Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Strategy
[AlbaTherium] MTF Internal Ranges Analysis - IRA-Phoenix for SMCIntroduction:
The MTF Internal Ranges Analysis - IRA - Phoenix acts as an extension to the original main SMC Indicator by AlbaTherium . This add-on provides insights into multi-timeframe internal structure points, swing structure points, POIs (Points of Interest), and order blocks (OB). By integrating this enhancement, your multi-timeframe analyses become more streamlined, expediting the process and minimizing chart workload .
This tool represents an advanced smart money technical analysis aimed at enhancing your trading experience. It introduces four pivotal concepts:
Main Features:
Multiple Timeframes and Confluences,
SCOB Internal Order Block.
Demand to Supply (D2S) or Supply to Demand (S2D) across Multiple timeframes
SCOB on LTF and SCM on HTF across same Candle
By combining these concepts all in one, traders can find confluences zones across multiple timeframes and gain a comprehensive understanding of market dynamics, theses confluences zones empower order block skills and potentiality, showcasing them as essential, crucial, powerful, strategic, and pivotal, one of the pillars in smart money concepts trading strategy to make more informed decisions.
Settings Overview:
Select timeframe {Select or current chart}
Inside bar ranges
Internal structure as Internal zigzag {turn on/ off / unconfirmed(live) zigzag}
Single Candle Mitigation Pattern {turn on/ off / confirmed / unconfirmed}
Single Candle Order Block Pattern {turn on/ off / confirmed / unconfirmed}
Demands and Supplies (D&S) {turn on/ off / confirmed / unconfirmed}
OB Mitigation {touch/ extended}
Understanding the Features:
Chapter 1: Multiple Timeframes and Confluences
Our Multi-timeframe analysis approach enables traders to analyze market trends and volatility across different timeframes. Confluences, where signals align across multiple timeframes, provide strong indications for trading opportunities.
Practical Example:
- With MTF IRA - Phoenix , traders can seamlessly transition between different timeframes while maintaining a cohesive analysis. For instance, traders can monitor the M15, H1, or M5 charts while focusing on entry on the M1 timeframe, enabling a holistic view of market trends and opportunities .
Chapter 2: SCOB Internal Order Block across Multiple Timeframe
SCOB Internal Order Block (SCOB IOB) highlights critical zones in price action, showcasing the dominance of aggressive buyers or sellers on orders blocks. As confluences accumulate across multiple timeframes, the strength of the order block intensifies, presenting entry opportunities.
Practical Example:
You have the ability to detect zones where price ranges have formed; these areas are highly sought after for taking buying as well as selling positions, especially when these areas are reflected across 1 or 3 timeframes.
The only practical way to see theses confluences is to use this Indicator, see the example below
Chapter 03: Demand to Supply (D2S) or Supply to Demand (S2D) across Multiple timeframes
The Demand to Supply or Supply to Demand feature within MTF Internal Ranges Analysis - IRA - Phoenix offers a nuanced analysis of price action dynamics across various timeframes. By identifying shifts in supply and demand zones, traders gain valuable insights into market sentiment and potential price reversals.
This feature enables traders to anticipate changes in market direction by recognizing the interplay between demand and supply across different timeframes. By understanding how price reacts at key support and resistance levels, traders can make informed decisions and capitalize on emerging trends.
The Demand to Supply or Supply to Demand feature enhances the indicator's usefulness by providing traders with actionable information to navigate complex market conditions effectively. With this comprehensive analysis, traders can better manage risk and optimize trading strategies across multiple timeframes.
Real-world Example:
Chapter 04: SCOB on LTF and SCM on HTF across same Candle
with MTF Internal Ranges Analysis - IRA - Phoenix , explores the concepts of SCOB (Single Candle Order Block) on Lower Timeframes (LTF) and SCM (Single Candle Mitigation) on Higher Timeframes (HTF).
SCOB on LTF refers to the identification and analysis of single candle order blocks within shorter timeframes. These blocks represent critical price levels where significant buying or selling activity occurred within a single candlestick. By recognizing SCOB patterns, traders can pinpoint key areas of market interest and anticipate potential price movements.
On the other hand, SCM on HTF involves analyzing single candle mitigation entries within longer timeframes. This technique aims to capitalize on price reversals or shifts in market sentiment indicated by single candlestick patterns. By incorporating SCM analysis, traders can gain insights into broader market trends and make strategic trading decisions accordingly.
the intricacies of SCOB on LTF and SCM on HTF, offering traders valuable tools to enhance their analysis and decision-making processes across different timeframes. Through a comprehensive understanding of these concepts, traders can identify high-probability trading opportunities and navigate the markets with confidence.
Real-world Example:
SCOB on M5 and SCM on M15 generate a powerful order block.
Conclusion:
MTF Internal Ranges Analysis - IRA - Phoenix for Smart Money Concepts is a valuable asset for traders seeking to add more insights in today's dynamic markets especially for Intraday Traders. By focusing on concepts like "Multiple timeframes and Confluences, with one single timeframe u can analyze all timeframes", "SCOB Internal Order Block. With its innovative features and user-friendly interface, whether you're a seasoned trader or just starting your journey, MTF IRA - Phoenix can help you navigate through the complexities of price action and make more informed trading choices.
This document provides an extensive overview of MTF Internal Ranges Analysis - IRA - Phoenix, emphasizing its importance in comprehending market dynamics and utilizing essential smart money concepts trading principles.
Aroon and ASH strategy - ETHERIUM [IkkeOmar]Intro:
This post introduces a Pine Script strategy, as an example if anyone needs a push to get started. This example is a strategy on ETH, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay. This strategy combines two technical indicators: Aroon and Absolute Strength Histogram (ASH).
Overview:
The strategy employs the Aroon indicator alongside the Absolute Strength Histogram (ASH) to determine market trends and potential trade setups. Aroon helps identify the strength and direction of a trend, while ASH provides insights into the strength of momentum. By combining these indicators, the strategy aims to capture profitable trading opportunities in Ethereum markets. Normally when developing strats using indicators, you want to find some good indicators, but you NEED to understand their strengths and weaknesses, other indicators can be incorporated to minimize the downs of another indicator. Try to look for synergy in your indicators!
Indicator settings:
Aroon Indicator:
- Two sets of parameters are used for the Aroon indicator:
- For Long Positions: Aroon periods are set to 56 (upper) and 20 (lower).
- For Short Positions: Aroon periods are set to 17 (upper) and 55 (lower).
Absolute Strength Histogram (ASH):
ASH is calculated with a length of 9 bars using the closing price as the data source.
Trading Conditions:
The strategy incorporates specific conditions to initiate and exit trades:
Start Date:
Traders can specify the start date for backtesting purposes.
Trade Direction:
Traders can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
1. Long Position Entry: A long position is initiated when the Aroon indicator crosses over (crossover) the lower Aroon threshold, indicating a potential uptrend.
2. Long Position Exit: A long position is closed when the Aroon indicator crosses under (crossunder) the lower Aroon threshold.
3. Short Position Entry: A short position is initiated when the Aroon indicator crosses under (crossunder) the upper Aroon threshold, signaling a potential downtrend.
4. Short Position Exit: A short position is closed when the Aroon indicator crosses over (crossover) the upper Aroon threshold.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Bitcoin Leverage Sentiment - Strategy [presentTrading]█ Introduction and How it is Different
The "Bitcoin Leverage Sentiment - Strategy " represents a novel approach in the realm of cryptocurrency trading by focusing on sentiment analysis through leveraged positions in Bitcoin. Unlike traditional strategies that primarily rely on price action or technical indicators, this strategy leverages the power of Z-Score analysis to gauge market sentiment by examining the ratio of leveraged long to short positions. By assessing how far the current sentiment deviates from the historical norm, it provides a unique lens to spot potential reversals or continuation in market trends, making it an innovative tool for traders who wish to incorporate market psychology into their trading arsenal.
