VuManChu/Noski B Backtester (Small Green/Red Dot)This is a backtest version of Vumanchu's original script Market Cipher-B. All credit goes to his original coding.
This has been coded to backtest Small Red/Green dot entries only, so please keep that in mind when using.
Hope this is helpful!
חפש סקריפטים עבור "backtest"
NoSKi MC-B Backtester (Green/Red Dot)This is a backtest version of Vumanchu's original script Market Cipher-B. All credit goes to his original coding.
This has been coded to backtest Red/Green dot entries only, so please keep that in mind when using.
Hope this is helpful!
Goose-X Auto Backtester Automated backtest strategy script for Goose-X 15 min indic. // Backtest purpose only
Megalodon Pro Automated Shorter Term Trader BacktesterSTRATEGY
When to buy: Green bar - Orange bar Closes
When to sell: Purple bar closes
Stop to trailing: No
Stop loss: No
Commission Rate: 1%
Willing to risk per trade: 10%
Maximum possible trades in one direction: 10
RESULTS
Net Profit without 1% commission: 112.64%
Net Profit with 1% commission: 103.92%
Starting Balance: $100,000
Profits Made: $103,918.38
New Balance with 1% commission: $203,918.38
Dates traded: 3/17/2019 and 8/3/2019
Total Close Trades: 80
Percent Profitable: 98.75%
Profit Factor: 152.158
Max Drawdown: 0.35% - $745.14
Buy & Hold Return: 174.66%
Commission Paid: $9621.46
Total Open Trades: 10
Number of Winning Trades: 79
Number of Losing Trades: 1
Avg Win Trade: 1.33%
Avg. Lose Trade: 0.92%
Largest Win Trade: 2.77%
Let me know what you guys think about the results?
Due to the tradingview's limitations on providing the shorter time frame price data, we had to provide a 60 minute time frame backtesting results.
The shorter time frames including 1 minute and 15 minutes backtesting results are way more accurate and precise than 60 minutes time frame results.
Megalodon Trading
Enlightening the Modern Investors
Profitable Moving Average CrossoverHi everyone!
Introduction
A popular use for moving averages is to develop simple trading systems based on moving average crossovers. A trading system using two moving averages would give a buy signal when the shorter (faster) moving average advances above the longer (slower) moving average. A sell signal would be given when the shorter moving average crosses below the longer moving average. The speed of the systems and the number of signals generated will depend on the length of the moving averages.
There are many types of averages that are based on different techniques. Each type has its drawbacks and merits. And if we decide to choose a certain type of average for the trading system, then how do we know that our choice is optimal?
What is this tool?
This tool will help you to choose this type to create the most profitable trading system based on crossovers for the specified periods. It backtests pairs of each type throughout the whole instrument's history and shows Net Profit curves as a result. So, the type of the most profitable crossover system will be at the top of list of labels on the chart. (Click on the price scale, point to "Labels" and switch off "No Overlapping Labels" option).
Settings
The main settings are periods for each type pair of fast and slow moving averages.
Additionally, it allows to customize some multi-parametric moving averages such as JMA, ALMA, McGinley Dynamic, Adaptive Laguerre Filter etc.
