Gauss KenJi Robot
Gauss KenJi Trading Robot: Precision and Automation for Traders
The Gauss KenJi robot is a cutting-edge trading solution designed for experienced traders seeking to enhance their decision-making through advanced statistical models and automation. Unlike traditional trading tools that rely on generic indicators prone to false signals, the Gauss KenJi robot offers an innovative approach by utilizing two unique indicators: the Kenji Indicator v.2.0 and the Gauss Indicator .
Kenji Indicator v.2.0
Traditional moving averages and related indicators often fail in flat market conditions, where frequent crossovers lead to confusing signals and false trends. The Kenji Indicator addresses this issue by using a combination of correlation analysis and moving averages to more accurately identify the market’s state. This real-time insight allows for better navigation of local trends, reducing noise and increasing the precision of trade signals.
Gauss Indicator
The Gauss Indicator brings the power of statistical analysis into trading by applying the 3 sigmas rule. It calculates and predicts the likely price ranges for specific time frames (hourly, daily, weekly) with probabilities of 68%, 95%, and 99%. This offers traders an actionable framework for setting stop-loss, take-profit, and identifying key support and resistance levels. By providing a clearer view of potential price movements, the Gauss Indicator improves decision-making, ensuring that traders enter and exit the market at optimal points.
Gauss KenJi Robot: How it Works
The Gauss KenJi robot operates on a statistical algorithm based on the Gaussian function, which uses market volatility as a core indicator of price movements. The robot opens positions in the direction of the trend when the price reaches the predetermined Gauss border. Position sizes are calculated according to the “Initial_lot” parameter, with stop-loss and take-profit levels defined by the “Pips” parameter. Trades are automatically closed either when profit targets or stop-loss limits are reached, or if local trend reversals are detected by the Kenji Indicator.
This highly adaptable algorithm can be applied to any asset class (stocks, forex, crypto, commodities) and any time frame, providing traders with a versatile tool to navigate various markets.
Why Gauss KenJi is Essential for Traders
1. Time Efficiency: The robot operates autonomously, allowing traders to step away from constant chart monitoring while still capitalizing on market movements.
2. Profit Maximization: By leveraging machine learning and advanced statistical models, the robot identifies opportunities faster than human traders, ensuring more profitable trades.
3. Risk Management: The robot strictly adheres to predefined rules, helping traders minimize losses and protect their capital in volatile market conditions.
4. Cross-market Versatility: Whether you’re trading forex, stocks, crypto, or commodities, Gauss KenJi adapts to different markets and time frames, making it a versatile tool for professional traders.
The Gauss KenJi robot is a comprehensive, scientifically driven trading solution designed to eliminate common pitfalls associated with traditional indicators. Its combination of the Kenji Indicator’s trend identification and the Gauss Indicator’s price prediction capabilities makes it an indispensable tool for traders looking to enhance both the precision of their trades and the automation of their strategies. Whether you are aiming for consistent daily profits or optimizing long-term trading strategies, Gauss KenJi offers the efficiency and accuracy required to stay ahead in today’s competitive markets.
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Universal All Assets Strategy | viResearchUniversal All Assets Strategy | viResearch
The Universal All Assets Strategy by viResearch is a sophisticated trend-following algorithm designed to operate seamlessly across various asset classes. It leverages seven unique trend-following indicators to provide robust and adaptive trading signals. The strategy dynamically adjusts to market conditions, making it suitable for equities, commodities, forex, and cryptocurrencies.
Core Methodologies and Features:
Seven Integrated Trend Indicators:
The strategy integrates seven powerful trend-following indicators. These include directional moving averages, smoothed moving averages, RSI loops, Supertrend filters, and more. When the majority of these indicators align, the strategy generates a long or short signal, ensuring that traders are capturing significant trend opportunities while minimizing noise from market fluctuations.
Universal Asset Adaptability:
Designed to work across all assets, the strategy adjusts its parameters dynamically based on the asset being traded. Whether applied to stocks, forex, or crypto, it adapts to the specific volatility and price behavior of the instrument, ensuring reliable signal generation in any market condition.
Customizable Directional Bias and Volatility Filters:
The strategy allows for an optional directional bias and incorporates volatility-based adjustments through ATR filters and standard deviation metrics. These features provide greater flexibility, allowing users to fine-tune the strategy for both trending and ranging markets.
Operational Parameters:
User-Friendly Customization:
Universal All Assets Strategy offers comprehensive customization options, including adjustable backtesting dates, starting capital settings, plotting options, and an experimental directional bias feature. These parameters can be easily tailored to meet the trader's unique needs, allowing for optimal performance across various markets and trading styles.
Seven-Trend Confirmation System:
The algorithm relies on its seven trend-following indicators to confirm market direction. If the majority of indicators generate a long signal, the strategy will initiate a long position. Conversely, a majority short signal will trigger a short position, providing strong validation for trade entries and exits.
Thoroughly Tested for Realistic Conditions:
This strategy has been rigorously backtested and forward-tested under real-world trading conditions, accounting for slippage, commissions, and various account sizes. Its robust risk management features ensure a balanced approach to trading, reducing unnecessary drawdowns and prioritizing capital preservation over time.
Concluding Remarks:
The Universal All Assets Strategy | viResearch is designed to offer traders a powerful tool for identifying and acting on market trends across multiple asset classes. With its seven-indicator confirmation system, adaptive logic, and customizable settings, this strategy is an excellent choice for traders looking for consistency and reliability in their trading approach. Whether used for long or short opportunities, this strategy provides the flexibility and precision needed to succeed in today's markets.
Advanced Trend Strategy [BITsPIP]The BITsPIP team is super excited to share our latest trading gem with you all. We're all about diving deep and ensuring our strategies can stand the test of time. So, we invite you to join us in exploring the awesome potential of this new strategy and really put it through its pace with some deep backtesting. This isn't just another strategy; it boasts a profit factor hovering around 1.5 across over 1000 trades, which is quite an achievement. Consider integrating it with your trading bots to further enhance your trading efficiency and profit generation. Curious? Ask for trial access or drop by our website for more details.
I. Deep Backtesting
We're all in on transparency and solid results, which is why we didn't stop at 100... or even 500 trades. We went over 1000, making sure this strategy is as robust as they come. No flimsy forecasts or sneaky repainting here. Just good, solid strategy that's ready for the real deal. Curious about the details? Check out our detailed backtesting screenshot for the BINANCE:BTCUSDT in a 5-minute timeframe. It's all about giving you the clear picture.
#No Overfitting
#No Repainting
Backtesting Screenshot
II. Algorithmic Trading
Thinking of trading as a manual game? Think again! Manual trading is a bit like rolling the dice - fun, but kind of risky if you're aiming for consistent wins. Instead, why not lean into the future with algorithmic trading? It's all about trusting the market's rhythm over the long term. By integrating your strategy with a trading bot, you can enjoy peace of mind, rest easy, and keep those emotional trades at bay.
III) Applications
Dive into the Advanced Trend Strategy, your versatile tool for navigating the market's waters. This strategy shines in under an hour timeframes, offering adaptability across stocks, commodities, forex, and cryptocurrencies. Initially fine-tuned for low-volatility cryptos like BINANCE:BTCUSDT , its default settings are a solid starting point.
But here's where your expertise comes into play. Each market beats to its own drum, necessitating nuanced adjustments to stop loss and take profit settings. This customization is key to maximizing the strategy's effectiveness in your chosen arena.
IV) Strategy's Logic
The Advanced Trend Strategy is a powerhouse, blending the precision of Hull Suite, RSI, and our unique trend detector technique. At its core, it’s designed for savvy risk management, aiming to lock in substantial profits while steering clear of minor market ripples. It utilizes stop-loss and take-profit thresholds to form a profit channel, providing a safety net for each trade. This is a trend-following strategy at heart, where these profit channels play a critical role in maximizing returns by securing positions within these "warranty channels."
1. Trend-Following
The market's complexity, influenced by countless factors, makes small movements seem almost chaotic. Yet, the principle of #Trend-Following shines in less volatile markets in long term. The strategy excels by pinpointing the ideal moments to enter the market, coupled with refined risk management to secure profits. It’s tailored for you, the individual trader, enabling you to ride the waves of market trends upwards or downwards.
2. Risk Management
A key facet of the strategy is its emphasis on pragmatic risk management. Traders are empowered to establish practical stop-loss and take-profit levels, tailoring these crucial parameters to the specific market they are engaging in. This customization is instrumental in optimizing long-term profitability, ensuring that the strategy adapts fluidly to the unique characteristics and volatility patterns of different trading environments.
V) Strategy's Input Settings and Default Values
1. Alerts
The strategy comes equipped with a flexible alert system designed to keep you informed and ready to act. Within the settings, you’ll find options to configure order/exit and comment/alert messages to your preference. This feature is particularly useful for staying on top of the strategy’s activities without constant manual oversight.
2. Hull Suite
i. Hull Suite Length: Designed for capturing long-term trends, the Hull Suite Length is configured at 1000. Functioning comparably to moving averages, the Hull Suite features upper and lower bands. Currently, it is set to 1000.
ii. Length Multiplier: It's advisable to maintain a minimal value for the Length Multiplier, prioritizing the optimization of the Hull Suite Length. Presently, it is set to 1.
3. RSI Indicator
i. The RSI is a widely recognized tool in trading. Adapt the oversold and overbought thresholds to better match the specifics of your market for optimal results.
4. StopLoss and TakeProfit
i. StopLoss and TakeProfit Settings: Two distinct approaches are available. Semi-Automatic StopLoss/TakeProfit Setting and Manual StopLoss/TakeProfit Setting. The Semi-Automatic mode streamlines the process by allowing you to input values for a 5-minute timeframe, subsequently auto-adjusting these values across various timeframes, both lower and higher. Conversely, the Manual mode offers full control, enabling you to meticulously define TakeProfit values for each individual timeframe.
ii. TakeProfit Threshold # and TakeProfit Value #: Imagine this mechanism as an ascending staircase. Each step represents a range, with the lower boundary (TakeProfit Value) designed to close the trade upon being reached, and the upper boundary (TakeProfit Threshold) upon being hit, propelling the trade to the next level, and forming a new range. This stair-stepping approach enhances risk management and increases profitability. The pre-set configurations are tailored for $BINANCE:BTCUSDT. It's advisable to devote time to tailoring these settings to your specific market, aiming to achieve optimal results based on backtesting.
iii. StopLoss Value: In line with its name, this value marks the limit of loss you're prepared to accept should the market trend go against your expectations. It's crucial to note that once your asset reaches the first TakeProfit range, the initial StopLoss value becomes obsolete, supplanted by the first TakeProfit Value. The default StopLoss value is pegged at 1.6(%), a figure worth considering in your trading strategy.
VI) Entry Conditions
The primary signal for entry is generated by our custom trend detection mechanism and hull suite values (ascending/descending). This is supported by additional indicators acting as confirmation.
VII) Exit Conditions
The strategy stipulates exit conditions primarily governed by stop loss and take profit parameters. On infrequent occasions, if the trend lacks confirmation post-entry, the strategy mandates an exit upon the issuance of a reverse signal (whether confirmed or unconfirmed) by the strategy itself.
