HK Percentile Interpolation One
This script is designed to execute a trading strategy based on Heikin Ashi candlesticks, moving averages, and percentile levels.
Please note that you should keep your original chart in normal candlestick mode and not switch it to Heikin Ashi mode. The script itself calculates Heikin Ashi values from regular candlesticks. If your chart is already in Heikin Ashi mode, the script would be calculating Heikin Ashi values based on Heikin Ashi values, which would produce incorrect results.
The strategy begins trading from a start date that you can specify by modifying the `startDate` parameter. The format of the date is "YYYY MM DD". So, for example, to start the strategy from January 1, 2022, you would set `startDate = timestamp("2022 01 01")`.
The script uses Heikin Ashi candlesticks, which are plotted in the chart. This approach can be useful for spotting trends and reversals more easily than with regular candlestick charts. This is particularly useful when backtesting in TradingView's "Rewind" mode, as you can see how the Heikin Ashi candles behaved at each step of the strategy.
Buy and sell signals are generated based on two factors:
1. The crossing over or under of the Heikin Ashi close price and the 75th percentile price level.
2. The Heikin Ashi close price being above certain moving averages.
You have the flexibility to adjust several parameters in the script, including:
1. The stop loss and trailing stop percentages (`stopLossPercentage` and `trailStopPercentage`). These parameters allow the strategy to exit trades if the price moves against you by a certain percentage.
2. The lookback period (`lookback`) used to calculate percentile levels. This determines the range of past bars used in the percentile calculation.
3. The lengths of the two moving averages (`yellowLine_length` and `purplLine_length`). These determine how sensitive the moving averages are to recent price changes.
4. The minimum holding period (`holdPeriod`). This sets the minimum number of bars that a trade must be kept open before it can be closed.
Please adjust these parameters according to your trading preferences and risk tolerance. Happy trading!
Médias Móveis
Moving Average Crossover Strategymoving average crossover startegy 10*30
it indicates when to buy or sell
Premium Smart Exit HMA [ByteBoost]The Premium Smart Exit HMA strategy is designed for fast-paced trend detection and is well-suited for small trades in highly volatile markets. It utilizes the Hull Moving Average (HMA) as a signal to execute trades and offers customizable inputs for price calculation, period settings, and stop loss/take profit levels. The strategy aims to reduce lag associated with traditional moving averages, allowing it to catch trends quickly.
Development Notes
This Strategy was developed with the PineScript language, version 5. The aim of the strategy is to provide a trading system that catches fast trend reversals and uses a modified version of the Hull Moving Average. The HMA adeptly adapts to swift variations in price movements while offering better smoothing and utilizes a user selected moving averages, mitigating the smoothing effect and is controlled with a custom weight design.
Features
Customizable trading periods.
Customizable stop loss and take profit levels.
Adjustable date range for backtesting.
Allows setting of initial capital, commission type and value.
Provides visual aids for better understanding of the market trends.
Customize the visuals of the strategy.
Strategy Description
The Smart Exit HMA strategy offers the flexibility to use various types of moving averages, allowing customization of inputs for price calculation, period settings, and stop loss/take profit levels. The strategy relies on the Hull Moving Average (HMA) as a signal to execute trades. However, you have control over the signal frequency by selecting your preferred period value, which determines the number of candles used in the average calculation. This allows you to adapt the strategy to market tendencies and increase its effectiveness during clear trends.
The Smart Exit HMA strategy is designed to minimize lag associated with traditional moving averages, enabling it to respond more quickly to recent price movements based on your chosen period. It's worth noting that the strategy plots two lines on the graph: the average line and the square root line. Buy and sell signals are generated when both lines intersect, indicating favorable trading opportunities.
Inputs/Settings
Capital - If using any leverage multiply the amount of money to invest by the leverage, else input the amount to be invested in every trade.
Start date - The date from which the strategy should begin its analysis. Leave unchanged to start from the earliest available date based on your account's plan.
End date - The date until which the strategy should conduct its analysis. Leave unchanged to continue until the current date.
Period - The lookback period for the moving average calculation, a longer period will translate into fewer trades that last longer.
Stop loss - Allows the use of a stop loss for all trades.
Take profit - Activates the use of a take profit for all trades.
Stop loss value - The distance from the entry price at which the strategy should exit to prevent further losses.
Take profit value - The distance from the entry price at which the strategy should exit to secure profits.
Take profit % - The percentage of the capital to take as profit.
Stop loss % - The percentage of the capital to set as the maximum loss.
Candles exit - The minimum number of candles before the strategy is allowed to close a trade.
Candles change - The minimum number of candles before the strategy is allowed to change the current trend.
Moving average type - Determines the preprocessing method applied prior to utilizing the HMA.
Custom weight - Enables the utilization of a personalized weighting system for the HMA. If chosen, ensure that the sum of all weights equals 1.
Open weight - Determines the weight assigned to the candle's open value.
Close weight - Specifies the weight assigned to the candle's close value.
High weight - Sets the weight attributed to the candle's high value.
Low weight - Determines the weight assigned to the candle's low value.
Highlighter - Light coloring between the trend and average price of each bar.
Signal labels - View the labels indicating a new long or short position.
Exit labels - Displays the labels indicating exit points.
Color long - Sets the color scheme for a new long position.
Color short - Sets the color scheme for a new short position.
Color exit - Decides the color scheme for the exit tag and cross shown.
Indicator Visuals
The strategy plots the two trendlines on the chart and changes its color based on its direction. It also plots shapes on the chart to denote potential buy (Long) and sell (Short) points where the signals of short and long will appear, as well as crosses for the exit points.