1st Period (default: 14 )
2nd Period (default: 50 )
1st ALF Median Length (default: 5 )
2nd ALF Median Length (default: 5 )
1st ALMA Offset (default: 0.85 )
1st ALMA Sigma (default: 6 )
2nd ALMA Offset (default: 0.85 )
2nd ALMA Sigma (default: 6 )
1st HF Scaling Factor (default: 3 )
2nd HF Scaling Factor (default: 3 )
1st JMA Phase (default: 50 )
2nd JMA Phase (default: 50 )
1st MD Constant (default: 0.6 )
2nd MD Constant (default: 0.6 )
1st MHLMA Range (default: 10 )
2nd MHLMA Range (default: 10 )
1st PWMA Power (default: 2 )
2nd PWMA Power (default: 2 )
1st REMA Lambda (default: 0.5 )
2nd REMA Lambda (default: 0.5 )
1st RMF Median Length (default: 5 )
2nd RMF Median Length (default: 5 )
1st T3 Alpha (default: 0.7 )
2nd T3 Alpha (default: 0.7 )
MAMA & FAMA Fast Limit (default: 0.5 )
MAMA & FAMA Slow Limit (default: 0.05 )
Supported types of averages and filters (use short titles to match averages on the chart)
AHMA , Ahrens MA (by Richard D. Ahrens)
ALMA , Arnaud Legoux MA (by Arnaud Legoux and Dimitris Kouzis-Loukas)
ALF , Adaptive Laguerre Filter (by John F. Ehlers)
ARSI , Adaptive RSI
BF2 , Butterworth Filter with 2 poles
BF3 , Butterworth Filter with 3 poles
DEMA , Double Exponential MA (by Patrick G. Mulloy)
DWMA , Double Weighted (Linear) MA
EDCF , Ehlers Distance Coefficient Filter (by John F. Ehlers)
EHMA , Exponential Hull MA
EMA , Exponential MA
EVWMA , Elastic Volume Weighted MA (by Christian P. Fries)
FRAMA , Fractal Adaptive MA (by John F. Ehlers)
GF1 , Gaussian Filter with 1 pole
GF2 , Gaussian Filter with 2 poles
GF3 , Gaussian Filter with 3 poles
GF4 , Gaussian Filter with 4 poles
HFSMA , Hampel Filter on Simple Moving Average
HFEMA , Hampel Filter on Exponential Moving Average
HMA , Hull MA (by Alan Hull)
HWMA , Henderson Weighted MA (by Robert Henderson)
IDWMA , Inverse Distance Weighted MA
IIRF , Infinite Impulse Response Filter (by John F. Ehlers)
JMA , Jurik MA (by Mark Jurik, )
LF , Laguerre Filter (by John F. Ehlers)
LMA , Leo MA (by ProRealCode' user Leo)
LSMA , Least Squares MA (Moving Linear Regression)
MAMA & FAMA , (by John F. Ehlers, special case that used as a benchmark)
MD , McGinley Dynamic (by John R. McGinley)
MHLMA , Middle-High-Low MA (by Vitali Apirine)
PWMA , Parabolic Weighted MA
REMA , Regularized Exponential MA (by Chris Satchwell)
RMA , Running MA (by J. Welles Wilder)
RMF , Recursive Median Filter (by John F. Ehlers)
RMTA , Recursive Moving Trend Average (by Dennis Meyers)
SHMMA , Sharp Modified MA (by Joe Sharp)
SMA , Simple MA
SSF2 , Super Smoother Filter with 2 poles (by John F. Ehlers)
SSF3 , Super Smoother Filter with 3 poles (by John F. Ehlers)
SWMA , Sine Weighted MA
TEMA , Triple Exponential MA (by Patrick G. Mulloy)
TMA , Triangular MA (generalized by John F. Ehlers)
T3 , (by Tim Tillson)
VIDYA , Variable Index Dynamic Average (by Tushar S. Chande)
VWMA , Volume Weighted MA (by Buff P. Dormeier)
WMA , Weighted (Linear) MA
ZLEMA , Zero Lag Exponential MA (by John F. Ehlers and Ric Way)
NOTE : The results may vary on different tickers and timeframes.
If you see the preview result it doesn't mean that these crossovers will be profitable on other instruments and timeframes. This is a normal situation because time series and their characteristics differ.
I know that because I tested this tool before publishing.
NOTE 2 : You can use this tool by yourself and experiment with it, or you can order a study and I will share the spreadsheet that contains results with you.
Good luck!
