Bollinger and Stochastic with Trailing Stop - D.M.P.This trading strategy combines Bollinger Bands and the Stochastic indicator to identify entry opportunities in oversold and overbought conditions in the market. The aim is to capitalize on price rebounds from the extremes defined by the Bollinger Bands, with the confirmation of the Stochastic to maximize the probability of success of the operations.
Indicators Used
- Bollinger Bands Used to measure volatility and define oversold and overbought levels. When the price touches or breaks through the lower band, it indicates a possible oversold condition. Similarly, when it touches or breaks through the upper band, it indicates a possible overbought condition.
- Stochastic: A momentum oscillator that compares the closing price of an asset with its price range over a certain period. Values below 20 indicate oversold, while values above 80 indicate overbought.
Strategy Logic
- Long Entry (Buy): A purchase operation is executed when the price closes below the lower Bollinger band (indicating oversold) and the Stochastic is also in the oversold zone.
- Short Entry (Sell): A sell operation is executed when the price closes above the upper Bollinger band (indicating overbought) and the Stochastic is in the overbought zone.
Penunjuk dan strategi
CryptoGraph Dynamic DCAA system to backtest and automate comprehensive trading strategies
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🟣 Supporting Your Trades
CryptoGraph Dynamic DCA serves as a comprehensive tool on TradingView, designed to refine your approach to cryptocurrency trading. It utilises dynamic dollar-cost averaging (DCA), based on external indicator sources, to provide structured market entry and exit strategies. Suitable for both short-term trading and long-term portfolio management, CryptoGraph Dynamic DCA can offer a methodical way to support your trading decisions.
The tool offers an intuitive interface with inputs for strategy customisation, visualised preferences, and bot alert configurations. It can assist traders seeking precision, adaptability, and control in their trading activities. In the example on the chart above, we use the CryptoGraph Entry Builder (part of CryptoGraph Dynamic DCA package) as an external source for our initial entry (base order) and our safety orders, as well as an external source for our second take profit, which can be configured to be signal based.
🟣 Features
External Entry/Exit sources: The strategy is designed to assist with accurate market entries and exits by utilising signals from external indicators. It offers the flexibility to tailor your trading approach, providing an opportunity to leverage the analytical capabilities of various indicators available on TradingView.
Strategic Direction Control: Configure your strategy to go long, short, or both, adapting to market trends and your trading style.
Leverage Customisation: Tailor your leverage settings for isolated or cross margin to align with your risk tolerance, a liquidation estimation level is plotted on the chart, based on your input settings.
Diverse Entry Points: Utilise base orders and safety orders to diversify your entry points, reducing risk and enhancing potential returns.
Tailored Order Size: Fine-tune your order sizes using margin percentages or fixed contract sizes to fit your strategy’s requirements.
Profit Taking & Loss Prevention: Set take profit levels and stop losses with percentage or ATR-based parameters to secure profits and minimise losses. Options for moving the stop loss to entry after Take Profit 1, with an adjustable buffer, give you control over your risk management.
Max Safety Orders Count: Determine the maximum number of safety orders to manage risk effectively.
Price Deviation for DCA Orders: Specify the minimum price deviation percentage to trigger DCA orders, ensuring strategic order placement.
DCA Size Method: Choose from scaling or fixed-size DCA orders to align with your capital allocation strategy.
Visualisation & Alerts: Analyse your strategy’s performance with a backtest results table and configure bot alerts for automated trading. Auto configuration methods are integrated for multiple automated trading platforms.
🟣 Features Impression
🟣 Usage Guide
1. Strategy Configuration:
Select the appropriate cryptocurrency pair and exchange that corresponds to your trading preferences.
Choose your desired chart timeframe to align with your trading strategy’s temporal scope.
Ensure that you’re utilising the regular candle type for consistent and reliable data interpretation.
Pick an external entry source to trigger your trades based on predefined indicators or conditions.
Determine your take profit and stop loss levels to manage risks and secure earnings effectively.
Configure your DCA (Dollar-Cost Averaging) settings, including safety orders and the scaling method, to enhance entry points and manage investment distribution.
Always consult the tooltips next to each strategy input, to better understand their functions.
2. Backtest and Analysis:
Run backtests with your configured parameters to assess the strategy’s potential performance.
Review the backtest results and statistics tables to understand the strategy’s effectiveness, risk profile, and profitability.
3. Automated Trading Platform Integration:
Connect the strategy to a compatible automated trading platform to enable real-time execution of trades.
Within the trading platform, ensure the proper API setup of the bot’s configuration to align with the signals from the tool.
4. Alert Configuration in TradingView:
Set up the alert conditions in the TradingView tool to match your strategy triggers for entry, exit, take profit, and stop loss.
Configure the connection parameters within the tool to communicate effectively with your chosen automated trading platform
Activate the alerts, ensuring they are set to trigger actions such as order placement, adjustments, or closures as per your strategy’s logic.
5. Capital Management:
Confirm that your initial capital and order size are logically set, keeping in mind that the sum of all deals, especially when using pyramiding with safety orders, should not exceed your initial capital to avoid overexposure.
🟣 Trade Example
A clear example of a trade. Base order entry, safety order 1 fills, take profit 1 hits at 1%, the remainder of the position runs until the exit signal fires.
🟣 Warning
This tool has been developed to support your trading analysis, yet it’s important to acknowledge the inherent risks associated with trading. It is advisable to perform thorough research, assess your risk tolerance, and utilise this tool as one element of an overall trading strategy. Ensure that you only trade with capital that you are prepared to risk. In addition, due to the complexity of the tool, bugs may be found. Please alert us whenever you think you have found a bug in the system.
Supertrend & CCI Strategy ScalpThis strategy is based on 2 Super Trend Indicators along with CCI .
The longer factor length gives you the current trend and the deviation in the short factor length gives us the opportunity to enter in the trade .
CCI indicator is used to determine the overbought and oversold levels.
Setup :
Long : When atrLength1 > close and atrLength2 < close and CCI < -100 we look for long trades as the longer factor length will be bullish .
Short : When atrLength1 < close and atrLength2 > close and CCI > 100 we look for short trades as the longer factor length will be bearish .
Please tune the settings according to your use .
Trade what you see not what you feel .
Please consult with your financial advisor before you deploy any real money for trading .
Pivot Percentile Trend - Strategy [presentTrading]
█ Introduction and How it is Different
The "Pivot Percentile Trend - Strategy" from PresentTrading represents a paradigm shift in technical trading strategies. What sets this strategy apart is its innovative use of pivot percentiles, a method that goes beyond traditional indicator-based analyses. Unlike standard strategies that might depend on single-dimensional signals, this approach takes a multi-layered view of market movements, blending percentile calculations with SuperTrend indicators for a more nuanced and dynamic market analysis.
This strategy stands out for its ability to process multiple data points across various timeframes and pivot lengths, thereby capturing a broader and more detailed picture of market trends. It's not just about following the price; it's about understanding its position in the context of recent historical highs and lows, offering a more profound insight into potential market movements.
BTC 6h L/S
Where traditional methods might react to market changes, the Pivot Percentile Trend strategy anticipates them, using a calculated approach to identify trend strengths and weaknesses. This foresight gives traders a significant advantage, allowing for more strategic decision-making and potentially increasing the chances of successful trades.
In essence, this strategy introduces a more comprehensive and proactive approach to trading, harnessing the power of advanced percentile calculations combined with the robustness of SuperTrend indicators. It's a strategy designed for traders who seek a deeper understanding of market dynamics and a more calculated approach to their trading decisions.
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█ Strategy, How It Works: Detailed Explanation
🔶 Percentile Calculations
- The strategy employs percentile calculations to assess the relative position of current market prices against historical data.
- For a set of lengths (e.g., `length * 1`, `length * 2`, up to `length * 7`), it calculates the 75th percentile for high values (`percentilesHigh`) and the 25th percentile for low values (`percentilesLow`).
- These percentiles provide a sense of where the current price stands compared to recent price ranges.
Length - 10
Length - 15
🔶 SuperTrend Indicator
- The SuperTrend indicator is a key component, providing trend direction signals.
- It uses the `currentTrendValue`, derived from the difference between bull and bear strengths calculated from the percentile data.
* used the Supertrend toolkit by @EliCobra
🔶 Trend Strength Counts
- The strategy calculates counts of bullish and bearish indicators based on comparisons between the current high and low against high and low percentiles.
- `countBull` and `countBear` track the number of times the current high is above the high percentiles and the current low is below the low percentiles, respectively.
- Weak bullish (`weakBullCount`) and bearish (`weakBearCount`) counts are also determined by how often the current lows and highs fall within the percentile range.
*The idea of this strength counts mainly comes from 'Trend Strength Over Time' @federalTacos5392b
🔶 Trend Value Calculation
- The `currentTrendValue` is a crucial metric, computed as `bullStrength - bearStrength`.
- It indicates the market's trend direction, where a positive value suggests a bullish trend and a negative value indicates a bearish trend.