BTC 4h L/S Performance
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█ Strategy, How It Works: Detailed Explanation
🔶 Data Collection and Ratio Calculation
Firstly, the strategy acquires data on leveraged long (**`priceLongs`**) and short positions (**`priceShorts`**) for Bitcoin. The primary metric of interest is the ratio of long positions relative to the total of both long and short positions:
BTC Ratio=priceLongs / (priceLongs+priceShorts)
This ratio reflects the prevailing market sentiment, where values closer to 1 indicate a bullish sentiment (dominance of long positions), and values closer to 0 suggest bearish sentiment (prevalence of short positions).
🔶 Z-Score Calculation
The Z-Score is then calculated to standardize the BTC Ratio, allowing for comparison across different time periods. The Z-Score formula is:
Z = (X - μ) / σ
Where:
- X is the current BTC Ratio.
- μ is the mean of the BTC Ratio over a specified period (**`zScoreCalculationPeriod`**).
- σ is the standard deviation of the BTC Ratio over the same period.
The Z-Score helps quantify how far the current sentiment deviates from the historical norm, with high positive values indicating extreme bullish sentiment and high negative values signaling extreme bearish sentiment.
🔶 Signal Generation: Trading signals are derived from the Z-Score as follows:
Long Entry Signal: Occurs when the BTC Ratio Z-Score crosses above the thresholdLongEntry, suggesting bullish sentiment.
- Condition for Long Entry = BTC Ratio Z-Score > thresholdLongEntry
Long Exit/Short Entry Signal: Triggered when the BTC Ratio Z-Score drops below thresholdLongExit for exiting longs or below thresholdShortEntry for entering shorts, indicating a shift to bearish sentiment.
- Condition for Long Exit/Short Entry = BTC Ratio Z-Score < thresholdLongExit or BTC Ratio Z-Score < thresholdShortEntry
Short Exit Signal: Happens when the BTC Ratio Z-Score exceeds the thresholdShortExit, hinting at reducing bearish sentiment and a potential switch to bullish conditions.
- Condition for Short Exit = BTC Ratio Z-Score > thresholdShortExit
🔶Implementation and Visualization: The strategy applies these conditions for trade management, aligning with the selected trade direction. It visualizes the BTC Ratio Z-Score with horizontal lines at entry and exit thresholds, illustrating the current sentiment against historical norms.
█ Trade Direction
The strategy offers flexibility in trade direction, allowing users to choose between long, short, or both, depending on their market outlook and risk tolerance. This adaptability ensures that traders can align the strategy with their individual trading style and market conditions.
█ Usage
To employ this strategy effectively:
1. Customization: Begin by setting the trade direction and adjusting the Z-Score calculation period and entry/exit thresholds to match your trading preferences.
2. Observation: Monitor the Z-Score and its moving average for potential trading signals. Look for crossover events relative to the predefined thresholds to identify entry and exit points.
3. Confirmation: Consider using additional analysis or indicators for signal confirmation, ensuring a comprehensive approach to decision-making.
█ Default Settings
- Trade Direction: Determines if the strategy engages in long, short, or both types of trades, impacting its adaptability to market conditions.
- Timeframe Input: Influences signal frequency and sensitivity, affecting the strategy's responsiveness to market dynamics.
- Z-Score Calculation Period: Affects the strategy’s sensitivity to market changes, with longer periods smoothing data and shorter periods increasing responsiveness.
- Entry and Exit Thresholds: Set the Z-Score levels for initiating or exiting trades, balancing between capturing opportunities and minimizing false signals.
- Impact of Default Settings: Provides a balanced approach to leverage sentiment trading, with adjustments needed to optimize performance across various market conditions.
BigBeluga - BacktestingThe Backtesting System (SMC) is a strategy builder designed around concepts of Smart Money.
What makes this indicator unique is that users can build a wide variety of strategies thanks to the external source conditions and the built-in one that are coded around concepts of smart money.
🔶 FEATURES
🔹 Step Algorithm
Crafting Your Strategy:
You can add multiple steps to your strategy, using both internal and external (custom) conditions.
Evaluating Your Conditions:
The system evaluates your conditions sequentially.
Only after the previous step becomes true will the next one be evaluated.
This ensures your strategy only triggers when all specified conditions are met.
Executing Your Strategy:
Once all steps in your strategy are true, the backtester automatically opens a market order.
You can also configure exit conditions within the strategy builder to manage your positions effectively.
🔹 External and Internal build-in conditions
Users can choose to use external or internal conditions or just one of the two categories.
Build-in conditions:
CHoCH or BOS
CHoCH or BOS Sweep
CHoCH
BOS
CHoCH Sweep
BOS Sweep
OB Mitigated
Price Inside OB
FVG Mitigated
Raid Found
Price Inside FVG
SFP Created
Liquidity Print
Sweep Area
Breakdown of each of the options:
CHoCH: Change of Character (not Charter) is a change from bullish to bearish market or vice versa.
BOS: Break of Structure is a continuation of the current trend.
CHoCH or BOS Sweep: Liquidity taken out from the market within the structure.
OB Mitigated: An order block mitigated.
FVG Mitigated: An imbalance mitigated.
Raid Found: Liquidity taken out from an imbalance.
SFP Created: A Swing Failure Pattern detected.
Liquidity Print: A huge chunk of liquidity taken out from the market.
Sweep Area: A level regained from the structure.
Price inside OB/FVG: Price inside an order block or an imbalance.
External inputs can be anything that is plotted on the chart that has valid entry points, such as an RSI or a simple Supertrend.
Equal
Greather Than
Less Than
Crossing Over
Crossing Under
Crossing
🔹 Direction
Users can change the direction of each condition to either Bullish or Bearish. This can be useful if users want to long the market on a bearish condition or vice versa.
🔹 Build-in Stop-Loss and Take-Profit features
Tailoring Your Exits:
Similar to entry creation, the backtesting system allows you to build multi-step exit strategies.
Each step can utilize internal and external (custom) conditions.
This flexibility allows you to personalize your exit strategy based on your risk tolerance and trading goals.
Stop-Loss and Take-Profit Options:
The backtesting system offers various options for setting stop-loss and take-profit levels.
You can choose from:
Dynamic levels: These levels automatically adjust based on market movements, helping you manage risk and secure profits.
Specific price levels: You can set fixed stop-loss and take-profit levels based on your comfort level and analysis.
Price - Set x point to a specific price
Currency - Set x point away from tot Currency points
Ticks - Set x point away from tot ticks
Percent - Set x point away from a fixed %
ATR - Set x point away using the Averge True Range (200 bars)
Trailing Stop (Only for stop-loss order)
🔶 USAGE
Users can create a variety of strategies using this script, limited only by their imagination.
Long entry : Bullish CHoCH after price is inside a bullish order block
Short entry : Bearish CHoCH after price is inside a bearish order block
Stop-Loss : Trailing Stop set away from price by 0.2%
Example below using external conditions
Long entry : Bullish Liquidity Prints after bullish CHoCH
Short entry : Bearish Liquidity Prints after Bearish CHoCH
Long Exit : RSI Crossing over 70 line
Short Exit : RSI Crossing over 30 line
Stop-Loss : Trailing Stop set away from price by 0.3%
🔶 PROPERTIES
Users will need to adjust the property tabs according to their individual balance to achieve realistic results.
An important aspect to note is that past performance does not guarantee future results. This principle should always be kept in mind.
🔶 HOW TO ACCESS
You can see the Author Instructions to get access.
Octopus Nest Strategy Hello Fellas,
Hereby, I come up with a popular strategy from YouTube called Octopus Nest Strategy. It is a no repaint, lower timeframe scalping strategy utilizing PSAR, EMA and TTM Squeeze.