LANZ Strategy 5.0 [Backtest]🔷 LANZ Strategy 5.0 — Rule-Based BUY Logic with Time Filter, Session Limits and Auto SL/TP Execution
This is the backtest version of LANZ Strategy 5.0, built as a strategy script to evaluate real performance under fixed intraday conditions. It automatically places BUY and SELL trades based on structured candle confirmation, EMA trend alignment, and session-based filters. The system simulates real-time execution with precise Stop Loss and Take Profit levels.
📌 Built for traders seeking to simulate clean intraday logic with fully automated entries and performance metrics.
🧠 Core Logic & Strategy Conditions
✅ BUY Signal Conditions:
Price is above the EMA200
The last 3 candles are bullish (close > open)
The signal occurs within the defined session window (NY time)
Daily trade limit has not been exceeded
If all are true, a BUY order is executed at market, with SL and TP set immediately.
🔻 SELL Signal Conditions (Optional):
Exactly inverse to BUY (below EMA + 3 bearish candles). Disabled by default.
🕐 Operational Time Filter (New York Time)
You can fully customize your intraday window:
Start Time: e.g., 01:15 NY
End Time: e.g., 16:00 NY
The system evaluates signals only within this range, even across midnight if configured.
🔁 Trade Management System
One trade at a time per signal
Trades include a Stop Loss (SL) and Take Profit (TP) based on pip distance
Trade result is calculated automatically
Each signal is shown with a triangle marker (BUY only, by default)
🧪 Backtest Accuracy
This version uses:
strategy.order() for entries
strategy.exit() for SL and TP
strategy.close_all() at the configured manual closing time
This ensures realistic behavior in the TradingView strategy tester.
⚙️ Flow Summary (Step-by-Step)
On every bar, check:
Is the time within the operational session?
Is the price above the EMA?
Are the last 3 candles bullish?
If conditions met → A BUY trade is opened:
SL = entry – X pips
TP = entry + Y pips
Trade closes:
If SL or TP is hit
Or at the configured manual close time (e.g., 16:00 NY)
📊 Settings Overview
Timeframe: 1-hour (ideal)
SL/TP: Configurable in pips
Max trades/day: User-defined (default = 99 = unlimited)
Manual close: Adjustable by time
Entry type: Market (not limit)
Visuals: Plotshape triangle for BUY entry
👨💻 Credits:
💡 Developed by: LANZ
🧠 Strategy logic & execution: LANZ
✅ Designed for: Clean backtesting, clarity in execution, and intraday logic simulation
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.
Heikin Ashi Smoothed Buy Sell with Filters Backtest What is the Heikin Ashi Smoothed Buy Sell with Filters Backtest ?
It is the backtesting version of the Heikin Ashi Smoothed Buy Sell with Filters indicator.
This Pine Script code defines a complex indicator used to determine buy-sell signals on financial charts. The indicator operates based on the smoothed version of Heikin Ashi and is fortified with various filters.
1. Parameters and Settings:
At the start of the code, there are a series of input parameters for the user to customize the indicator. These parameters include:
Trend Filter: Checks whether it is above or below the long-term moving average.
Momentum Filter: Uses the RSI (Relative Strength Index) indicator to check if the market is overbought or oversold.
Volatility Filter: Evaluates the market's volatility level using the ATR (Average True Range) indicator.
Volume Filters: Uses various volume-related parameters to measure the strength of the trade signal.
Trade Settings: Specifies percentage values for target and stop-loss levels to be used in trading.
Moving Average Settings: Allows you to select which moving average to use and its duration.
2. Heikin Ashi Smoothed Calculations:
Heikin Ashi is a charting method used to more clearly represent price movements. The smoothed Heikin Ashi ensures smoother price movements.
3. Moving Average Calculations:
The indicator contains a function to calculate different types of moving averages. These moving averages are used to determine the market trend.
4. Filters:
This indicator includes a series of filters to enhance the quality of the signal. Filters help reduce false signals and produce more robust trading signals.
5. Buy-Sell Signals:
All these filters and calculations are brought together to determine potential buy and sell signals. Signals are triggered when all the specified conditions are met.
