring indicate the probability of a reversion, providing strategic entry or exit points.
- Alert conditions for crossing the midline or significant shifts in trend direction enhance its utility within a trading strategy.
1. What is an LSMA?
The Least Squares Moving Average (LSMA) is a technical indicator that smoothens price data to help identify trends. It uses the least squares regression method to fit a straight line through the selected price points over a specified period. This approach minimizes the sum of the squares of the distances between the line and the price points, providing a more statistically grounded moving average that can adapt more smoothly to price changes.
2. What is a Z-Score?
A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values, measured in terms of standard deviations from the mean. If a Z-Score is 0, it indicates that the data point's score is identical to the mean score. A Z-Score helps in understanding if a data point is typical for a given data set or if it is atypical. In finance, a Z-Score is often used to measure how far a piece of data is from the average of a set, which can be helpful in identifying outliers or unusual data points.
3. Why Turning LSMA into a Z-Score is Innovative and Its Benefits
Converting LSMA into a Z-Score is innovative because it combines the trend identification capabilities of the LSMA with the statistical significance testing of Z-Scores. This transformation normalizes the LSMA, creating a detrended oscillator that oscillates around a mean (zero line), with standard deviation levels to show trend strength. This method offers several benefits:
Enhanced Trend Detection:
- By normalizing the LSMA, traders can more easily identify when the price is deviating significantly from its trend, which can signal potential trading opportunities.
Standardization:
- The Z-Score transformation allows for comparisons across different assets or time frames, as the score is standardized.
Objective Measurement of Trend Strength:
- The use of standard deviation levels provides an objective measure of trend strength and volatility.
4. How It Can Be Used in the Context of a Trading System
This indicator can serve as a versatile tool within a trading system for a range of things:
Trend Confirmation:
- A positive Z-Score can confirm an uptrend, while a negative Z-Score can confirm a downtrend, providing traders with signals to enter or exit trades.
Oversold/Overbought Conditions:
- Extreme Z-Score levels can indicate overbought or oversold conditions, suggesting potential reversals or pullbacks.
Volatility Assessment:
- The standard deviation levels can help traders assess market volatility, with wider bands indicating higher volatility.
5. How It Can Be Used for Trend Following
For trend following strategies, this indicator can be particularly useful:
Trend Strength Indicator:
- By monitoring the Z-Score's distance from zero, traders can gauge the strength of the current trend, with larger absolute values indicating stronger trends.
Directional Bias:
- Positive Z-Scores can be used to establish a bullish bias, while negative Z-Scores can establish a bearish bias, guiding trend following entries and exits.
Color-Coding for Trend Changes :
- The adaptive coloring of the indicator based on the rate of change and extreme levels provides visual cues for potential trend reversals or continuations.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
This is using the Midline Crossover:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Gold Friday Anomaly StrategyThis script implements the " Gold Friday Anomaly Strategy ," a well-known historical trading strategy that leverages the gold market's behavior from Thursday evening to Friday close. It is a backtesting-focused strategy designed to assess the historical performance of this pattern. Traders use this anomaly as it captures a recurring market tendency observed over the years.
What It Does:
Entry Condition: The strategy enters a long position at the beginning of the Friday trading session (Thursday evening close) within the defined backtesting period.
Exit Condition: Friday evening close.
Backtesting Controls: Allows users to set custom backtesting periods to evaluate strategy performance over specific date ranges.
Key Features:
Custom Backtest Periods: Easily configurable inputs to set the start and end date of the backtesting range.
Fixed Slippage and Commission Settings: Ensures realistic simulation of trading conditions.
Process Orders on Close: Backtesting is optimized by processing orders at the bar's close.
Important Notes:
Backtesting Only: This script is intended purely for backtesting purposes. Past performance is not indicative of future results.
Live Trading Recommendations: For live trading, it is highly recommended to use limit orders instead of market orders, especially during evening sessions, as market order slippage can be significant.