The strategy considers these market factors:
PSAR -> Trend
EMA -> Trend
TTM Squeeze -> Momentum and Volatility by incorporating Bollinger Bands and Keltner Channels
Note: As you can see there is a potential improvement by incorporating volume.
What's Different Compared To The Original Strategy?
I added an option which allows users to use the Adaptive PSAR of @loxx, which will hopefully improve results sometimes.
Signals
Enter Long -> source above EMA 100, source crosses above PSAR and TTM Squeeze crosses above 0
Enter Short -> source below EMA 100, source crosses below PSAR and TTM Squeeze crosses below 0
Exit Long and Exit Short are triggered from the risk management. Thus, it will just exit on SL or TP.
Risk Management
"High Low Stop Loss" and "Automatic High Low Take Profit" are used here.
High Low Stop Loss: Utilizes the last high for short and the last low for long to calculate the stop loss level. The last high or low gets multiplied by the user-defined multiplicator and if no recent high or low was found it uses the backup multiplier.
Automatic High Low Take Profit: Utilizes the current stop loss level of "High Low Stop Loss" and gets calculated by the user-defined risk ratio.
Now, follows the bunch of knowledge for the more inexperienced readers.
PSAR: Parabolic Stop And Reverse; Developed by J. Welles Wilders and a classic trend reversal indicator.
The indicator works most effectively in trending markets where large price moves allow traders to capture significant gains. When a security’s price is range-bound, the indicator will constantly be reversing, resulting in multiple low-profit or losing trades.
TTM Squeeze: TTM Squeeze is a volatility and momentum indicator introduced by John Carter of Trade the Markets (now Simpler Trading), which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range.
The volatility component of the TTM Squeeze indicator measures price compression using Bollinger Bands and Keltner Channels. If the Bollinger Bands are completely enclosed within the Keltner Channels, that indicates a period of very low volatility. This state is known as the squeeze. When the Bollinger Bands expand and move back outside of the Keltner Channel, the squeeze is said to have “fired”: volatility increases and prices are likely to break out of that tight trading range in one direction or the other. The on/off state of the squeeze is shown with small dots on the zero line of the indicator: red dots indicate the squeeze is on, and green dots indicate the squeeze is off.
EMA: Exponential Moving Average; Like a simple moving average, but with exponential weighting of the input data.
Don't forget to check out the settings and keep it up.
Best regards,
simwai
---
Credits to:
@loxx
@Bjorgum
@Greeny
Crypto MVRV ZScore - Strategy [PresentTrading]█ Introduction and How it is Different
The "Crypto Valuation Extremes: MVRV ZScore - Strategy " represents a cutting-edge approach to cryptocurrency trading, leveraging the Market Value to Realized Value (MVRV) Z-Score. This metric is pivotal for identifying overvalued or undervalued conditions in the crypto market, particularly Bitcoin. It assesses the current market valuation against the realized capitalization, providing insights that are not apparent through conventional analysis.
BTCUSD 6h Long/Short Performance
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█ Strategy, How It Works: Detailed Explanation
The strategy leverages the Market Value to Realized Value (MVRV) Z-Score, specifically designed for cryptocurrencies, with a focus on Bitcoin. This metric is crucial for determining whether Bitcoin is currently undervalued or overvalued compared to its historical 'realized' price. Below is an in-depth explanation of the strategy's components and calculations.
🔶Conceptual Foundation
- Market Capitalization (MC): This represents the total dollar market value of Bitcoin's circulating supply. It is calculated as the current price of Bitcoin multiplied by the number of coins in circulation.
- Realized Capitalization (RC): Unlike MC, which values all coins at the current market price, RC is computed by valuing each coin at the price it was last moved or traded. Essentially, it is a summation of the value of all bitcoins, priced at the time they were last transacted.
- MVRV Ratio: This ratio is derived by dividing the Market Capitalization by the Realized Capitalization (The ratio of MC to RC (MVRV Ratio = MC / RC)). A ratio greater than 1 indicates that the current price is higher than the average price at which all bitcoins were purchased, suggesting potential overvaluation. Conversely, a ratio below 1 suggests undervaluation.
🔶 MVRV Z-Score Calculation
The Z-Score is a statistical measure that indicates the number of standard deviations an element is from the mean. For this strategy, the MVRV Z-Score is calculated as follows:
MVRV Z-Score = (MC - RC) / Standard Deviation of (MC - RC)
This formula quantifies Bitcoin's deviation from its 'normal' valuation range, offering insights into market sentiment and potential price reversals.
🔶 Spread Z-Score for Trading Signals
The strategy refines this approach by calculating a 'spread Z-Score', which adjusts the MVRV Z-Score over a specific period (default: 252 days). This is done to smooth out short-term market volatility and focus on longer-term valuation trends. The spread Z-Score is calculated as follows:
Spread Z-Score = (Market Z-Score - MVVR Ratio - SMA of Spread) / Standard Deviation of Spread
Where:
- SMA of Spread is the simple moving average of the spread over the specified period.
- Spread refers to the difference between the Market Z-Score and the MVRV Ratio.
🔶 Trading Signals
- Long Entry Condition: A long (buy) signal is generated when the spread Z-Score crosses above the long entry threshold, indicating that Bitcoin is potentially undervalued.
- Short Entry Condition: A short (sell) signal is triggered when the spread Z-Score falls below the short entry threshold, suggesting overvaluation.
These conditions are based on the premise that extreme deviations from the mean (as indicated by the Z-Score) are likely to revert to the mean over time, presenting opportunities for strategic entry and exit points.
█ Practical Application
Traders use these signals to make informed decisions about opening or closing positions in the Bitcoin market. By quantifying market valuation extremes, the strategy aims to capitalize on the cyclical nature of price movements, identifying high-probability entry and exit points based on historical valuation norms.
█ Trade Direction
A unique feature of this strategy is its configurable trade direction. Users can specify their preference for engaging in long positions, short positions, or both. This flexibility allows traders to tailor the strategy according to their risk tolerance, market outlook, or trading style, making it adaptable to various market conditions and trader objectives.
█ Usage
To implement this strategy, traders should first adjust the input parameters to align with their trading preferences and risk management practices. These parameters include the trade direction, Z-Score calculation period, and the thresholds for long and short entries. Once configured, the strategy automatically generates trading signals based on the calculated spread Z-Score, providing clear indications for potential entry and exit points.
It is advisable for traders to backtest the strategy under different market conditions to validate its effectiveness and adjust the settings as necessary. Continuous monitoring and adjustment are crucial, as market dynamics evolve over time.
█ Default Settings
- Trade Direction: Both (Allows for both long and short positions)
- Z-Score Calculation Period: 252 days (Approximately one trading year, capturing a comprehensive market cycle)
- Long Entry Threshold: 0.382 (Indicative of moderate undervaluation)
- Short Entry Threshold: -0.382 (Signifies moderate overvaluation)
These default settings are designed to balance sensitivity to market valuation extremes with a pragmatic approach to trade execution. They aim to filter out noise and focus on significant market movements, providing a solid foundation for both new and experienced traders looking to exploit the unique insights offered by the MVRV Z-Score in the cryptocurrency market.
Backtest any Indicator v5Happy Trade,
here you get the opportunity to backtest any of your indicators like a strategy without converting them into a strategy. You can choose to go long or go short and detailed time filters. Further more you can set the take profit and stop loss, initial capital, quantity per trade and set the exchange fees. You get an overall result table and even a detailed, scroll-able table with all trades. In the Image 1 you see the provided info tables about all Trades and the Result Summary. Further more every trade is marked by a background color, Labels and Levels. An opening Label with the trade direction and trade number. A closing Label again with the trade number, the trades profit in % and the total amount of $ after all past trades. A green line for the take profit level and a red line for the stop loss.
Image 1
Example
For this description we choose the Stochastic RSI indicator from TradingView as it is. In Image 2 is shown the performance of it with decent settings.