6. Chart Visualizations:
This indicator uses various plotting functions to visualize signals and trend information on the chart. This allows the user to easily see signals and the trend on the chart.
7. Trade Settings:
When buy and sell signals are triggered, this section checks if it has reached the specified targets and stop-loss levels.
8. Alerts:
This indicator also sends alerts to the user when specific conditions are met. This ensures that the user doesn't miss potential trading opportunities.
In conclusion, this Pine Script indicator produces buy-sell signals by analyzing market movements and applying various filters. Based on the smoothed version of Heikin Ashi, this indicator is useful for trend followers and is fortified with various filters, thus enhancing the quality of trading signals.
Heikin Ashi Smoothed Buy Sell with Filters Backtest Nedir?
Heikin Ashi Smoothed Buy Sell with Filters indikatörünün backtest yapan versiyonudur
Bu Pine Script kodu, finansal grafiklerde al-sat sinyallerini belirlemek için kullanılan karmaşık bir göstergeyi tanımlar. Gösterge, Heikin Ashi'nin yumuşatılmış sürümünü temel alarak çalışır ve çeşitli filtrelerle güçlendirilmiştir.
1. Parametreler ve Ayarlar:
Kodun başlangıcında, kullanıcının göstergeyi kişiselleştirmesi için bir dizi giriş parametresi bulunmaktadır. Bu parametreler şunları içerir:
Trend Filtresi: Uzun vadeli hareketli ortalamanın üstünde veya altında olup olmadığını kontrol eder.
Momentum Filtresi: RSI (Göreceli Güç Endeksi) göstergesini kullanarak piyasanın aşırı alım veya aşırı satım durumunu kontrol eder.
Oynaklık Filtresi: ATR (Ortalama Gerçek Aralık) göstergesi ile piyasanın oynaklık seviyesini değerlendirir.
Hacim Filtreleri: Ticaret sinyalinin gücünü ölçmek için hacimle ilgili çeşitli parametreleri kullanır.
Ticaret Ayarları: Ticarette kullanılacak hedef ve stop-loss seviyeleri için yüzdelik değerleri belirtir.
Hareketli Ortalama Ayarları: Hangi hareketli ortalamayı kullanacağınızı ve bu ortalamanın süresini seçmenizi sağlar.
2. Heikin Ashi Yumuşatılmış Hesaplamaları:
Heikin Ashi, fiyat hareketlerini daha net bir şekilde göstermek için kullanılan bir grafikleme yöntemidir. Yumuşatılmış Heikin Ashi, fiyat hareketlerinin daha pürüzsüz olmasını sağlar.
3. Hareketli Ortalama Hesaplamaları:
Gösterge, farklı türde hareketli ortalamaları hesaplamak için bir fonksiyon içerir. Bu hareketli ortalamalar, piyasa trendini belirlemek için kullanılır.
4. Filtreler:
Bu gösterge, sinyal kalitesini artırmak için bir dizi filtre içerir. Filtreler, yanlış sinyalleri azaltmaya yardımcı olur ve daha sağlam ticaret sinyalleri üretir.
5. Al-Sat Sinyalleri:
Tüm bu filtreler ve hesaplamalar, potansiyel al ve sat sinyallerini belirlemek için bir araya getirilir. Sinyaller, belirlenen koşulların tümü karşılandığında tetiklenir.
6. Grafik Görselleştirmeleri:
Bu gösterge, sinyalleri ve trend bilgisini grafik üzerinde görselleştirmek için çeşitli çizim fonksiyonları kullanır. Bu, kullanıcının grafik üzerinde kolayca sinyalleri ve trendi görmesini sağlar.
7. Ticaret Ayarları:
Alış ve satış sinyalleri tetiklendiğinde, bu bölüm belirlenen hedeflere ve stop-loss seviyelerine ulaşıp ulaşmadığını kontrol eder.
8. Uyarılar:
Bu gösterge ayrıca, belirli koşullar karşılandığında kullanıcıya uyarı gönderir. Bu, kullanıcının potansiyel ticaret fırsatlarını kaçırmamasını sağlar.