BITsPIP
LuxAlgo - Backtester (PAC)The PAC Backtester is an innovative strategy script that allows users to create a wide variety of strategies derived from price action-related concepts for a data-driven approach to discretionary trading strategies.
Thanks to our 'Step' and 'Match' algorithm, users can create custom and complex strategy entries and exits from features such as market structure, order blocks, imbalances, as well as any external indicators, allowing users to create entries from a sequence of conditions and/or multiple matching conditions.
We included a complete alert system that will send a notification for each action taken by the strategy and we also allow users to set custom messages for each action taken by a strategy.
🔶 Features
🔹 Step & Match Algorithm
More complex entry rules can be created by using multiple conditions together, this is done thanks to the Step dropdown setting on the right of each condition.
The Step setting is directly related to the Step & Match algorithm and works in two ways:
When two or more conditions have the same step number, both conditions are evaluated. Used to test matching conditions.
When two or more conditions have different step numbers, each condition will be evaluated in order, testing for the first step and switching to the next step once the previous one is true. When the final step is true the strategy will open a market order. Used to create a sequence of conditions.
This operation is complementary, as you can create a sequence of conditions with one step consisting of two or more matching conditions as long as they have the same step number.
🔹 Fully Customizable Price Action Concepts As Entries
We allow the users to use market structures, order blocks, imbalances, and external sources together to set their custom entry and exit conditions.
Market structures are commonly used to determine trend direction by indicating when prices break prior swing points. Their occurrence can be used as entry conditions.
Order blocks highlight areas where institutional market participants open positions, one can use order blocks to determine confirmation entries or potential targets as we can expect there is a large amount of liquidity at these order blocks. Price entering, being within, or mitigating an order block can be used as an entry condition.
Market imbalances highlight areas where there is a disparity between supply and demand. Price entering, being within, or mitigating an imbalance can be used as an entry condition.
This system also allows the use of external sources to create entry and exit conditions, such as moving averages, bands, trailing stops...etc.
🔹 Complete Alert System
Users can get alerted for any action executed by a strategy, from opening positions to closing them.
The message field in the Alert Messages setting section allows for the strategy to send a custom alert message depending on the action taken by the strategy, if no messages are set the strategy will send default messages.
🔶 Usage
Users can create complete price action strategies from this script, let's see an example using the following entry conditions:
Long: Mitigated bearish order block occurring during the New York session after a mitigated bearish imbalance.
Short: Mitigated bullish order block occurring during the New York session after a mitigated bullish imbalance.
Take Profit: 2 points away from the entry price.
Stop Loss: 1 point away from the entry price.
We can also use features from Price Action Concepts™ to construct custom exit conditions, leading to the following strategy conditions:
Long: Bullish CHoCH and price mitigates bearish FVG.
Short: Bearish CHoCH and price mitigates bullish FVG.
Exit Long: Price mitigates bearish order block.
Exit Short: Price mitigates bullish order block.
Users can achieve a wide variety of results by using external indicators as an input source for entries and exits, combining the best from price action and technical indicators. We might for example be interested in exiting a position when the RSI oscillator is overbought or oversold.
🔶 Strategy Properties (Important)
This script backtest is done on daily EURGBP, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Comission: 3.4 pips (average spread for EURGBP)
Slippage: 1 tick
Stop Loss: 0.01 points away from entry price
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from strategies built are realistic.
🔶 How to access
You can see the Author's Instructions below to learn how to get access.
Multi-TF AI SuperTrend with ADX - Strategy [PresentTrading]
## █ Introduction and How it is Different
The trading strategy in question is an enhanced version of the SuperTrend indicator, combined with AI elements and an ADX filter. It's a multi-timeframe strategy that incorporates two SuperTrends from different timeframes and utilizes a k-nearest neighbors (KNN) algorithm for trend prediction. It's different from traditional SuperTrend indicators because of its AI-based predictive capabilities and the addition of the ADX filter for trend strength.
BTC 8hr Performance
ETH 8hr Performance
## █ Strategy, How it Works: Detailed Explanation (Revised)
### Multi-Timeframe Approach
The strategy leverages the power of multiple timeframes by incorporating two SuperTrend indicators, each calculated on a different timeframe. This multi-timeframe approach provides a holistic view of the market's trend. For example, a 8-hour timeframe might capture the medium-term trend, while a daily timeframe could capture the longer-term trend. When both SuperTrends align, the strategy confirms a more robust trend.
### K-Nearest Neighbors (KNN)
The KNN algorithm is used to classify the direction of the trend based on historical SuperTrend values. It uses weighted voting of the 'k' nearest data points. For each point, it looks at its 'k' closest neighbors and takes a weighted average of their labels to predict the current label. The KNN algorithm is applied separately to each timeframe's SuperTrend data.
### SuperTrend Indicators
Two SuperTrend indicators are used, each from a different timeframe. They are calculated using different moving averages and ATR lengths as per user settings. The SuperTrend values are then smoothed to make them suitable for KNN-based prediction.
### ADX and DMI Filters
The ADX filter is used to eliminate weak trends. Only when the ADX is above 20 and the directional movement index (DMI) confirms the trend direction, does the strategy signal a buy or sell.
### Combining Elements
A trade signal is generated only when both SuperTrends and the ADX filter confirm the trend direction. This multi-timeframe, multi-indicator approach reduces false positives and increases the robustness of the strategy.
By considering multiple timeframes and using machine learning for trend classification, the strategy aims to provide more accurate and reliable trade signals.
BTC 8hr Performance (Zoom-in)
## █ Trade Direction
The strategy allows users to specify the trade direction as 'Long', 'Short', or 'Both'. This is useful for traders who have a specific market bias. For instance, in a bullish market, one might choose to only take 'Long' trades.
## █ Usage
Parameters: Adjust the number of neighbors, data points, and moving averages according to the asset and market conditions.
Trade Direction: Choose your preferred trading direction based on your market outlook.
ADX Filter: Optionally, enable the ADX filter to avoid trading in a sideways market.
Risk Management: Use the trailing stop-loss feature to manage risks.
## █ Default Settings
Neighbors (K): 3
Data points for KNN: 12
SuperTrend Length: 10 and 5 for the two different SuperTrends
ATR Multiplier: 3.0 for both
ADX Length: 21
ADX Time Frame: 240
Default trading direction: Both
By customizing these settings, traders can tailor the strategy to fit various trading styles and assets.
AI SuperTrend - Strategy [presentTrading]
█ Introduction and How it is Different
The AI Supertrend Strategy is a unique hybrid approach that employs both traditional technical indicators and machine learning techniques. Unlike standard strategies that rely solely on traditional indicators or mathematical models, this strategy integrates the power of k-Nearest Neighbors (KNN), a machine learning algorithm, with the tried-and-true SuperTrend indicator. This blend aims to provide traders with more accurate, responsive, and context-aware trading signals.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How it Works: Detailed Explanation
SuperTrend Calculation
Volume-Weighted Moving Average (VWMA): A VWMA of the close price is calculated based on the user-defined length (len). This serves as the central line around which the upper and lower bands are calculated.
Average True Range (ATR): ATR is calculated over a period defined by len. It measures the market's volatility.
Upper and Lower Bands: The upper band is calculated as VWMA + (factor * ATR) and the lower band as VWMA - (factor * ATR). The factor is a user-defined multiplier that decides how wide the bands should be.
KNN Algorithm
Data Collection: An array (data) is populated with recent n SuperTrend values. Corresponding labels (labels) are determined by whether the weighted moving average price (price) is greater than the weighted moving average of the SuperTrend (sT).
Distance Calculation: The absolute distance between each data point and the current SuperTrend value is calculated.
Sorting & Weighting: The distances are sorted in ascending order, and the closest k points are selected. Each point is weighted by the inverse of its distance to the current point.
Classification: A weighted sum of the labels of the k closest points is calculated. If the sum is closer to 1, the trend is predicted as bullish; if closer to 0, bearish.
Signal Generation
Start of Trend: A new bullish trend (Start_TrendUp) is considered to have started if the current trend color is bullish and the previous was not bullish. Similarly for bearish trends (Start_TrendDn).
Trend Continuation: A bullish trend (TrendUp) is considered to be continuing if the direction is negative and the KNN prediction is 1. Similarly for bearish trends (TrendDn).
Trading Logic
Long Condition: If Start_TrendUp or TrendUp is true, a long position is entered.
Short Condition: If Start_TrendDn or TrendDn is true, a short position is entered.
Exit Condition: Dynamic trailing stops are used for exits. If the trend does not continue as indicated by the KNN prediction and SuperTrend direction, an exit signal is generated.
The synergy between SuperTrend and KNN aims to filter out noise and produce more reliable trading signals. While SuperTrend provides a broad sense of the market direction, KNN refines this by predicting short-term price movements, leading to a more nuanced trading strategy.
Local picture
█ Trade Direction
The strategy allows traders to choose between taking only long positions, only short positions, or both. This is particularly useful for adapting to different market conditions.
█ Usage
ToolTips: Explains what each parameter does and how to adjust them.
Inputs: Customize values like the number of neighbors in KNN, ATR multiplier, and moving average type.
Plotting: Visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy/sell orders.
█ Default Settings
The default settings are selected to provide a balanced approach, but they can be modified for different trading styles and asset classes.
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
By combining both machine learning and traditional technical analysis, this strategy offers a sophisticated and adaptive trading solution.
Elliott Wave with Supertrend Exit - Strategy [presentTrading]## Introduction and How it is Different
The Elliott Wave with Supertrend Exit provides automated detection and validation of Elliott Wave patterns for algorithmic trading. It is designed to objectively identify high-probability wave formations and signal entries based on confirmed impulsive and corrective patterns.
* The Elliott part is mostly referenced from Elliott Wave by @LuxAlgo
Key advantages compared to discretionary Elliott Wave analysis:
- Wave Labeling and Counting: The strategy programmatically identifies swing pivot highs/lows with the Zigzag indicator and analyzes the waves between them. It labels the potential impulsive and corrective patterns as they form. This removes the subjectivity of manual wave counting.
- Pattern Validation: A rules-based engine confirms valid impulsive and corrective patterns by checking relative size relationships and fib ratios. Only confirmed wave counts are plotted and traded.
- Objective Entry Signals: Trades are entered systematically on the start of new impulsive waves in the direction of the trend. Pattern failures invalidate setups and stop out positions.
- Automated Trade Management: The strategy defines specific rules for profit targets at fib extensions, trailing stops at swing points, and exits on Supertrend reversals. This automates the entire trade lifecycle.
- Adaptability: The waveform recognition engine can be tuned by adjusting parameters like Zigzag depth and Supertrend settings. It adapts to evolving market conditions.
ETH 1hr chart
In summary, the strategy brings automation, objectivity and adaptability to Elliott Wave trading - removing subjective interpretation errors and emotional trading biases. It implements a rules-based, algorithmic approach for systematically trading Elliott Wave patterns across markets and timeframes.
## Trading Logic and Rules
The strategy follows specific trading rules based on the detected and validated Elliott Wave patterns.
Entry Rules
- Long entry when a new impulsive bullish (5-wave) pattern forms
- Short entry when a new impulsive bearish (5-wave) pattern forms
The key is entering on the start of a new potential trend wave rather than chasing.