🔶 Trade Entry and Exit Logic
- The entry points for trades are determined by the combination of the trend value and the direction indicated by the SuperTrend indicator.
- For a long entry (`shouldEnterLong`), the `currentTrendValue` must be positive and the SuperTrend indicator should show a downtrend.
- Conversely, for a short entry (`shouldEnterShort`), the `currentTrendValue` should be negative with the SuperTrend indicating an uptrend.
- The strategy closes positions when these conditions reverse.
█ Trade Direction
The strategy is versatile, allowing traders to choose their preferred trading direction: long, short, or both. This flexibility enables traders to tailor their strategies to their market outlook and risk appetite.
█ Default Settings and Customization
1. Trade Direction: Selectable as Long, Short, or Both, affecting the type of trades executed.
2. Indicator Source: Pivot Percentile Calculations, key for identifying market trends and reversals.
3. Lengths for Percentile Calculation: Various configurable lengths, influencing the scope of trend analysis.
4. SuperTrend Settings: ATR Length 20, Multiplier 18, affecting indicator sensitivity and trend detection.
5. Style Options: Custom colors for bullish (green) and bearish (red) trends, aiding visual interpretation.
6. Additional Settings: Includes contrarian signals and UI enhancements, offering strategic and visual flexibility.
PresentTrend RMI Synergy - Strategy [presentTrading] █ Introduction and How it is Different
The "PresentTrend RMI Synergy Strategy" is the combined power of the Relative Momentum Index (RMI) and a custom presentTrend indicator. This strategy introduces a multifaceted approach, integrating momentum analysis with trend direction to offer traders a more nuanced and responsive trading mechanism.
BTCUSD 6h L/S Performance
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█ Strategy, How It Works: Detailed Explanation
The "PresentTrend RMI Synergy Strategy" intricately combines the Relative Momentum Index (RMI) and a custom SuperTrend indicator to create a powerful tool for traders.
🔶 Relative Momentum Index (RMI)
The RMI is a variation of the Relative Strength Index (RSI), but instead of using price closes against itself, it measures the momentum of up and down movements in price relative to previous prices over a given period. The RMI for a period length `N` is calculated as follows:
RMI = 100 - 100/ (1 + U/D)
where:
- `U` is the average upward price change over `N` periods,
- `D` is the average downward price change over `N` periods.
The RMI oscillates between 0 and 100, with higher values indicating stronger upward momentum and lower values suggesting stronger downward momentum.
RMI = 21
RMI = 42
For more information - RMI Trend Sync - Strategy :
🔶 presentTrend Indicator
The presentTrend indicator combines the Average True Range (ATR) with a moving average to determine trend direction and dynamic support or resistance levels. The presentTrend for a period length `M` and a multiplier `F` is defined as:
- Upper Band: MA + (ATR x F)
- Lower Band: MA - (ATR x F)
where:
- `MA` is the moving average of the close price over `M` periods,
- `ATR` is the Average True Range over the same period,
- `F` is the multiplier to adjust the sensitivity.
The trend direction switches when the price crosses the presentTrend bands, signaling potential entry or exit points.
presentTrend length = 3
presentTrend length = 10
For more information - PresentTrend - Strategy :
🔶 Strategy Logic
Entry Conditions:
- Long Entry: Triggered when the RMI exceeds a threshold, say 60, indicating a strong bullish momentum, and when the price is above the presentTrend, confirming an uptrend.
- Short Entry: Occurs when the RMI drops below a threshold, say 40, showing strong bearish momentum, and the price is below the present trend, indicating a downtrend.
Exit Conditions with Dynamic Trailing Stop:
- Long Exit: Initiated when the price crosses below the lower presentTrend band or when the RMI falls back towards a neutral level, suggesting a weakening of the bullish momentum.
- Short Exit: Executed when the price crosses above the upper presentTrend band or when the RMI rises towards a neutral level, indicating a reduction in bearish momentum.
Equations for Dynamic Trailing Stop:
- For Long Positions: The exit price is set at the lower SuperTrend band once the entry condition is met.
- For Short Positions: The exit price is determined by the upper SuperTrend band post-entry.
These dynamic trailing stops adjust as the market moves, providing a method to lock in profits while allowing room for the position to grow.
This strategy's strength lies in its dual analysis approach, leveraging RMI for momentum insights and presentTrend for trend direction and dynamic stops. This combination offers traders a robust framework to navigate various market conditions, aiming to capture trends early and exit positions strategically to maximize gains and minimize losses.
█ Trade Direction
The strategy provides flexibility in trade direction selection, offering "Long," "Short," or "Both" options to cater to different market conditions and trader preferences. This adaptability ensures that traders can align the strategy with their market outlook, risk tolerance, and trading goals.
█ Usage
To utilize the "PresentTrend RMI Synergy Strategy," traders should input their preferred settings in the Pine Script™ and apply the strategy to their charts. Monitoring RMI for momentum shifts and adjusting positions based on SuperTrend signals can optimize entry and exit points, enhancing potential returns while managing risk.
█ Default Settings
1. RMI Length: 21
The 21-period RMI length strikes a balance between capturing momentum and filtering out market noise, offering a medium-term outlook on market trends.
2. Super Trend Length: 7
A SuperTrend length of 7 periods is chosen for its responsiveness to price movements, providing a dynamic framework for trend identification without excessive sensitivity.
3. Super Trend Multiplier: 4.0
The multiplier of 4.0 for the SuperTrend indicator widens the trend bands, focusing on significant market moves and reducing the impact of minor fluctuations.
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The "PresentTrend RMI Synergy Strategy" represents a significant step forward in trading strategy development, blending momentum and trend analysis in a unique way. By providing a detailed framework for understanding market dynamics, this strategy empowers traders to make more informed decisions.
EMA Crossover Strategy with RSI Filter BIGTIME 5mThis script essentially creates a trading strategy that goes long when there is an EMA crossover, but only if the RSI is below a certain overbought level. It goes short when there is an EMA crossunder, but only if the RSI is above a certain oversold level. The moving averages are plotted on the chart for visual reference.
SCALPING 5m
Pairs: BIGTIME/USDT--- API3/USDT---BAKE/USDT--- ZIL/USDT
Self Optimizing PSAR [Starbots]Self Optimizing Parabolic SAR Strategy (non-repainting)
Strategy constantly backtest 169 different combinations of Parabolic SAR indicator for maximum profitability and trades based on the best performing combination at that time.
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# Parabolic SAR (PSAR)
Parabolic SAR is a time and price technical analysis tool created by J. Welles Wilder and it's primarily used to identify points of potential stops and reverses. In fact, the SAR in Parabolic SAR stands for "Stop and Reverse". The indicator's calculations create a parabola which is located below price during a Bullish Trend and above Price during a Bearish Trend.
You can read more about this indicator here:
www.tradingview.com
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The logic of self - optimizing:
This script is always backtesting 169 different combinations of Parabolic SAR settings in the background and saves the net. profit gained for every single one of them, then strategy selects and use the best performing combination of settings currently available for you to trade.
It's recalculating on every bar close - if one of the parameters starts performing better than others - have a higher net profit gain (it's literally like running 169 backtests with different settings) strategy switches to that parameter and continues trading like that until one of the other indicator parameters starts performing better again and switches to that settings.
We are optimizing our strategy based on 13 different 'Increment' factors of PSAR. We keep the 'Start' factor (default 0.02) and 'Max Value' factor (default 0.2) at default for all of them.
According to creator of this indicator J. Welles Wilder, we usually want to change only 'Increment' factors of PSAR in the calculation and leave the rest at default and that's what we do, we are changing only 'Increment' input.
Inputs : (you don't need to change them at all, it's a good balance for fast and slow detection of trends on PSAR)
Start = 0.02
Max value = 0.2
Increment1 = 0.005, Increment2 = 0.01, Increment3 = 0.015
Increment4 = 0.02, Increment5 = 0.025, Increment6 = 0.03
Increment7 = 0.035, Increment8 = 0.04, Increment9 = 0.045
Increment10 = 0.05, Increment11 = 0.055, Increment12 = 0.06
Increment13 = 0.065
PSAR buy / sell conditions looks like this:
PSAR1 = start 0.02, max value 0.2, increment1 0.005
PSAR2 = start 0.02, max value 0.2, increment2 0.01
PSAR3 = start 0.02, max value 0.2, increment3 0.015
PSAR4 = start 0.02, max value 0.2, increment3 0.02
...
PSAR13 = start 0.02, max value 0.2, increment13 0.065
Backtester in the background works like this:
backtest buying PSAR1 settings with selling PSAR1 settings => save net. profit
backtest buy PSAR1 with sell PSAR2 ;
backtest buy PSAR1 with sell PSAR3 ;
backtest buy PSAR1 with sell PSAR4 ;
..........
backtest buy PSAR1 with sell PSAR13 ;
..........
backtest buy PSAR13 with sell PSAR1 ;
backtest buy PSAR13 with sell PSAR2 ;
......
backtest buy PSAR13 with sell PSAR13 ;
=>
It will backtest 16x16=169 different PSAR settings and save their profits.