Sonuç olarak, bu Pine Script göstergesi, piyasa hareketlerini analiz ederek ve çeşitli filtreleri uygulayarak al-sat sinyalleri üretir. Heikin Ashi'nin yumuşatılmış sürümüne dayanan bu gösterge, trend takipçileri için kullanışlıdır ve çeşitli filtrelerle güçlendirilmiştir, böylece ticaret sinyallerinin kalitesi artar.
TradeMaster SignalsTrading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. To address this, we present a powerful indicator package designed to assist traders on their journey to success.
The TradeMaster indicator package encompasses a variety of trading strategies, including the SMC (Supply, Demand, and Price Action) approach, along with many other techniques. By leveraging concepts such as price action trading, support and resistance analysis, supply and demand dynamics, these indicators can empower traders to analyze entry and exit positions with precision. Unlike other forms of technical analysis that produce values or plots based on historical price data, Price Action brings you the facts straight from the source - the current price movements.
The indicator package consists of three powerful indicators that can be used individually or together to maximize trading effectiveness.
⭐ About the Signals Indicator
This indicator offers a unique opportunity for traders to design their own personalized trading strategy. It has a built-in backtesting system, which allows you to thoroughly analyze the performance of your strategy before implementing it in live trading. With the ability to customize and test your strategy using historical data, the Signals indicator empowers you to make data-driven decisions and refine your trading approach.
👉 How does it work?
The Signals indicator provides users with the ability to select trigger conditions and further narrow them down using confirmations.
Conditions are quantitative factors that influence the generation of signals on the chart and in the backtest table. You can enable multiple conditions to create a comprehensive set of criteria for signal generation.
Confirmations, on the other hand, are qualitative factors that selectively filter out conditions based on their alignment with the chosen confirmations. This helps refine the signals and provide more targeted trading opportunities. Multiple confirmations can be enabled to further enhance the precision of the signals.
A well-balanced strategy in the Signals indicator involves carefully selecting a combination of conditions and confirmations to generate accurate trading signals. Finding the right balance between them is crucial for consistent and profitable trading.
To offer even more flexibility, the Signals indicator includes two powerful main functions:
Target Placement System: This feature allows you to set up to 6 targets with a stop loss level and partial exit percentages. You can choose between automatic target creation or manual customization, giving you control over your profit targets.
Exit Strategy: With this feature, you can define your preferred trailing stop strategy, allowing you to implement a systematic approach to exiting trades. By setting appropriate trailing stop levels, you can limit potential losses, while the system secures profits by automatically closing positions partially when certain price targets are reached. This may help you to maintain discipline in your trading and optimize your risk-reward ratio.
With over 30 unique conditions, 10 confirmations, and the deep Target Placement and Exit Strategy systems, the Signals indicator offers a vast array of possibilities. In fact, there are potentially millions of different strategy outputs available for each ticker. Despite its complexity, the script remains lightweight and fast, ensuring smooth performance.
The Signals Backtest table provides a comprehensive overview of your strategy's performance. You can track your current position with all the necessary details, allowing you to monitor your trades effectively and make informed decisions based on the backtest results.
⚠️ WARNING!
Backtest results do not guarantee future performance. Strategies tested on synthetic data may not accurately represent real-world results. Testing should be conducted on charts that reflect actual closing prices.
The indicator displays buy/sell signals intended to support traders' analysis. There are numerous possibilities and combinations available to create your own unique strategies, whether trading with or against the trend or capturing oversold bounces. These are just a few of the many options! Our indicator can easily be tailored to fit your trading strategy.
The settings that influence the signal-generating algorithm play a crucial role in effectively utilizing the signals. We provide users with the flexibility to modify the settings to align with their trading style, while also offering simple adjustment methods using various techniques.
Each method for modifying the signal settings has been designed to meet specific user needs. It is important to understand that one method is not necessarily more accurate than another.