Exit Rules
- Invalidation of wave pattern stops out the trade
- Close long trades on Supertrend downturn
- Close short trades on Supertrend upturn
- Use a stop loss of 10% of entry price (configurable)
Trade Management
- Scale out partial profits at Fibonacci levels
- Move stop to breakeven when price reaches 1.618 extension
- Trail stops below key swing points
- Target exits at next Fibonacci projection level
Risk Management
- Use stop losses on all trades
- Trade only highest probability setups
- Size positions according to chart timeframe
- Avoid overtrading when no clear patterns emerge
## Strategy - How it Works
The core logic follows these steps:
1. Find swing highs/lows with Zigzag indicator
2. Analyze pivot points to detect impulsive 5-wave patterns:
- Waves 1, 3, and 5 should not overlap
- Waves 3 and 5 must be longer than wave 1
- Confirm relative size relationships between waves
3. Validate corrective 3-wave patterns:
- Look for overlapping, choppy waves that retrace the prior impulsive wave
4. Plot validated waves and Fibonacci retracement levels
5. Signal entries when a new impulsive wave pattern forms
6. Manage exits based on pattern failures and Supertrend reversals
Impulsive Wave Validation
The strategy checks relative size relationships to confirm valid impulsive waves.
For uptrends, it ensures:
```
Copy code- Wave 3 is longer than wave 1
- Wave 5 is longer than wave 2
- Waves do not overlap
```
Corrective Wave Validation
The strategy identifies overlapping corrective patterns that retrace the prior impulsive wave within Fibonacci levels.
Pattern Failure Invalidation
If waves fail validation tests, the strategy invalidates the pattern and stops signaling trades.
## Trade Direction
The strategy detects impulsive and corrective patterns in both uptrends and downtrends. Entries are signaled in the direction of the validated wave pattern.
## Usage
- Use on charts showing clear Elliott Wave patterns
- Start with daily or weekly timeframes to gauge overall trend
- Optimize Zigzag and Supertrend settings as needed
- Consider combining with other indicators for confirmation
## Default Settings
- Zigzag Length: 4 bars
- Supertrend Length: 10 bars
- Supertrend Multiplier: 3
- Stop Loss: 10% of entry price
- Trading Direction: Both
Bitcoin 30m Swing Trader Long/Short StrategyIntro
I want to share the results of my passionate hobby and the unstoppable chase for a profitable automated trading strategy. It has been created with the intention of trading only Bitcoin. Altcoins are not interesting for me, as I have discovered lots of issues with finding the right parameter values for experiencing a good performance. As altcoins typically follow the trend of bitcoin and characteristically have a high volatility that may cause stop-hunts, I decided to not over complicate this project. I was just aiming for a profitable trading strategy with an acceptable drawdown and enough confidence by a statistically significant number of trades beside a wide backtesting timespan (credits going out to TradingView: Deep Backtesting).
Total time spent on this is approximately 2 years.
Indicators used
RSI: Used for entries and trend reversal spots
MACD: Used for entry and exit optimiziation
ATR: Used for dynamic offsets in trend definition indicator
Custom trend indicator: Self-made indicator, based on simple price action of higher timeframes using pivot points to find support and resistance zones that have formerly been created
Strategy parameters
I have reduced the total parameters used to just a few. It took lots of working hours to find appropriate values along the trading algorithm and I don’t want to overcomplicate it to you.
This strategy is for those, who have been looking for a working strategy. No DIY kit.
Feel free to adapt Take profit or stop loss targets. But it’s not recommended to do so.
How it works
Entries:
I started with a kind of template that I have been using for strategies for a long time. This includes how to find the right Entries during a trend as well as spotting trend reverse opportunities. Here I combine simple indicators like RSI and MACD beside necessary trend conditions. If a target RSI Value is hit, it will enter a trade, after MACD histogram has stopped to fall/rise. Depends on long/short. While we are in a trade and trend reversed, it waits for a specific RSI target level to be hit, to reverse the trade. As simple as it is, it closes the open one and starts a trade in other direction.
Micro trend:
It starts to get more interesting when it comes to trend recognition, as it forms the core of the strategy and discovering appropriate values for it has been very hard. The final trend variable is defined by the responses over higher timeframes of my self-made trend indicator. Executed on the current timeframe, the trend indicator is quite interesting. But for a automated trading strategy it is necessary to deviate trading instructions from higher timeframes trends.
Macro trend:
The same process that happens for micro trend is also applied with much higher timeframes, like 3D or weekly. The basic assumption is, that if we are in a bull or bear run, where retail investors are flooding the markets, we are increasing our take profit targets respectively. This way we can catch bigger moves in bigger trends.
Exits:
Closing a trade generally happens when a TP target (in %) is hit, or the SL (in %) is hit. The strategy has a special treatment with SL’s. After it happens, the strategy is more careful about market conditions and typically waits for a countertrade. The third way of closing a trade has already been mentioned: the reverse trades. They happen during choppy market conditions. The strategy has also special awareness here and tracks, if reverse trades start to happen more often. After a while, it starts to be more restrictive in opening new reverse trades.
Performance
Capabilities and limitations:
As I have already mentioned the strategy is only optimized for bitcoin (Perpetual Futures). This does not mean, it can not be used on other markets, because the algorithm itself is universal appliable. A very hard task was about finding the right parameter values for the strategy performing like this. If you have a special wish to configure this strategy for a specific market, DM me. The strategy has been tested with different configurations on the following timeframes: 30, 15, 10, 5, 1. I have decided to publish the one for 30m TF, because its performance simply convinced me.
Repainting:
It has been tested lots of times against repainting.
Confidence:
The total backtesting performance reaches out to 2019-09-08. So the strategy has been managing to be successful since then, but this does not guarantee that the logic, this strategy follows, is going to continue this level in future.
Commission:
The algorithm is configured with 0.04% commission per trade, as it is on Binance (for Future Market orders).
Ordersize:
Its totally up to you, how much of your total equity should be traded. Nevertheless, I would personally recommend to not exceed 50% ordersize of your equity with this strategy. In the past, you would have had great performance beside a drawdown, that was from psychological point of view good to handle with. This strategy additionally uses STOP LOSSES, so you can never loose you whole ordersize at one trade.
Slippage:
You also must consider about getting slipped when trading this strategy on live markets. Statistically one could assume, that the slippage could be neutral, as it can be both positive or negative. It depends on your execution time, the exchange, on which you are executing trades and market conditions. But keep it in mind, as if you have too much slippage, this strategy would be unprofitable.
Strategy Myth-Busting #7 - MACDBB+SSL+VSF - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our seventh one we are automating is the "Magic MACD Indicator: Crazy Accurate Scalping Trading Strategy ( 74% Win Rate )" strategy from "TradeIQ" who claims to have backtested this manually and achieved 427% profit with a 74% winrate over 100 trades in just a 4 months. I was unable to emulate these results consistently accommodating for slippage and commission but even so the results and especially the high win-rate and low markdown is pretty impressive and quite respectable.
This strategy uses a combination of 3 open-source public indicators:
AK MACD BB v 1.00 by Algokid
SSL Hybrid by Mihkel00
Volume Strength Finder by Saravanan_Ragavan
This is considered a trend following Strategy. AK MACD BB is being used as the primary short term trend direction indicator with an interesting approach of using Bollinger Bands to define an upper and lower range and upon the MACD going above the upper Bollinger Bands, it's indicative of an up trend, where as if the MACD is below the lower Bollinger Band, it's indicative of a down trend. To eliminate false signals, SSL Hyrbid is used as a trend confirmation filter, confirming and eliminating false signals from the MACD BB. It does this by validating the price action is above the the EMA and the SSL is positive that is a confirmation of an uptrend. When the price action is below the EMA and the SSL is negative, that is an confirmation of a downtrend. To avoid taking trades during ranged markets, VSF Buyer's Strength is used so the buyers/sellers strength and must be above 50% or the trade will not be inititiated.
Trading Rules
5 min candles but other lower time frames even below 5m work quite well too.
Best results can be found by tweaking these 2 input parameters:
Number Of bars to look back to ensure MACD isn't above/below Zero Line
Number Of bars back to look for SSL pullback
Long Entry when these conditions are true
AK MACD BB BB issues a new continuation long signal. A new green circle must appear on the indicator and these circles should not be touching across the zero level while they were previously red
SSL Hybrid price action closes above the EMA and the line is blue color and then creates a pullback . The pullback is confirmed when the color changes from blue to gray or from blue to red.
VSF Buyers strength above 50% at the time the MACD indicator issues a new long signal.
Short Entry when these conditions are true
AK MACD BB issues a new continuation short signal. A new red circle must appear on the indicator and these circles should not be touching across the zero level while they were previously green
SSL Hybrid price action closes below the EMA and the line is red color then it has to create a pullback . The pullback is confirmed when the color changes from red to gray or from red to blue.
VSF Sellers strength above 50% at the time the MACD indicator issues a new short signal.
Stop Loss at EMA Line with TP Target 1.5x the risk
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Kioseff Trading - AI-Optimized RSIAI-Optimized RSI
Introducing AI-Optimized RSI: a streamlined solution for traders of any skill level seeking to rapidly test and optimize RSI. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized RSI learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and RSI straightforward.
Features
Purpose : Uncover optimal RSI settings and entry levels with precision. Say goodbye to random guesses and arbitrary indicator use—this tool provides clear direction based on data.
Target Performance : You set the goal, and AI-RSI seeks it out, whether it's maximizing profits, efficient trading, or achieving the highest win rate.
AI-Powered : With intelligent AI recommendations, the tool dynamically fine-tunes your RSI approach, steering you towards ideal strategy performance.
Rapid Testing : Evaluate thousands of RSI strategies.
Dual Direction : Perfect both long and short RSI strategies with equal finesse.
Deep Insights : Access detailed metrics including profit factor, PnL, win rate, trade counts, and more, all within a comprehensive strategy script.
Instant Alerts : Set alerts and trade.
Full Customization : Test and optimize all RSI settings, including cross levels, profit targets and stop losses.
Simulated Execution : Explore the impact of limit orders and other trade types through simulation.
Integrative Capability : Combine your own custom indicators or others from the TradingView community for a personalized optimization experience.
Flexible Timeframes : Set your optimization and backtesting to any date range.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Direction : This setting controls trade direction: Long or Short.
Entry Condition : Define RSI entry: Select whether to trigger trades on RSI crossunders or crossovers.
RSI Lengths Range : Choose the range of RSI periods to test and find the best one.The AI will find the best RSI period for you.
RSI Cross Range : Set the range for RSI levels where crosses trigger trade signals. The AI will find the best level for you.
Combinations : Select how many RSI strategies to compare.
Optimization Type : Choose the goal for optimization and the AI: profit, win rate, or efficiency.
Profit Target : Set your profit target with this setting.
Stop Loss : Decide your maximum allowable loss (stop loss) per trade.
Limit Order : Specify whether to include limit orders in the strategy.
Stop Type : Choose your stop strategy: a fixed stop loss or a trailing stop.
How to: Find the best RSI for trading
It's important to remember that merely having the AI-Optimized RSI on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal RSI settings and strategy.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for RSI lengths and cross ranges at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
The image above shows our chart prior to any optimization efforts.