Your strategy then trades based on the best performing (highest net.profit) PSAR Setting currently available. It will check the calculations and backtest them on every new bar close - it's like running 169 strategies at time, and manually selecting the best performing one.
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If you wish to use it as INDICATOR - turn on 'Recalculate after every tick' in Properties tab to have this script updating constantly and use it as a normal Indicator tool for manual trading.
Strategy example is backtested on Daily chart of SHIBUSDT Binance
All settings at default. (1000 capital, 100 order size, 0.1% fee, 1 tick slippage)
Settings:
-Start = default Parabolic SAR setting is 0.02
-Max Value = default Parabolic SAR setting is 0.2
--Recommended PSAR Increment settings:
0.02 is default, higher timeframes usually performs good on the faster Increment factors 0.03-0.05+, smaller timeframes on slow Increment factors 0.005-0.02. I recommend you the most common and logical 13 different Increment factors for optimizing in the strategy as default already (from 0.005 to 0.065 - strategy will then optimize and trade based on the most profitable combination).
- Noise-Intensity Filter 🐎0.00-0.20%🐢
This will punish the tiny trades made by certain combinations and give more advantage to big average trades. It's basically like fee calculation, it will deduct 0.xx% fee from every trade when optimizing on their backtests.
You will usually want to have it around 0.05-0.10% like your fees on exchange.
-> 🐎Less than <0.10% allows strategy to be VERY SENSITIVE to market. (a lot of trades - quick buy-sell changes)
-> 🐢More than >0.10% will slow down the strategy, it will be LESS SENSITIVE to market volatility. (less trades - slowly switches the trend direction from buy to sell)
Close Trades on Neutral
After a lot of Trades, Algo starts developing self-intelligence. It can also have a neutral score. (Grey Plots). Sell when the strategy is neutral.
Other settings:
-Take Profit, Multiple Take Profit, Trailing Take Profit, Stop Loss, Trailing Stop Loss with functional alerts.
-Backtesting Range - backtest within your desired time window. Example: 'from 01 / 01 /2020 to 01 / 01 /2023'.
- Strategy is trading on the bar close without repaint. You can trade Long-Sell/Short Sell or Long-Short both directions. Alerts available, insert webhook messages in the inputs.
- Turn on Profit Calendar for better overview of how your strategy performs monthly/annualy
- Notes window : add your custom comments in here or save your webhook message text inside here for later use. I find this helpful to save texts inside.
Recommended TF : 4h, 8h, 1d (Trend Indicators are good at detecting directions of the market, but we can have a lot of noise and false movements on charts, you want to avoid that and ride the long term movements)
This script is fairly simple to use. It's self-optimizing and adjusting to the markets on the go.
RPPI Futures & Indices Strategy Tester [SS Premium]Hello everyone,
As promised, here is the strategy companion to the RPPI Futures & Indicies Indicator.
It contains all of the models of the RPPI but the functionality is all about back-testing the strategy. As such, you cannot use this to run probabilities, run autoregression assessments, or do any of the advanced RPPI features, this is solely to allow you to develop and implement a sustainable strategy in your trading using the RPI.
When you launch the indicator, in the settings menu, you will see toggles to customize the strategy you would like to apply:
You can customize your short and long entries and your short and long exits and then review the backtest results of these various combinations.
From there, you can open up tradingview's strategy tester to see the immediate success of the strategy. If you want to test how effective your strategy is further back, you can make use of Tradingview's "Deep Backtesting" option. This allows you to select a start date way in the past, and back-test over numerous months / years, to see if the strategy has been sustainable in the long term.
To read more about the RPPI, you can check out its own page which lists the details of the indicator, how it works and how to use it. As a synopsis, the RPPI is a compendium indicator that contains various models of multiple futures and stocks. This is to attempt to accurately forecast daily, weekly, monthly, 3 month and annual moves on various futures and indices.
This strategy companion will help you hone in on ideal entries and exits and allow you to tailor them to each ticker that you are interested in trading, on whichever timeframe you are interested in trading.
Some important notes when applying the back-testing results:
1. If you are back-testing daily levels, it is recommended to use the 1 to 5-minute chart max.
2. iF you are back-testing weekly levels, it is recommended to use at least 15 to 30 minutes, up to 60 minute candles.
3. Monthly levels, its best to use 1 hour and up.
4. Greater than monthly, its best to use 3 to 4 hours, to daily candles and up.
As always, feel free to leave your questions or suggestions below.
Thank you for reading and, as always, safe trades!
PS January Barometer BacktesterPS January Barometer Backtester (PS JBB)
The PS January Barometer Backtester (PS JBB) is a simple strategy designed to test the "January Effect" hypothesis in financial markets. This effect theorizes that stock market performance in January can predict the trend for the rest of the year. The script operates on a monthly timeframe, focusing on capturing and analyzing the price movements in January and their subsequent influence on the market until the end of each year.
User Input:
January Trifecta Selectors
These are user-selectable options allowing traders to incorporate additional criteria into their market analysis.
The Santa Claus Rally refers to a stock market increase typically seen in the last week of December through the first two trading days in January.
The First Five Days Indicator assesses market performance during the initial five days of the year.
Script Operation:
The script automatically detects the start of each year, tracks January's high, and signals entry and exit points for trades based on the strategy's logic. It's an excellent tool for traders and investors looking to explore the January Effect's validity and its potential impact on their trading decisions.
In essence, the "PS January Barometer Backtester" is designed to exploit specific seasonal market trends, particularly focusing on the early part of the year, by analyzing and acting upon defined market movements. This strategy is ideal for traders who focus on yearly cyclical patterns and seek to incorporate historical trends into their trading decisions.
Note: This script is intended for educational and research purposes and should not be construed as financial advice. Always conduct your own due diligence before making trading/investment decisions.
Candle StrategyThis strategy is based candle count number also strategy analysis -
Rules for buy-
1) choose Candle Number(Ex.-47) For Trade
2) Trade Sell if price is above high of day 1st candle that mean direction is upside
3) We are taking stop loss on lowest low of candle since day first candle to trade no.
4) close Trade at last bar of the day
5) Trader Can Choose Trade Direction From input
Rules for Sell-
1) Choose Candle Number(Ex.-47) For Trade
2) Trade Sell if price is below low of day 1st candle that mean direction is downside
3) We are taking stop loss on highest of candle since day first candle to trade no.
4) close Trade at last bar of the day
5) Trader Can Choose Trade Direction From input
Note - this strategy can be also use for static to understand which candle will make low/high of the day high chance Example in bank nifty 5 minutes chart candle no 47 have highest trade
opportunity appear on long side ...this data is small based on 5000 previous bar ...
Disclaimer: market involves significant risks, including complete possible loss of funds. Consequently trading is not suitable for all investors and traders. By increasing leverage risk increases as well.With the demo account you can test any trading strategies you wish in a risk-free environment. Please bear in mind that the results of the transactions of the practice account are virtual, and do not reflect any real profit or loss or a real trading environment, whereas market conditions may affect both the quotation and execution
FluxFilter Trend Strategy [BITsPIP]Hello fellow traders, I'm excited to share with you the FluxFilter Trend Strategy, a trading approach I've developed for those interested in exploring trend-following strategies. My goal was to create something straightforward and accessible, so traders looking to refine their portfolios can easily integrate its features. By the end of this guide, I hope you'll have a solid grasp of how the FluxFilter Trend Strategy functions, appreciate its benefits, understand its potential drawbacks, and see how it might fit into various trading contexts.
I) Overview
The FluxFilter Trend Strategy is tailored to align with the market's long-term trend. It examines the price data from the previous year to gauge the market's overall trajectory by employing moving averages. Subsequently, within shorter timeframes, the strategy utilizes a combination of modified Supertrend, Hull Suite, and various trend-following and filtering techniques to generate buy or sell signals. Although its advanced take profit and stop loss mechanisms might initially present a learning curve, they are integral to the strategy's effectiveness. They are designed to secure gains by capturing prevailing trends and mitigating the impact of false reversal signals.
II) Deep Backtesting
Deep backtesting stands as a cornerstone in the development of trading strategies, offering a robust method for traders to assess the performance of their strategy against historical data. This process yields a retrospective view, illustrating how the strategy might have navigated through past market fluctuations, thereby shedding light on its potential robustness and areas for refinement. However, it's crucial to acknowledge that a strategy's performance can be influenced by a myriad of factors including market dynamics, the chosen timeframe, and the inherent attributes of the traded asset. Consequently, it's advisable to conduct thorough backtesting under various conditions to ascertain the strategy's reliability before applying it to actual trading scenarios.
III) Benefits
A primary advantage of the FluxFilter Trend Strategy is its proficiency in discerning genuine market trends from mere price fluctuations, thereby avoiding premature or uncertain trades. Unlike approaches that take high risks on speculative trades, this strategy prioritizes a high degree of confidence in the direction of the trade. It meticulously waits for a clear confirmation of the market trend. Once this certainty is established, the strategy promptly generates trade signals, ensuring that traders are positioned to capitalize on optimal market entry points without delay. This approach not only enhances the potential for profit but also aligns with a disciplined and methodical trading ethos.