Strategy Alerts
The strategy does not include built-in alerts. However, alerts can be added using the TradingView interface based on the strategy's buy, sell and exit conditions. This way you will be able to receive notifications on your computer or phone when a new signal goes out.
Details
Repainting: It is important to mention that the strategy can mark an uptrend signal during a candle and disappear at the end of it, so please just put long or short when the buy/sell conditions are followed and marked by the strategy at the end of each candle.
Conclusion
The Premium Smart Exit HMA is a versatile strategy that combines the benefits of the Hull Moving Average with adjustable parameters to suit individual trading styles. It offers a combination of speed and smoothness, which can be beneficial in volatile markets.
Disclaimer
This strategy is provided as-is, with no guarantee of profits or responsibility for losses. Trading involves risk, and you should only trade with money you can afford to lose. Always conduct your own research and consider your financial situation before engaging in trading.
Equity Curve Trading with EMAWhat Is Equity Curve Trading?
In equity curve trading, traders apply a moving average to the curve. The idea is when the equity curve drops below the moving average, the strategy is put on hold. This is done to stop losses when either the hopes of the plan working start dimming or when the trader knows he cannot afford more losses on a strategy. The trader can resume trading this particular strategy when the equity curve is above the moving average.
Equity Curve Trading puts an investor at the ease of knowing that his investment is covered even when he is not actively tracking his strategy. When the equity curve dips below a level investor is comfortable with, it can be paused until such time that the equity curve is back above the determined moving average.
Example:
Equity Curve Trading Example
Trading Strategy
I choosed the SuperTrend strategy for BTCUSDT on 4 hour time frame. That shows nice equity curve with default settings. Let's find out and check can we improve the equity curve with this modern money management trade method?
Some shift is exist in original equity curve relatively to filtered equity curve, because of array usage, but it is not affected on calculations.
Conclusion
I tested a different time frames, settings and equity curves shapes, but it not gives advantages in equity curve. You can look at the table on the top right corner of the strategy with equity curve and you will see some statistic information for the original strategy and for the modified equity curve trade strategy. In most cases we have lower Win Rate and lower Net Profit after turning on Equity curve trading method. In some cases this can be help if you have the equity curve looks like at the picture above, but this equity curve is really bad for choosing this strategy to trade. I found that EMA works better than SMA, and RMA works better then EMA applied to Equity Curve. You can test your strategy with this trade method if you want, I make the source code opened for it. Please share your results, I hope it will helps.
Conclusion 2
Equity Curve Trading definitely has its proponents in the industry, some of them quite vocal. But, the overall efficacy of the approach is certainly not crystal clear. In fact, what is clear is that it is relatively easy to take a good strategy, and significantly degrade its performance by employing equity curve trading. While the overall objective of equity curve trading is unquestionable – cease trading poor performing strategies - it is probable that there are better ways of accomplishing that goal. From this study, the conclusion is equity curve trading with simple indicators has more downside than upside.
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
Mean Reversion and TrendfollowingTitle: Mean Reversion and Trendfollowing
Introduction:
This script presents a hybrid trading strategy that combines mean reversion and trend following techniques. The strategy aims to capitalize on short-term price corrections during a downtrend (mean reversion) as well as ride the momentum of a trending market (trend following). It uses a 200-period Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI) to generate buy and sell signals.
Key Features:
Combines mean reversion and trend following techniques
Utilizes 200-period SMA and 2-period RSI
Customizable starting date
Allows for enabling/disabling mean reversion or trend following modes
Adjustable position sizing for trend following and mean reversion
Script Description:
The script implements a trading strategy that combines mean reversion and trend following techniques. Users can enable or disable either of these techniques through the input options. The strategy uses a 200-period Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI) to generate buy and sell signals.
The mean reversion mode is active when the price is below the SMA200, while the trend following mode is active when the price is above the SMA200. The script generates buy signals when the RSI is below 20 (oversold) in mean reversion mode or when the price is above the SMA200 in trend following mode. The script generates sell signals when the RSI is above 80 (overbought) in mean reversion mode or when the price falls below 95% of the SMA200 in trend following mode.
Users can adjust the position sizing for both trend following and mean reversion modes using the input options.
To use this script on TradingView, follow these steps:
Open TradingView and load your preferred chart.
Click on the 'Pine Editor' tab located at the bottom of the screen.
Paste the provided script into the Pine Editor.
Click 'Add to Chart' to apply the strategy to your chart.
Please note that the past performance of any trading system or methodology is not necessarily indicative of future results. Always use proper risk management and consult a financial advisor before making any investment decisions.
------
The following is a summary of the underlying whitepaper (onlinelibrary.wiley.com) for this strategy:
This paper proposes a theory of securities market under- and overreactions based on two psychological biases: investor overconfidence about the precision of private information and biased self-attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. The authors show that overconfidence implies negative long-lag autocorrelations, excess volatility, and public-event-based return predictability. Biased self-attribution adds positive short-lag autocorrelations (momentum), short-run earnings "drift," and negative correlation between future returns and long-term past stock market and accounting performance.
The paper explains that there is empirical evidence challenging the traditional view that securities are rationally priced to reflect all publicly available information. Some of these anomalies include event-based return predictability, short-term momentum, long-term reversal, high volatility of asset prices relative to fundamentals, and short-run post-earnings announcement stock price "drift."
The authors argue that investor overconfidence can lead to stock prices overreacting to private information signals and underreacting to public signals. This overreaction-correction pattern is consistent with long-run negative autocorrelation in stock returns, excess volatility, and further implications for volatility conditional on the type of signal. The market's tendency to over- or underreact to different types of information allows the authors to address the pattern that average announcement date returns in virtually all event studies are of the same sign as the average post-event abnormal returns.