Note: the settings shown above in the key settings section will be used to start our demonstration.
2. Follow AI’s suggestions
Optimization Prompt: After loading your strategy, the indicator will prompt you to change the RSI length range and RSI level range to a better performing range.
Continue changing the RSI length range and RSI level range to match the indicator's suggestions until "Best Found" is displayed!
The image above shows results after we applied the tool’s suggestions. New suggestions have appeared, and we will continue to apply them.
Continue to adjust settings as recommended by the optimizer. If no better options are found, the optimizer will suggest increasing the number of combinations. Repeat this process until the optimizer indicates that the optimal setting has been identified.
Success! With the "Best Found" notification, an optimized RSI is now active. The AI will keep refining the strategy based on ongoing performance, ensuring continuous optimization.
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple RSI-based trading strategies using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Adaptive Learning Aggressiveness:
Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics.
Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Kioseff Trading - AI-Optimized Supertrend
AI-Optimized Supertrend
Introducing AI-Optimized Supertrend: a streamlined solution for traders of any skill level seeking to rapidly test and optimize Supertrend. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized Supertrend learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and Supertrend straightforward.
Features
Rapid Supertrend Strategy Testing : Quickly evaluate thousands of Supertrend strategies to find the most effective ones.
AI-Assisted Optimization : Leverage AI recommendations to fine-tune strategies for superior results.
Multi-Objective Optimization : Prioritize Supertrend based on your preference for the highest win rate, maximum profit, or efficiency.
Comprehensive Analytics : The strategy script provides an array of statistics such as profit factor, PnL, win rate, trade counts, max drawdown, and an equity curve to gauge performance accurately.
Alerts Setup : Conveniently set up alerts to be notified about critical trade signals or changes in performance metrics.
Versatile Stop Strategies : Experiment with profit targets, trailing stops, and fixed stop losses.
Binary Supertrend Exploration : Test binary Supertrend strategies.
Limit Orders : Analyze the impact of limit orders on your trading strategy.
Integration with External Indicators : Enhance strategy refinement by incorporating custom or publicly available indicators from TradingView into the optimization process.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Set the Factor Range Limits : The AI suggests optimal upper and lower limits for the Factor range, defining the sensitivity of the Supertrend to price fluctuations. A wider range tests a greater variety, while a narrower range focuses on fine-tuning.
Adjust the ATR Range : Use the AI's recommendations to establish the upper and lower bounds for the Average True Range (ATR), which influences the Supertrend's volatility threshold.
ATR Flip : This option lets you interchange the order of ATR and Factor values to quicky test different sequences, giving you the flexibility to explore various combinations and their impact on the Supertrend indicator's performance.
Strategies Evaluated : Adjust this setting to determine how many Supertrend strategies you want to assess and compare.
Enable AI Mode : Turn this feature on to allow the AI to determine and employ the optimal Supertrend strategy with the desired performance metric, such as the highest win rate or maximum profitability.
Target Metric : Adjust this to direct the AI towards optimizing for maximum profit, top win rates, or the most efficient profits.
AI Mode Aggressiveness : Set how assertively the AI pursues the chosen performance goal, such as highest profit or win rate.
Strategy Direction : Choose to focus the AI's testing and optimization on either long or short Supertrend strategies.
Stop Loss Type : Specify the stop loss approach for optimization—fixed value, a trailing stop, or Supertrend direction changes.
Limit Order : Decide if you want to execute trades using limit orders for setting your profit targets, stop losses, or apply them to both.
Profit Target : Define your desired profit level when using either a fixed stop loss or a trailing stop.
Stop Loss : Define your desired stop loss when using either a fixed stop loss or a trailing stop.
How to: Find the best Supertrend for trading
It's important to remember that merely having the AI-Optimized Supertrend on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal Supertrend settings and strategy.
Optimizing Supertrend involves adjusting two key parameters: the Factor and the Average True Range (ATR). These parameters significantly influence the Supertrend indicator's sensitivity and responsiveness to price movements.
Factor : This parameter multiplies the ATR to determine the distance of the Supertrend line from the price. Higher values will create a wider band, potentially leading to fewer trade signals, while lower values create a narrower band, which may result in more signals but also more noise.
ATR (Average True Range) : ATR measures market volatility. By using the ATR, the Supertrend adapts to changing market volatility; a higher ATR value means a more volatile market, so the Supertrend adjusts accordingly.
During the optimization process, these parameters are systematically varied to determine the combination that yields the best performance based on predefined criteria such as profitability, win rate, or risk management efficiency. The optimization aims to find the optimal Factor and ATR settings.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss, or if all trades exit when Supertrend changes direction. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for Supertrend Factor Range and Supertrend ATR Range at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
Demonstration Start: We'll begin with the settings outlined in the key settings section, using Supertrend's direction change to the downside as our exit signal for all trades.
2. Continue applying the AI’s suggestions
Keep updating your optimization settings based on the AI's recommendations. Proceed with this iterative optimization until the "Best Found" message is displayed, signaling that the most effective strategy has been identified.
While following the AI's suggestions, we've been prompted with a new suggestion: increase the
number of strategies evaluated. Keep following the AI's new suggestions to evaluate more strategies. Do this until the "Best Found" message shows up.
Success! We continued to follow the AI’s suggestions until “Best Found” was indicated!
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple Supertrend-based trading strategies using metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
AI Mode Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
LuxAlgo - Backtester (S&O)The S&O Backtester is an innovative strategy script that encompasses features + optimization methods from our Signals & Overlays™ toolkit and combines them into one easy-to-use script for backtesting the most detailed trading strategies possible.
Our Signals & Overlays™ toolkit is notorious for its signal optimization methods such as the 'Optimal Sensitivity' displayed in its dashboard which provides optimization backtesting of the Sensitivity parameter for the Confirmation & Contrarian Signals.
This strategy script allows even more detailed & precise backtests than anything available previously in the Signals & Overlays™ toolkit; including External Source inputs allowing users to use any indicator including our other paid toolkits for take profit & stop loss customization to develop strategies, along with 10+ pre-built filters directly Signals & Overlays™' features.
🔶 Features
Full Sensitivity optimization within the dashboard to find the Best Win rates or Best Profits.
Counter Trade Mode to reverse signals in undesirable market conditions (may introduce higher drawdowns)
Built-in filters for Confirmation Signals w/ Indicator Overlays from Signals & Overlays™.
Built-in Confirmation exit points are available within the settings & on by default.
External Source Input to filter signals or set custom Take Profits & Stop Losses.
Optimization Matrix dashboard option showing all possible permutations of Sensitivity.
Option to Maximize for Winrate or Best Profit.
🔶 Settings
Sensitivity signal optimizations for the Confirmation Signals algorithm
Buy & Sell conditions filters with Indicator Overlays & External Source
Take Profit exit signals option
External Source for Take Profit & Stop Loss
Sensitivity ranges
Backtest window default at 2,000 bars
External source
Dashboard locations
🔶 Usage
Backtests are not necessarily indicative of future results, although a trader may want to use a strategy script to have a deeper understanding of how their strategy responds to varying market conditions, or to use as a tool for identifying possible flaws in a strategy that could potentially be indicative of good or bad performance in the future.
A strategy script can also be useful in terms of it's ability to generate more complete & configurable alerts, giving users the option to integrate with external processes.
In the chart below we are using default settings and built-in optimization parameters to generate the highest win rate.
Results like the above will vary & finding a strategy with a high win rate does not necessarily mean it will persist into the future, however, some indications of a well-optimized strategy are:
A high number of closed trades (100+) with a consistently green equity curve
An equity curve that outperforms buy & hold
A low % max drawdown compared to the Net Profit %.
Profit factor around 1.5 or above
In the chart below we are using the Trend Catcher feature from Signals & Overlays™ as a filter for standard Confirmation Signals + exits on a higher timeframe.
By filtering bullish signals only when the Trend Catcher is bullish, as well as bearish signals for when the Trend Catcher is bearish, we have a highly profitable strategy created directly from our flagship features.
While the Signals & Overlays features being used as built-in filters can generate interesting backtests, the provided External Sources can allow for even more creativity when creating strategies. This feature allows you to use many indicators from TradingView as filters or to trigger take-profit/stop-loss events, even if they aren't from LuxAlgo.
The chart below shows the HyperWave Oscillator from our Oscillator Matrix™ being used for take-profit exit conditions, exiting a long position on a profit when crossing 80, and exiting a short position when crossing 20.
🔶 Counter Trade Mode
Our thesis has always firmly remained to use Confirmation Signals within Signals & Overlays™ as a supportive tool to find trends & use as extra confirmation within strategies.
We included the counter-trade mode as a logical way to use the Confirmation signals as direct entries for longs & shorts within more contrarian trading strategies. Many traders can relate to using a trend-following indicator and having the market not respect its conditions for entries.
This mode directly benefits a trader who is aware that market conditions are generally not-so-perfect trends all the time. Acknowledging this, allows the user to use this to their advantage by introducing countertrend following conditions as direct entries, which tend to perform very well in ranging markets.
The big downfall of using counter-trade mode is the potential for very large max-drawdowns during trending market conditions. We suggest for making a strategy to consider introducing stop-loss conditions that can efficiently minimize max-drawdowns during the process of backtesting your creations.
Sensitivity Optimization
Within the Signals & Overlays™ toolkit, we allow users to adjust the Confirmation Signals with a Sensitivity parameter.
We believe the Sensitivity paramter is the most realistic way to generate the most actionable Confirmation Signals that can navigate various market conditions, and the Confirmation Signals algorithm was designed specifically with this in mind.
This script takes this parameter and backtests it internally to generate the most profitable value to display on the dashboard located in the top right of the chart, as well as an optimization table if users enable it to visualize it's backtesting.
In the image below, we can see the optimization table showing permutations of settings within the user-selected Sensitivity range.
The suggested best setting is given at the current time for the backtesting window that's customizable within the indicator. Optimized settings for technical indicators are not indicative of future results and the best settings are highly likely / guaranteed to change over time.
Optimizing signal settings has become a popular activity amongst technical analysts, however, the real-time beneficial applications of optimizing settings are limited & best described as complicated (even with forward testing).
🔶 Strategy Properties (Important)
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from strategies built are realistic.
🔶 How to access
You can see the Author's Instructions below to learn how to get access on our website.
The Flower - Multiple Strategy Options in OneStrategy Overview
This strategy code currently includes four separate strategies to be used to either aid in discretionary trading or to be used algorithmically through the third-party system Profitview (profitview.app). Support for Pineconnector for use with MetaTrader 4 is in the works. The strategies have been designed with cryptocurrency trading in mind, however, the fundamentals apply to other assets.
The four strategies currently included are labeled “TSI Cross” (the default setting), “Oscillator Bands”, “Scalping”, and “McG/MA Cross”. Detailed information for each independent strategy can be found below, including sample settings configurations for each. A dropdown menu to select the strategy can be found under the “Strategy Options” set of settings under the Input tab of the strategy settings menu.
Additionally, the option to receive only long or short signals can be found alongside the Strategy Choice menu.
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly.
The only visuals associated with the strategy are two McGinley Dynamic lines, red (slow length) and green (fast length). These are relevant to the McGinley Cross strategy, but can be used alongside the other strategies if desired.