IV) Applications
FluxFilter Trend Strategy can be applied across various timeframes, with a particular efficacy in those under 15 minutes. Its adaptable framework means it can be customized to cater to a variety of asset classes, encompassing stocks, commodities, forex, and cryptocurrencies. Initially, the strategy was specifically calibrated for low-volatile cryptocurrencies, as reflected in the default settings for stop loss and take profit values. It's important to recognize that the unique volatility and trend patterns of your selected market necessitate careful adjustments to these parameters. This fine-tuning of profit targets and stop loss thresholds is crucial for aligning the strategy with the specific dynamics of your chosen market, which I will discuss shortly.
V) Strategy's Logic
1. Trend Identification: My conviction lies in the power of trend trading to yield long-term gains. Central to the FluxFilter Trend Strategy is the Hull Suite indicator, a tool developed by InSilico, serving as one of the confirmation indicators. This indicator acts as a compass for trend direction; a price residing above the Hull Suite line signals an uptrend, potentially marking an entry point for a buy position or confirming it. In contrast, a price positioned below this line suggests a downtrend, potentially indicating a strategic moment to sell or confirming the sell.
2. Noise Reduction: The financial markets are known for their 'noise'—short-lived price movements that can obscure the true market direction. The FluxFilter Trend Strategy is designed to sift through this noise, thereby facilitating more lucid and informed trading decisions. It employs a set of straightforward yet innovative techniques to single out significant misleading fluctuations. This is achieved by analyzing recent bars to spot bars with unusually large bodies, which often represent misleading market noise.
3. 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.
VI) Strategy's Input Settings and Default Values
1. Modified Supertrend
i. Factor: Serving as a multiplier in the Average True Range (ATR) calculation, this parameter adjusts the distance of the Supertrend line relative to the price chart. Elevating the factor value widens the gap between the Supertrend line and price, offering a more conservative stance. On the flip side, diminishing the factor value pulls the Supertrend line closer to the price action, heightening its sensitivity. While the preset value is 1, you have the flexibility to modify this to suit your trading approach.
ii. ATR Length: This defines the count of bars that are incorporated into the ATR computation, directly influencing the Supertrend's adaptability to market changes. With a default setting of 30 bars, it strikes a balance, smoothing over short-term fluctuations while maintaining a meaningful sensitivity to market trends. Adjusting this parameter allows you to tailor the indicator's responsiveness to suit your trading strategy, considering the volatility and behavioral patterns of the asset you are trading.
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, though these are not employed in our current strategy.
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. Filtering Indicators
i. Fluctuation Filtering Percentage: It's advisable to set this parameter to ten times the size of the average bar in your specific market, as this helps effectively mitigate the impact of market fluctuations. While the initial default is 0.4(%), based on the BTCUSDT market, it's crucial to adjust this figure to align with the characteristics of different assets or markets you're trading in.
ii. Fluctuation Filtering Bars: This parameter designates the count of preceding bars to consider when assessing market fluctuations. It's fully customizable, allowing you to tailor it based on your market insights. The preset default is 3, a balance chosen to minimize susceptibility to potentially misleading signals.
iii. Trend Confirmation Percentage: This metric is pivotal for verifying the viability of a trend post-entry. If the trade doesn't achieve this percentage in profit, it indicates a deviation from the expected trend. Under such circumstances, it may be prudent to exit the trade prematurely rather than awaiting the stop-loss trigger. It's recommended to set this parameter at half the size of the average candle body for the market you're analyzing. The initial default is set at 0.2(%).
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 has the potential to increase profitability. The pre-set configurations are tailored for volatile markets, such as 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 1.8(%), a figure worth considering in your trading strategy.
VII) Entry Conditions
The principal element that triggers the signal is the Modified Supertrend. Additional indicators serve as confirmatory tools. Nonetheless, to refine your strategy effectively, it's crucial to fine-tune the parameters. This involves adjusting input variables such as take profit levels, threshold parameters, and the filtering values discussed previously.
VIII) 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.
Good Luck!!
Single Swing Strategy (SSS)Introduction
The Single Swing Strategy (SSS) is a trading strategy designed for assets that trend. It utilises a single technical indicator to identify potential buying opportunities in upward-trending markets. The strategy focuses on moments when the price of an asset breaks out to a new high, suggesting a strong upward momentum.
Components
1. Exponential Moving Averages (EMAs): SSS uses two EMAs to evaluate the overall asset trend. SSS describes an uptrend as identified, when the fast EMA crosses above the slow EMA and vice versa for a downtrend.
2. Breakout: The strategy validates the trend identified by the EMAs through breakouts in the price action of the asset over a specified lookback period. No indicator is required for this step.
3. Average Directional Index (ADX): The ADX is used to measure the strength of a trend. It does not indicate the trend's direction but rather its strength, whether it's an uptrend or downtrend. A high ADX value (typically above 25) suggests a strong trend, either up or down while a low ADX value (typically below 20) indicates a weak or non-trending market. The ADX itself is a moving average of the expanding range between the +DI and -DI.
4. Positive Directional Indicator (DI+): DI+ helps identify the presence and strength of uptrends. It is calculated based on the upward price movement between current and previous highs. A rising DI+ alongside a rising ADX suggests a strengthening uptrend. When DI+ crosses above DI-, it's often interpreted as a bullish signal.
5. Negative Directional Indicator (DI-): DI- is used to detect the presence and strength of downtrends.It is derived from the downward price movement between current and previous lows. An increasing DI- along with a rising ADX indicates a strengthening downtrend while a crossover of DI- above DI+ is typically seen as a bearish signal.
How it works
1. Regime filter with ADX, DI+, and DI-: The first step in taking a trade is to determine the direction of the trend using the +DI. If in an uptrend, the strategy checks if the ADX is above 25 to confirm a strong uptrend. -DI is not used since the strategy is long only. If in an uptrend and the trend is strong, trades can be opened.
2. Trend Identification with EMAs: Initially, the strategy uses two Exponential Moving Averages (fast and slow) to determine the asset trend. A fast EMA crossing above the slow EMA signifies an uptrend, and vice versa for a downtrend. This is the Entry signal to open a long position.
3. Trend Confirmation with Breakout: The strategy confirms the EMA-indicated trend through price breakouts over a specified lookback period. An EMA crossover without a price action breakout does not lead to an entry signal
4. Trade Management: After entering a trade, the strategy uses predefined levels for taking profit and setting stop losses. Trades are closed either when the price reaches the take-profit level or falls to the stop-loss level. Hence, risk management is built in.
Results
The backtest results can be found below. Initial capital of 10000 was used, this is a convenient amount for most retail traders, commission of $3 per order, position size of 3% of initial capital and slippage of 3 ticks. These are all representative of real world retail trading conditions.
Originality
The Single Swing Strategy (SSS)'s originality is in its blending of classical technical analysis; Trend Analysis through EMAs and Price Action through Breakout, into an innovative trading logic.
1. The Essence of Trend and Breakout in SSS
(i) Trend Recognition: At the heart of SSS is the Exponential Moving Averages (EMAs). While the use of EMAs is common, SSS employs them for trend analysis so an entry decision can be made. The strategy's core algorithm assesses the inception of an upward trend by observing a specific crossing pattern of the EMAs, a moment where the asset's momentum shifts, offering a strategic advantage.
(ii) Breakout Significance: The strategy's reliance on price breakouts isn't just about identifying a new high; it's about understanding market psychology. A breakout beyond a previous high signals not only momentum but also a collective market sentiment that favors upward movement. SSS attempts to capture this momentum, translating it into a tangible trading opportunity.
(iii)Strength of trend: The ADX and +DI double checks the trend is in the right direction and checks to see if the trend is strong enough hence, it prevents trading when the trend is not supportive.
2. Simplicity as a Cornerstone
(i) Clarity and Efficiency: In the realm of algorithmic trading, complexity isn't always synonymous with effectiveness. SSS' simplicity ensures its logic is transparent and its execution, efficient. This simplicity is a strategic choice, designed to reduce overfitting to past data and improve adaptability to real-market conditions.
(ii) Ease of Use and Decision Making: The straightforward nature of SSS may empower traders to make informed decisions without being overwhelmed by convoluted indicators. This is particularly useful because of the embedding of risk management using defined exit points after entry through a Take Profit and Stop Loss. This hardcodes a 3:1 risk reward ratio into every trade.
3. Positive Expectancy
(i) Performance Metrics: The SSS strategy shows its edge in its backtesting results. A 62% win rate, a profit factor of 1.7, profit ratio of 1.05 and an average trade gain of 4.7% are not just numbers; they show the mathematical edge over the backtest period, especially considering the high commissions and slippage factored into its design.
Trading
The SSS strategy has been backtested on the 1D timeframe of BTCUSD but users are encouraged to try it on other assets such as SPXL (5min), AAPL (5min) and others but the appropriate timeframe and trading costs may vary.