Biased self-attribution implies short-run momentum and long-term reversals in security prices. The dynamic analysis based on biased self-attribution can also lead to a lag-dependent response to corporate events. Cash flow or earnings surprises at first tend to reinforce confidence, causing a same-direction average stock price trend. Later reversal of overreaction can lead to an opposing stock price trend.
The paper concludes by summarizing the findings, relating the analysis to the literature on exogenous noise trading, and discussing issues related to the survival of overconfident traders in financial markets.
Pure Morning 2.0 - Candlestick Pattern Doji StrategyThe new "Pure Morning 2.0 - Candlestick Pattern Doji Strategy" is a trend-following, intraday cryptocurrency trading system authored by devil_machine.
The system identifies Doji and Morning Doji Star candlestick formations above the EMA60 as entry points for long trades.
For best results we recommend to use on 15-minute, 30-minute, or 1-hour timeframes, and are ideal for high-volatility markets.
The strategy also utilizes a profit target or trailing stop for exits, with stop loss set at the lowest low of the last 100 candles. The strategy's configuration details, such as Doji tolerance, and exit configurations are adjustable.
In this new version 2.0, we've incorporated a new selectable filter. Since the stop loss is set at the lowest low, this filter ensures that this value isn't too far from the entry price, thereby optimizing the Risk-Reward ratio.
In the specific case of ALPINE, a 9% Take-Profit and and Stop-Loss at Lowest Low of the last 100 candles were set, with an activated trailing-stop percentage, Max Loss Filter is not active.
Name : Pure Morning 2.0 - Candlestick Pattern Doji Strategy
Author : @devil_machine
Category : Trend Follower based on candlestick patterns.
Operating mode : Spot or Futures (only long).
Trades duration : Intraday
Timeframe : 15m, 30m, 1H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility .
Entry : When a Doji or Morning Doji Star formation occurs above the EMA60.
Exit : Profit target or Trailing stop, Stop loss on the lowest low of the last 100 candles.
Configuration :
- Doji Settings (tolerances) for Entry Condition
- Max Loss Filter (Lowest Low filter)
- Exit Long configuration
- Trailing stop
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: ALPINEUSDT
⁃ Timeframe: 30m
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start: 2022-02-28 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Index Strength Strategy with Signal Using the Index Strength Strategy Indicator for Trading
Introduction:
In this article, we'll explore the Index Strength Strategy Indicator and how it can be used for trading. The Index Strength Strategy Indicator is a technical analysis tool designed to help traders identify trends, determine trend strength, and generate buy and sell signals.
Overview of the Index Strength Strategy Indicator:
The Index Strength Strategy Indicator is based on two moving averages - a fast moving average and a slow moving average - and the Relative Strength Index (RSI). The fast and slow moving averages are used to determine the trend direction, while the RSI is used to calculate the trend strength. The indicator assigns a strength score to the current trend, which is then classified into one of four categories - Very Weak, Weak, Strong, or Very Strong. Traders can use this information to identify the strength of the trend and adjust their trading strategy accordingly.
The indicator also generates buy and sell signals based on a user-defined threshold level. When the strength score crosses above the threshold level, a buy signal is generated, and when the strength score crosses below the threshold level, a sell signal is generated.
Using the Index Strength Strategy Indicator for Trading:
Traders can use the Index Strength Strategy Indicator to identify trends, determine trend strength, and generate buy and sell signals. To use the indicator, traders should first determine the appropriate fast and slow moving average periods and the strength threshold level for their trading style. These input parameters can be adjusted in the indicator's settings.
Once the indicator is added to the chart, traders can use the strength score and trend direction to identify potential trading opportunities. If the trend is classified as Strong or Very Strong, traders may look for opportunities to enter long or short positions in the direction of the trend. If the trend is classified as Very Weak or Weak, traders may look for opportunities to exit or avoid positions.
Traders can also use the buy and sell signals generated by the indicator to enter or exit positions. When a buy signal is generated, traders can enter a long position, and when a sell signal is generated, traders can enter a short position. Traders should set stop-loss and take-profit levels based on their risk management strategy.
Avoiding Mistakes:
To avoid mistakes when using the Index Strength Strategy Indicator, traders should keep the following tips in mind:
Don't rely solely on the indicator - it should be used in conjunction with other technical analysis tools and fundamental analysis.
Use appropriate risk management strategies, including setting stop-loss and take-profit levels.
Adjust the input parameters of the indicator to match your trading style and preferences.
Avoid overtrading and chasing trades - wait for the right opportunities to enter or exit positions.
Trading Strategy Test Results: Time Frame Tested for 15 Mins
To provide an idea of the potential performance of the Index Strength Strategy Indicator, let's look at some recent test results for two popular indices - Bank Nifty and Nifty 50.
From 1-May-2023 to 12-May-2023, using 2 lots of Bank Nifty with the Index Strength Strategy Indicator, a profit of 15,175 was achieved, with a percentage profitable trade rate of 80% and a profit factor of 3.395. The maximum drawdown was 7,000, and the average trade was 3,035.
During the same time period, using 1 lot of Nifty 50 with the Index Strength Strategy Indicator, a profit of 8,187 was achieved
Conclusion:
The Index Strength Strategy Indicator is a useful tool for traders to identify trends, determine trend strength, and generate buy and sell signals. Traders can use the indicator in conjunction with other technical analysis tools and fundamental analysis to make informed trading decisions. By following proper risk management strategies and avoiding common mistakes, traders can use the indicator to improve their trading performance.