When viewing the backtesting data in the TradingView Strategy Tester, ensure that “use bar magnifier” is activated. This option can be found in the Properties tab of the strategy settings menu.
Profitview Settings
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. A sample of our Profitview syntax can be found below.
To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Strategy Choices
As mentioned above, this strategy code contains four separate strategy options. A detailed breakdown of each follows below:
Total Strength Index (TSI) Cross
This strategy option is the default choice. The main signal involved in this strategy is a crossover or crossunder of the TSI value line and TSI signal line, however, there are a few other signals involved in the creation of a long or short entry. In addition to the TSI, the strategy includes an Average Directional Index (ADX) threshold value, Jurik Volatility Bands (JVB), a Stoch RSI threshold, and an oscillator of choice in conjunction with a threshold of 0. This oscillator choice can be selected under the “Signal Options” menu in the Input tab of the strategy settings. The default oscillator is the Detrended Price Oscillator (DPO), though the option for Chande Momentum (CMO) or Rate of Change (RoC) are both viable for this strategy.
Individual settings for these can be found in the Input tab under “Oscillator Settings” (TSI, Stoch RSI, DPO, CMO, ROC), “Band/Channel Settings” (Jurik Volatility Bands Length/Smoothing), and “Directional Settings” (ADX Smoothing Long, DI Length Short, ADX Threshold).
Sample settings for SOLUSDT using the 20M timeframe:
- Oscillator Settings -- DPO Length (21), DPO *not* centered, RSI (Stoch) Length (4), Stochastic Length (4), TSI Long Length (25), TSI Short Length (13), TSI Signal Length (13), K (3), D (3)
- Band/Channel Settings -- Jurik Volatility Bands Length (25), Jurik Volatility Bands Smoothing (5)
- Directional Settings – JVB Price Threshold (0), ADX Smoothing Long (5), DI Length Short (5), ADX Threshold (23)
- Take Profit/Stop Loss – 0.85% TP, 0.005% TTP, 1.3% SL
Oscillator Bands
This strategy involves the usage of bands or channels that use oscillators as a source input. The main signal for this strategy derives from a cross of the band or channel and a hline of 0. Additionally, this includes a “Directional Filter” and a “MA Filter”. The selections for all of these can be found in the “Signal Options” section of the Input tab.
First option is for Oscillator Choice and includes DPO, CMO, ROC, RSI, TSI, and the Jurik price line. The individual settings for these can be found in the “Oscillator Settings” section. Different channels can be selected for the upper or lower bands, though it is not necessary for them to differ. These current options include Bollinger Bands and Jurik Volatility Bands, the individual settings for each found in the “Band/Channel Settings” section. Next is the MA Filter, of which you can select SMA, EMA, SMMA, WMA, VWMA, KAMA, JMA, or McGinley Dynamic. All options for these settings can be found in the “MA Filter Settings” section. Lastly, the Directional Filters can be selected for either direction like the upper/lower band selection. These filters include the ADX, Bull-Bear Power (BBP), Parabolic SAR (PSAR), or Jurik.
Sample settings for WAVESUSDT using the 20M timeframe:
- Oscillator Choice – DPO (Length – 30, uncentered)
- Upper and Lower Band – JVB Upper/Lower (Jurik Volatility Bands Length – 25; Smoothing – 10)
- MA Filter – VWMA – (MA Length – 40; Source – Open)
- Directional Filter – ADX (ADX Smoothing Long – 14; DI Length Short – 5; ADX Threshold – 22)
- Take Profit/Stop Loss – 0.85% TP, 0.005% TTP, 1.3% SL
Scalping
This strategy heavily relies on the usage of Parabolic SAR, accompanied by a “Directional Filter” (as discussed in the previous section) other than PSAR. This strategy can provide a higher frequency of trades as opposed to the other strategies available, however, it comes with slightly higher risk inherently. A riskier take profit/stop loss spread is recommended here, though risk should always be managed. The settings required for this strategy are all found under the “Directional Settings” section of the strategy inputs.
Sample settings for NEARUSDT using the 20M timeframe:
- Directional Filter set to ADX
- Directional Settings – ADX Smoothing Long (5), DI Length Short (5), ADX Threshold (22), PSAR Start Value (0.02), PSAR Increment (0.005), PSAR Max Value (0.15), PSAR Source (Close)
- Take Profit/Stop Loss – 0.75% TP, 0.005% TTP, 1.5% SL
McGinley Cross
This strategy revolves around the crossing of two McGinley Dynamic lines of varying lengths alongside an ADX filter as well as a DPO filter. McGinley is used as opposed to a standard moving average cross strategy as it adjusts for shifts in market speed and can better gauge market trends. The McGinley length settings can be found with the “MA Filter” settings, labeled as Fast Length and Slow Length. The fast length number should be smaller than the slow length.
Sample settings for SOLUSDT using the 20M timeframe:
- Oscillator Settings – DPO Length (30), uncentered
- MA Filter Settings – McGinley Fast Length (4), McGinley Slow Length (21)
- Take Profit/Stop Loss – 0.85% TP, 0.005% TTP, 1.4% SL
Comprehensive Settings List
Date and Time: From date and to date, adjustable for backtesting purposes.
Signal Options:
Oscillator Choices: Chande Momentum Oscillator (CMO), Detrended Price Oscillator (DPO), Rate of Change (ROC), Relative Strength Index (RSI), True Strength Index (TSI), Jurik Volatility Bands Priceline (JVB) – *** for use with TSI Cross or Oscillator Bands strategies only ***
Upper and Lower Band/Channel Choices: Bollinger Bands (BB) or Jurik Volatility Bands (JVB) -- *** for use with Oscillator Bands strategy only ***
MA/McG Filter: SMA, EMA, RMA, WMA, VWMA, Kaufmann MA, Jurik MA, McGinley Dynamic -- *** for use with Oscillator Bands strategy only ***
Directional Filter Long/Short: Average Directional Index (ADX), Bull/Bear Power (BBP), Parabolic SAR (PSAR), Jurik -- *** for use with Oscillator Bands strategy only ***
Profitview Settings: *** For use with ProfitView extension only, otherwise ignore ***
Oscillator Settings: *** For use with TSI Cross, Oscillator Bands, and McGinley Cross strategies ***
CMO Length, CMO Source – for Chande Momentum Oscillator
DPO Length, DPO Centered – for Detrended Price Oscillator
RoC Length, RoC Source – for Rate of Change
RSI Length, RSI MA Length – for Relative Strength Index
RSI (Stoch) Length, Stochastic Length, Stoch RSI Source, K, D – for Stochastic RSI
TSI Long Length, TSI Short Length, TSI Signal Length – for True Strength Index
Band/Channel Settings: *** For use with Oscillator Bands strategy ***
Jurik Volatility Bands Length, Jurik Volatility Bands Smoothing – for Jurik Volatility Bands
Bollinger Band Length, Bollinger Band Multiplier – for Bollinger Bands
Directional Settings: *** For use with Scalping and Oscillator Bands strategies ***
JVB Price Threshold – for Jurik Volatility as a directional setting
ADX Smoothing Long, DI Length Short, ADX Threshold – for Average Directional Index
PSAR Start Value, PSAR Increment, PSAR Max Value, PSAR Source – for Parabolic SAR
MA Filter Settings: *** For use with Oscillator Bands and McGinley Cross strategies ***
McGinley Fast/Slow Length – for McGinley Dynamic
MA Length, MA Source, MA Offset – for any other moving average
TP and TTP / Stop Loss: *** For use with ALL strategies ***
Long/Short Take Profit % -- for standard take profit settings
Enable Trailing, Trailing Take Profit % -- for trailing settings
Stop Loss % -- for standard stop loss settings; trailing can be enabled or disabled for stop loss
Disclaimers:
Some open-source code has been included -- Jurik Volatility Bands (by "ProValueTrader") and Trailing Take Profit/Stop Loss code (by jason5480). Additional code was used from the TradingView built-ins.
These strategies do NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Invites to the strategy will only be disseminated to those with express consent and knowledge of the invite prior to the action itself.
GT 5.1 Strategy═════════════════════════════════════════════════════════════════════════
█ OVERVIEW
People often look an indicator in their technical analysis to enter a position. We may also need to look at the signals of one or more indicators to verify the signals given by some indicators. In this context, I developed a strategy to test whether it really works by choosing some of the indicators that capture trend changes with the same characteristics. Also, since the subject is to catch the trend change, I thought it would be right to include an indicator using the heikin ashi logic. By averaging and smoothing the market noise, Heiken Ashi makes it easier to detect the direction of the trend helps to see possible reversal points on the chart. However, it should be noted that Heiken Ashi is a lagging indicator.
I picked 5 different indicators (but their purpose are similar) and combined them to produce buy and sell signals based on your choice(not repaint). First of all let's get some information about our indicators. So you will understand me why i picked these indicators and what is the meaning of their signals.
1 — Coral Trend Indicator by LazyBear
Coral Trend Indicator is a linear combination of moving averages, all obtained by a triple or higher order exponential smoothing. The indicator comes with a trend indication which is based on the normalized slope of the plot. the usage of this indicator is simple. When the color of the line is green that means the market is in uptrend. But when the color is red that means the market is in downtrend.
As you see the original indicator it is simple to find is it in uptrend or downtrend.
So i added a code to find when the color of the line change. When it turns green to red my script giving sell signals, when it turns red to green it gives buy signals.
I hide the candles to show you more clearly what is happening when you choose only Coral Strategy. But sometimes it is not enough only using itself. Even if green dots turn to red it continues in uptrend. So we need a to look another indicator to approve our signal.
2 — SSL channel by ErwinBeckers
Known as the SSL , the Semaphore Signal Level channel is an indicator that combines moving averages to provide you with a clear visual signal of price movement dynamics. In short, it's designed to show you when a price trend is forming. This indicator creates a band by calculating the high and low values according to the determined period. Simply if you decide 10 as period, it calculates a 10-period moving average on the latest 10 highs. Calculate a 10-period moving average on the latest 10 lows. If the price falls below the low band, the downtrend begins, if the price closes above the high band, the uptrend begins. Lets look the original form of indicator and learn how it using.
If the red line is below and the green band is above, it means that we are in uptrend, and if it is on the opposite side, it means that we are in downtrend. Therefore, it would be logical to enter a position where the trend has changed. So i added a code to find when the crossover has occured.
As you see in my strategy, it gives you signals when the trend has changed. But sometimes it is not enough only using this indicator itself. So lets look 2 indicator together in one chart.
Look circle SSL is saying it is in downtrend but Coral is saying it has entered in uptrend. if we just look to coral signal it can misleads us. So it can be better to look another indicator for validating our signals.
3 — Heikin Ashi RSI Oscillator by JayRogers
The Heikin-Ashi technique is used by technical traders to identify a given trend more easily. Heikin-Ashi has a smoother look because it is essentially taking an average of the movement. There is a tendency with Heikin-Ashi for the candles to stay red during a downtrend and green during an uptrend, whereas normal candlesticks alternate color even if the price is moving dominantly in one direction. This indicator actually recalculates the RSI indicator with the logic of heikin ashi. Due to smoothing, the bars are formed with a slight lag, reflecting the trend rather than the exact price movement. So lets look the original version to understand more clearly. If red bars turn to green bars it means uptrend may begin, if green bars turn to red it means downtrend may begin.