NOTE
Like any trading strategy, SSS does not guarantee profits. It's a tool to assist in decision-making, not a foolproof solution. Trading involves risks, particularly in volatile markets. Users should trade responsibly, considering their risk tolerance and financial situation. While SSS automates some aspects of trading, it requires continuous monitoring and does not replace the need for sound judgement and decision-making by the trader.
AI SuperTrend x Pivot Percentile - Strategy [PresentTrading]█ Introduction and How it is Different
The AI SuperTrend x Pivot Percentile strategy is a sophisticated trading approach that integrates AI-driven analysis with traditional technical indicators. Combining the AI SuperTrend with the Pivot Percentile strategy highlights several key advantages:
1. Enhanced Accuracy in Trend Prediction: The AI SuperTrend utilizes K-Nearest Neighbors (KNN) algorithm for trend prediction, improving accuracy by considering historical data patterns. This is complemented by the Pivot Percentile analysis which provides additional context on trend strength.
2. Comprehensive Market Analysis: The integration offers a multi-faceted approach to market analysis, combining AI insights with traditional technical indicators. This dual approach captures a broader range of market dynamics.
BTC 6H L/S Performance
Local
█ Strategy: How it Works - Detailed Explanation
🔶 AI-Enhanced SuperTrend Indicators
1. SuperTrend Calculation:
- The SuperTrend indicator is calculated using a moving average and the Average True Range (ATR). The basic formula is:
- Upper Band = Moving Average + (Multiplier × ATR)
- Lower Band = Moving Average - (Multiplier × ATR)
- The moving average type (SMA, EMA, WMA, RMA, VWMA) and the length of the moving average and ATR are adjustable parameters.
- The direction of the trend is determined based on the position of the closing price in relation to these bands.
2. AI Integration with K-Nearest Neighbors (KNN):
- The KNN algorithm is applied to predict trend direction. It uses historical price data and SuperTrend values to classify the current trend as bullish or bearish.
- The algorithm calculates the 'distance' between the current data point and historical points. The 'k' nearest data points (neighbors) are identified based on this distance.
- A weighted average of these neighbors' trends (bullish or bearish) is calculated to predict the current trend.
For more please check: Multi-TF AI SuperTrend with ADX - Strategy
🔶 Pivot Percentile Analysis
1. Percentile Calculation:
- This involves calculating the percentile ranks for high and low prices over a set of predefined lengths.
- The percentile function is typically defined as:
- Percentile = Value at (P/100) × (N + 1)th position
- Where P is the desired percentile, and N is the number of data points.
2. Trend Strength Evaluation:
- The calculated percentiles for highs and lows are used to determine the strength of bullish and bearish trends.
- For instance, a high percentile rank in the high prices may indicate a strong bullish trend, and vice versa for bearish trends.
For more please check: Pivot Percentile Trend - Strategy
🔶 Strategy Integration
1. Combining SuperTrend and Pivot Percentile:
- The strategy synthesizes the insights from both AI-enhanced SuperTrend and Pivot Percentile analysis.
- It compares the trend direction indicated by the SuperTrend with the strength of the trend as suggested by the Pivot Percentile analysis.
2. Signal Generation:
- A trading signal is generated when both the AI-enhanced SuperTrend and the Pivot Percentile analysis agree on the trend direction.
- For instance, a bullish signal is generated when both the SuperTrend is bullish, and the Pivot Percentile analysis shows strength in bullish trends.
🔶 Risk Management and Filters
- ADX and DMI Filter: The strategy uses the Average Directional Index (ADX) and the Directional Movement Index (DMI) as filters to assess the trend's strength and direction.
- Dynamic Trailing Stop Loss: Based on the SuperTrend indicator, the strategy dynamically adjusts stop-loss levels to manage risk effectively.
This strategy stands out for its ability to combine real-time AI analysis with established technical indicators, offering traders a nuanced and responsive tool for navigating complex market conditions. The equations and algorithms involved are pivotal in accurately identifying market trends and potential trade opportunities.
█ Usage
To effectively use this strategy, traders should:
1. Understand the AI and Pivot Percentile Indicators: A clear grasp of how these indicators work will enable traders to make informed decisions.
2. Interpret the Signals Accurately: The strategy provides bullish, bearish, and neutral signals. Traders should align these signals with their market analysis and trading goals.
3. Monitor Market Conditions: Given that this strategy is sensitive to market dynamics, continuous monitoring is crucial for timely decision-making.
4. Adjust Settings as Needed: Traders should feel free to tweak the input parameters to suit their trading preferences and to respond to changing market conditions.
█Default Settings and Their Impact on Performance
1. Trading Direction (Default: "Both")
Effect: Determines whether the strategy will take long positions, short positions, or both. Adjusting this setting can align the strategy with the trader's market outlook or risk preference.
2. AI Settings (Neighbors: 3, Data Points: 24)
Neighbors: The number of nearest neighbors in the KNN algorithm. A higher number might smooth out noise but could miss subtle, recent changes. A lower number makes the model more sensitive to recent data but may increase noise.
Data Points: Defines the amount of historical data considered. More data points provide a broader context but may dilute recent trends' impact.
3. SuperTrend Settings (Length: 10, Factor: 3.0, MA Source: "WMA")
Length: Affects the sensitivity of the SuperTrend indicator. A longer length results in a smoother, less sensitive indicator, ideal for long-term trends.
Factor: Determines the bandwidth of the SuperTrend. A higher factor creates wider bands, capturing larger price movements but potentially missing short-term signals.
MA Source: The type of moving average used (e.g., WMA - Weighted Moving Average). Different MA types can affect the trend indicator's responsiveness and smoothness.
4. AI Trend Prediction Settings (Price Trend: 10, Prediction Trend: 80)
Price Trend and Prediction Trend Lengths: These settings define the lengths of weighted moving averages for price and SuperTrend, impacting the responsiveness and smoothness of the AI's trend predictions.
5. Pivot Percentile Settings (Length: 10)
Length: Influences the calculation of pivot percentiles. A shorter length makes the percentile more responsive to recent price changes, while a longer length offers a broader view of price trends.
6. ADX and DMI Settings (ADX Length: 14, Time Frame: 'D')
ADX Length: Defines the period for the Average Directional Index calculation. A longer period results in a smoother ADX line.
Time Frame: Sets the time frame for the ADX and DMI calculations, affecting the sensitivity to market changes.
7. Commission, Slippage, and Initial Capital
These settings relate to transaction costs and initial investment, directly impacting net profitability and strategy feasibility.
Four WMA Strategy with TP and SLBasically I read a research paper on how they used different moving averages for long entries and short entries, and it kind of dawned on me that I always used the same one for long entry or exit, or even swing trading. So I smashed this together to see what would happen.
The strategy combines the use of four different WMAs for identifying trade entry points, along with a predefined take profit (TP) and stop loss (SL) for risk management. Here's a detailed description of its features and how it operates:
Main Features
1. **WMAs as the Core Indicator**:
- The strategy uses four WMAs with different lengths. Two WMAs (`longM1` and `longM2`) are used for long entry signals, and the other two (`shortM1` and `shortM2`) for short entry signals.
- The lengths of these WMAs are adjustable through input parameters.
2. **Trade Entry Conditions**:
- A long entry is signaled when the shorter WMA crosses under the longer WMA .
- Conversely, a short entry is signaled when the shorter WMA crosses under the longer WMA.
3. **Take Profit and Stop Loss**:
- The strategy includes a take profit and stop loss mechanism.
- The TP and SL levels are set as a percentage of the entry price, with the percentage values being adjustable through input parameters.
4. **Visual Representation**:
- The WMAs are plotted on the chart for visual aid, each with a distinct color for easy identification.
How It Works
- The strategy continuously monitors the crossing of WMAs to detect potential entry points for long and short positions.
- Upon detecting a long or short condition, it automatically enters a trade and sets the corresponding TP and SL levels based on the current price and the specified percentages.
- The strategy then actively manages the trade, exiting the position when either the TP or SL level is reached.
Drawbacks
- **Overreliance on WMAs**: The strategy heavily relies on WMAs for trade signals. While WMAs are useful for identifying trends, they might not always provide timely entry and exit signals.
- **Market Conditions**: It may not perform well in highly volatile or sideways markets where WMA crossovers could lead to false signals.
- **Risk Management**: The fixed percentage for TP and SL might not be suitable for all market conditions. Traders might need to adjust these values frequently based on market volatility and their risk tolerance.
Apparently I need to emphasize to use brains when using indicators and setting them up to achieve the results you can or want. Also risk of 12% is considered very high so I lowered the numbers to 5%, which tanked the profits, try adjusting them on your own. Check the properties settings for more info on comission and slippage.
Conclusion
The "Four WMA Strategy with TP and SL" is suitable for traders who prefer a moving average-based approach to trading, combined with a straightforward mechanism for risk management through take profit and stop loss. However, like all strategies, it should be used with an understanding of its limitations and ideally tested thoroughly in various market conditions before applying it to live trading.
