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.
In den Scripts nach "backtest" suchen
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.
PIVOT STRATEGY [INDIAN MARKET TIMING]
A Back-tested Profitable Strategy for Free!!
A PIVOT INTRADAY STRATEGY for 5 minute Time-Frame , that also explains the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above ema1 ,indicated by pivot highest line in green color .
2) Price crosses below ema1 ,indicated by pivot lowest line in red color .
3) Candle high crosses above pivot highest , is the Long condition .
4) Candle low crosses below pivot lowest , is the Short condition .
5) Maximum Risk per trade for the intraday trade can be changed .
6) Default_qty_size is set to 60 contracts , which can be changed under settings → properties → order size .
7) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
Leftbars —————> Length of pivot highs and lows
Rightbars —————> Length of pivot highs and lows
Price Cross Ema —————> Added condition
ATR LONG —————> ATR stoploss trail for Long positions
ATR SHORT —————> ATR stoploss trail for Short positions
RISK —————> Maximum Risk per trade for the day
The strategy was back-tested on RELIANCE ,the input values and the results are mentioned under "BACKTEST RESULTS" below .
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 60 contracts , which can be changed under settings
↓
properties
↓
order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 25 .
The Indian Markets open at 9:15am and closes at 3:30pm .
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm, at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 103 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
NSE:RELIANCE
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 128 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better back-test results.
The strategy applied to NIFTY ( 5 min Time-Frame and contract size 60 ) gives us 60% profitability y , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.45 ,net Profit of 21,500Rs profit .
Sharpe Ratio : 0.311
Sortino Ratio : 0.727
The graph has a Linear Curve with consistent profits .
The INPUTS are as follows,
1) Leftbars ————————> 3
2) Rightbars ————————> 5
3) Price Cross Ema ——————> 150
4) ATR LONG ————————> 2.7
5) ATR SHORT ———————> 2.9
6) RISK —————————> 2500
7) Default qty size ——————> 60
NSE:RELIANCE
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Consolidation Breakout [Indian Market Timing]OK let's get started ,
A Day Trading (Intraday) Consolidation Breakout Indication Strategy that explains time condition for Indian Markets .
The commission is also included in the strategy .
The basic idea is ,
1) Price crosses above upper band , indicated by a color change (green) is the Long condition .
2) Price crosses below lower band , indicated by a color change (red) is the Short condition .
3) ATR is used for trailing after entry
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The Indian Markets open at 9:15am and closes at 3:30pm.
The time_condition specifies the time at which Entries should happen .
"Close All" function closes all the trades at 2:57pm.
All open trades get closed at 2:57pm , because some brokers dont allow you to place fresh intraday orders after 3pm.
NSE:NIFTY1!
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 114 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
LENGTH , MULT (factor) and ATR can be changed for better backtest results.
The strategy applied to NIFTY (3 min Time-Frame and contract size 5) gives us 60% profitability , as shown below
It was tested for a period a 8 months with a Profit Factor of 2.2 , avg Trade of 6000Rs profit and Sharpe Ratio : 0.67
The graph has a Linear Curve with consistent profits.
NSE:NIFTY1!
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Apply it to your charts Now !!
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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!**
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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.
HFT Scalper BacktesterThis strategy is a scalper strategy developed by HFT Research. Scalper is highly customizable and provides endless opportunities to find profitable setups in the market.
Use Bollinger Bands
This piece of the settings will turn and off Bollinger band’s input in the decision making. BB Length will determine the Moving average you are using to take the standard deviation off of which is named as BB Multiplier. Default settings will use 20 moving average and take standard deviation of 2 to create lower and upper bands. Increasing the Multiplier will give you fewer but safer entries.
Use Bollinger Bands %
This setting will allow the user to determine at what Bollinger band width %, he wants to take start looking to take trades. It is known that when prices are stable and moving sideways, Bollinger bands contract and it becomes more reactive to small moves in the market. Using this setting, you can ignore the signals that would be generated while Bollinger bands are contracted. This setting will allow the user to weed out the noise in the market and really allow them to make the most out of Bollinger bands .