Chandelier Exit ZLSMA StrategyIntroducing a Powerful Trading Indicator: Chandelier Exit with ZLSMA
If you're a trader, you know the importance of having the right tools and indicators to make informed decisions. That's why we're excited to introduce a powerful new trading indicator that combines the Chandelier Exit and ZLSMA: two widely-used and effective indicators for technical analysis.
The Chandelier Exit (CE) is a popular trailing stop-loss indicator developed by Chuck LeBeau. It's designed to follow the price trend of a security and provide an exit signal when the price crosses below the CE line. The CE line is based on the Average True Range (ATR), which is a measure of volatility. This means that the CE line adjusts to the volatility of the security, making it a reliable indicator for trailing stop-losses.
The ZLEMA (Zero Lag Exponential Moving Average) is a type of exponential moving average that's designed to reduce lag and improve signal accuracy. The ZLSMA takes into account not only the current price but also past prices, using a weighted formula to calculate the moving average. This makes it a smoother indicator than traditional moving averages, and less prone to giving false signals.
When combined, the CE and ZLSMA create a powerful indicator that can help traders identify trend changes and make more informed trading decisions. The CE provides the trailing stop-loss signal, while the ZLSMA provides a smoother trend line to help identify potential entry and exit points.
In our indicator, the CE and ZLSMA are plotted together on the chart, making it easy to see both the trailing stop-loss and the trend line at the same time. The CE line is displayed as a dotted line, while the ZLSMA line is displayed as a solid line.
Using this indicator, traders can set their stop-loss levels based on the CE line, while also using the ZLSMA line to identify potential entry and exit points. The combination of these two indicators can help traders reduce their risk and improve their trading performance.
In conclusion, the Chandelier Exit with ZLSMA is a powerful trading indicator that combines two effective technical analysis tools. By using this indicator, traders can identify trend changes, set stop-loss levels, and make more informed trading decisions. Try it out for yourself and see how it can improve your trading performance.
Warning: The results in the backtest are from a repainting strategy. Don't take them seriously. You need to do a dry live test in order to test it for its useability.
-
Here is a description of each input field in the provided source code:
length: An integer input used as the period for the ATR (Average True Range) calculation. Default value is 1.
mult: A float input used as a multiplier for the ATR value. Default value is 2.
showLabels: A boolean input that determines whether to display buy/sell labels on the chart. Default value is false.
isSignalLabelEnabled: A boolean input that determines whether to display signal labels on the chart. Default value is true.
useClose: A boolean input that determines whether to use the close price for extrema calculations. Default value is true.
zcolorchange: A boolean input that determines whether to enable rising/decreasing highlighting for the ZLSMA (Zero-Lag Exponential Moving Average) line. Default value is false.
zlsmaLength: An integer input used as the length for the ZLSMA calculation. Default value is 50.
offset: An integer input used as an offset for the ZLSMA calculation. Default value is 0.
-
Ty for checking this out and good luck on your trading journey! Likes and comments are appreciated. 👍
--
Credits to:
▪ @everget – Chandelier Exit (CE)
▪ @netweaver2022 – ZLSMA
X48 - Strategy | ADAPTIVE CONSECUTIVE + TP/SL | V.1Thanks For Tradingview Built-in Script :: << Original From Consecutive Strategy Built-in Script >>
================== Read This First Before Use This Strategy ==============
Please be aware that this strategy is not a guarantee of success and may lead to losses.
Trading involves risk and you should always do your own research before making any decisions.
This Strategy Just an Idea For Help Your Decision For Open Position.
You Must Be Search and Make Your Self Understand What You Doing In This Strategy.
Example :: This Strategy and Indicator Find The Consecutive Bars And You, You Are Reading Must Be Decision Up to You !!
For Backtest Show It's That For a Newbie 100$ Portfolio and 16.333$ Per Order Size
>>>> Read Me First !! <<<<<
========== Detailed and meaningful description =========
How It's Work : This Strategy are Following Green or Red Candle :: example 3 Green Candle To OpenLong Position
Can Set TP/SL if you want :: Just Fine The Best Value of Asset as you want
Fast Trend = MA FAST LINE
SLOW Trend = MA SLOW LINE
MID-TERM TREND = MA MID-TERM
LONG-TERM TREND = MA LONG-TERM
=========== Condition And Statement ===========
Long Condition Statement :: Candles Consecutive Bars Up and close > golden_line and fast_line > golden_line
Short Condition Statement :: Candles Consecutive Bars Down and close < golden_line and fast_line < golden_line
AutoCloseLong Condition :: Candles ConsecutiveBarsDownStop and close > golden_line and close < death_line and close < death_line and close < death_line or fastUpdeath
AutoCloseShort Condition :: Candles ConsecutiveBarsUpStop and close < golden_line and close > death_line and close > death_line and close > death_line or fastUpdeath
====== For ADAPTIVE you can customize your ALL MA For Your Statement
/////////For Example Hook Alert Command ////////////
Just Easy Command >> :: {{strategy.order.alert_message}}
Or Other Json You Should Edit Command Like This Example
{"ex":"'bnfuture'","side": "AutoLong", "$16.333", "symbol": "{{ticker}}", "passphrase": "1234","leverage":"10", "tp" : "5", "sl" : "2", "tl" : "2", "callback" : "1"}
{"ex":"'bnfuture'","side": "AutoShort", "$16.333", "symbol": "{{ticker}}", "passphrase": "1234","leverage":"10", "tp" : "5", "sl" : "2", "tl" : "2", "callback" : "1"}
FRAMA & CPMA Strategy [CSM]The script is an advanced technical analysis tool specifically designed for trading in financial markets, with a particular focus on the BankNifty market. It utilizes two powerful indicators: the Fractal Adaptive Moving Average (FRAMA) and the CPMA (Conceptive Price Moving Average), which is similar to the well-known Chande Momentum Oscillator (CMO) with Center of Gravity (COG) bands.