Grid Bot BacktestingBinance, Bybit, Bitget, and other cross-exchange (grid) trading bot backtesting.
Auto bound: Automatically setting upper and lower price bounds.
Manual: Setting upper and lower price bounds manually.
The graph below represents the overall asset changes (initial investment amount + current position profit + grid profit).
Try using backtesting when setting up a grid bot on the exchange!
바이낸스, 바이비트, 비트겟 등 교차거래(그리드) 봇 백테스팅
Auto bound : 자동으로 상,하단 가격 설정
Manual : 직접 상,하단 가격 설정
아래 그래프는 총 자산 변화입니다.(초기투자금액 + 현재 포지션 수익 + 그리드 수익)
거래소에서 그리드 봇 설정할 때 백테스팅 유용하게 써보세요!
Ichimoku Clouds Strategy Long and ShortOverview:
The Ichimoku Clouds Strategy leverages the Ichimoku Kinko Hyo technique to offer traders a range of innovative features, enhancing market analysis and trading efficiency. This strategy is distinct in its combination of standard methodology and advanced customization, making it suitable for both novice and experienced traders.
Unique Features:
Enhanced Interpretation: The strategy introduces weak, neutral, and strong bullish/bearish signals, enabling detailed interpretation of the Ichimoku cloud and direct chart plotting.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Dual Trading Modes: Long and Short modes are available, allowing alignment with market trends.
Flexible Risk Management: Offers three styles in each mode, combining fixed risk management with dynamic indicator states for versatile trade management.
Indicator Line Plotting: Enables plotting of Ichimoku indicator lines on the chart for visual decision-making support.
Methodology:
The strategy utilizes the standard Ichimoku Kinko Hyo model, interpreting indicator values with settings adjustable through a user-friendly menu. This approach is enhanced by TradingView's built-in strategy tester for customization and market selection.
Risk Management:
Our approach to risk management is dynamic and indicator-centric. With data from the last year, we focus on dynamic indicator states interpretations to mitigate manual setting causing human factor biases. Users still have the option to set a fixed stop loss and/or take profit per position using the corresponding parameters in settings, aligning with their risk tolerance.
Backtest Results:
Operating window: Date range of backtests is 2023.01.01 - 2024.01.04. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Maximum Single Position Loss: -6.29%
Maximum Single Profit: 22.32%
Net Profit: +10 901.95 USDT (+109.02%)
Total Trades: 119 (51.26% profitability)
Profit Factor: 1.775
Maximum Accumulated Loss: 4 185.37 USDT (-22.87%)
Average Profit per Trade: 91.67 USDT (+0.7%)
Average Trade Duration: 56 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. Backtest is calculated using deep backtest option in TradingView built-in strategy tester
How to Use:
Add the script to favorites for easy access.
Apply to the desired chart and timeframe (optimal performance observed on the 1H chart, ForEx or cryptocurrency top-10 coins with quote asset USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
BitBell - EMA PullBack RSI EXO
🔵 Introduction
Version 1.1
This is a Pine 5 trend following strategy. It has a four strategy with several alerts and signals. The design intent is to produce a commercial grade signal generator that can be adapted to any symbol in cryptocurrency and only 1H Chart. Ideally, the script is reliable enough to be the basis of an automated trading system web-hooked to a server with API access to crypto brokerages. The strategy can be run in three different modes: long, short and bidirectional.
As a trend following strategy, the behavior of the script is to buy on strength and sell on weakness. As such the trade orders maintain its directional bias according to price pressure. What you will see on the chart is long positions on the left side of the mountain and short on the right. Long and short positions are not intermingled as long as there exists a detectable trend. This is extremely beneficial feature in long running bull or bear markets. The script uses multiple setups to avoid the situation where you got in on the trend, took a small profit but couldn’t get back in because the logic is waiting for a pullback or some other intricate condition.
Deep draw-downs are a characteristic of trend following systems and this system is no different. However, this script makes use of the TradingView pyramid feature with three NPUs to find better place and even you can change drop percentage in settings for another trigger, accessible from the properties tab.
When trend market break it will stop the trade and usually it takes 2-4 percent loss but don't worry it has prefect money management and you can use it for Futures market and even Spot market.
🔵 Design
This script uses twelve indicators on two time frames. The chart (primary) interval and one higher time frame which is based on the primary. The higher time frame identifies the trend for which the primary will trade. I’ve tried to keep the higher time frame around five times greater than the primary. The original trading algorithms are a port from a much larger program on another trading platform. I’ve converted some of the statistical functions to use standard indicators available on TradingView. The setups make heavy use of the Hull Moving Average in conjunction with EMAs that form the Bill Williams Alligator as described in his book “New Trading Dimensions” Chapter 3. Lag between the Hull and the EMAs form the basis of the entry and exit points. The alligator itself is used to identify the trend main body.
The entire script is around 740 lines of Pine code which is the maximum incidental size given the TradingView limits: local scopes, run-time duration and compile time. I’ve been working on this script for over a year and have tested it on various instruments stock crypto. It performs well on higher liquidity markets that have at least a year of historical data. Though it can be configured to work on any interval between 15 minutes and 4 hour, trend trading is generally a longer term paradigm. For day trading the 10 to 15 minute interval will allow you to catch momentum breakouts. For intraweek trades 30 minutes to 1 hour should give you a trade every other a day.
Inputs to the script use cone centric measurements in effort to avoid exposing adjustments to the various internal indicators. The goal was to keep the inputs relevant to the actual trade entry and exit locations as opposed to a series of MA input values and the like. As a result the strategy exposes over 12 inputs grouped into long or short sections. Inputs are available for the usual minimum profit and stop-loss as well as trade, modes, presets, reports and lots of calibrations. The inputs are numerous, I’m aware. Unfortunately, at this time, TradingView does not offer any other method to get data in the script. The usual initialization files such as cnf, cfg, ini, json and xml files are currently unsupported.
Example configurations for various instruments along with a detailed PDF user manual is available.
it has no repaint i guaranty this, and you can have 10 days free with comment and check it by yourself
One issue that comes up when comparing the strategy with the study is that the strategy trades show on the chart one bar later than the study. This problem is due to the fact that “strategy.entry()” and “strategy_close()” do not execute on the same bar called. The study, on the other hand, has no such limitation since there are no position routines. However, alerts that are subsequently fired off when triggered in the study are dispatched from the TradingView servers one bar later from the study plot. Therefore the alert you actually receive on your cell phone matches the strategy plot but is one bar later than the study plot.
Please be aware that the data source matters. Cryptocurrency has no central tick repository so each exchange supplies TradingView its feed. Even though it is the same symbol the quality of the data and subsequently the bars that are supplied to the chart varies with the exchange. This script will absolutely produce different results on different data feeds of the same symbol. Be sure to backtest this script on the same data you intend to receive alerts for. Any example settings I share with you will always have the exchange name used to generate the test results.
🟡 Usage
It sends long and short signals with pyramid orders of up to 3, meaning that the strategy can trigger up to 3 orders in the same direction. Good risk and money management.
It's important to note that the strategy combines 2 systems working together (Long and LongX). Let’s describe the specific features of this strategy.
🔵 If Findes Supports And Ressitances And Trend Lines As Best As It Can, And You Can See:
🟢 Frist Simple Long Condition = It Look At The Trend Wait For RSI Cross 30 Number Then Ckeck Risk To Reward, check something else such as divergence:
🟢 Another Long Example:
🔴 Frist Simple Short Condition = It Look At The Trend Wait For RSI Cross 70 Number Then Ckeck Risk To Reward, check something else such as divergence:
🔴 Another Short Example:
The following steps provide a very brief set of instructions that will get you started but will most certainly not produce the best backtest. A trading system that you are willing to risk your hard earned capital will require a well crafted configuration that involves time, expertise and clearly defined goals. As previously mentioned, I have several example configs that I use for my own trading that I can share with you along with a PDF which describes each input in detail. To get hands on experience in setting up your own symbol from scratch please follow the steps below.
The input dialog box contains over 12 inputs, There are four options must to be configured: Choose Target, side, Choose Settings, Money Management,and settings that apply to both. The following steps address these four main options only.
Money Management System For Leverage 10:
Bot Finds Last Lower Low And Calculate Distance From Entry Price, Then Cross It To Initial Capitan And Cross Leverage =>
Position_Size = (((1.64) * (initial Capital)) * (leverage))
And Check Dominances Too For Getting Best Money Management Result
🔵 Settings
* Side, You Can Set Long Or Short Or Both.
* Choose Target, You Can Set One Target Or All Targets.
* Money Management, You Can ON Or OFF It, With OFF You Can USE It For SPOT Trades.
* Choose Settings, In This Field You Can Set Mathematical Optimization, Ddepends On Which Pair You USE.
* Clear With Daily PullBack?, With This Check Box You Can Clear Signals With Daily PullBack.
* Long X, You Can Set Long Leverage.
* Short X, You Can Set Short Leverage.
* Second Order X, You Can Set Pyramiding Leverage.
* Target Long, You Can Set Percent For Long Target.