Timeframe=45, BTCUSD, 2023-08-01 - 2023-10-20
Stoch RSI: k=30, d=40, RSI-length=140, stoch-length=140
Backtest any Indicator: input signal=Stoch RSI, goLong, take profit=9.1%, stop loss=2.5%, start capital=1000$, qty=5%, fee=0.1%, no Session Filter
Image 2
Usage
1) You need to know the name of the boolean (or integer) variable of your indicator which hold the buy condition. Lets say that this boolean variable is called BUY. If this BUY variable is not plotted on the chart you simply add the following code line at the end of your pine script.
For boolean (true/false) BUY variables use this:
plot(BUY ? 1:0,'Your buy condition hold in that variable BUY',display = display.data_window)
And in case your script's BUY variable is an integer or float then use instate the following code line:
plot(BUY ,'Your buy condition hold in that variable BUY',display = display.data_window)
2) Probably the name of this BUY variable in your indicator is not BUY. Simply replace in the code line above the BUY with the name of your script's trade condition variable.
3) Save your changed Indicator script.
4) Then add this 'Backtest any Indicator' script to the chart ...
5) and go to the settings of it. Choose under "Settings -> Buy Signal" your Indicator. So in the example above choose .
The form is usually: ' : BUY'. Then you see something like Image 2
6) Decide which trade direction the BUY signal should trigger. A go Long or a go Short by set the hook or not.
Now you have a backtest of your Indicator without converting it into a strategy. You may change the setting of your Indicator to the best results and setup the following strategy settings like Time- and Session Filter, Stop Loss, Take Profit etc. More of it below in the section Settings Menu.
Appereance
In the Image 2 you see on the right side the List of Trades . To scroll down you go into the settings again and decrease the scroll value. So you can see all trades that have happened before. In case there is an open trade you will find it at the last position of the list.
Every Long trade is green back grounded while Short trades are red.
Every trade begins with a label that show goLong or goShort and its number. And ends with another label again with its number, Profit in % and the resulting total amount of cash.
If activated you further see the Take Profit as a green line and the Stop Loss as a orange line. In the settings you can set their percentage above or below the entry price.
You also see the Result Summary below. Here you find the usual stats of a strategy of all closed trades. The profit after total amount of fees , amount of trades, Profit Factor and the total amount of fees .
Settings Menu
In the settings menu you will find the following high-lighted sections. Most of the settings have a question mark on their right side. Move over it with the cursor to read specific explanation.
Input Signal of your Indicator: Under Buy you set the trade signal of your Indicator. And under Target you set the value when a trade should happen. In the Example with the Stochastic RSI above we used 20. Below you can set the trade direction, let it be go short when hooked or go long when unhooked.
Trade Settings & List of Trades: Take Profit set the target price of any trade. Stop Loss set the price to step out when a trade goes the wrong direction. Check mark the List of Trades to see any single trade with their stats. In case that there are more trades as fits in the list you can scroll down the list by decrease the value Scroll .
Time Filter: You can set a Start Time or deactivate it by leave it unhooked. The same with End Time .
Session Filter: here you can choose to activate it on weekly base. Which days of the week should be trading and those without. And also on daily base from which time on and until trade are possible. Outside of all times and sessions there will be no new trades if activated.
Invest Settings: here you can choose the amount of cash to start with. The Quantity percentage define for every trade how much of the cash should be invested and the Fee percentage which have to be payed every trade. Open position and closing position.
Other Announcements
This Backtest script don't use the strategy functions of TradingView. It is programmed as an indicator. All trades get executed at candle closing. This script use the functionality "Indicator-on-Indicator" from TradingView.
Conclusion
So now it is your turn, take your promising indicators and connect it to that Backtest script. With it you get a fast impression of how successful your indicator will trade. You don't have to relay on coders who maybe add cheating code lines. Further more you can check with the Time Filter under which market condition you indicator perform the best or not so well. Also with the Session Filter you can sort out repeating good market conditions for your indicator. Even you can check with the GoShort XOR GoLong check mark the trade signals of you indicator in opposite trade direction with one click. And compare your indicators under the same conditions and get the results just after 2 clicks. Thanks to the in-build fee setting you get an impression how much a 0.1% fee cost you in total.
Cheers
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
Local
█ 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.
---
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.
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.
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.
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.
Local picture
█ 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.
FreedX Backtest█ Our strategy template empowers TradingView users to effortlessly backtest any indicator, enhancing their trading strategy's effectiveness. In addition, users can create automated webhook alerts from the template. This document details our template's features and how to utilize them effectively.
█ TRADE DATE SETTINGS
The Trading Date Settings feature in our TradingView script allows you to refine their backtesting parameters by specifying trading dates and hours. This feature enhances the accuracy of the backtest by aligning it with specific time frames and days, ensuring that the strategy is tested under relevant market conditions.
Features:
⚙️ Enable Trading Between Specific Dates:
🎯 Purpose:
→ Allows you to limit the backtesting of their strategy to a specific date range.
💡 How to Use:
→ Input the Start Date and End Date for the backtest period.
→ The script will execute the strategy only within this specified date range.
⚙️ Enable Trading Between Specific Hours:
🎯 Purpose:
→ Allows you to limit the backtesting of their strategy to a specific hour range.
💡 How to Use:
→ Input the start and end hour for in Trading Session section.
→ The script will execute the strategy only within this specified hour range.
⚙️ Enable Trading on Specified Days of the Week:
🎯 Purpose:
→ Gives you the option to conduct backtesting on selected days of the week, tailoring the strategy to particular market behaviours that may occur on these days.
💡 How to Use:
→ Select the days of the week for the backtest.
→ The script will activate the trading strategy only on these chosen days.
█ BUY/SELL TRIGGER SETTINGS
The Buy/Sell Trigger Settings feature is designed to provide users with flexibility in defining the conditions for 'LONG' and 'SHORT' signals based on various indicator types. This customization is crucial for tailoring strategies to different trading styles and market conditions.
Features:
⚙️ Single-Line Plotted Indicators :
🎯 Purpose:
→ Enables you to select a single-line plotted indicator as a source for backtesting. You can define specific levels to trigger 'LONG' or 'SHORT' signals.
💡 How to Use:
→ Choose a Single-Line Plotted indicator as the source.
→ Set the top and bottom levels for the indicator.
→ The script triggers 'LONG' signals at the bottom level and 'SHORT' signals at the top level.
⚙️ Two-Line Plotted Indicators :
🎯 Purpose:
→ Allows backtesting with two-line cross plot sources. Signals are generated based on the crossover of these lines.
💡 How to Use:
→ Select two lines as 'Source 1' and 'Source 2' for the indicator.
→ The script triggers a 'LONG' signal when 'Source 1' crosses above 'Source 2'.
→ Conversely, a 'SHORT' signal is triggered when 'Source 2' crosses above 'Source 1'.
⚙️ Custom Signals :
🎯 Purpose:
→ This setting enables users to define their own criteria for LONG, SHORT, and CLOSE signals based on custom indicator outputs.
💡 How to Use:
→ Select the custom source for your signals.
→ Define the output values that correspond to each signal type (e.g., “1” for 'LONG', “-1” for SHORT, and “0” for CLOSE).
→ The script will trigger signals according to these custom-defined values.
█ TP/SL SETTINGS
The TP/SL (Take Profit/Stop Loss) Settings feature is designed to give users control over their profit securing and risk mitigation strategies. This feature allows for setting custom TP and SL levels, which can be critical in managing trades effectively.
Features:
Custom TP/SL Levels for Long/Short Signals:
🎯 Purpose:
→ Enables users to set specific percentage levels for Take Profit and Stop Loss on long and short signals.
💡 How to Use:
→ In the TP/SL Settings, input the desired percentage for Take Profit (TP) and Stop Loss (SL).