Use RSI
You can also turn on and off the RSI as well. Alternatively, there is an option to use RSI on a different time frame than you are currently on. For example, if you are looking at the 5min chart to use Bollinger bands but you would like to look at the RSI value on the 15min chart. You can do so by selecting the custom RSI timeframe as well as adjusting the Oversold and Overbought value.
Use STOCH
For those who want extra protection on their entry can throw STOCH into their decision making. STOCH acts like RSI but it is more prone to small moves. It will help the users to get a better entry if used correctly. Stoch may not be in the buy zone when RSI is at say 35, however, if price dips a little more and STOCH might be in the buy zone when RSI is at say 20. This way it will help you have better entries than just using RSI . In a way, you can use STOCH to scalp RSI .
Use VWAP
VWAP stands for volume weighted average price . It is an extremely useful indicator when trading intra-day. It does reset every trading session which is at 00:00 UTC . Instead of looking at x number of candles and providing an average price, it will take into consideration volume that’s traded at a certain price and weigh it accordingly.
Use ADX
ADX stands for average directional index . It is an indicator that measures volatility in the market. Unfortunately, the worst market condition for this strategy is sideways market. ADX becomes a useful tool since it can detect trend. If the volatility is low and there is no real price movement, ADX will pick that up and will not let you get in trades during a sideways market. It will allow you to enter trades only when the market is trending.
Use MA Filters
Lookback: It is an option to look back x number of candles to validate the price crossing. If the market is choppy and the price keeps crossing up and down the moving average you have chosen, it will generate a lot of “noisy” signals. This option allows you to confirm the cross by selecting how many candles the price needs to stay above or below the moving average. Setting it 0 will turn it off.
MA Filter Type: There is a selection of moving averages that is available on TradingView currently. You can choose from 14 different moving average types to detect the trend as accurate as possible.
Filter Length: You can select the length of your moving average. Most commonly used length being 50,100 and 200.
Filter Type: This is our propriety smoothing method in order to make the moving averages lag less and influence the way they are calculated slightly. Type 1 being the normal calculation and type 2 being the secret sauce .
Reverse MA Filter: This option allows you to use the moving average in reverse. For example, the strategy will go long when the price is above the moving average. However, if you use the reserve MA Filter, you will go short when the price is above the moving average. This method works best in sideways market where price usually retraces back to the moving average. So in an anticipation of price reverting back to the moving average, it is a useful piece of option to use during sideway markets which is the worst market condition for scalper.
Please visit our website for more information
Quickie (Free) BacktesterQuickie is a free tradingview Indicator developed by HFT Research. It works in sideways and trending markets depending the way you set it as well as both on short time frame and long time frame. It comes with backtesting abilities on tradingview.
BITMEX:XBTUSD
Use Bollinger Bands
This piece of the settings will turn and off Bollinger band’s input in the decision making. BB Length will determine the Moving average you are using to take the standard deviation off of which is named as BB Multiplier. Default settings will use 20 moving average and take standard deviation of 2 to create lower and upper bands. Increasing the Multiplier will give you fewer but safer entries
Use RSI
You can also turn on and off the RSI as well. Alternatively, there is an option to use RSI on a different time frame than you are currently on. For example, if you are looking at the 5min chart to use Bollinger bands but you would like to look at the RSI value on the 15min chart. You can do so by selecting the custom RSI timeframe as well as adjusting the Oversold and Overbought value.
Use MA Filter
Lookback: The indicator has an option to look back x number of candles to validate the price crossing. If the market is choppy and the price keeps crossing up and down the moving average you have chosen, it will generate a lot of “noisy” signals. This option allows you to confirm the cross by selecting how many candles the price needs to stay above or below the moving average. Setting it 0 will turn it off.
MA Filter Type: There is a selection of moving averages that is available on TradingView currently. You can choose from 14 different moving average types to detect the trend as accurate as possible.
Filter Length: You can select the length of your moving average. Most commonly used length being 50,100 and 200.
Filter Type: This is our propriety smoothing method in order to make the moving averages lag less and influence the way they are calculated slightly. Type 1 being the normal calculation and type 2 being the secret sauce.