Default Settings:
Entry size: 10% of equity per trade.
Slippage: 1 tick.
Commission: 0.05% per trade.
[blackcat] L2 VWAP CCI Trading SystemLevel: 2
Background
Volume-Weighted Average Price (VWAP) is a trading benchmark used by traders that indicates the average price that a security has traded for throughout the day based on volume and price. This is important as it gives traders insight into the trend and value of a security.
The Commodity Channel Index (CCI) indicator was created to identify bullish and bearish market cycles, as well as to define market turning points and the strongest and weakest market periods. CCI was developed for commodities and quickly found application in other markets, including forex.
Function
blackcat L2 VWAP CCI Trading System is an innovative indicator that combines vwap and cci indicator together. Not only long and short entries can be disclosed, but also the overbought and oversold zones are clearly observed.
Key Signal
cci ---> vwap cci indicator output
long --> long entry condition
short --> short entry condition
backtest --> indicator backtest scheme "NLX-L3 Backtest" required input source for strategy backtest
longentry --> visual long entry
shortentry --> visual short entry
Pros and Cons
Pros:
1. exact long and short entries are produced by overbought and oversold conditions
2. support "NLX-L3 Backtest" framework
Cons:
1. noise may be produced under extreme market condition
2. due to this is un-optimized version, time frame and trading pairs need to be selected
Remarks
Courtesy of @nilux "NLX-L3 Backtest" easy backtest framework for dummies.
Step by step backtest guide with "NLX-L3 Backtest" framework:
STEP1: Add this indicator into your chart
STEP2: Add "NLX-L3 Backtest" into your chart
STEP3: Click "Settings" gear icon of "NLX-L3 Backtest" to select "Select L2 Indicator" in the 1st line as "blackcat L2 VWAP CCI Trading System: backtest"
STEP4: Configure your backtest other settings under "NLX-L3 Backtest" framework
STEP5: Click "OK" and view the results in "Strategy Tester" tab
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Customizable MACD (how to detect a strong convergence)Helloooo traders
I wondered once if a MACD was based on an EMA/EMA/SMA or SMA/SMA/EMA (or WHATEVA/WHATEVA/WHATEVA).
Seems they're so many alternatives out there.
I decided to empower my audience more by choosing the type of moving averages you want for your MACD.
More options doesn't always mean better performance - but who knows - some might find a config that they like with it for their favorite asset/timeframe.
I added also a multi-timeframe component because I'm a nice guy ^^
Convergence is my BEST friend
An oscillator (like MACD) is to measure how strong a momentum is - generally, traders use those indicators to confirm a trend.
So understand that a MACD (or any other indicator not based on convergence ) won't likely be sufficient for doing great on the market.
Combined with your favorite indicator, however, you may get great results.
My indicators fav cocktail is mixing :
1) an oscillator (momentum confirmation)
2) a trendline/key level break (momentum confirmation)
3) adding-up on a different trading method but still converging with the first entry.
The reason I'm deep with convergence detection is because I'm obsessed with removing those fakeout signals. You know which ones I'm talking about :)
Those trades when the market goes sideways but our capital goes South (pun 100% intended) - 2 days later, the price hasn't changed much but some lost some capital due to fees, being overexposed, buying the top/selling the bottom of a range they didn't identify.
It's publicly known that ranges are the worst traders' enemy. It's boring, not fun, and .... end up moving in the direction we expected when we go to sleep or outside.
NO ONE/BROKER/EX-GF is tracking your computer - I checked also for mine as it happened for me way too often in the past.
I surely preferred blaming a few external unknown conditions than improving my TA back in the days #bad #dave
But my backtest sir...
Our backtests show what they're being told to show . A backtest without a stop-loss/hard exit logic will show incredible results.