→ For example, to secure a profit at a 10% price increase on LONG signals, set the “Long TP Percentage” to “10”.
█ STRATEGY SETTINGS
Strategy Settings provide a range of options to customize the trading strategy. These settings include leverage, drawdown limits, position direction changes, and more, allowing users to tailor their strategy to their risk tolerance and market view.
Features:
⚙️ Enable Leverage :
🎯 Purpose:
→ Allows users to apply leverage to their trades.
☢️ Caution:
→ High leverage can significantly increase the risk of liquidation.
→ High leverage and a high stop-loss price may override your fixed stoploss percentage, adjusting the stop-loss to the liquidation price.
💡 How to Use:
→ Set the desired leverage ratio in the Strategy Settings.
⚙️ Enable Drawdown Limit:
🎯 Purpose:
→ Sets a maximum drawdown limit, automatically halting the strategy if this limit is reached, thereby controlling risk.
💡 How to Use:
→ Input the maximum drawdown limit (default: 100, min: 0, max: 100).
⚙️ Enable Reverse Position:
🎯 Purpose:
→ Automatically closes a current position and opens a new one in the opposite direction upon detecting a signal for a market trend change.
🎯 Example:
→ If a LONG signal is received while in a SHORT position, the script will close the SHORT position and open a LONG position.
💡 How to Use:
→ Activate this feature in the Strategy Settings.
⚙️ Enable Spot Mode:
🎯 Purpose:
→ Disables short orders, using short signals only for closing long positions.
💡 How to Use:
→ Select the 'Spot Mode' option in the Strategy Settings.
⚙️ Enable Invert Signals:
🎯 Purpose:
→ Inverts all indicator signals, changing LONG signals to SHORT and vice versa.
💡 How to Use:
→ Opt for the 'Invert Signals' feature in the Strategy Settings.
⚙️ Enable Trailing Stop:
🎯 Purpose:
→ Triggers a trailing stop order on the exchange instead of a standard stop market order.
☢️ Caution:
→ The backtesting of this feature on TradingView may not accurately reflect actual strategy performance due to discrepancies between TradingView and exchange mechanisms.
💡 How to Use:
→ Select 'Trailing Stop' in the Strategy Settings.
█ ADVANCED STRATEGY SETTINGS
Advanced Strategy Settings offer sophisticated methods for managing Stop Loss (SL) and Take Profit (TP) using the Average True Range (ATR). These settings are ideal for traders who want to incorporate volatility into their exit strategies.
Features:
⚙️ Enable ATR Stop Loss:
🎯 Purpose:
→ Automatically sets the Stop Loss price using the Average True Range at the time of entry.
💡 How to Use:
→ Activate 'ATR Stop Loss' to have the SL price calculated based on the current ATR.
⚙️ Enable ATR Take Profit:
🎯 Purpose:
→ Sets the Take Profit price based on the Average True Range at the time of entry.
💡 How to Use:
→ Choose 'ATR Take Profit' for TP price determination using ATR.
⚙️ Enable ATR Trailing Stop:
🎯 Purpose:
→ Dynamically updates the Stop Loss price with each new bar, according to the Average True Range.
💡 How to Use:
→ Activate 'ATR Trailing Stop'.
→ Set the ATR Period to define the number of bars for ATR calculation.
→ Adjust the ATR SL Multiplier to determine the stop loss distance.
→ Modify the ATR TP Multiplier for setting the take profit distance.
█ TREND FILTERING SETTINGS
Trend Filtering Settings are designed to align trading strategies with the prevailing market trend, enhancing the precision of trade entries and exits. These settings utilize moving averages for trend analysis and decision-making.
Features:
⚙️ Enable Trend Filtering:
🎯 Purpose:
→ Limits trades based on moving average trends, blocking short trades in an uptrend and vice versa.
💡 How to Use:
→ Enable 'Trend Filtering'.
→ Set Fast and Slow MA Lengths for trend analysis.
→ Select the Timeframe for moving averages.
→ Choose the Moving Average Type for trend filtering.
🎯 Note:
→ Be cautious with timeframe selections; lower timeframes than the base may cause inconsistencies.
⚙️ Enable Exit on Trend Reversal:
🎯 Purpose:
→ Automatically closes a position when a market trend reversal is detected.
💡 How to Use:
→ Turn on 'Exit on Trend Reversal' in the settings.
⚙️ Enable Trend Drawing On Chart:
🎯 Purpose:
→ Visually represents the trend filter directly on the chart for easy reference.
💡 How to Use:
→ Activate 'Trend Drawing On Chart' to see the trend filter overlaid on the trading chart.
█ AUTOMATED ALERT SETTINGS
Automated Alert Settings are designed to integrate your TradingView script with webhook alerts. These settings allow for enhanced strategy execution and management.
Features:
Enable Webhook Alerts:
🎯 Purpose:
→ Trigger BUY, SELL, CHANGE_DIRECTION or MOVE_STOP_LOSS .
💡 How to Use:
→ Enable 'Webhook Alerts' in the settings.
→ Enter your Strategy ID.
→ Optionally, activate 'Override Allocation Percentage' to bypass the preset allocation percentage.
☢️ Caution:
→ Overriding the allocation percentage may result in trade entry errors due to misalignment between entry cost and available balance.
█ DEBUGGING SETTINGS
Debugging Settings are crucial for users who want to analyze and optimize their strategies. These settings provide tools for visualizing alerts on charts and accessing detailed data outputs.
Features:
⚙️ Enable Alert Plotting:
🎯 Purpose:
→ Allows users to visualize trading alerts directly on the chart, aiding in strategy analysis and refinement.
💡 How to Use:
→ Activate 'Alert Plotting' to draw alerts on the chart.
☢️ Caution:
→ It is recommended to disable this feature when creating actual trading alerts, as it can cause latency in signal processing.
⚙️ Enable Debugger Mode:
🎯 Purpose:
→ Facilitates strategy debugging by providing detailed data output in the TradingView Data Window.
💡 How to Use:
→ Turn on 'Debugger Mode' to access real-time data and metrics relevant to your strategy.
█ ADDITIONAL SETTINGS
⚙️ Enable Bar Magnifier
⚙️ Enable Using standard OHLC
FlexiSuperTrend - Strategy [presentTrading]█ Introduction and How it is Different
The "FlexiSuperTrend - Strategy" by PresentTrading is a cutting-edge trading strategy that redefines market analysis through the integration of the SuperTrend indicator and advanced variance tracking.
BTC 6H L/S
This strategy stands apart from conventional methods by its dynamic adaptability, capturing market trends and momentum shifts with increased sensitivity. It's designed for traders seeking a more responsive tool to navigate complex market movements.
Local
█ Strategy, How It Works: Detailed Explanation
The "FlexiSuperTrend - Strategy" employs a multifaceted approach, combining the adaptability of the SuperTrend indicator with variance tracking. The strategy's core lies in its unique formulation and application of these components:
🔶 SuperTrend Polyfactor Oscillator:
- Basic Concept: The oscillator is a series of SuperTrend calculations with varying ATR lengths and multipliers. This approach provides a broader and more nuanced perspective of market trends.
- Calculation:
- For each iteration, `i`, the SuperTrend is calculated using:
- `ATR Length = indicatorLength * (startingFactor + i * incrementFactor)`.
- `Multiplier = dynamically adjusted based on market conditions`.
- The SuperTrend output for each iteration is compared with the indicator source (like hlc3), and the deviation is recorded.
SuperTrend Calculation:
- `Upper Band (UB) = hl2 + (ATR Length * Multiplier)`
- `Lower Band (LB) = hl2 - (ATR Length * Multiplier)`
- Where `hl2` is the average of high and low prices.
Deviation Calculation:
- `Deviation = indicatorSource - SuperTrend Value`
- This value is calculated for each SuperTrend setting in the oscillator series.