* Target Short, You Can Set Percent For Short Target.
* Short Martin Percent, You Can Set Short Martingale Percent.
* Long Martin Percent, You Can Set Long Martingale Percent.
🟡 Pyraming 3
🟡 Commission Is 0.065 %
🟡 Slippage Is 10 ticks
🔴Only Use For 1 Hour Chart
🔴 CONCLUSION
We believe that success lies in the association of the user with the indicator, opposed to many traders who have the perspective that the indicator itself can make them become profitable. The reality is much more complicated than that.
The aim is to provide an indicator comprehensive, customizable, and intuitive enough that any trader can be led to understand this truth and develop an actionable perspective of technical indicators as support tools for decision making.
🔴 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by BitBell are purely for informational & educational purposes only. Past performance does not guarantee future results.
Table to filter trades per dayThis script contains a block of code that allows users to filter the total number of trades, loss trades, win trades and win rate per day in a table. This makes it easier to compare which days were profitable and which were not.
Be aware that this script can only be used in strategy scripts. To use the script, open it and copy every line from "START" to "STOP". Then, paste these lines at the very bottom of the strategy script that you want to attach it to.
The user has the ability to adjust the position of the table and customize the size of the text displayed.
If the user sets "Check when the trade:" to "Opened", the script will monitor when the trade opens and add it to the table once it has been closed. If "Check when the trade:" is set to "Closed", the script will track when the trade is closed and add it to the table once it has been closed.
It is recommended to run the script on the "Exchange" setting for more accurate results, even though a "Set the timezone" option is available. This will prevent discrepancies caused by daylight saving time changes.
Please note that the code will only work properly if you choose a daily timeframe or lower.
Turtle Trader StrategyTurtle Trader Strategy :
Introduction :
This strategy is based on the well known « Turtle Trader Strategy », that has proven itself over the years. It sends long and short signals with pyramid orders of up to 5, meaning that the strategy can trigger up to 5 orders in the same direction. Good risk and money management.
It's important to note that the strategy combines 2 systems working together (S1 and S2). Let’s describe the specific features of this strategy.
1/ Position size :
Position size is very important for turtle traders to manage risk properly. This position sizing strategy adapts to market volatility and to account (gains and losses). It’s based on ATR (Average True Range) which can also be called « N ». Its length is per default 20.
ATR(20) = (previous_atr(20)*19 + actual_true_range)/20
The number of units to buy is :
Unit = 1% * account/(ATR(20)*dollar_per_point)
where account is the actual account value and dollar_per_point is the variation in dollar of the asset with a 1 point move.
Depending on your risk aversion, you can increase the percentage of your account, but turtle traders default to 1%. If you trade contracts, units must be rounded down by default.
There is also an additional rule to reduce the risk if the value of the account falls below the initial capital : in this case and only in this case, account in the unit formula must be replace by :
account = actual_account*actual_account/initial capital
2/ Open a position :
2 systems are working together :
System 1 : Entering a new 20 day breakout
System 2 : Entering a new 55 day breakout
A breakout is a new high or new low. If it’s a new high, we open long position and vice versa if it’s a new low we enter in short position.
We add an additional rule :
System 1 : Breakout is ignored if last long/short position was a winner
System 2 : All signals are taken
This additional rule allows the trader to be in the major trends if the system 1 signal has been skipped. If a signal for system 1 has been skipped, and next candle is also a new 20 day breakout, S1 doesn’t give a signal. We have to wait S2 signal or wait for a candle that doesn’t make a new breakout to reactivate S1.
3/ Pyramid orders :
Turtle Strategy allows us to add extra units to the position if the price moves in our favor. I've configured the strategy to allow up to 5 orders to be added in the same direction. So if the price varies from 0.5*ATR(20) , we add units with the position size formula. Note that the value of account will be replaced by "remaining_account", i.e. the cash remaining in our account after subtracting the value of open positions.
4/ Stop Loss :
We set a stop loss at 1.5*ATR(20) below the entry price for longs and above the entry price for shorts. If pyramid units are added, the stop is increased/decreased by 0.5*ATR(20). Note that if SL is configured for a loss of more than 10%, we set the SL to 10% for the first entry order to avoid big losses. This configuration does not work for pyramid orders as SL moves by 0.5*ATR(20).
5/ Exit signals :
System 1 :
Exit long on a 10 day low
Exit short on a 10 day high
System 2 :
Exit long on a 20 day low
Exit short on a 20 day high
6/ What types of orders are placed ?
To enter in a position, stop orders are placed meaning that we place orders that will be automatically triggered by the signal at the exact breakout price. Stop loss and exit signals are also stop orders. Pyramid orders are market orders which will be triggered at the opening of the next candle to avoid repainting.
PARAMETERS :
Risk % of capital : Percentage used in the position size formula. Default is 1%
ATR period : ATR length used to calculate ATR. Default is 20
Stop ATR : Parameters used to fix stop loss. Default is 1.5 meaning that stop loss will be set at : buy_price - 1.5*ATR(20) for long and buy_price + 1.5*ATR(20) for short. Turtle traders default is 2 but 1.5 is better for cryptocurrency as there is a huge volatility.
S1 Long : System 1 breakout length for long. Default is 20
S2 Long : System 2 breakout length for long. Default is 55
S1 Long Exit : System 1 breakout length to exit long. Default is 10
S2 Long Exit : System 2 breakout length to exit long. Default is 20
S1 Short : System 1 breakout length for short. Default is 15
S2 Short : System 2 breakout length for short. Default is 55
S1 Short Exit : System 1 breakout length to exit short. Default is 7
S2 Short Exit : System 2 breakout length to exit short. Default is 20
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Pyramiding : Number of orders that can be passed in the same direction. Default is 5.
Important : Turtle traders don't trade crypto. For this specific asset type, I modify some parameters such as SL and Short S1 in order to maximize return while limiting drawdown. This strategy is the most optimal on BINANCE:BTCUSD in 1D timeframe with the parameters set per default. If you want to use this strategy for a different crypto please adapt parameters.
NOTE :
It's important to note that the first entry order (long or short) will be the largest. Subsequent pyramid orders will have fewer units than the first order. We've set a maximum SL for the first order of 10%, meaning that you won't lose more than 10% of the value of your first order. However, it is possible to lose more on your pyramid orders, as the SL is increased/decreased by 0.5*ATR(20), which does not secure a loss of more than 10% on your pyramid orders. The risk remains well managed because the value of these orders is less than the value of the first order. Remain vigilant to this small detail and adjust your risk according to your risk aversion.
Enjoy the strategy and don’t forget to take the trade :)
mikul's Ichimoku Cloud Strategy v 2.0This is an Ichimoku cloud (long) strategy with both pump signals and trend signals.
It has both ATR stop loss, trailing percentage stop loss and also ichomoku cloud exit signal.
You can also combine the ATR stop loss and the trailing percentage stop loss with the Ichimoku cloud exit signal and a the take profit percentage.
In this example I use the default ATR stop loss method for taking profit.
10000$ is my initial capital and I risking 10% every trade. Commission is set to 0.075%.
Everything is set to default in this example.
There is also a moving average filter that is available, set to 200 EMA and turned off by default.
Conditions for taking a long position:
Trend Signal:
• Positive cross above the cloud
• Chikou span(lagging span) above price action
• Price above the Cloud
Pump Signal:
• Cloud ahead of you is green
• Price above the cloud
• Positive cross (Doesn’t Matter Where)
• Chikou span(lagging span) above the cloud
Ichimoku cloud exit signals:
• Negative cross
• Chikou span(lagging span) touches the price action
This strategy is totally free as freedom and as in free beer!
I do this for myself, but I like sharing and I want everyone to have the ability to use what I make no matter your economic situation.
If you have any suggestions for this strategy or perhaps any filtering options that could be fun to experiment with, then please leave a comment with your suggestion and maybe I can add it to the next version.
FlexiMA x FlexiST - Strategy [presentTrading]█ Introduction and How it is Different
The FlexiMA x FlexiST Strategy blends two analytical methods - FlexiMA and FlexiST, which are opened in my early post.
- FlexiMA calculates deviations between an indicator source and a dynamic moving average, controlled by a starting factor and increment factor.
- FlexiST, on the other hand, leverages the SuperTrend model, adjusting the Average True Range (ATR) length for a comprehensive trend-following oscillator.
This synergy offers traders a more nuanced and multifaceted tool for market analysis.
BTC 6H L/S Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy combines two components: FlexiMA and FlexiST, each utilizing unique methodologies to analyze market trends.
🔶FlexiMA Component:
- Calculates deviations between an indicator source and moving averages of variable lengths.
- Moving average lengths are dynamically adjusted using a starting factor and increment factor.
- Deviations are normalized and analyzed to produce median and standard deviation values, forming the FlexiMA oscillator.
Length indicator (50)
🔶FlexiST Component:
- Uses SuperTrend indicators with varying ATR (Average True Range) lengths.
- Trends are identified based on the position of the indicator source relative to the SuperTrend bands.