Then trying that backtest with live trading is like in the Matrix movie - discovering the real world is tough and we must choose between the blue pill (learning how to evaluate properly risk/opportunity caught) and the red pill (increasing the position sizing, not setting a stop loss, holding the positions hoping for the best)
Last few words
Convergences aren't invented because it's cool to mix indicators with others. (it is actually and even fun)
They're created to remove most of the fakeouts . For those that can't be removed - a strong risk management would cut most of the remaining potential big losses.
No system works 100% of the time - so a convergence system needs a back-up plan in case the converged signal is wrong (could be stop-loss, hard exit, reducing position sizing, ...)
Wishing you the BEST and happy beginning of your week
Daveatt
LANZ Strategy 4.0 [Backtest]🔷 LANZ Strategy 4.0 — Strategy Execution Based on Confirmed Structure + Risk-Based SL/TP
LANZ Strategy 4.0 is the official backtesting engine for the LANZ Strategy 4.0 trading logic. It simulates real-time executions based on breakout of Strong/Weak Highs or Lows, using a consistent structural system with SL/TP dynamically calculated per trade. With integrated risk management and lot size logic, this script allows traders to validate LANZ Strategy 4.0 performance with real strategy metrics.
🧠 Core Components:
Confirmed Breakout Entries: Trades are executed only when price breaks the most recent structural level (Strong High or Strong Low), detected using swing pivots.
Dynamic SL and TP Logic: SL is placed below/above the breakout point with a customizable buffer. TP is defined using a fixed Risk-Reward (RR) ratio.
Capital-Based Risk Management: Lot size is calculated based on account equity, SL distance, and pip value (e.g. $10 per pip on XAUUSD).
Clean and Controlled Executions: Only one trade is active at a time. No new entries are allowed until the current position is closed.
📊 Visual Features:
Automatic plotting of Entry, SL, and TP levels.
Full control of swing sensitivity (swingLength) and SL buffer.
SL and TP lines extend visually for clarity of trade risk and reward zones.
⚙️ How It Works:
Detects pivots and classifies trend direction.
Waits for breakout above Strong High (BUY) or below Strong Low (SELL).
Calculates dynamic SL and TP based on buffer and RR.
Computes trade size automatically based on risk per trade %.
Executes entry and manages exits via strategy engine.
📝 Notes:
Ideal for evaluating the LANZ Strategy 4.0 logic over historical data.
Must be paired with the original indicator (LANZ Strategy 4.0) for live trading.
Best used on assets with clear structural behavior (gold, indices, FX).
📌 Credits:
Backtest engine developed by LANZ based on the official rules of LANZ Strategy 4.0. This script ensures visual and logical consistency between live charting and backtesting simulations.
CAGR - Candle based BackTesterThe "CAGR - Candle based BackTester" is a tool for traders and investors seeking precise insights into individual candle performance!
Do you want to backtest based on candles and understand their CAGR? Curious about the average CAGR of all candles? Interested in comparing how an individual candle performs against others? Then this tool is your go-to solution.
How It Works:
Candle Selection: Specify a start date, and watch as the script tracks investments from that point forward.
Dynamic Calculations: Experience real-time CAGR calculations that adapt as market conditions evolve.
CAGR Display: At the final candle, gain insights into individual CAGR, average CAGR of all candles, alpha (difference), and outperformance percentage—all conveniently displayed for informed decision-making.
Key Features:
Accurate Candle-based CAGR Calculation: Gain clarity on investment performance with precise CAGR metrics.
Lumpsum Investment Tracking: Track lumpsum investments seamlessly with detailed share and investment calculations.
Outperformance Metrics: Measure how your investment performs relative to others with dedicated outperformance metrics.
User-Friendly Visualization: Access intuitive charts and visuals that simplify complex financial data.
Price Legs: Time & Distance. Measuring moves in time & price-Tool to measure price legs in terms of both time and price; gives an idea of frequency of market movements and their typical extent and duration.