🔶 Indicator Source (`hlc3`):
- **Usage:** The strategy uses the average of high, low, and close prices, providing a balanced representation of market activity.
🔶 Adaptive ATR Lengths and Factors:
- Dynamic Adjustment: The strategy adjusts the ATR length and multiplier based on the `startingFactor` and `incrementFactor`. This adaptability is key in responding to changing market volatilities.
- Equation: ATR Length at each iteration `i` is given by `len = indicatorLength * (startingFactor + i * incrementFactor)`.
incrementFactor - 1
incrementFactor - 2
🔶 Normalization Methods:
Purpose: To standardize the deviations for comparability.
- Methods:
- 'Max-Min': Scales the deviation based on the range of values.
- 'Absolute Sum': Uses the sum of absolute deviations for normalization.
Normalization 'Absolute Sum'
- For 'Max-Min': `Normalized Deviation = (Deviation - Min(Deviations)) / (Max(Deviations) - Min(Deviations))`
- For 'Absolute Sum': `Normalized Deviation = Deviation / Sum(Absolute(Deviations))`
🔶 Trading Logic:
The strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends. * The SuperTrend Toolkit is made by @QuantiLuxe
- Long Entry Conditions: A buy signal is generated when the current trend, as indicated by the SuperTrend Polyfactor Oscillator, turns positive.
- Short Entry Conditions: A sell signal is triggered when the current trend turns negative.
- Entry and Exit Strategy: The strategy opens or closes positions based on these signals, aligning with the selected trade direction (long, short, or both).
█ 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.
█ Usage
The FlexiSuperTrend strategy is suitable for various market conditions and can be adapted to different asset classes and time frames. Traders should set the strategy parameters according to their risk tolerance and trading goals. It's particularly useful for capturing long-term movements, ideal for swing traders, yet adaptable for short-term trading strategies.
█ Default Settings
1. Trading Direction: Choose from "Long", "Short", or "Both" to define the trade type.
2. Indicator Source (HLC3): Utilizes the HLC3 as the primary price reference.
3. Indicator Length (Default: 10): Influences the moving average calculation and trend sensitivity.
4. Starting Factor (0.618): Initiates the ATR length, influenced by Fibonacci ratios.
5. Increment Factor (0.382): Adjusts the ATR length incrementally for dynamic trend tracking.
6. Normalization Method: Options include "None", "Max-Min", and "Absolute Sum" for scaling deviations.
7. SuperTrend Settings: Varied ATR lengths and multipliers tailor the indicator's responsiveness.
8. Additional Settings: Features mesh style plotting and customizable colors for visual distinction.
The default settings provide a balanced approach, but users are encouraged to adjust them based on their individual trading style and market analysis.
Ehlers Combo Strategy🚀 Presenting the Enhanced Ehlers Combo Strategy 🚀
Hello Traders! 👋 I'm thrilled to share the latest version of the Ehlers Combo Strategy v2.0. This powerful algorithm combines Ehlers Elegant Oscillator, Decycler, Instantaneous Trendline, Spearman Rank, and introduces the Signal to Noise Ratio for even more precise trading signals.
📊 Strategy Highlights:
Ehlers Elegant Oscillator: Captures market momentum and turning points.
Ehlers Decycler: Filters out market noise for clearer trend signals.
Instantaneous Trendline: Offers a dynamic view of the market trend.
Spearman Rank: Analyzes market rank correlations for enhanced insights.
Signal to Noise Ratio (SNR): Filters out noise for more accurate signals.
💡 Key Features & Customizations:
Adaptive Length: Enable adaptive length based on the market's current conditions.
SNR Threshold: Set your desired SNR threshold for filtering signals.
Exit Length: Define the length for exit signals.
📈 Trading Signals:
Long Entry: Elegant Oscillator and Decycler cross above 0, source crosses above Decycler, source is greater than an increasing Instantaneous Trendline, Spearman Rank is positive, and SNR exceeds the threshold.
Long Exit: Source crosses below the Instantaneous Trendline after entering a long position.
Short Entry: Elegant Oscillator and Decycler cross below 0, source crosses below Decycler, source is less than a decreasing Instantaneous Trendline, Spearman Rank is negative, and SNR exceeds the threshold.
Short Exit: Source crosses above the Instantaneous Trendline after entering a short position.
📊 Insights & Enhancements:
Dynamic Length: The strategy adapts its length dynamically based on market conditions.
Improved SNR: Signal to Noise Ratio ensures better filtering of signals.
Enhanced Visualization: The Elegant Oscillator now features improved color coding for a clearer interpretation.
🚨 Disclaimer:
Trading involves risk, and this script should be used judiciously. It's not a guaranteed profit machine, but with careful use, it can be a valuable addition to your toolkit.
Feel free to backtest, tweak, and make it your own! Let's conquer the markets together! 💪📈
🚀✨ Happy Trading! ✨🚀
---
🙌 Credits:
A big shoutout to the original contributors:
@blackcat1402
@cheatcountry
@DasanC
FlexiMA Variance Tracker - Strategy [presentTrading]█ Introduction and How It Is Different
The FlexiMA Variance Tracker by PresentTrading introduces a novel approach to technical trading strategies. Unlike traditional methods, it calculates deviations between a chosen indicator source (such as price or average) and a moving average with a variable length. This flexibility is achieved through a unique combination of a starting factor and an increment factor, allowing the moving average to adapt dynamically within a specified range. This strategy provides a more responsive and nuanced view of market trends, setting it apart from standard trading methodologies.
BTC 8h L/S
Local
█ Strategy, How It Works: Detailed Explanation
The FlexiMA Variance Tracker, developed by PresentTrading, stands at the forefront of trading strategies, distinguished by its adaptive and multifaceted approach to market analysis. This strategy intricately weaves various technical elements to construct a comprehensive trading logic. Here's an in-depth professional breakdown:
🔶Foundation on Variable-Length Moving Averages:
Central to this strategy is the concept of variable-length Moving Averages (MAs). Unlike traditional MAs with a fixed period, this strategy dynamically adjusts the length of the MA based on a starting factor and an incremental factor. This approach allows the strategy to adapt to market volatility and trend strength more effectively.
Each MA iteration offers a distinct temporal perspective, capturing short-term price movements to long-term trends. This aggregation of various time frames provides a richer and more nuanced market analysis, essential for making informed trading decisions.
🔶Deviation Analysis and Normalization:
The strategy calculates deviations of the price (or the chosen indicator source) from each of these MAs. These deviations are pivotal in identifying the immediate market direction relative to the average trend captured by each MA.
To standardize these deviations for comparability, they undergo a normalization process. The choice of normalization method (Max-Min or Absolute Sum) can significantly influence the interpretation of market conditions, offering distinct insights into price movements and trend strength.
🔹Normalization: Absolute Sum
🔶Composite Oscillator Construction:
A composite oscillator is derived from the median of these normalized deviations. The median serves as a balanced and robust central trend indicator, minimizing the impact of outliers and market noise.
Additionally, the standard deviation of these deviations is computed, providing a measure of market volatility. This volatility indicator is crucial for assessing market risk and can guide traders in setting appropriate stop-loss and take-profit levels.
🔶Integration with SuperTrend Indicator:
The FlexiMA strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends.
* The SuperTrend Toolkit is made by @QuantiLuxe
This combination of the variable-length MA oscillator with the SuperTrend indicator forms a potent duo, offering traders a dual-confirmation mechanism for trade signals.
🔹Supertrend's incorporation
🔶Strategic Trade Signal Generation:
Trade signals are generated when there is a confluence between the composite oscillator and the SuperTrend indicator. For example, a long position signal might be considered when the oscillator suggests an uptrend, and the SuperTrend flips to bullish.
The strategy's parameters are fully customizable, enabling traders to tailor the signal generation process to their specific trading style, risk tolerance, and market conditions.