The FRAMA is a dynamic moving average that adapts to changing market conditions, providing traders with a more precise representation of price movements. The CMO is an oscillator that measures momentum in the market, helping traders identify potential entry and exit points. The COG bands are a technical indicator used to identify potential support and resistance levels in the market.
Custom functions are included in the script to calculate the FRAMA and CSM_CPMA indicators, with the FRAMA function calculating the value of the FRAMA indicator based on user-specified parameters of length and multiplier, while the CSM_CPMA function calculates the value of the CMO with COG bands indicator based on the user-specified parameters of length and various price types.
The script also includes trailing profit and stop loss functions, which while not meeting expectations, have been backtested with a success rate of over 90%, making the script a valuable tool for traders.
Overall, the script provides traders with a comprehensive technical analysis tool for analyzing cryptocurrency markets and making informed trading decisions. Traders can improve their success rate and overall profitability by using smaller targets with trailing profit and minimizing losses. Feedback is always welcome, and the script can be improved for future use. Special thanks go to Tradingview for providing inbuilt functions that are utilized in the script.
Stochastic RSI Strategy (with SMA and VWAP Filters)The strategy is designed to trade on the Stochastic RSI indicator crossover signals.
Below are all of the trading conditions:
-When the Stochastic RSI crosses above 30, a long position is entered.
-When the Stochastic RSI crosses below 70, a short position is entered.
-The strategy also includes two additional conditions for entry:
-Long entries must have a positive spread value between the 9 period simple moving average and the 21 period simple moving average.
-Short entries must have a negative spread value between the 9 period simple moving average and the 21 period simple moving average.
-Long entries must also be below the volume-weighted average price.
-Short entries must also be above the volume-weighted average price.
-The strategy includes stop loss and take profit orders for risk management:
-A stop loss of 20 ticks is placed for both long and short trades.
-A take profit of 25 ticks is placed for both long and short trades.
JS-TechTrading: Supertrend-Strategy_Basic versionAre you looking for a reliable and profitable algorithmic trading strategy for TradingView? If so, you might be interested in our Supertrend basic strategy, which is based on three powerful indicators: Supertrend (ATR), RSI and EMA.
Supertrend is a trend-following indicator that helps you identify the direction and strength of the market. It also gives you clear signals for entry and exit points based on price movements.
RSI is a momentum indicator that measures the speed and change of price movements. It helps you filter out false signals and avoid overbought or oversold conditions.
EMA is a moving average indicator that smooths out price fluctuations and shows you the long-term trend of the market. It helps you confirm the validity of your trades and avoid trading against the trend.
Our Supertrend basic strategy combines these three indicators to give you a simple yet effective way to trade any market. Here's how it works:
- For long trades, you enter when the price is above Supertrend and pulls back below it (the low of the candle crosses Supertrend) and then rebounds above it (the high of the next candle goes above the pullback candle). You exit when the price closes below Supertrend or when you reach your target profit or stop loss.
- For short trades, you enter when the price is below Supertrend and pulls back above it (the high of the candle crosses Supertrend) and then drops below it (the low of the next candle goes below the pullback candle). You exit when the price closes above Supertrend or when you reach your target profit or stop loss.
- You can also use RSI and EMA filters to improve your results. For long trades, you only enter if RSI is above 50 and price is above 200 EMA. For short trades, you only enter if RSI is below 50 and price is below 200 EMA.
- You can set your stop loss and target profit as a percentage of your entry price or based on other criteria. You can also adjust the parameters of each indicator according to your preferences and risk tolerance.
Our Supertrend basic strategy is easy to use and has been tested on various markets and time frames. It can help you capture consistent profits while minimizing your losses.
DLX-NationThis Strategy is based on 8 EMAs and the RSI ( 14 Length )
Its algorism check for the trend of the market using crossover EMAs, then it waits for a 38% - 50% pullback. During this Pullback it checks the behaviour of the EMAs by making sure consolidation is coming to and end by checking if the red EMA cuts through certain candle bodies. Then it detects a takeover in the market, meaning during a pullback ( in case of a buy ) it calculates the selling volume and waits to confirm that buyers retake over the Market by calculating the candle sizes making sure the current candle is bigger than the previous candle using the 3rd EMA (if 50 EMA is below market price) then finally It checks if there is enough buying Strength ( in case of a buy ) or enough selling strength ( in case of a sell) by checking the RSI level over a certain period of time. When all these confirmations are done, it then analyses previous supports and resistence, and only sends a signal if there is not resistance for a buy and no support for a sell.
Its best for a strong bullish or bearish 1min, 5mins and 15mins market, thats why it only available on US30 and NAS100 for now. Its best when all the EMAs are spreading out or in other words the distance between the EMAs are increasing.
In case of a consolidation, you will see all EMAs moving together and in this case you shouldnt take any signal called. Following EMAs should guide you identifying a consilidation
50 EMA = Aqua
90 EMA = Green
150 EMA = Purple
200 EMA = Gray
400 EMA = Orange
800 EMA = Blue
Note: If you see all these EMA coming closer to each other, it indicates a long going consolidation and during these moments you shouldnt execute any signal. These is the reason why we decided to plot them on the Chart. We understand trading with a clean Chart is important, moreover using certain tools to be more profitable is essential. In case the 50 EMA ( Aqua ) Crosses over or below the 150 EMA ( Green ) and 200 EMA (Gray), this will indicate end of the consolidation and the signals will have more liquidity and movement.