-Written for backtesting: seeing times of day where setups are most likely to unfold dynamically; getting an idea of typical and minimum sizes of small/large legs.
-Two sets of editable lookback numbers to measure both small and large legs independently.
-Works across timeframes and assets (units = mins/hours/days dependent on timeframe; units = '$' for indices & futures, 'pips' for FX).
~toggle on/off each set of bull/bear boxes.
~choose lookback/forward length for each set. Increase number for larger legs, decrease for smaller legs.
(for assets outside of the big Indices and FX, you may want to edit the multiplier, pMult, on lines 23-24)
small legs
large legs
Real Candles Heikin Ashi (HA) Candle functionsThis script plots both real and HA candles regardless or which are used on the chart in TV settings.
(and has the functions for you to use.)
Lots of people seem to misunderstand backtesting (or scam people) based on HA candles.
Backtesting with HA candles leads to impossible trades. ALWAYS backtest with real candles.
That doesn't mean you might not want to look at HA candle values to make trading decisions.
Add the code below to calculate HA candles from real and use that in your HA trading algo,
but test it on real charts.
Intellitrader - Buy Random BACKTESTERI created a little backtester that it combines some of what we need to backtest to finetune a good strategy for Intellitrader.
RSI
STOCH
STOCHRSI
CCI
Price Change
Divergence BacktesterThere is n number of possible ways in which we can backtest divergence and this is just a start :)
In this script, we are trying to count how many times the pivots made HH, HL, LH, LL after a particular divergence state.
An example of using data is as below:
The script keeps track of each pivot sentiment and resulting next pivot state. As mentioned in the chart snapshot, we can look at two of the previous pivot states and collect stats on how each of these state impacted price action.
As mentioned before, this is just tip of iceberg. Further combinations for which we can do backtest are:
1. m X n combinations of last pivot and last to last pivot divergence state
2. divergence combined with double divergence state.
Only issue to explore further is lack of space on the chart as tables can take up huge space.
PS: As you can see based on historical stats, probability of divergence impacting the change of trend is very low in most cases.
ATR BacktesterATR backtester... input the desired number of bars backwards (I'd recommend 100 or so), and then it'll spit out in the columns on the right side of the screen how many times each ATR was hit. Helps to tell at a glance where bullish and bearish is for the stock. May not be insanely useful since you can just look at the chart, but feel free to use the code yourself for something.
Key Levels CustomTF + Backtest: SpacemanBTCKey Levels Backtest, same logic as the key levels script, provide levels based:
High, Low, Mid and Close.
This was requested, took a long time to post as I fell sick and was given a lot of Dev Work.
Hope this helps those who use it, very useful to see liquidity grabs in my opinion.
Input time in minutes!
Result of a user request.
Configurable BB+RSI+Aroon strategy backtest for binary optionsI wanted to share this strategy that I use myself for binary options trading. After trading binary options for several years I have learned that every single day is unique... assets behave differently every single day. So, when I start the day I want to know which is the optimum combination of parameters in my indicators that will give me the signals I want during the day and I get that by doing a quick backtest of the parameters combination in a specific asset that same day. When trading Binary Options I usually do 3 or 4 trades max per day and, yes, there are moments in which even with the right backtest data the signals fail (I strongly believe that there is no strategy that guarantees 100% success in any type of trade, and this one here is not an exception - but has worked well with some assets). So, here is my contribution to improve your productivity by automating a bit that backtesting part.
How this script works?
It is a simple price crossunder / crossover Bollinger Bands (BB) with a confirmation from RSI overbought / oversold signals and a fast Aroon. You will see the BB plotted with its confirmations:
(1) a blue circle that plots in the chart when the price is coming back inside the channel (within the Bollinger Bands)
(2) an orange square that plots in the chart when the RSI is coming back from the overbought or oversold areas
(3) a triangle that could be red or green depending on the Aroon confirmation: Red if Aroon Down is crossing down Aroon Up or green if vice versa.