It is essential to understand that signal indications generally serve as trend confirmations, rather than direct entry and exit points. Focusing on the easy use of signal settings and utilizing other functionalities in our toolkit will likely be a better decision than attempting to find the "holy grail" of optimized signal settings and solely relying on following the signals.
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. Our aim is to offer useful features that meet the needs of the 21st century and that we actually use.
🛑 Risk Notice:
Everything provided by trademasterindicator – from scripts, tools, and articles to educational materials – is intended solely for educational and informational purposes. Past performance does not assure future returns.
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!
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
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.
PD Crypto Performer (Backtest)Description:
This is the backtesting version of the PD Crypto Performer (Alert) . The strategy assumes the same capital amount invested ($10,000) each trade. You can also see how your capital grows over time by enabling the reinvesting proceeds option. For details, please check out this tutorial . The backtesting results could be easily improved in live trading by following the recommended methods of use below.
To assist the decision-making process, the code currently references BTCUSD. As a result, it is only suitable for crypto traders. However, we are working on the stock and forex versions, and the Performer will have these compatibilities soon.
Most importantly, our signals DO NOT REPAINT !
Recommended Use:
- Time Frame: 1HR
- Asset: Large cap crypto assets.
For lower risk tolerance, we recommend using the indicator on ETHUSD. For maximizing profits, we recommend using the indicator on BCHUSD.
- Always set stop loss according to your own risk tolerance
- Take profits along the way.
Recommended Use for Advanced Traders:
- Position sizing:
Larger position if the 1HR signal is in the same direction compared to the 4HR trend.
Smaller position if the 1HR signal is in the opposite direction compared to the 4HR trend.
- Better entry/exit points:
Track the 1HR signal for the asset you are trading on other exchanges along with the BTCUSD 1HR signal. Sometimes, the signals from different exchanges occur with a 1-2 hour difference. You could use these earlier signals along with a lower time frame (eg. 15min) entry confirmation from your own exchange for better entry / exit points.
Go to www.phi-deltalytics.com and sign up for a FREE trial today!
Let us know if you have any questions or recommendations. We are here for your success!
Disclaimer:
It should not be assumed that the methods, techniques, or indicators presented will be profitable or that they will not result in losses. Past results are not necessarily indicative of future results. This is not a solicitation of any order to buy or sell.
Cyber Strategy V1Сyber Strategy V1 – Indicator Testing & Strategy Execution Framework
✅ Overview
Cyber Strategy V1 is a closed-source strategy framework engineered to turn any of yours external indicator into a systematic, rule-based trading system. Designed for rigorous testing and live deployment, it combines multi-signal inputs, confirmations and automated execution paths to help traders and developers validate signal quality and manage risk with precision.
✅ Core Functionality
Multi-Source Independent Signal Inputs
Reversal Logic
Take Profit: up to 5 staggered TP levels, specified as percentage
Stop Loss: configurable via fixed percentage or dynamic SL that trails a reverse signals.
✅ Statistical Drawdown Analysis
For all profitable trades, tracks the maximum intratrade drawdown.
Computes percentile levels of profitable trades that hits minimum drawdowns to inform:
Entry buffer zones (e.g. avoid entering during transient noise)
Partial entry scaling prices.
✅ Signal Confirmation
Optional confirmation delays: hold entry until other signal section send a confirmation from another indicator.
✅ Automated Execution Integrations
Cornix Text Alerts: Generates pre-formatted alerts compatible with Cornix for semi-automated or bot trading.
Webhook Support: Emits JSON payloads on order-fill events to any endpoint, enabling full automation through third-party services or custom order-routing systems.
Important Notes
⚠️ THIS STRATEGY DOES NOT INCLUDE INDICATORS. Examples shown on screenshots use third-party tools. NO PROPRIETARY INDICATORS INCLUDED: Cyber Strategy V1 relies entirely on external signal inputs.
⚠️ All backtesting parameters are customizable; thorough backtesting under realistic slippage, fees and spread assumptions is essential before live deployment.