Lastly when a signal is being called make sure the last candle is clearly bigger than the previous candles, this indicates that the buyer ( in case of a buy candle ) are clearly taking over the market or the sellers ( in case of a sell candle ) are clearly taking over the market giving you more volume and liquidity.
To optain the max Profit:
After adding the Strategy / Indicator on your Chart go to Settings -> Properties and set the Pyramiding to 30. These implies that we can have 30 consecutive buy signals in a row or sell signals in a row. We recommend an initail Balance of 2000$, but mininum 1000% and a lotsize of 10cent per pip (0.1). Strickly follow the Take Profit (100pips) and StopLoss (500pips) level that will be provided in this case also risk only 1% of your account per trade and maximun 5% per running trades.
Keep in mind, the smaller the TImeframe the more trades you will recieve and the stronger the momentum the more profitable the trade will be.
FTR, WMA, OBV & RSI StrategyThis Pine Script code is a trading strategy that uses several indicators such as Fisher Transform (FTR), On-Balance Volume (OBV), Relative Strength Index (RSI), and a Weighted Moving Average (WMA). The strategy generates buy and sell signals based on the conditions of these indicators.
The Fisher Transform function is a technical indicator that uses past prices to determine whether the current market is bullish or bearish. The Fisher Transform function takes in four multipliers and a length parameter. The four multipliers are used to calculate four Fisher Transform values, and these values are used in combination to determine if the market is bullish or bearish.
The Weighted Moving Average (WMA) is a technical indicator that smooths out the price data by giving more weight to the most recent prices.
The Relative Strength Index (RSI) is a momentum indicator that measures the strength of a security's price action. The RSI ranges from 0 to 100 and is typically used to identify overbought or oversold conditions in the market.
The On-Balance Volume (OBV) is a technical indicator that uses volume to predict changes in the stock price. OBV values are calculated by adding volume on up days and subtracting volume on down days.
The strategy uses the Fisher Transform values to generate buy and sell signals when all four Fisher Transform values change color. It also uses the WMA to determine if the trend is bullish or bearish, the OBV to confirm the trend, and the RSI to filter out false signals.
The red and green triangular arrows attempt to indicate that the trend is bullish or bearish and should not be traded against in the opposite direction. This helps with my FOMO :)
All comments welcome!
The script should not be relied upon alone, there are no stop loss or take profit filters. The best results have been back-tested using Tradingview on the 45m - 3 hour timeframes.
Seer's HutThis is a strategy based on Exponential Moving Averages or Volume Weighted Moving Averages against Adaptive fib resistance / support level and profit percentage which can be definetly defined by user and targeting small profits(profits will be raised by leverages).
In this strategy, there are predefined values which are collected one by one with statistical background and backtests. This gives an advantage to see which ratios are working better for each symbol. Also this statistics are re-evaluated monthly and if there is a need they are going to be changed with the help of libraries. Also IT IS RECOMMENDED TO USE IN DAILY INTERVAL GRAPHICS!!!!
When we deep dive to strategy, it is based on profit percentages. it is similar to the MOST system. MOST only changes the way with default value of %2. But this hardcoded strategy is not working well with each Symbol.
So this is the point where DC and ADR Statistics are involved.
For Ex. while BTC is suits well with %2, it does not do wonders for RSR or RUNE which is 4-5% for each.
There is 3 options for setting the statistical usage of this indicator.
1. Auto calculated based on 1000 days of ADR and DC
imgur.com
2. Using Library where statistical values are stored.
imgur.com
3. User-defined values used. Yeah you read it right. Fully on-demand changes are supported. Which gives freedom to users for setup their own Adaptive FIB and Profit Percentages.
imgur.com
Based on this 3 options, TP and SL points are calculated on bar closures. Strategy Orders are also shown / raised with the closures.
Ok, system calculates these values but how to read / use them. what is this strategy based on ?
This strategy is mostly looking for minimizing the LOSS in case of any stop. So because of this, in each TP, system gives order signal to close half of the remaining open position.
There are 7 type of orders
OL : Open Long (Close Short and Open Long if in position)
CL 50 : Close Long - %50 of Open Position
CL 100 : Close Long - Close all position
OS : Open Short (Close Long and Open Short if in position)
CL 50 : Close Short - %50 of Open Position
CL 100 : Close Short - Close all position
TP5 : Highest TP reached. Close all position.
Script checks cross of EMA / VWMA and adFib to decide open a position. In reversal / crosses, adFib line had been set to defined Fib. Percentage (FP) level.
For creating the TP points, Profit Percentage (PP) parameter had been used which I briefly introduce at the beginning with the options.
One important topic about this strategy, it is not stacking / pyramiding the positions. Which means, it always calculate one way position. For example we are in the long position after OL signal.
We reached TP values and take profits. Later on due to FP crossing EMA, OS order signal given. This means you have to close all long position and open short position.
But beware. These calculated points are based on given values or calculated regarding to average ADR / DC ratings. For supporting strategy, several methods also had been included in the options.
imgur.com
These are:
1. MA plotting (Optional 4 EMA, 1WMA) - checking for Golden and Death Cross
2. Bollinger Bands (Length 25 and Multiplier 2.5 set as default. Used in correlation with TEMA)
3. Kama 2 / Kama 5 - Crossing speaks of Trend way
4. TEMA (TEMA 50, VWMA 25 calculations and plotting. Used for TEMA 50 / VWMA 25 / SMA 25 cross checks for weakening or strengthening trend analysis)
5. ATR plotting
6. Chandelier Exit plotting (Widely used for calculating Stop levels in market)
7. PSAR (Widely used for indicating trend reversal)
Also for the ease of use, if the users does not want to plot any values on the graph and just want to see the values there is couple of tables also included.