The strategy will call for long (Call) if:
(1) the price is crossing over the lower band of the Bollinger Bands, coming back inside the channel
(2) Aroon Up is crossing or has crossed above Aroon Down
(3) RSI is crossing over the oversold limit
Consequently, the strategy will call for a short (Put) if:
(1) the price is crossing down the upper band of the Bollinger Bands, coming back inside the channel
(2) Aroon Down is crossing or has crossed below Aroon Up
(3) RSI is crossing under the overbought limit
You can configure:
1. Aroon length (keep it as fast as possible: 3, 4 or 5 are recommended values)
2. The point where Aroon Up and Aroon Down cross to make the signal valid (50 is by default. It could also be 25 or 75)
3. The RSI length
4. RSI Overbought and Oversold limits (they do not need to be symmetric: you can use 29 and 93, for example)
5. Bollinger Bands length and standard deviation
6. Number of bars to keep your option open. Depending on the timeframe used, this will determine the time you will keep your binary option open. If you are in a 1 min chart and keep this parameter in 3, then you will need to configure your binary option to expire in 3 minutes.
How to evaluate your backtest?
In Binary Options you only need the success rate, so what I do is that when I am manually updating the parameters I keep my strategy tester window open checking the winning trades vs losing trades ratio ("Percent Profitable"). I personally will only keep an asset monitored looking for signals that day if the Percent Profitable on the backtest of the same day is above 80%.
Regarding the code: it is open, public and free. No need to ask for permission if you want to copy+paste and use it in whole or parts.
Happy pip hunting!
-marco
LANZ Strategy 1.0 [Backtest]🔷 LANZ Strategy 1.0 — Time-Based Session Trading with Smart Reversal Logic and Risk-Controlled Limit Orders
This backtest version of LANZ Strategy 1.0 brings precision to session-based trading by using directional confirmation, pre-defined risk parameters, and limit orders that execute overnight. Designed for the 1-hour timeframe, it allows traders to evaluate the system with configurable SL, TP, and risk settings in a fully automated environment.
🧠 Core Strategy Logic:
1. Directional Confirmation at 18:00 NY:
At 18:00 NY, the system compares the 08:00 open vs the 18:00 close:
If the direction matches the previous day, the signal is reversed.
If the direction differs, the current day's trend is kept.
This logic is designed to avoid momentum exhaustion and capture corrective reversals.
2. Entry Level Definition:
Based on the confirmed direction:
For BUY, the Low of the day is used as Entry Point (EP).
For SELL, the High of the day becomes EP.
The system plots a Stop Loss and Take Profit based on user-defined pip inputs (default: SL = 18 pips, TP = 54 pips → RR 1:3).
3. Time-Limited Entry Execution (LIMIT Orders):
Orders are sent after 18:00 NY and can be triggered anytime between 18:00 and 08:00 NY.
If EP is not touched before 08:00, the order is automatically cancelled.
4. Manual Close Feature:
If the trade is still open at the configured hour (default 09:00 NY), the system closes all positions, simulating realistic intraday exit scenarios.
5. Lot Size Calculation Based on Risk:
Lot size is dynamically calculated using the account size, risk percentage, and SL distance.
This ensures consistent risk exposure regardless of market volatility.
⚙️ Step-by-Step Flow:
08:00 NY → Captures the open of the day.
18:00 NY → Confirms direction and defines EP, SL, and TP.
After 18:00 NY → If conditions are met, a LIMIT order is placed at EP.
Between 18:00–08:00 NY → If price touches EP, the trade is executed.
At 08:00 NY → If EP wasn’t touched, the order is cancelled.
At Configured Manual Close Time (default 09:00 NY) → All open positions are force-closed if still active.