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!
SME Backtesting [TFO]This strategy script is an extension of my Smart Money Essentials (SME) indicator and aims to provide a simplified means of backtesting complex trade models that incorporate a variety of Smart Money Concepts.
Among other things, Smart Money Essentials contains logic for:
- Market structure
- Fair Value Gaps
- Order Blocks
- Breaker Blocks
- Optimal Trade Entries
- HTF Market Structure
The Confluence section can then be utilized to build and test trade models from any combination of the included factors. As a basic example, we could test a strategy that only utilizes market structure. With Manual Exit turned off, we would simply be flipping long on bullish market structure shifts, and reversing short on bearish market structure shifts for the duration of the user-defined session.
As one might expect, such a simple strategy isn't expected to produce very reliable results by itself. However, we could build on these ideas by adding extra layers of Confluence, like looking for entries where Market Structure aligns with Order Block interactions. We could also turn on Manual Exit with a 40 tick stop loss and 80 tick profit target (10 points and 20 points, respectively, for ES futures), for more defined exit criteria.
One could expand on these ideas by adding factors like Fair Value Gaps, HTF Market Structure, etc. Any of the core pieces of SME can be used to build and backtest strategies that would otherwise be extremely tedious to do by hand, and as the SME indicator grows, so too will this backtesting script. Ultimately, the purpose of this is to make Smart Money Concepts more objective and easily testable so that users may better understand where these concepts may perform best.
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.
Kairos [Backtester]Kairos bot looks for the opportune time to buy low and sell high at targets
It provides signals to open and close trades, and indicates favorable positions for a stop loss and profit taking
The Kairos bot can be used on any chart and on any time frame
---BACKTESTER---
Using the backtester script the user can look at a chart's history between selected dates to find optimal bot settings and optimal time frames
The backtester is based on general percentages for profit taking as indicated below:
-------------T1 T2 T3 T4 T5 T6 CLOSE
1 Target: 50% 50%
2 Targets: 50% 25% 25%
3 Targets: 40% 30% 20% 10%
4 Targets: 40% 25% 20% 10% 5%
5 Targets: 35% 25% 20% 10% 5% 5%
6 Targets: 30% 25% 20% 10% 5% 5% 5%
ie: If 2 targets are selected:
- 50% of investment will be taken at target 1
- 25% of investment will be taken at target 2
- and the remainder 25% will be taken when the trade is closed on a close signal
However, it is up to the user's own risk appetite to determine where and how much profit to take
Note that the backtester does not have any on screen indicators other than OPEN and CLOSE, however profit taking can be indicated by ticking the Style -> Trades on Chart tick box on the settings userform
---SIGNALS---
The signals script can be used for automation and can indicate up to 6 potential Profit Targets, as well as a Stop Loss based on how many bars back needs to be taken into consideration
The signals (Open/Close) can be automated using TradingView alerts, however the Stop Loss and Profit Taking are only indicators and are for the users own interpretation
The user does not have to place a Stop Loss or take profit at the Targets if so wished, the bot can be used to simply buy on an OPEN signal and sell on a CLOSE signal, however, the backtester will indicate that it is far more profitable to take profits.
It is advised to take profits just below indicated Targets as these are potentially high selling zones and price action can sometimes turn down just short of these targets.
---INVITE-ONLY SCRIPT---
This is an invite-only script, so if you would like to try out Kairos Bot, send me a message
RSI-RENKO Divine StrategyLive, non-repainting strategy using RENKO and RSI mixed together to multiple types of long and short positions.
- Features -
Live entry direction with trade warnings and alerts
Live trade building buy and sell limits (for buy/sell limits)
Entry location icons as well as pyramid entries (to add to existing position)
Swing trades that keep you in the trade for the maximum possible profit
1 scalp target based on the RSI settings and entry location
Dynamic trailing stop for swings and scalps
Alert conditions for every update and condition change of the strategy (Provided by indicator study)
4 pre-built color themes, including candlestick coloring
This script is used solely for alerts to the RSI-RENKO Divine Strategy , because Trading View still after 3 years of requesting does not provide the ability to use alert conditions inside a strategy script, only an indicator script. This strategy should be used to backtest your settings. Beyond alerts and strategy inputs, the strategy and indicator are identical.