1. EMA info
2. KAMA info
3. Order info
4. TP/SL info
imgur.com
Some important notes:
1. To minimize the stop just after the order opening candle in volatile grounds, system prevents to raise new order signals if there is a signal already raised in last 4 candle.
2. if system reach and give close order in one of the TP points (For Ex TP1.), then index goes down and goes up again same TP (above TP1 in scenario) after 4 candle, system gives a close order signal again in the same TP.
3. There is a Profit Factor value had been shown at Order Info table. This information shows how profitable is the setup regarding to given FP and PP values.
In general market conditions, A Profit Factor above 1.50 is considered good enough and above 2.0 it is considered ideal. A strategy with profit factor less than 1.20 suggests too bigger a risk taken for making money.
In some cases automatic ADR and DC calculations are not good enough. so if you want to find a good Profit Factor value, you can change the system automatic calculation to manual value entering and you can see the results directly with in this field.
Optimized Zhaocaijinbao strategyIntroduction:
The Optimized Zhaocaijinbao strategy is a mid and long-term quantitative trading strategy that combines momentum and trend factors. It generates buy and sell signals by using a combination of exponential moving averages, moving averages, volume and slope indicators. It generates buy signals when the stock is above the 35-day moving average, the trading volume is higher than the 20-day moving average, and the stock is in an upward trend on a weekly timeframe."招财进宝" is a Chinese phrase that can be translated to "Attract Wealth and Bring in Treasure" in English. It is a common expression used to wish for good luck and prosperity in various contexts, such as in business or personal finances.
Highlights:
The strategy has several special optimizations that make it unique.
Firstly, the strategy is optimized for T+1 trading in the Chinese stock market and is only suitable for long positions. The optimizations are also applicable to international stock markets.
Secondly, the trend strategy is optimized to only show indicators on the right side and oscillations. This helps to prevent false signals in choppy markets.
Thirdly, the strategy uses a risk factor for dynamic position sizing to ensure position sizes are adjusted according to the current net asset value and risk preferences. This helps to lower drawdown risks.
The strategy has good resilience even without using stop loss modules in backtesting, making it suitable for trading hourly, 2-hourly, and daily K-line charts (depending on the stock being traded). We recommend experimenting with backtesting using SSE 1-hour or 2-hour or daily Kline charts.
Backtesting outcomes:
The strategy was backtested over the period from October 13th, 2005 to April 14th, 2023, using daily candlestick charts for the commodity code SSE:600763, with a currency of CNY and tick size of 0.01. The strategy used an initial capital of 1,000,000 CNY, with order sizes set to 10% equity and a pyramid of 1 order. The strategy also had a Max Position Size of 0.01 and a Risk Factor of 2.
Here is a summary of the performance of the trading strategy:
Total net profit: 288,577.32 CNY, representing a return of 128.86%
Total number of closed trades: 61
Winning trades: 37, representing a win rate of 60.66%
Profit factor: 2.415
Largest losing trade: 222,021.46 CNY, representing a loss of 14.08%
Average trade: 21,124.22 CNY, representing a return of 3.1%
Average holding period for all trades: 12 days
Conclusion:
In conclusion, the Optimized Zhaocaijinbao strategy is a mid and long-term quantitative trading strategy that combines momentum and trend factors. It is suitable for both Chinese stocks and global stocks. While the Optimized Zhaocaijinbao strategy has performed well in backtesting, it is important to note that past performance is not a guarantee of future results. Traders should conduct their own research and analysis and exercise caution when using any trading strategy.
LowFinder_PyraMider_V2This strategy is a result of an exploration to experiment with other ways to detect lows / dips in the price movement, to try out alternative ways to exit and stop positions and a dive into risk management. It uses a combination of different indicators to detect and filter the potential lows and opens multiple positions to spread the risk and opportunities for unrealized losses or profits. This script combines code developed by fellow Tradingview community_members.
LowFinder
The lows in the price movement are detected by the Low finder script by RafaelZioni . It finds the potential lows based on the difference between RSI and EMA RSI. The MTF RSI formula is part of the MTFindicators library developed by Peter_O and is integrated in the Low finder code to give the option to use the RSI of higher timeframes. The sensitivity of the LowFinder is controlled by the MA length. When potential lows are detected, a Moving Average, a MTF Stochastic (based the the MTFindiicators by Peter_O) and the average price level filter out the weak lows. In the settings the minimal percentage needed for a low to be detected below the average price can be specified.
Order Sizing and Pyramiding
Pyramiding, or spreading multiple positions, is at the heart of this strategy and what makes it so powerful. The order size is calculated based on the max number of orders and portfolio percentage specified in the input settings. There are two order size modes. The ‘base’ mode uses the same base quantity for each order it opens, the ‘multiply’ mode multiplies the quantity with each order number. For example, when Long 3 is opened, the quantity is multiplied by 3. So, the more orders the bigger the consecutive order sizes. When using ‘multiply’ mode the sizes of the first orders are considerably lower to make up for the later bigger order sizes. There is an option to manually set a fixed order size but use this with caution as it bypasses all the risk calculations.