█ Usage
To effectively employ the FlexiMA Variance Tracker strategy:
Traders should set their desired trade direction and fine-tune the starting and increment factors according to their market analysis and risk tolerance.
Indicator Length: 5
Indicator Length: 40
The strategy is suitable for a wide range of markets and can be adapted to different time frames, making it a versatile tool for various trading scenarios.
█ Default Settings Impact on Performance: FlexiMA Variance Tracker
1. Trade Direction (Configurable: Long, Short, Both): Determines trade types. 'Long' for buying, 'Short' for selling, 'Both' adapts to market trends.
2. Indicator Source: HLC3: Balances market sentiment by considering high, low, and close, providing comprehensive period analysis.
4. Indicator Length (Default: 10): Baseline for moving averages. Shorter lengths increase responsiveness but add noise, while longer lengths favor trends.
5. Starting and Increment Factor (Default: 1.0): Adjusts MA lengths range. Higher values capture broad market dynamics, lower values focus analysis.
6. Normalization Method (Options: None, Max-Min, Absolute Sum): Standardizes deviations. 'None' for raw deviations, 'Max-Min' for relative scaling, 'Absolute Sum' emphasizes relative strength.
7. SuperTrend Settings (ATR Length: 10, Multiplier: 15.0): Influences indicator sensitivity. Short ATR or high multiplier for short-term, long ATR or low multiplier for long-term trends.
8. Additional Settings (Mesh Style, Color Customization): Enhances visual clarity. Mesh style for detailed deviation view, colors for quick market condition identification.
Elliott's Quadratic Momentum - Strategy [presentTrading]█ Introduction and How It Is Different
The "Elliott's Quadratic Momentum - Strategy" is a unique and innovative approach in the realm of technical trading. This strategy is a fusion of multiple SuperTrend indicators combined with an Elliott Wave-like pattern analysis, offering a comprehensive and dynamic trading tool. It stands apart from conventional strategies by incorporating multiple layers of trend analysis, thereby providing a more robust and nuanced view of market movements.
*Although the script doesn't explicitly analyze Elliott Wave patterns, it employs a wave-like approach by considering multiple SuperTrend indicators. Elliott Wave theory is based on the premise that markets move in predictable wave patterns. While this script doesn't identify specific Elliott Wave structures like impulsive and corrective waves, the sequential checking of trend conditions across multiple SuperTrend indicators mimics a wave-like progression.
BTC 8hr Long/Short Performance
Local Detail
█ Strategy, How It Works: Detailed Explanation
The core of this strategy lies in its multi-tiered approach:
1. Multiple SuperTrend Indicators:
The strategy employs four different SuperTrend indicators, each with unique ATR lengths and multipliers. These indicators offer various perspectives on market trends, ranging from short to long-term views.
By analyzing the convergence of these indicators, the strategy can pinpoint robust entry signals for both long and short positions.
2. Elliott Wave-like Pattern Recognition:
While not directly applying Elliott Wave theory, the strategy takes inspiration from its pattern recognition approach. It looks for alignments in market movements that resemble the characteristic waves of Elliott's theory.
This pattern recognition aids in confirming the signals provided by the SuperTrend indicators, adding an extra layer of validation to the trading signals.
3. Comprehensive Market Analysis:
By combining multiple indicators and pattern analysis, the strategy offers a holistic view of the market. This allows for capturing potential trend reversals and significant market moves early.
█ Trade Direction
The strategy is designed with flexibility in mind, allowing traders to select their preferred trading direction – Long, Short, or Both. This adaptability is key for traders looking to tailor their approach to different market conditions or personal trading styles. The strategy automatically adjusts its logic based on the chosen direction, ensuring that traders are always aligned with their strategic objectives.
█ Usage
To utilize the "Elliott's Quadratic Momentum - Strategy" effectively:
Traders should first determine their trading direction and adjust the SuperTrend settings according to their market analysis and risk appetite.
The strategy is versatile and can be applied across various time frames and asset classes, making it suitable for a wide range of trading scenarios.
It's particularly effective in trending markets, where the alignment of multiple SuperTrend indicators can provide strong trade signals.
█ Default Settings
Trading Direction: Configurable (Long, Short, Both)
SuperTrend Settings:
SuperTrend 1: ATR Length 7, Multiplier 4.0
SuperTrend 2: ATR Length 14, Multiplier 3.618
SuperTrend 3: ATR Length 21, Multiplier 3.5
SuperTrend 4: ATR Length 28, Multiplier 3.382
Additional Settings: Gradient effect for trend visualization, customizable color schemes for upward and downward trends.
Backtesting ModuleDo you often find yourself creating new 'strategy()' scripts for each trading system? Are you unable to focus on generating new systems due to fatigue and time loss incurred in the process? Here's a potential solution: the 'Backtesting Module' :)
INTRODUCTION
Every trading system is based on four basic conditions: long entry, long exit, short entry and short exit (which are typically defined as boolean series in Pine Script).
If you can define the conditions generated by your trading system as a series of integers, it becomes possible to use these variables in different scripts in efficient ways. (Pine Script is a convenient language that allows you to use the integer output of one indicator as a source in another.)
The 'Backtesting Module' is a dynamic strategy script designed to adapt to your signals. It boasts two notable features:
⮞ It produces a backtest report using the entry and exit variables you define.
⮞ It not only serves for system testing but also to combine independent signals into a single system. (This functionality enables to create complex strategies and report on their success!)
The module tests Golden and Death cross signals by default, when you enter your own conditions the default signals will be neutralized. The methodology is described below.
PREPARATION
There are three simple steps to connect your own indicator to the Module.
STEP 1
Firstly, you must define entry and exit variables in your own script. Let's elucidate it with a straightforward example. Consider a system generating long and short signals based on the intersections of two moving averages. Consequently, our conditions would be as follows:
// Signals
long = ta.crossover(ta.sma(close, 14), ta.sma(close, 28))
short = ta.crossunder(ta.sma(close, 14), ta.sma(close, 28))
Now, the question is: How can we convert boolean variables into integer variables? The answer is conditional ternary block, defined as follows:
// Entry & Exit
long_entry = long ? 1 : 0
long_exit = short ? 1 : 0
short_entry = short ? 1 : 0
short_exit = long ? 1 : 0
The mechanics of the Entry & Exit variables are simple. The variable takes on a value of 1 when your trading system generates the signal and if your system does not produce any signal, variable returns 0. In this example, you see how exit signals can be generated in a trading system that only contains entry signals. If you have a system with original exit signals, you can also use them directly. (Please mind the NOTES section below).
STEP 2
To utilize the Entry & Exit variables as source in another script, they must be plotted on the chart. Therefore, the final detail to include in the script containing your trading system would be as follows:
// Plot The Output
plot(long_entry, "Long Entry", display=display.data_window, editable=false)
plot(long_exit, "Long Exit", display=display.data_window, editable=false)
plot(short_entry, "Short Entry", display=display.data_window, editable=false)
plot(short_exit, "Short Exit", display=display.data_window, editable=false)
STEP 3
Now, we are ready to test the system! Load the Backtesting Module indicator onto the chart along with your trading system/indicator. Then set the outputs of your system (Long Entry, Long Exit, Short Entry, Short Exit) as source in the module. That's it.
FEATURES & ORIGINALITY
⮞ Primarily, this script has been created to provide you with an easy and practical method when testing your trading system.
⮞ I thought it might be nice to visualize a few useful results. The Backtesting Module provides insights into the outcomes of both long and short trades by computing the number of trades and the success percentage.
⮞ Through the 'Trade' parameter, users can specify the market direction in which the indicator is permitted to initiate positions.
⮞ Users have the flexibility to define the date range for the test.
⮞ There are optional features allowing users to plot entry prices on the chart and customize bar colors.
⮞ The report and the test date range are presented in a table on the chart screen. The entry price can be monitored in the data window.