Reverse MA Filter: This option allows you to use the moving average in reverse. For example, the strategy will go long when the price is above the moving average. However, if you use the reserve MA Filter, you will go short when the price is above the moving average. This method works best in sideways market where price usually retraces back to the moving average. So, in an anticipation of price reverting back to the moving average, it is a useful piece of option to use during sideway markets.
For more information please check out our website
APEX - Tester - Buy/Sell Strategies - Basic - BACKTESTERThis is a upgraded version of the following study.
This is a simple Strategy for backtesting your APEX trading ideas.
Be aware that the results will not be exact same as with apex 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.
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.
Grid Spot Trading Algorithm V2 - The Quant ScienceGrid Spot Trading Algorithm V2 is the last grid trading algorithm made by our developer team.
Grid Spot Trading Algorithm V2 is a fixed 10-level grid trading algorithm. The grid is divided into an accumulation area (red) and a selling area (green).
In the accumulation area, the algorithm will place new buy orders, selling the long positions on the top of the grid.
BUYING AND SELLING LOGIC
The algorithm places up to 5 limit orders on the accumulation section of the grid, each time the price cross through the middle grid. Each single order uses 20% of the equity.
Positions are closed at the top of the grid by default, with the algorithm closing all orders at the first sell level. The exit level can be adjusted using the user interface, from the first level up to the fifth level above.
CONFIGURING THE ALGORITHM
1) Add it to the chart: Add the script to the current chart that you want to analyze.
2) Select the top of the grid: Confirm a price level with the mouse on which to fix the top of the grid.
3) Select the bottom of the grid: Confirm a price level with the mouse on which to fix the bottom of the grid.
4) Wait for the automatic creation of the grid.
USING THE ALGORITHM
Once the grid configuration process is completed, the algorithm will generate automatic backtesting.
You can add a stop loss that destroys the grid by setting the destruction price and activating the feature from the user interface. When the stop loss is activated, you can view it on the chart.
Rocket Grid Algorithm - The Quant ScienceThe Rocket Grid Algorithm is a trading strategy that enables traders to engage in both long and short selling strategies. The script allows traders to backtest their strategies with a date range of their choice, in addition to selecting the desired strategy - either SMA Based Crossunder or SMA Based Crossover.
The script is a combination of trend following and short-term mean reversing strategies. Trend following involves identifying the current market trend and riding it for as long as possible until it changes direction. This type of strategy can be used over a medium- to long-term time horizon, typically several months to a few years.
Short-term mean reversing, on the other hand, involves taking advantage of short-term price movements that deviate from the average price. This type of strategy is usually applied over a much shorter time horizon, such as a few days to a few weeks. By rapidly entering and exiting positions, the strategy seeks to capture small, quick gains in volatile market conditions.
Overall, the script blends the best of both worlds by combining the long-term stability of trend following with the quick gains of short-term mean reversing, allowing traders to potentially benefit from both short-term and long-term market trends.
Traders can configure the start and end dates, months, and years, and choose the length of the data they want to work with. Additionally, they can set the percentage grid and the upper and lower destroyers to manage their trades effectively. The script also calculates the Simple Moving Average of the chosen data length and plots it on the chart.
The trigger for entering a trade is defined as a crossunder or crossover of the close price with the Simple Moving Average. Once the trigger is activated, the script calculates the total percentage of the side and creates a grid range. The grid range is then divided into ten equal parts, with each part representing a unique grid level. The script keeps track of each grid level, and once the close price reaches the grid level, it opens a trade in the specified direction.
The equity management strategy in the script involves a dynamic allocation of equity to each trade. The first order placed uses 10% of the available equity, while each subsequent order uses 1% less of the available equity. This results in the allocation of 9% for the second order, 8% for the third order, and so on, until a maximum of 10 open trades. This approach allows for risk management and can help to limit potential losses.
Overall, the Rocket Grid Algorithm is a flexible and powerful trading strategy that can be customized to meet the specific needs of individual traders. Its user-friendly interface and robust backtesting capabilities make it an excellent tool for traders looking to enhance their trading experience.
Gann HiLo Activator Strategy█ OVERVIEW
Strategy based on the Gann Hilo Activator . This is a trend following strategy, which means it will go long (and close the previous short position) once the price closes above the high SMA, and go short (and close the previous long position) once the price closes below the low SMA.