Smart MA Crossover BacktesterSmart MA Crossover Backtester - Strategy Overview
Strategy Name: Smart MA Crossover Backtester
Published on: TradingView
Applicable Markets: Works well on crypto (tested profitably on ETH)
Strategy Concept
The Smart MA Crossover Backtester is an improved Moving Average (MA) crossover strategy that incorporates a trend filter and an ATR-based stop loss & take profit mechanism for better risk management. It aims to capture trends efficiently while reducing false signals by only trading in the direction of the long-term trend.
Core Components & Logic
Moving Averages (MA) for Entry Signals
Fast Moving Average (9-period SMA)
Slow Moving Average (21-period SMA)
A trade signal is generated when the fast MA crosses the slow MA.
Trend Filter (200-period SMA)
Only enters long positions if price is above the 200-period SMA (bullish trend).
Only enters short positions if price is below the 200-period SMA (bearish trend).
This helps in avoiding counter-trend trades, reducing whipsaws.
ATR-Based Stop Loss & Take Profit
Uses the Average True Range (ATR) with a multiplier of 2 to calculate stop loss.
Risk-Reward Ratio = 1:2 (Take profit is set at 2x ATR).
This ensures dynamic stop loss and take profit levels based on market volatility.
Trading Rules
✅ Long Entry (Buy Signal):
Fast MA (9) crosses above Slow MA (21)
Price is above the 200 MA (bullish trend filter active)
Stop Loss: Below entry price by 2× ATR
Take Profit: Above entry price by 4× ATR
✅ Short Entry (Sell Signal):
Fast MA (9) crosses below Slow MA (21)
Price is below the 200 MA (bearish trend filter active)
Stop Loss: Above entry price by 2× ATR
Take Profit: Below entry price by 4× ATR
Why This Strategy Works Well for Crypto (ETH)?
🔹 Crypto markets are highly volatile – ATR-based stop loss adapts dynamically to market conditions.
🔹 Long-term trend filter (200 MA) ensures trading in the dominant direction, reducing false signals.
🔹 Risk-reward ratio of 1:2 allows for profitable trades even with a lower win rate.
This strategy has been tested on Ethereum (ETH) and has shown profitable performance, making it a strong choice for crypto traders looking for trend-following setups with solid risk management. 🚀
PS January Barometer BacktesterPS January Barometer Backtester (PS JBB)
The PS January Barometer Backtester (PS JBB) is a simple strategy designed to test the "January Effect" hypothesis in financial markets. This effect theorizes that stock market performance in January can predict the trend for the rest of the year. The script operates on a monthly timeframe, focusing on capturing and analyzing the price movements in January and their subsequent influence on the market until the end of each year.
User Input:
January Trifecta Selectors
These are user-selectable options allowing traders to incorporate additional criteria into their market analysis.
The Santa Claus Rally refers to a stock market increase typically seen in the last week of December through the first two trading days in January.
The First Five Days Indicator assesses market performance during the initial five days of the year.
Script Operation:
The script automatically detects the start of each year, tracks January's high, and signals entry and exit points for trades based on the strategy's logic. It's an excellent tool for traders and investors looking to explore the January Effect's validity and its potential impact on their trading decisions.
In essence, the "PS January Barometer Backtester" is designed to exploit specific seasonal market trends, particularly focusing on the early part of the year, by analyzing and acting upon defined market movements. This strategy is ideal for traders who focus on yearly cyclical patterns and seek to incorporate historical trends into their trading decisions.
Note: This script is intended for educational and research purposes and should not be construed as financial advice. Always conduct your own due diligence before making trading/investment decisions.