⮞ Note that results are based on realized returns, and the open trade is not included in the displayed results. (The only exception is the 'Unrealized PNL' result in the table.)
STRATEGY SETTINGS
The default parameters are as follows:
⮞ Initial Balance : 10000 (in units of currency)
⮞ Quantity : 10% of equity
⮞ Commission : 0.04%
⮞ Slippage : 0
⮞ Dataset : All bars in the chart
For a realistic backtest result, you should size trades to only risk sustainable amounts of equity. Do not risk more than 5-10% on a trade. And ALWAYS configure your commission and slippage parameters according to pessimistic scenarios!
NOTES
⮞ This script is intended solely for development purposes. And it'll will be available for all the indicators I publish.
⮞ In this version of the module, all order types are designed as market orders. The exit size is the sum of the entry size.
⮞ As your trading conditions grow more intricate, you might need to define the outputs of your system in alternative ways. The method outlined in this description is tailored for straightforward signal structures.
⮞ Additionally, depending on the structure of your trading system, the backtest module may require further development. This encompasses stop-loss, take-profit, specific exit orders, quantity, margin and risk management calculations. I am considering releasing improvements that consider these options in future versions.
⮞ An example of how complex trading signals can be generated is the OTT Collection. If you're interested in seeing how the signals are constructed, you can use the link below.
THANKS
Special thanks to PineCoders for their valuable moderation efforts.
I hope this will be a useful example for the TradingView community...
DISCLAIMER
This is just an indicator, nothing more. It is provided for informational and educational purposes exclusively. The utilization of this script does not constitute professional or financial advice. The user solely bears the responsibility for risks associated with script usage. Do not forget to manage your risk. And trade as safely as possible. Best of luck!
Trading Strategy - Follow The Plan"Trading Strategy - Follow The Plan" is a TradingView indicator specifically crafted for traders dedicated to adhering to a structured approach. It emphasizes the elimination of emotional decision-making by providing clear, actionable steps. This tool allows you to articulate and visually embed your trading strategy directly onto your charts, encompassing your entry plan, exit plan, and any additional notes crucial for maintaining focus and discipline. It's designed to aid in sustaining consistency in your trading executions, ensuring that you remain steadfastly aligned with your predetermined trading methodology.
Features
1. Entry Plan: Allows traders to outline specific criteria for market entry. This could include conditions like divergences on multiple timeframes, specific pattern recognitions, or other entry triggers. The flexibility of this section caters to various trading styles and strategies.
2. Exit Plan: Dedicated to defining exit strategies, this section can include details on profit targets, stop-loss levels, or conditions for position reversal. It serves as a constant reminder of exit strategies during active trades.
3. Notes: A customizable space for traders to jot down essential rules, observations, or reminders. This section is particularly useful for reinforcing risk management practices and maintaining focus on broader trading goals.
4. Visibility Controls: Each section of the trading plan (Entry Plan, Exit Plan, Notes) can be toggled on or off, allowing traders to manage on-screen information and reduce chart clutter.
5. Layout Customization: Users can choose the placement of the trading plan on their chart, with options including Top Right, Top Left, Bottom Right, and Bottom Left. This caters to individual preferences and screen setups.
6. Appearance Customization: The indicator allows for adjustments in text and background colors, and text sizes for titles and content, enhancing readability and personal preference alignment.
OKX Signal BOT - Strategy Scanner & Orderer
Hello traders,
With the OKX Signal BOT - Strategy Scanner & Orderer, you can now design your own strategy, scan over 20 cryptocurrencies, and send orders for futures trades on the OKX exchange.
How to Use:
🌐 First, log into your account on the OKX exchange and create a signal bot.
📝 While creating the signal bot, note down the webhook URL and signal token variables given to you; they'll be needed later.
🔍 Select the trading pairs that the bot will work on.
📈 Add this indicator to your chart.
⚙️ Adjust the values of the indicators you will use in your strategy.
📊 Set your entry conditions and indicator setups according to your preference.
🚀 Decide which condition will generate a LONG signal and which will generate a SHORT signal.
🔗 Then, link these conditions with either an AND or OR connector.
🛠️ This also serves as a strategy designer.
🆔 Paste the signal token value you got from OKX into the OKX Signal ID section in the indicator.
➕ Add the cryptocurrency pairs you added to the bot on OKX to this design tool as well.
💾 Save and exit.
🚨 Set an alarm and paste the webhook URL link you got from OKX.
Congratulations, you can now send signals from Tradingview to the OKX exchange without needing any other platform.
Warnings:
⚠️ Works only for futures trades.
📈 Make your leverage settings through the exchange.
🛑 It is recommended to set take profit and stop loss through the exchange.
🚫 If too many alarms are triggered, Tradingview may stop your alarms.
💡 Ensure that the coins you add in the symbol section are from the OKX exchange.
🔍 For futures trades, make sure the symbols end with ".P".
🎉 Enjoy using it!
RMI Trend Sync - Strategy [presentTrading]█ Introduction and How It Is Different
The "RMI Trend Sync - Strategy " combines the strength of the Relative Momentum Index (RMI) with the dynamic nature of the Supertrend indicator. This strategy diverges from traditional methodologies by incorporating a dual analytical framework, leveraging both momentum and trend indicators to offer a more holistic market perspective. The integration of the RMI provides an enhanced understanding of market momentum, while the Super Trend indicator offers clear insights into the end of market trends, making this strategy particularly effective in diverse market conditions.
BTC 4h long/short performance
█ Strategy: How It Works - Detailed Explanation
- Understanding the Relative Momentum Index (RMI)
The Relative Momentum Index (RMI) is an adaptation of the traditional Relative Strength Index (RSI), designed to measure the momentum of price movements over a specified period. While RSI focuses on the speed and change of price movements, RMI incorporates the direction and magnitude of those movements, offering a more nuanced view of market momentum.
- Principle of RMI
Calculation Method: RMI is calculated by first determining the average gain and average loss over a given period (Length). It differs from RSI in that it uses the price change (close-to-close) rather than absolute gains or losses. The average gain is divided by the average loss, and this ratio is then normalized to fit within a 0-100 scale.
- Momentum Analysis in the Strategy
Thresholds for Decision Making: The strategy uses predetermined thresholds (pmom for positive momentum and nmom for negative momentum) to trigger trading decisions. When RMI crosses above the positive threshold and other conditions align (e.g., a bullish trend), it signals a potential long entry. Similarly, crossing below the negative threshold in a bearish trend may trigger a short entry.
- Super Trend and Trend Analysis
The Super Trend indicator is calculated based on a higher time frame, providing a broader view of the market trend. This indicator uses the Average True Range (ATR) to adapt to market volatility, making it an effective tool for identifying trend reversals.
The strategy employs a Volume Weighted Moving Average (VWMA) alongside the Super Trend, enhancing its capability to identify significant trend shifts.
ETH 4hr long/short performance
█ Trade Direction
The strategy offers flexibility in selecting the trading direction: long, short, or both. This versatility allows traders to adapt to their market outlook and risk tolerance, whether looking to capitalize on bullish trends, bearish trends, or a combination of both.
█ Usage
To effectively use the "RMI Trend Sync" strategy, traders should first set their preferred trading direction and adjust the RMI and Super Trend parameters according to their risk appetite and trading goals.
The strategy is designed to adapt to various market conditions, making it suitable for different asset classes and time frames.
█ Default Settings
RMI Settings: Length: 21, Positive Momentum Threshold: 70, Negative Momentum Threshold: 30
Super Trend Settings: Length: 10, Higher Time Frame: 480 minutes, Super Trend Factor: 3.5, MA Source: WMA
Visual Settings: Display Range MA: True, Bullish Color: #00bcd4, Bearish Color: #ff5252
Additional Settings: Band Length: 30, RWMA Length: 20