█ PARAMETERS
- Length
- Displace (or offset): default is 1
- Begin from start: strategy will run since the beggining
- From year, month, day: Choose an specific date to start backtesting (must disable the parameter above to work)
█ HOW TO USE
After choosing the start date to run the strategy, you can change the length field and look at the backtest results to find the most optimal settings for the current symbol.
This strategy was tested on the stock and crypto market with good results. Hope you enjoy!
200DMA last DOM - ajhImplements and backtests a simple 200 day moving average trend following rules based on last day of month to limits trades to 12 per year.
From the book : 5 BEST Moving Average Strategies (That beat buy and hold) by Steve Burns and Holly Burns
Click on the cog to set the input date range eg; 2000-01-01 to 2016-12-31
The book back tested SP500 returns from 2000-2016 317% using this method vs 125% buy and hold only with less drawdown.
Simple 200 day moving average test and trading on last day of month.
(you may find it trades on next available day close to end of month as not all dates can be traded weekends etc..)
Rules are ;
1. if last day of month and stock over 200 day moving average, then go long 100%
2. if last day of month and stock under 200 day moving average, then close long 100% and goto cash.
Aims to miss market declines and keep you long for upside.
Note: Have found doesn't work well in choppy markets moving sideways like the FTSE100 for same period 2000-2016 and causes losses. Also for many stocks.
Flawless Victory Strategy - 15min BTC Machine Learning StrategyHello everyone, I am a heavy Python programmer bringing machine learning to TradingView. This 15 minute Bitcoin Long strategy was created using a machine learning library and 1 year of historical data in Python. Every parameter is hyper optimized to bring you the most profitable buy and sell signals for Bitcoin on the 15min chart. The historical Bitcoin data was gathered from Binance API, in case you want to know the best exchange to use this long strategy. It is a simple Bollinger Band and RSI strategy with two versions included in the tradingview settings. The first version has a Sharpe Ratio of 7.5 which is amazing, and the second version includes the best stop loss and take profit positions with a Sharpe Ratio of 2.5 . Let me talk a little bit more about how the strategy works. The buy signal is triggered when close price is less than lower Bollinger Band at Std Dev 1, and the RSI is greater than a certain value. The sell signal is triggered when close price is greater than upper Bollinger Band at Std Dev 1, and the RSI is greater than a certain value. What makes this strategy interesting is the parameters the Machine Learning library found when backtesting for the best Sharpe Ratio. I left my computer on for about 28 hours to fully backtest 5000 EPOCHS and get the results. I was able to create a great strategy that might be one of TradingView's best strategies out on the website today. I will continue to apply machine learning to all my strategies from here on forward. Please Let me know if you have any questions or certain strategies you would like me to hyper optimize for you. I'm always willing to create profitable strategies!
P.S. You can always pyramid this strategy for more gains! I just don't add pyramiding when creating my strategies because I want to show you the true win/loss ratio based buying one time and one selling one time. I feel like when creating a strategy that includes pyramiding right off the bat falsifies the win rate. This is my way of being transparent with you all. Have fun trading!
TradeChartist Donchian Channels Breakout Strategy™TradeChartist Donchian Channels Breakout Strategy is the strategy backtester version of ™TradeChartist Donchian Channels Breakout Filter .
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Features of ™TradeChartist Donchian Channels Breakout Strategy
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Option to plot Donchian Channels of user preferred length, based on the Source price in addition to High/Low Donchian Channels.
Generates trade entries based on user preferred Breakout Price. For example, if the user prefers HL2 as breakout price, irrespective of the Donchian Channels type, trade entries are generated only when hl2 price (average of high/low) breaks out of the upper or lower band.
Option to plot background colour based on Breakout trend. The bull zones are filled with green background, the Bear zones are filled with red background and the bar that broke out is filled with orange background.
Option to colour price bars using Donchian Channels price trend. The Donchian Channels basis line is plotted using the same colours as coloured bars as default.