🧪 Backtest Settings:
Timeframe: 1-hour only
Order Type: strategy.entry() with limit=
SL/TP Configurable: Yes, in pips
Risk Input: % of capital per trade
Manual Close Time: Fully adjustable (default 09:00 NY)
👨💻 Credits:
Developed by LANZ
Strategy logic and trading concept built with clarity and precision.
Code structure and documentation by Kairos, your AI trading assistant.
Designed for high-confidence execution and clean backtesting performance.
LANZ Strategy 3.0 [Backtest]🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Scalping Strategy
LANZ Strategy 3.0 is a precision-engineered backtesting tool tailored for intraday traders who rely on the Asian session range to determine directional bias. This strategy implements dynamic Fibonacci projections and strict time-window validation to simulate a clean and disciplined trading environment.
🧠 Core Components:
Asian Range Bias Definition: Direction is established between 01:15–02:15 a.m. NY time based on the candle’s close in relation to the midpoint of the Asian session range (18:00–01:15 NY).
Limit Order Execution: Only one trade is placed daily, using a limit order at the Asian range high (for sells) or low (for buys), between 01:15–08:00 a.m. NY.
Fibonacci-Based TP/SL:
Original Mode: TP = 2.25x range, SL = 0.75x range.
Optimized Mode: TP = 1.95x range, SL = 0.65x range.
No Trade After 08:00 NY: If the limit order is not executed before 08:00 a.m. NY, it is canceled.
Fallback Logic at 02:15 NY: If the market direction misaligns with the setup at 02:15 a.m., the system re-evaluates and can re-issue the order.
End-of-Day Closure: All positions are closed at 15:45 NY if still open.
📊 Backtest-Ready Design:
Entries and exits are executed using strategy.entry() and strategy.exit() functions.
Position size is fixed via capital risk allocation ($100 per trade by default).
Only one position can be active at a time, ensuring controlled risk.
📝 Notes:
This strategy is ideal for assets sensitive to the Asian/London session overlap, such as Forex pairs and indices.
Easily switch between Fibonacci versions using a single dropdown input.
Fully deterministic: all entries are based on pre-defined conditions and time constraints.
👤 Credits:
Strategy developed by rau_u_lanz using Pine Script v6. Built for traders who favor clean sessions, directional clarity, and consistent execution using time-based logic and Fibonacci projections.
Breakout Probability (Expo)█ Overview
Breakout Probability is a valuable indicator that calculates the probability of a new high or low and displays it as a level with its percentage. The probability of a new high and low is backtested, and the results are shown in a table— a simple way to understand the next candle's likelihood of a new high or low. In addition, the indicator displays an additional four levels above and under the candle with the probability of hitting these levels.
The indicator helps traders to understand the likelihood of the next candle's direction, which can be used to set your trading bias.
█ Calculations
The algorithm calculates all the green and red candles separately depending on whether the previous candle was red or green and assigns scores if one or more lines were reached. The algorithm then calculates how many candles reached those levels in history and displays it as a percentage value on each line.
█ Example
In this example, the previous candlestick was green; we can see that a new high has been hit 72.82% of the time and the low only 28.29%. In this case, a new high was made.
█ Settings
Percentage Step
The space between the levels can be adjusted with a percentage step. 1% means that each level is located 1% above/under the previous one.
Disable 0.00% values
If a level got a 0% likelihood of being hit, the level is not displayed as default. Enable the option if you want to see all levels regardless of their values.
Number of Lines
Set the number of levels you want to display.
Show Statistic Panel
Enable this option if you want to display the backtest statistics for that a new high or low is made. (Only if the first levels have been reached or not)
█ Any Alert function call
An alert is sent on candle open, and you can select what should be included in the alert. You can enable the following options:
Ticker ID
Bias
Probability percentage
The first level high and low price
█ How to use
This indicator is a perfect tool for anyone that wants to understand the probability of a breakout and the likelihood that set levels are hit.
The indicator can be used for setting a stop loss based on where the price is most likely not to reach.