As you see HARSI giving lots of signal some of them is really good but some of them are not very well. Because it gives so much signals Now i will change time period and lets look same chart again.
Now results are better because of heikin ashi's logic. it is not suitable for day traders, it gives more accurate result when using the time period is longer. But it can be useful to use this indicator in short time periods using with other indicators. So you may catch the trend changes more accurately.
4 — MACD DEMA by ToFFF
This indicator uses a double EMA and MACD algorithm to analyze the direction of the trend. Though it might seem a tough task to manage the trades with the help of MACD DEMA once you know how the proper way to interpret the signal lines, it will be an easy task.
This indicator also smoothens the signal lines with the time series algorithm which eventually makes the higher time frame important. So, expecting better results in the lower time frame can result in big losses as the data reading from the MACD DEMA will not be accurate. In order to understand the function of this indicator, you have to know the functions of the EMA also.
The exponential moving average tends to give more priority to the recent price changes. So, expecting better results when the volatility is very high is a very risky approach to trade the market. Moreover, the MACD has some lagging issues compared to the EMA, so it is super important to use a trading method that focuses on the higher time frame only. What does MACD 12 26 Close 9 mean? When the DEMA-9 crosses above the MACD(12,26), this is considered a bearish signal. It means the trend in the stock – its magnitude and/or momentum – is starting to shift course. When the MACD(12,26) crosses above the DEMA-9, this is considered a bullish signal. Lets see this indicator on Chart.
When the blue line crossover red line it is good time to buy. As you see from the chart i put arrows where the crossover are appeared.
When the red line crossover blue line it is good time to sell or exit from position.
5 — WaveTrend Oscillator by LazyBear
This is a technical indicator that creates high and low bands between two values. It then creates a trend indicator that draws waves with highs and lows within these boundaries. WaveTrend is a widely used indicator for finding direction of an asset.
Calculation period: number of candles used to calculate WaveTrend, defaults to 10. Averaging period: number of candles used to average WaveTrend, defaults to 21.
As you see in chart when the lines crossover occured my strategy gives buy or sell signals.
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█ HOW TO USE
I hope you understand how the indicators I mentioned above work and what they are used for. Now, I will explain in detail how to use the strategy I have created.
When you enter the settings section, you will see 5 types of indicators. If you want to use the signals of the indicators, simply tick the box next to the indicators. Also, under each option there is an area where you can set the "lookback". This setting is a field that will make the signals overlap when you select more than one option. If you are going to trade with only one option, you should make sure that this field is 0. Otherwise, it may continue to generate as many signals as you choose.
Lets see in chart for easy understanding.
As you see chart, if i chose only HARSI with lookback 0 (HARSI and CORAL should be 1 minumum because of algorithm-we looking 1 bar before, others 0 because we are looking crossovers), it will give signals only when harsı bar's color changed. But when i changed Lookback as 7 it will be like this in chart.
Now i will choose 2 indicator with settings of their lookback 0.
As you see it will give signals when both of them occurs same time. But HARSI is an indicator giving very early signal so we can enter position 5-6 bars after the first bar color change. So i will change HARSI Lookback settings as 7. Lets look what happens when we use lookback option.
So it wil be useful to change lookback settings to find best signals in each time period and in each symbol. But it shouldnt be too high. Because you can be late to catch trend's starting.
this is an image of MACD and WAVE trend used and lookback option are both 6.
Now lets see an example with 3 options are chosen with lookback option 11-1-5
Now lets talk about indicators settings. After strategy options you will see each indicators settings, you can change their settings as you desired. So each indicators signal will be changed according to your adjustment.
I left strategy options with default settings. You can change it manually as if you want.
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█ LIMITATIONS: Don't rely on non-standard charts results. For example Heikin Ashi is a technical analysis method used with the traditional candlestick chart.Heikin Ashi vs. Candlestick Chart: The decisive visual difference between Heikin Ashi and the traditional chart is that Heikin Ashi flattens the traditional candlestick chart using a modified formula.
The primary advantage of Heikin Ashi is that it makes the chart more reader-friendly and helps users identify and analyze trends .
Because Heikin Ashi provides averaged price information rather than real-time price and reacts slowly to volatility — not suitable for scalpers and high-frequency traders. I added HARSI indicator as a supportive signal because it is useful with using CORAL and SSL channel indicators. If you change your candle types to Heikin Ashi , your profit will change in good way but dont rely on it.
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█ THANKS:
Special thanks to authors of the scripts that i used.
@LazyBear and @ErwinBeckers and @JayRogers and @ToFFF
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█ DISCLAIMER
Any trade decisions you make are entirely your own responsibility.
Longbithello Traders !
Inspired by the indicator Range Filter Buy and Sell 5min by guikroth , namely calculation and works price movement range filter .
And Inspired by the indicator by the indicator VuManChu Cipher B + Divergences by vumanchu namely calculation and working out divergences and convergences , i was inspired to create a strategy .
This is indicator - strategy - ( Longbit ) - aggregate and my modification indicators : Range Filter Buy and Sell 5min by guikroth , VuManChu Cipher B + Divergences by vumanchu , and diferent exponential moving average .
The strategy - ( Longbit ) works on the basis of the price movement range filter , first a smooth average price range is calculated for the basis of the filter and multiplied by a specified amount by indicator Range Filter Buy and Sell 5min by guikroth , and some calculations working out divergences and convergences by indicator VuManChu Cipher B + Divergences by vumanchu . And diferent exponential moving averages for zones Bull / Bear trend for trend trading , and using take and diferent stop loss : algo , user or percentage .
Thus, using my strategy, we get the best entry point to open trades after confirming divergences
example in the picture
or
And when these trend signals are much stronger
example in the picture
Actual Version recommended used for BTCUSDC / BTCUSDT 4 hours time frame and used default settings and stop loss - algo , take profit 6 %
example in the picture
But it can also be used on all time frame with these settings: MaxMin3 Data Sampling period 6 Range Multiplier 2 and Take profit 2.3 % , stop loss algo
DISCLAIMER: This informational planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. I am not responsible for any losses you may incur.
Привет, Трейдеры ! Вдохновленный индикатором Range Filter Buy and Sell 5min by guikroth , а именно работой и вычеслением диапазона фильтра движения цены . А также вдохновленный индикатором VuManChu Cipher B + Divergences by vumanchu, а именно дивергенций и конвергенций , я был вдохновлен создать эту стратегию
Эта тратегия - (Longbit) - это совокупность индикаторов : Range Filter Buy and Sell 5min by guikroth , VuManChu Cipher B + Divergences by vumanchu, и разние виды экспоненциальных средних .
Стратегия - (Longbit) работает на основе фильтра диапазона изменения цен, сначала рассчитывается гладкий средней диапазон цен для базы фильтра и умножается на оговоренную сумму по индикатору Range Filter Buy and Sell 5min by guikroth модифицированой версии , а также некоторые расчеты вычислений дивергенций и конвергенции по показателю индикатора VuManChu Cipher B+ Divergences by vumanchu. И различные экспоненциальные среднее и их зон для определения тенденции либо трендов для торговли по тренду , и с использованием стоп лоса : алго, пользовательский или процентный .
Таким образом, используя мою стратегию, мы получим лучшую точку для открытия сделок после подтверждения дивергенций или конвергенций
А когда эти сигналы по тренду они намного сильнее на рисунке , примеры на картинках выше
Рекомендуемую для 4-часового тм BTCUSDC/BTCUSDT , и работать с помощью algo stop loss , и take в 6 % с настройками по умолчанию , но можно также на использовать на всех тм с такой вот настройкой :
Данные МакМин3
Sampling period 6
Range Multiplier 2
Примеры на картинках выше
Предупреждаю : Эта стратегия информационного планирования предназначен исключительно для индивидуального пользования и образовательных целей. Это не финансовая или инвестиционная консультация. Инвестиции всегда осуществляются на собственном риске и основываются на вашем личном суждении. Я не отвечаю за потери, которые вы можете понести.
MY_TRENDThe MY_TREND strategy is designed to work with cryptocurrencies and stocks.
The optimal working timeframe is 1 - 4 hours.
The search for trading zones and main entry points is based on the Donchian channel using the author's filtering by pinning.
To avoid manipulations in the market, the algorithm monitors the level of the price relative to the global trend and thus filters out a large part of the false signals.
If the price fixes above the trend line, we expect an upward movement, and if it fixes below, we expect a downward movement.
In addition, in the settings it is possible to use additional trend entries, as well as aggressive trading.
To do this, in the area of action of the main trend, built on the basis of the Donchian channel, a local trend is formed at the moving average price of the asset.
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📗 Algorithm for selecting optimal parameters:
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1. Disable the use of takes and stops, and set up the setup (described below) so that the back test readings are positive and have growing dynamics.
Pay attention to the level of drawdown and the percentage of correct trades.
2. Enable the use of a stop line, and select the most optimal stop parameters so that the drawdown level on the back test is acceptable for you.
3. Enable the use of takes and select the most optimal take for your strategy.
4. Select the type of trade (described below) and make sure that the back test readings are acceptable to you.
5. By default, the strategy uses a trading commission of 0.04% (standard for crypto futures), but for stocks it should be set in accordance with the commissions of your broker.
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💹 SETUP SETTINGS:
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Setup_length - distance for calculating and evaluating volatility in the Donchian channel.
For an older timeframe, it is better to lower the value, otherwise we may get a delay in the reaction of the trend to the price movement.
Setup_mult - multiplier to smooth out the reaction of the trend in the Donchian channel.
For an older TF, it is better to increase the value in order to avoid false entry signals.
Selecting the type of trade:
BASED - gives trading signals only when the basic trend changes (trading without additional entry signals).
IN_TREND - gives BASED trading signals and additional signals on the underlying trend, using the ADD SMA as a local trend indicator.
AGRESSIVE - gives BASED trading signals and additional signals on the underlying trend, when the price falls below the ADD SMA local trend line.
ADD SMA length - SMA period to form a local trend within the underlying Donchian trend (values in the range of 3-9 should be used to get a fast response).
This setting is relevant for IN_TREND and AGRESSIVE trading types.
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🟢 TAKE SETTINGS:
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The strategy has 3 types of take:
ATR - take based on the instrument's volatility value (adjusted by a multiplier).
FIX - take, set as a percentage (set manually).
STDEV - take, based on the calculation of the standard deviation of the price (adjusted by a multiplier and a period).
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⛔️ STOP SETTINGS:
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The strategy has 3 types of stops:
ATR - stop based on the instrument's volatility value (adjustable by a multiplier).
FIX - stop specified in percentage (set manually).
TREND - the stop line is equal to the base trend line.
It is possible to turn on the stop line tightening to the level of the price of entry into a position, when the price passes the value of one standard deviation into profit.
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💡 OTHER USEFUL FEATURES
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✅ In the strategy, you can enable / disable the use of takes and stop lines.
✅ In the strategy, you can enable / disable the display of the base and local trend lines, and enable the background highlighting of the current trend.
✅ You can choose the direction of trading: long, short or any.
✅ Leverage can be set (x3 by default).
✅ The screen has a compact display of a table with the current strategy settings and the current state (position, takes, stop).