Note: This script does not repaint. To use the script for trade entries, wait for the bar close without Backtester or Strategy entries (with Backtester) and use a second confirmator (includes fundamentals) based on asset type as some markets require users to have good pulse on the fundamentals as trading by Technicals/price action dynamic alone may not be safe.
Note: Trend Based Stochastic of the same DC Length can be used from ™TradeChartist Risk Meter for Trade Confirmations too.
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Best Practice: Test with different settings first using Paper Trades before trading with real money
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This is not a free to use strategy. Get in touch with me (PM me directly if you would like trial access to test the strategy)
Premium Scripts - Trial access and Information
Trial access offered on all Premium scripts.
PM me directly to request trial access to the scripts or for more information.
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Custom Triple Moving Average Strategy | Auto BacktestingCreate your own MA Strategy set of up to three moving averages!
Auto Backtesting.
Cloud between MA1 and MA2.
Many different MA types to choose from.
Totally Custom!
Happy Trading, and algorithm analysis!
Scaling The Bull (STB) - StrategyThis is one of my powerful strategy which I might probably have ever came up. After a lot of backtesting over multiple timeframes and testing different values of the indicator on those multiple timeframes I finally came to a point where this indicator reaches its ultimate goal " Higher Reward Than Risk ". The final result is fantastic as you all can see it's trading performance report where the Net Profit floating around 100%+ also within a month! Yes, you heard it right it's a strategy which has been created solely based on 1 minute main timeframe and has done backtest over nearly 1-month historical data where we can see the drawdown % is only 20% while the net profit is 100%+ of the total initial capital which I kept fix around $1,000 (for the purpose of realistic result). Let me aware you all this that I have made this strategy using fixed contract size or we can say unit size which is 50,000 units (or in forex world 5 mini lots) so, every trade executes constantly with 5 mini lots size but you can change this from the strategy setting. I'm doing this all in the sense of leverage trading in the forex market and please don't forget it I made this strategy in first place for forex trading only for now so, I had made the strategy in the sense of leverage trading of '1:100' in the forex market which is why I kept fix contract size or we say unit size . Every trade is executed on 5 mini lots and I also set up a broker commission just to make it nearly like a real trading account report. This strategy has been made by using a famous oscillator indicator Relative Strength Index (RSI) in conjunction with my own tactics. This strategy was build in an AUD denominated account so you can see the calculation are all done in the Aussie currency but everything is changeable from the setting of the strategy which I mentioned above already. This strategy has only been made for AUDUSD on a 1minute main timeframe and it won't work in different pairs or with different timeframes or different strategy settings but you can test if you are lucky you may find for sure. The strategy usage a powerful tactic which is Scaling in the bullish trend. It usages Relative Strength Index (RSI) in conjunction with my own tactic in the calculation to enter or add only a long (buy) position. It doesn't care about the short (sell) position and totally ignores it. It has been created in such a way just to eliminate unnecessary bogus signals and to avoid making multiple directional trades as it might not make more profit but it will also not end up with huge trade reports with many potential losses. Trading in one direction and also scaling in on that certain long direction (in our case long side) is a great feature of this strategy.
Jackrabbit.modulus.AnalyzerThis is the module Analyzer for the Jackrabbit suite and modulus framework.
As the modulus framework has grown both in size and complexity, it has become ever increasingly difficult to evaluate the profitability a very complex multi-layered modules combined.
The Jackrabbit Analyzer module allows you to do just that. Connect this module to the end of your IoI chain and it will tell you the profitability of your current combination, using TradingView's strategy backtesting capabilities.
With this module connected to your IoI chain, you can literally watch in real time as the analyzer evaluates your current settings and updates each time you make a change in those settings, giving you a better and more realistic approach to what is possible with your current strategy.
While this module is not a substitute for paper trading, it significantly increases the construction and analysis of a multi-layered trading paradigm that can then be taken to a paper trader with a high level of confidence of success.
Only the signal line is displayed.
The Jackrabbit modulus framework is a plug in play paradigm built to operate through TradingView's indicator on indicatior (IoI) functionality. As such, this script receives a signal line from the previous script in the IoI chain, and evaluates the buy/sell signals appropriate to the current analysis.
This script is by invitation only. To learn more about accessing this script, please see my signature or send me a PM. Thank you.