The indicator can help traders to set their bias based on probability. For example, look at the daily or a higher timeframe to get your trading bias, then go to a lower timeframe and look for setups in that direction.
-----------------
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!
NoNonsense Forex - high timeframe trading absurd NON-REPAINTINGSome time ago I bumped into NoNonsense Forex - pretty good-looking course with well-designed videos, reasonable rules, etc. Nice explanatory videos, not selling anything, building indicators-only strategy. But there was one thing that really annoyed me - it was supposed to work only on Daily timeframe. What is the point in trading such high timeframe, if decisions changing market direction are playing out within 1 minute? What is the point in evaluating trades from 1994 if we are 25 years later?
Anyway, I have developed this strategy, which is:
- non-repainting
- not using trailing-stop
- not using any other known TradingView backtest bugs
And I'm showing it as an example of OVERFITTING. Backtesting results look absurd: 100% profitable. But if you change any of the many parameters in the Settings popup, they will turn into disaster. It means, the rules of this strategy are very fragile. Don't trade this! Remember about backtesting rule #1: past results do not guarantee success in the future.
I'm giving this strategy out with the source code. Feel free to do anything you want with it. But if you find parameters or modifications on, which allow profitable trading on lower timeframes, don't be shy, let me know :)
*********
Forex / Indices / Commodities traders who want to start AUTO-TRADING might want to take a look at "TradingConnector", which allows no-latency trades execution from TradingView to MT4/MT5.
Aroon and ASH strategy - ETHERIUM [IkkeOmar]Intro:
This post introduces a Pine Script strategy, as an example if anyone needs a push to get started. This example is a strategy on ETH, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay. This strategy combines two technical indicators: Aroon and Absolute Strength Histogram (ASH).
Overview:
The strategy employs the Aroon indicator alongside the Absolute Strength Histogram (ASH) to determine market trends and potential trade setups. Aroon helps identify the strength and direction of a trend, while ASH provides insights into the strength of momentum. By combining these indicators, the strategy aims to capture profitable trading opportunities in Ethereum markets. Normally when developing strats using indicators, you want to find some good indicators, but you NEED to understand their strengths and weaknesses, other indicators can be incorporated to minimize the downs of another indicator. Try to look for synergy in your indicators!
Indicator settings:
Aroon Indicator:
- Two sets of parameters are used for the Aroon indicator:
- For Long Positions: Aroon periods are set to 56 (upper) and 20 (lower).
- For Short Positions: Aroon periods are set to 17 (upper) and 55 (lower).
Absolute Strength Histogram (ASH):
ASH is calculated with a length of 9 bars using the closing price as the data source.
Trading Conditions:
The strategy incorporates specific conditions to initiate and exit trades:
Start Date:
Traders can specify the start date for backtesting purposes.
Trade Direction:
Traders can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
1. Long Position Entry: A long position is initiated when the Aroon indicator crosses over (crossover) the lower Aroon threshold, indicating a potential uptrend.
2. Long Position Exit: A long position is closed when the Aroon indicator crosses under (crossunder) the lower Aroon threshold.
3. Short Position Entry: A short position is initiated when the Aroon indicator crosses under (crossunder) the upper Aroon threshold, signaling a potential downtrend.
4. Short Position Exit: A short position is closed when the Aroon indicator crosses over (crossover) the upper Aroon threshold.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Key Performance IndicatorWe are happy to introduce the Key Performance Indicator by Detlev Matthes. This is an amazing tool to quantify the efficiency of a trading system and identify potential spots of improvement.
Abstract
A key performance indicator with high explanatory value for the quality of trading systems is introduced. Quality is expressed as an indicator and comprises the individual values of qualitative aspects. The work developing the KPI was submitted for the 2017 VTAD Award and won first prize.