For the convenience of saving your settings, use the standard PrintScreen function.
✅ You can sign the strategy in the Notes field - this is convenient if you place several versions of the MY_TREND strategy on the chart with different settings (for different pairs or for different timeframes).
✅ You can choose the type of alerts - ALERT or BOT.
ALERT - tradingview pop-up trading alerts (you can configure them to be sent to e-mail or to the application).
BOT - trading commands following the Binance/Finandy syntax, designed to be sent to a trading bot using a webhook.
To use alerts, select "Only when the alert() function is called"
✅ 👉 In the strategy settings, each field has hints, to do this, hover over the ⓘ sign
💰 Be sure to follow the risk management when trading!
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The MY_TREND strategy is private! You can get test access to it for 24 hours.
👉 In order to gain access or ask questions, write to me in private messages or at the contacts indicated in my signature.
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Стратегия MY_TREND предназначена для работы с криптовалютами и акциями.
Оптимальный рабочий таймфрейм 1 - 4 часа.
Поиск торговых зон и основных точек входа производится на базе канала Donchian используя авторскую фильтрацию по закреплению.
Чтобы избежать манипуляций на рынке, алгоритм отслеживает уровень нахождения цены относительно глобального тренда и тем самым фильтрует немалую часть ложных сигналов.
При закреплении цены выше трендовой, мы ожидаем восходящее движение, а при закреплении ниже - нисходящее.
Кроме этого в настройках есть возможность использовать дополнительные входы по тренду, а также агрессивную торговлю.
Для этого в зоне действия основного тренда, построенного на базе канала Donchian, формируется локальный тренд по средней скользящей цены актива.
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📗 Алгоритм подбора оптимальных параметров:
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1. Отключите использование тейков и стопов, и настройте сетап (ниже подробно описано) так, чтобы показания бэк-теста были положительными и имели растущую динамику.
Обращайте внимание на уровень просадки и процент верных сделок.
2. Включите использование стоп-линии, и подберите наиболее оптимальные параметры стопа так, чтобы уровень просадки на бэк-тесте был для Вас приемлемым.
3. Включите использование тейков и подберите наиболее оптимальный тейк для Вашей стратегии.
4. Выберите тип торговли (ниже описано) и убедитесь в приемлемых для Вас показаниях бэк-теста.
5. По умолчанию в стратегии используется торговая комиссия 0,04% (стандартно для крипто-фьючерсов), но для акций её следует выставить в соответствии с комиссиями Вашего брокера.
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💹 НАСТРОЙКА СЕТАПА:
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Setup_length - дистанция для расчета и оценки волатильности в канале Donchian.
Для более старшего ТФ, значение лучше понижать, иначе мы можем получить запаздывание реакции тренда на движение цены.
Setup_mult - множитель, для сглаживания реакции тренда в канале Donchian.
Для более старшего ТФ, значение лучше повышать, чтобы избежать ложных сигналов на вход.
Выбор типа торговли:
BASED - даёт торговые сигналы только при смене базового тренда (торговля без дополнительных сигналов на вход).
IN_TREND - даёт торговые сигналы BASED и дополнительные сигналы по базовому тренду, используя ADD SMA как индикатор локального тренда.
AGRESSIVE - даёт торговые сигналы BASED и дополнительные сигналы по базовому тренду, при просадке цены ниже линии локального тренда ADD SMA.
ADD SMA length - Период SMA для формирования локального тренда внутри базового тренда Donchian (следует использовать значения в диапазоне 3-9, для получения быстрой реакции).
Данная настройка актуальна для типов торговли IN_TREND и AGRESSIVE.
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🟢 НАСТРОЙКА ТЕЙКОВ:
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Стратегия имеет 3 типа тейка:
ATR - тейк на базе значения волатильности инструмента (регулируется множителем).
FIX - тейк, заданный в процентах (задаётся вручную).
STDEV - тейк, на базе расчёта стандартного отклонения цены (регулируется множителем и периодом).
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⛔️ НАСТРОЙКА СТОПА:
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Стратегия имеет 3 типа стопа:
ATR - стоп на базе значения волатильности инструмента (регулируется множителем).
FIX - стоп, заданный в процентах (задаётся вручную).
TREND - стоп-линия равна базовой линии тренда.
Есть возможность включить подтяжку стоп-линии на уровень цены входа в позицию, при прохождении цены значения одного стандартного отклонения в профит.
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💡 ПРОЧИЕ ПОЛЕЗНЫЕ ФУНКЦИИ
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✅ В стратегии можно включить/отключить использование тейков и стоп-линии.
✅ В стратегии можно включить/отключить отображение линии базового и локального тренда, а включить фоновую подкраску текущего тренда.
✅ Можно выбрать направление торговли: лонг, шорт или любое.
✅ Можно установить кредитное торговое плечо (по умолчанию x3).
✅ На экране есть компактное отображение таблицы с текущими настройками стратегии и текущим состоянием (позиция, тейки, стоп).
Для удобства сохранения своих настроек - воспользуйтесь стандартной функцией PrintScreen.
✅ Вы можете подписать стратегию в поле Notes - это удобно, если Вы размещаете на графике несколько версий стратегии MY_TREND с разными настройками (для разных пар или для разных ТФ).
✅ Вы можете выбрать тип оповещений - ALERT или BOT.
ALERT - всплывающие торговые оповещения tradingview (можно настроить их отправку на e-mail или в приложение).
BOT - торговые команды с соблюдением синтаксиса Binance/Finandy, предназначенные для отправки их торговому боту с помощью webhook.
Для использования оповещений выбирайте "Только при вызове функции alert()"
✅ 👉 В настройках стратегии у каждого поля есть подсказки, для этого наведите курсор на знак ⓘ
💰 Обязательно соблюдайте риск-менеджмент при торговле!
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Стратегия MY_TREND является закрытой! Вы можете получить к ней тестовый доступ на 24 часа.
👉 Для того, чтобы получить доступ или задать вопросы пишите мне в личные сообщения или по контактам, указанным в моей подписи.
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ETH long bot - 8hrThis is a high-latency algorithm, safely running on the Ethereum 8hr chart where it can execute trades on a multi-day timeframe, making it easy to enter and exit large positions and without incurring excessive commission fees.
As a long bot, this script should be ran in markets that are trending upwards. Nonetheless, the operator can be at ease knowing that the script can safely run autonomously during these extended periods. It is shown here performing full-time over a 46 month period, from January 2019 through October 2021, steadily increasing the available capital despite the asset's fluctuations. While the buy and hold return over this time was 714%, the algorithm produced a net profit 4,060%, outperforming the market by over 5.5x. This equates to a 40x return on investment in 4 years.
The strategy behind this algorithm is to always capitalize on significant jumps in the market. This is accomplished by using a simple combination of RSIs:
- One RSI uses VWAP as a source, which is primarily responsible for entering growth trends whenever they begin
- The other is a Stochastic RSI , which is primarily responsible for identifying exhausted periods of growth
These calculations are calibrated so that the bot can jump in and out of trades to improve its position when there isn't significant price action one way or the other, but is then able to remain in positions during uptrends that are backed by volume to achieve maximum gains. This strategy is reflected by the fact that while profitable trades are almost 3 times larger than losing trades, on average, they also last for an average of 6 days, whereas losing trades usually last about 2.
[Sextan] PINEv5 Sextans Backtest Framework V3.3Level: 5
Background
In order to celebrate the breakthrough of 4000 followers of my account, I decided to release the Sextan backtesting framework for free use to help more quantitative traders quickly evaluate any technical indicators.
The version released this time is based on the algorithm framework optimization of the old version, and integrates the new feature in Pine V5: Bar Magnifier. This new feature to make Sextan strategy backtesting even more accurate. FYI.
www.tradingview.com
Backtesting of technical indicators and strategies is the most common way to understand a quantitative strategy. However, the complicated configuration and adaptation work of backtesting many quantitative tools makes many traders who do not understand the code daunted. Moreover, although I have written a lot of strategies,
However, I am still not very satisfied with the backtest configuration and writing efficiency. Therefore, I have been thinking about how to build a backtesting framework that can quickly and easily evaluate the backtesting performance of any indicator with a "long/short entry" indicator, that is, a "simple backtesting tool for dummies". The performance requirements should be stable, and the operation should be simple and convenient. It is best to "copy", "paste", and "a few mouse clicks" to complete the quick backtest and evaluation of a new indicator.
Luckily, I recently realized that TradingView provides an "Indicator on Indicator" feature, which is the perfect foundation for doing "hot swap" backtesting. My basic idea is to use a two-layer design. The first layer is the technical indicator signal source that needs to be embedded, which is only used to provide buy and sell signals of custom strategies; the second layer is the trading system, which is used to receive the output signals of the first layer, and filter the signals according to the agreed specifications. , Take Profit, Stop Loss, draw buy and sell signals and cost lines, define and send custom buy and sell alert messages to mobile phones, social software or trading interfaces. In general, this two-layer design is a flexible combination of "fixed and flexiable", which can meet the needs of most traders to quickly evaluate the performance of a certain technical indicator. The first layer here is flexible. Users can insert their own strategy codes according to my template, and they can draw buy and sell signals and output them to the second layer. The second layer is fixed, and the overall framework is solidified to ensure the stability and unity of the trading system. It is convenient to compare different or similar strategies under the same conditions. Finally, all trading signals are drawn on the chart, and the output strategy returns. test report.
The main function:
The first layer: "{Sextan} Your Indicator Source", the script provides a template for personalized strategy input, and the signal and definition interfaces ensure full compatibility with the second layer. Backtesting is performed stably in the backtesting framework of the layer. The first layer of this script is also relatively simple: enter your script in the highlighted custom script area, and after ensuring the final buy and sell signals long = bool condition, short = bool condition, the design of the first layer is considered complete. Input it into the PINE script editor of TradingView, save it and add it to the chart, you can see the pulse sequence in yellow (buy) and purple (sell) on the sub-picture, corresponding to the main picture, you can subjectively judge that the quality of the trading point of the strategy is good Bad.
Pine v4 your indicator template:
Pine v5 your indicator template:
Pine v4 your MTF indicator template:
Pine v5 your MTF indicator template:
The second layer: "{Sextan} PINEv4 Sextans Backtest Framework". This script is the standardized trading system strategy execution and alarm, used to generate the final report of the strategy backtest and some key indicators that I have customized that I find useful, such as: winning rate , Odds, Winning Surface, Kelly Ratio, Take Profit and Stop Loss Thresholds, Trading Frequency, etc. are evaluated according to the Kelly formula. To use the second layer, first load it into the TrainingView chart, no markers will appear on the chart, since you have not specified any strategy source signals, click on the gear-shaped setting next to the "{Sextan} PINEv4 Sextans BTFW" header button, you can open the backtest settings, the first item is to select your custom strategy source. Because we have added the strategy source to the chart in the previous step, you can easily find an option "{Sextan} Your Indicator Source: Signal" at the bottom of the list, this is the strategy source input we need, select and confirm , you can see various markers on the main graph, and quickly generate a backtesting profit graph and a list of backtesting reports. You can generate files and download the backtesting reports locally. You can also click the gear on the backtest chart interface to customize some conditions of the backtest, including: initial capital amount, currency type, percentage of each order placed, amount of pyramid additions, commission fees, slippage, etc. configuration. Note: The configuration in the interface dialog overrides the same configuration implemented by the code in the backtest script.