- Deviations between the indicator source and SuperTrend values are calculated and normalized.
Starting Factor (5)
🔶Combined Strategy Logic:
- Entry Signals:
- Long Entry: Triggered when median values of both FlexiMA and FlexiST are positive.
- Short Entry: Triggered when median values of both FlexiMA and FlexiST are negative.
- Exit Signals:
- Long Exit: Triggered when median values of FlexiMA or FlexiST turn negative.
- Short Exit: Triggered when median values of FlexiMA or FlexiST turn positive.
This strategic blend of FlexiMA and FlexiST allows for a nuanced analysis of market trends, providing traders with signals based on a comprehensive view of market momentum and trend strength.
█ Trade Direction
The strategy is designed to cater to various trading preferences, offering "Long", "Short", and "Both" options. This flexibility allows traders to align the strategy with their specific market outlook, be it bullish, bearish, or a combination of both.
█ Usage
Traders can effectively utilize the FlexiMA x FlexiST Strategy by first selecting their desired trade direction. The strategy then generates entry signals when the conditions for either the FlexiMA or FlexiST are met, indicating potential entry points in the market. Conversely, exit signals are generated when the conditions for these indicators diverge, thus signaling a potential shift in market trends and suggesting a strategic exit point.
█ Default Settings
1. Indicator Source (HLC3): Provides a balanced and stable price source, reducing the impact of extreme market fluctuations.
2. Indicator Lengths (20 for FlexiMA, 10 for FlexiST): Longer FlexiMA length smooths out short-term fluctuations, while shorter FlexiST length allows for quicker response to market changes.
3. Starting Factors (1.0 for FlexiMA, 0.618 for FlexiST): Balanced start for FlexiMA and a harmonized approach for FlexiST, resonating with natural market cycles.
4. Increment Factors (1.0 for FlexiMA, 0.382 for FlexiST): FlexiMA captures a wide range of market behaviors, while FlexiST provides a gradual transition to capture finer trend shifts.
5. Normalization Methods ('None'): Uses raw deviations, suitable for markets where absolute price movements are more significant.
6. Trade Direction ('Both'): Allows strategy to consider both long and short opportunities, ideal for versatile market engagement.
*More details:
1. FlexiMA
2. FlexiST
5 ema strategyThis Strategy is based of Subhashish Pani's (power of stocks) 5 EMA Strategy.strategy used for sell in 5 minutes and for buy in 15 minutes ..
Rules for this strategy ..
Sell signal -
1) if price is above 5 Ema and not touching Ema use as alert candle..
2) if price break low of alert candle strategy open trade ..
3) if price move more upside low of alert candle keep change into next candle ..
4) input we can select number of trade per day .as rule should take only 4 signal should execute
5) stop loss is fixed highest high of last 2 candle and take profit is input multiply of stop loss
buy signal-
1) if price is below 5 Ema and not touching Ema use as alert candle..
2) if price break high of alert candle strategy open trade ..
3) if price move more downside high of alert candle keep change into next candle ..
4) input we can select number of trade per day .as rule should take only 4 signal should execute
5) stop loss is fixed lowest low of last 2 candle and take profit is input multiply of stop loss
notes -input can be selected which side should take signal either buy or sell side ...number of trade can be adjusted ..
Disclaimer -Traders can use this script as a starting point for further customization or as a reference for developing their own trading strategies. It's important to note that past performance is not indicative of future results, and thorough testing and validation are recommended before deploying any trading strategy.
CCI based support and resistance strategy
WARNING:
Commissions and slippage has not been considered! Don’t take it easy adding commissions and slippage could turns a fake-profitable strategy to a real disaster.
We consider account size as 10k and we enter 1000 for each trade.
Less than 100 trades is too small sample community and it’s not reliable, Also the performance of the past do not guarantee future performance. This result was handpicked by author and will differ by other timeframes, instruments and settings.
*PLEASE SHARE YOUR SETTINGS THAT WORK WITH THE COMMUNITY.
Introduction:
The CCI-based dynamic support and resistance is a "Bands and Channels" kind of indicator consisting an upper and lower band. This is a strategy which uses CCI-based (Made by me) indicator to execute trades.
SL and TP are calculated based on max ATR during last selected time period. You can edit strategy settings using "Ksl", "Ktp" and the other button for time period. “KSL” and “KTP” are 2.5 and 5 by default.
Bands are calculated regarding CCI previous high and low pivot. CCI length, right pivot length and left pivot length are 50.
A dynamic support and resistance has been calculated using last upper-cci minus a buffer and last lower-cci plus the buffer. The buffer is 10.
If "Trend matter?" button is on you can detect trend by color of the upper and lower line. Green is bullish and red is bearish! "Trend matter?" is on.
The "show mid?" button makes mid line visible, which is average of upper and lower lines, visible. The button is not active by default.
Reaction to the support could be a buy signal while a reaction to the resistance could interpreted as a sell signal.
How this strategy work?
Donald Lambert, a technical analyst, created the CCI, or Commodity Channel Index, which he first published in 1980. CCI is calculated regarding CCI can be used both as trend-detector or an oscillator. As an oscillator most traders believe in static predefined levels. Overbought and oversold candles which are clear in the chart could be used as sell and buy signals.
During my trading career I’ve noticed that there might be some reversal points for the CCI. I believe CCI could have to potential to reverse more from lately reversal point. Of course, just like other trading strategies we are talking about probabilities. We do not expect a win trade each time.
On price chart
Now this the question! What price should the instrument reach that CCI turns to be equal to our reversing aim for CCI? Imagine we have found last important bearish reversal of CCI in 200. Now, if we need the CCI to be 200 what price should we wait for?
How to calculate?
This is the CCI formula:
CCI = (Typical Price - SMA of TP) / (0.015 x Mean Deviation)
Where, Typical Price (TP) = (High + Low + Close)/3
For probable reversing points, high and low pivots of 50 bars have been used.
So we do have an Upper CCI and a Lower CCI. They are valid until the next pivot is available.
By relocating factors in CCI formula you can reach the “Typical Price”.
“
Typical Price = CCI (0.015 * Mean Deviation) + SMA of TP
So we could have a Support or Resistance by replacing CCI with Upper and Lower CCI.
A buy signal is valid if the trend is bullish (or “trend matter” is off) and lowest low of last 2 candles is lower than support and close is greater than both support and open.
A Sell signal is produced in opposite situation.
There are 2+1 options for trend!
Trend matter box is on by default, which means we’ll just open trades in direction of the trend. It’s available to turn it off.
Other 2 options are cross and slope. Cross calculated by comparing fast SMA and slow SMA. The slope one differentiate slow SMA to last “n” one.
Considering last day and today highest ATR as the ATR to calculating SL and TP is our unique technique.
Hulk Grid Algorithm V2 - The Quant ScienceIt's the latest proprietary grid algorithm developed by our team. This software represents a clearer and more comprehensive modernization of the deprecated Hulk Grid Algorithm. In this new release, we have optimized the source code architecture and investment logic, which we will describe in detail below.
Overview
Hulk Grid Algorithm V2 is designed to optimize returns in sideways market conditions. In this scenario, the algorithm divides purchases with long orders at each level of the grid. Unlike a typical grid algorithm, this version applies an anti-martingale model to mitigate volatility and optimize the average entry price. Starting from the lower level, the purchase quantity is increased at each new subsequent level until reaching the upper level. The initial quantity of the first order is fixed at 0.50% of the initial capital. With each new order, the initial quantity is multiplied by a value equal to the current grid level (where 1 is the lower level and 10 is the upper level).
Example: Let's say we have an initial capital of $10,000. The initial capital for the first order would be $50 * 1 = $50, for the second order $50 * 2 = $100, for the third order $50 * 3 = $150, and so on until reaching the upper level.
All previously opened orders are closed using a percentage-based stop-loss and take-profit, calculated based on the extremes of the grid.
Set Up
As mentioned earlier, the user's goal is to analyze this strategy in markets with a lack of trend, also known as sideways markets. After identifying a price range within which the asset tends to move, the user can choose to create the grid by placing the starting price at the center of the range. This way, they can consider trading the asset, if the backtesting generates a return greater than the Buy & Hold return.
Grid Configuration
To create the grid, it's sufficient to choose the starting price during the launch phase. This level will be the center of the grid from which the upper and lower levels will be calculated. The grid levels are computed using an arithmetic method, adding and subtracting a configurable fixed amount from the user interface (Grid Step $).
Example: Let's imagine choosing 1000 as the starting price and 50 as the Grid Step ($). The upper levels will be 1000, 1050, 1100, 1150, 1200. The lower levels will be 950, 900, 850, 800, and 750.
Markets
This software can be used in all markets: stocks, indices, commodities, cryptocurrencies, ETFs, Forex, etc.
Application
With this backtesting software, is possible to analyze the strategy and search for markets where it can generate better performance than Buy & Hold returns. There are no alerts or automatic investment mechanisms, and currently, the strategy can only be executed manually.
Design
Is possible to modify the grid style and customize colors by accessing the Properties section of the user interface.