Introduction
Imagine that you have a variety of stock trading systems from which to select. During backtesting, each trading system will deliver different results with regard to its indicators (depending on, inter alia, its parameters and the stock used). You will also get different forms of progression for profit development. It requires great experience to select the “best” trading system from this variety of information (provided by several indicators) and significantly varying equity progression forms. In this paper, an indicator will be introduced that expresses the quality of a trading system in just one figure. With such an indicator, you can view the results of one backtest at a glance and also more easily compare a variety of backtesting results with one another.
If you are interested in learning more about the calculations behind this indicator then I have included a link to the english version of his research paper.
Along with this, we now offer indicator development services. If you are interested in learning more then feel free to reach out to get a quote for your project.
**Please note that we have NOT inputted any real strategy into the code and therefore it is not producing any real value. Feel free to change the code as desired to test any strategy!**
drive.google.com
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.
[Autoview][BackTest]Dual MA Ribbons R0.12 by JustUncleLThis is an implementation of a strategy based on two MA Ribbons, a Fast Ribbon and a Slow Ribbon. This strategy can be used on Normal candlestick charts or Renko charts (if you are familiar with them).
The strategy revolves around a pair of scripts: One to generate alerts signals for Autoview and one for Backtesting, to tune your settings.
The risk management options are performed within the script to set SL(StopLoss), TP(TargetProfit), TSL(Trailing Stop Loss) and TTP (Trailing Target Profit). The only requirement for Autoview is to Buy and Sell as directed by this script, no complicated syntax is required.
The Dual Ribbons are designed to capture the inferred behavior of traders and investors by using two groups of averages:
> Traders MA Ribbon: Lower MA and Upper MA (Aqua=Uptrend, Blue=downtrend, Gray=Neutral), with center line Avg MA (Orange dotted line).
> Investors MAs Ribbon: Lower MA and Upper MA (Green=Uptrend, Red=downtrend, Gray=Neutral), with center line Avg MA (Fuchsia dotted line).
> Anchor time frame (0=current). This is the time frame that the MAs are calculated for. This way 60m MA Ribbons can be viewed on a 15 min chart to establish tighter Stop Loss conditions.
Trade Management options:
Option to specify Backtest start and end time.
Trailing Stop, with Activate Level (as % of price) and Trailing Stop (as % of price)
Target Profit Level, (as % of price)
Stop Loss Level, (as % of price)
BUY green triangles and SELL dark red triangles
Trade Order closed colour coded Label:
>> Dark Red = Stop Loss Hit
>> Green = Target Profit Hit
>> Purple = Trailing Stop Hit
>> Orange = Opposite (Sell) Order Close
Trade Management Indication:
Trailing Stop Activate Price = Blue dotted line
Trailing Stop Price = Fuschia solid stepping line
Target Profit Price = Lime '+' line
Stop Loss Price = Red '+' line
Dealing With Renko Charts:
If you choose to use Renko charts, make sure you have enabled the "IS This a RENKO Chart" option, (I have not so far found a way to Detect the type of chart that is running).
If you want non-repainting Renko charts you MUST use TRADITIONAL Renko Bricks. This type of brick is fixed and will not change size.
Also use Renko bricks with WICKS DISABLED. Wicks are not part of Renko, the whole idea of using Renko bricks is not to see the wick noise.
Set you chart Time Frame to the lowest possible one that will build enough bricks to give a reasonable history, start at 1min TimeFrame. Renko bricks are not dependent on time, they represent a movement in price. But the chart candlestick data is used to create the bricks, so lower TF gives more accurate Brick creation.
You want to size your bricks to 2/1000 of the pair price, so for ETHBTC the price is say 0.0805 then your Renko Brick size should be about 2*0.0805/1000 = 0.0002 (round up).
You may find there is some slippage in value, but this can be accounted for in the Backtest by setting your commission a bit higher, for Binance for example I use 0.2%
Special thanks goes to @CryptoRox for providing the initial Risk management Framework in his "How to automate this strategy for free using a chrome extension" example.