How to output charts:
The first layer: "{Sextan} Your Indicator Source", the output of this script is the pulse value of yellow and purple, yellow +1 means buy, purple -1 means sell.
The second layer: PINEv4 Sextans Backtest Framework". The output of this script is a bit complicated. After all, it is the entire trading system with a lot of information:
1. Blue and red arrows. The blue upward arrow indicates long position, the red downward arrow indicates short position, and the horizontal bar at the end of the purple arrow indicates take profit or stop loss exit.
2. Red and green lines. This is the holding cost line of the strategy, green represents the cost of holding a long position, and red represents the cost of holding a short position. The cost line is a continuous solid line and the price action is relatively close.
3. Green and yellow long take profit and stop loss area and green and yellow long take profit and stop loss fork. Once a long position is held, there is a conditional order for take profit and stop loss. The green horizontal line is the long take profit ratio line, and the yellow is the long stop loss ratio line; the green cross indicates the long take profit price, and the yellow cross indicates the long position. Stop loss price. It's worth noting that the prongs and wires don't necessarily go together. Because of the optimization of the algorithm, for a strong market, the take profit will occur after breaking the take profit line, and the profit will not be taken until the price falls.
4. The purple and red short take profit and stop loss area and the purple red short stop loss fork. Once a short position is held, there will be a take profit and stop loss conditional order, the red is the short take profit ratio line, and the purple is the short stop loss ratio line; the red cross indicates the short take profit price, and the purple cross indicates the short stop loss price.
5. In addition to the above signs, there are also text and numbers indicating the profit and loss values of long and short positions. "L" means long; "S" means short; "XL" means close long; "XS" means close short.
TradingView Strategy Tester Panel:
The overview graph is an intuitive graph that plots the blue (gain) and red (loss) curves of all backtest periods together, and notes: the absolute value and percentage of net profit, the number of all closed positions, the winning percentage, the profit factor, The maximum trading loss, the absolute value and ratio of the average trading profit and loss, and the average number of K-lines held in all trades.
Another is the performance summary. This is to display all long and short statistical indicators of backtesting in the form of a list, such as: net profit, gross profit, Sharpe ratio, maximum position, commission, times of profit and loss, etc.
Finally, the transaction list is a table indexed by the transaction serial number, showing the signal direction, date and time, price, profit and loss, accumulated profit and loss, maximum transaction profit, transaction loss and other values.
Remarks
Free to use but closed source.
AlphaTrend For ProfitViewThis strategy is based on the AlphaTrend indicator by KivancOzbilgic A full description of this algorithm functionality may be found by clicking the linked image above.
Changes and/or additions:
It is now a backtestable strategy
Updated alert trigger logic
Easy integration with ProfitView to use this algorithm for automated trading
When you create an alert, and you are using ProfitView, select " alert() function calls only " as the condition option. If you would rather set your own custom alert message, select " Order fills only " instead.
There is a selectable setting in the options to trigger alert() function calls immediately, that you may use to see what text it will send.
Crypto Spot Market Bot | BacktestHello Friends.
This script is only for long positions.
How does the algorithm work ?
The Relative Momentum Index
Relative Strength İndex
Average Directional Movement İndex
Momentum
When rsi and adx produce signals in the same direction, the rmi indicator confirms the signal. After the Confirmed Signal, the buy-side transaction is entered , the closed according to the % of profit taking and stoploss specified on the algorithm in the entered transaction.
In the spot market, it is possible to make money even in a down trend
All shared charts run within a 1-hour time frame.
Note : The shared backtest results have been shared as of 9/9/2021 by calculating 50% balance and 2 pyramiding methods in an account of 1000 dollars. Keep in mind that this algorithm will want to try to average down in possible worst-case scenarios. 2% - %3take profit levels will provide consecutive gains in the spot market.
How should the adjustments be made?
Value variables should be made according to formula a and formula b values and backtest results. You can increase the frequency of transactions by lowering the adx and rsi values.
Overview :
v1 Automatic Trading Bot | BacktestHello Friends.
We have been working on this script for a long time. Briefly, our scenario works as follows.
This test data includes results as of January 1, 2022 using a balance of $1000 and 10%.
WORKİNG LOGİC :
Relative Strength Index
Directional Movement Index
Relative Momentum Index
Indicators are Blended.
1 conditions are met in the overbought and oversold zone.
If the Directional Movement Index Signal is in the same direction, If all signals are in the same decision, it will be position.
We can set the take profit and stop loss levels on the algorithm as % over the entry price.
HOW TO ADJUST :
Formula a and formula b values are adjusted by increments or decrements of 1 each. these adjustments should be changed according to the time frame and chart layout.
You do not need to intervene in overbought and oversold zones. The Best Values were thus deemed appropriate.
If you still want to intervene, you need to know; When you change the overbought and oversold values, the entry time and risk will increase.
Together with the backtest script we are able to adjust the algorithm to all timeframes.
For example, while these settings are ideal for 5 minutes, it is necessary to change the strenght and formul values for a 15-minute period. This provides a user-specific adjustable strategy.
There are 6 different triggers in total on the alarm version.
Enter a long position.
Long position take profit
Long position stop loss
Enter a Short position.
Short position take profit
Short position stop loss
Currently, one platform is also connected to the binance exchange via an API .
The maximum leverage is set to 5 and a maximum of 5 trades are ordered to enter.
I will post the alarm version soon.
Good Luck Everyone !
Cava Signals Backtesting/VisualizerPLEASE READ THE DESCRIPTION CAREFULLY
Trying this again, as it seems I keep violating the rules unintentionally. Moderator, please forgive me as I try to make this right.
This backtesting/visualizer script was created for me to get a visual idea of the Cava Signals indicator throughout its development time and continuous optimization.
This script is to be used on the 30-minute timeframe on supported markets, and whether I can only publish strategies on regular candles, the indicator is meant to trigger on heikin ashi candles.I understand backtesting on non-regular candles produces unrealistic results, but I emphasize that this script is more for visualization purposes rather than accurate $ amounts from the trades. The signals are used along with a dedicated bot configuration, so part of the strategy is not managed by the script, but by the bot's config.
Some behind the scenes on what we are looking at:
a combination of ema and sma crosses on different time frames (5m, 15m, 30m, 60m and 90m) - we call this the wave trend
a combination of stochastic rsi on different time frames (10m, 30m)
a combination of schaff trend cycles on different time frames (5m, 20m and 30m)
a combination of money flow index on different time frames (10m and 30m)
volume information for each supported market/pair
and a couple of other info particular to each pair
With the above combination of data points, we try to optimize our strategy for an entry, for dca'ing down in case the coin goes down as well as dca'ing up to maximize profit when a coin is going up, take profit levels when we recognize a good time to do so, and of course, a closing level. I would like to emphasize the *visualization* purpose of this script in recognizing lows, highs, and market structure to identify the important levels to signal - this script is NOT to be used for accurate backtesting, but for an idea of the overall performance of when signals are triggered.
Let me try to explain the workflow and icons you see on the chart:
The colored circles on the bottom of the chart are all buy signals; each color corresponds to a particular buy signal, we have a combination of 9 possible situations that would trigger a buy signal. Some would trigger a buy signal only in combination with other buy signals or other indicators within the script. we also display a green upwards arrow below bars when a buy signal is triggered.
The colored arrows pointing down on the top of the chart are close signals. We have a combination of 5 closing criteria each color corresponds to one, just like the buy signals do. We only close a trade in profit. If not in profit, we will look to DCA down.
DCA signals are shown by the green flag above bars. they are signals to DCA up or down depending on the trade being negative or positive. DCA'ing up or down is also managed by the bot's configuration for limits on when to accept the signal.
Take Profit levels are shown by the green diamond above bars and work in conjunction with the bot's config on when to take the signal if at all and other take profit levels. Usually, when we hit the first take profit level we move our stop loss to entry via the bot's take profit safety feature. You can see this call with the close entry named TPS .
The black bars you may see on the chart is to illustrate when the market is extended based on a particular strategy. During this period we will not trigger a buy signal unless there is a huge spike in positive volume .
The green number below the bars is the total positive delta volume on the buy candles.
On the table on the right upper corner, we show some information on the market and performance of the backtesting - for visualization purposes only!
Currently, the script is tailored to work with the following markets/pairs:
Binance Spot: ADA, ALGO, ATOM, AVAX, BNB, BTC , DOT, ETH, LINK, LUNA, MATIC, SOL, VET, XRP, XTZ
Binance Futures: BTC , ETH, ADA, ALGO, ATOM, BNB, COMP, DOT, ENJ , LINK, OCEAN, OMG, SOL, VET, XMR, XRP, XTZ, AVAX, AAVE, DOGE, LTC, LUNA, MKR , NEAR, ONT, RUNE, SUSHI, LTC, XLM , COMP, ONT, THETA, FTM , EGLD , WAVES, ONE, HTN , CHZ , HOT, MANA, CRV , RVN, BAT, ANKR, 1INCH, ALICE, ATA , AXS , CHR , COTI, NKN , RAY, REN, SRM , SXP , TLM
ByBit Inverse Perpetual: BTCUSD , ETHUSD
ByBit Futures: AAVE, ADA, ALGO, AVAX, AXS , BNB, BTC , DOT, ETH, LINK, LTC, MATIC, SOL, SUSHI, UNI , XEM, XRP, XTZ
The chosen pairs are subject to change based on the best-performing assets we are constantly analyzing.
I hope this helps to understand the script, its purpose and ideas. I hope this satisfies the community rules - it was not my intention to break them - if there's anything on the above or the script that still violates the guidelines, please let me know and accept my apologies in advance.
If anyone would like to know more, let me know in the comment section.
Thank you!
alGROWithm Premium - Strategy TesterThe alGROWithm Strategy Tester is a supplement to the original alGROWithm indicator.
Use this strategy to do your own back testing and find the best settings that work for your asset of choice.
█ WHY THIS IS IMPORTANT
Different assets require different settings for optimal results. This strategy script will allow you back test different settings for alGROWithm in order to analyze key metrics such as win rate and P/L. TradingView functionality also enables you to view a high level performance summary and even see every single individual trade made by the algo.
█ BEST PRACTICES
Depending on the asset you are testing, it is very important to update the settings as needed. For example, if you are back testing on US30, you will likely need to increase the starting capital. For other assets, you may also need to change the order size to use the Contracts option.
It is important to decide for yourself which back testing parameter you will weigh more heavily in terms of importance. For example, a day trader may want to use a setting that maximizes win rate rather than profit % since we are humans and not computers. Further, it is highly recommended to utilize all of the rich features that TradingView provides with regards to back testing. For example, using the List of Trades tab, go back to find a failed trade and analyze the trade to see if you actually would have taken it in the moment.
After finding the best sensitivity for your asset, it is important to set that sensitivity value on the non-strategy version of alGROWithm for usage. Changing settings on this version will not carry over to the non-strategy version.
█ DEFAULT SETTINGS
We have set the following default settings on the strategy:
Starting capital: $100k
Order size: 30% of equity
Sell 1/5 of position every Take Profit level