Stop Level, Take Profit, Trailing Stop
The one indicator that controls the exits is the Stop Level. When close crosses over the Stop Level, the complete position is closed and all orders are exited. The Stop Level is calculated based on the highest high given a specified candle lookback (settings). There is an option to deviate above this level with a specified percentage to tweak for better results. You can activate a Take Profit / Trailing Stop. When activated and close crosses the specified percentage, the Stop Level logic changes to a trailing stop to gain more profits. Another option is to use the percentage as a take profit, either when the stop level crosses over the take profit or close. With this option active, you can make this strategy more conservative. It is active by default.
And finally there is an option to Take Profit per open order. If hit, the separate orders close. In the current settings this option is not used as the percentage is 10%.
Stop Loss
I published an earlier version of this script a couple of weeks ago, but it got hidden by the moderators. Looking back, it makes sense because I didn’t pay any attention to risk management and save order sizing. This resulted in unrealistic results. So, in this script update I added a Stop Loss option. There are two modes. The ‘average price’ mode calculates the stop loss level based on a given percentage below the average price of the total position. The ‘equity’ mode calculates the stop loss level based on a given percentage of your equity you want to lose. By default, the ‘equity’ mode is active. By tweaking the percentage of the portfolio size and the stop loss equity mode, you can achieve a quite low risk strategy set up.
Variables in comments
To sent alerts to my exchange I use a webhook server. This works with a sending the information in the form of a comment. To be able to send messages with different quantities, a variable is added to the comment. This makes it possible to open different positions on the exchange with increasing quantities. To test this the quantities are printed in the comment and the quantities are switched off in the style settings.
This code is a result of a study and not intended for use as a worked out and full functioning strategy. Use it at your own risk. To make the code understandable for users that are not so much introduced into pine script (like me), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
VWAP+15EMA with RSIVWAP+EMA+RSI Strategy for the group MelléCasH
This strategy will enter a long position when the closing price is above both the VWAP and the 15 EMA, and the RSI is above the specified overbought level. It will exit the position when the price falls by the specified stop loss percentage, rises by the specified take profit percentage, or when the trailing stop loss (which trails the highest price achieved after the position was entered by the specified percentage) is hit. The VWAP, EMA, and RSI indicators are also plotted on the chart for reference.
VWAP Breakout Strategy (Momentum, Vol, VWAP, RSI, TrSL)General Description and Unique Features of this Script
Introducing the VWAP Breakout Trading Algorithm for TradingView – the timeless strategy designed to identify the highest probability entries and trades for all financial securities and timeframes.
Unlike other strategies, the VWAP Breakout Strategy considers the buying/selling pressure in the market and supply/demand balance to generate real-time trading signals. The Relative Strength Index (RSI) is used as a technical measure to capture typical breakouts from consolidation periods and pullback entries.
With flexible backtesting options, traders can improve parameter settings depending on their time horizon and the type of financial securities being used. Plus, this pro-version of the VWAP Breakout Strategy offers stop-loss, take-profit, and trailing stop-loss exit strategies for better risk management.
The VWAP Breakout Strategy combines a number of technical indicators, the Moving Average (MA), the Volume Weighted Average Price (VWAP) and the RSI-qualifier to identify potential trend reversals and entry/exit points in the market. The VWAP Breakout Strategy can be used in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions.
To further optimize trading results, this strategy generates trading signals based on real-time price action, rather than relying on the close / open of candles.
The VWAP Breakout Strategy
One important qualifier for generating buy signals is that the stock or other financial security is not in a short-term overbought status (for long-positions), or in a short-term oversold status (for short-positions), respectively.
Additionally, the stock or other financial security needs to go through a consolidation period before buy signals are being generated.
The RSI-indicator is being used as a technical measure in this strategy for that.
• Using moderate parameters for the RSI-qualifier (oversold-level 40 or higher, overbought level 60 or lower) will capture more typical breakouts from consolidation periods.
• Using more extreme parameters for the RSI-qualifier (oversold-level 35 or lower, overbought level 65 or higher) will capture the so-called pullback entries.
Long Entries
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MA / VWAP crossover after reaching a price low, a buy signal is issued by this strategy.
Short Entries
When the byuing pressure is over and the continuation of the downtrend can be confirmed by the MA / VWAP crossover after reaching a price high, a sell signal is issued by this strategy.
Timeless Strategy
The underlying principles of this strategy are based on the buying- / selling pressure in the market as well as the supply and demand balance. The buying / selling volumes are being considered for the generation of trading signals. These sophisticated market principles make this strategy timeless which means it can be applied to 1min-charts, weekly charts as well as anything between those.
Generation of Trading Signals
Real-time process are considered for this pro-version of the VWAP Breakout Strategy. This is another benefit versus many other strategies which only consider the close or open of the canldes for trading signals:
Exit Strategies
This pro-version offers the following exit strategies:
• Stop-Loss
• Take-Profit
• Trailing Stop-Loss
The trailing SL functionality provides another benefit versus most other trading strategies resulting in significantly backtesting- and real-time trading results.
Trades will also be closed when an opposite trading signal is being generated (only applicable for combined long/short strategies).
Flexible Backtesting Option
The strategy offers fully flexible backtesting options to improve the parameter setting strategy, depending on time horizon and type of financial securities being used.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
The MA / VWAP Crossover Trading Strategy
This strategy combines two popular technical indicators: the Moving Average (MA) and the Volume Weighted Average Price (VWAP). The MA VWAP crossover strategy is used to identify potential trend reversals and entry/exit points in the market.
The VWAP is calculated by taking the average price of an asset for a given period, weighted by the volume traded at each price level. The MA, on the other hand, is calculated by taking the average price of an asset over a specified number of periods. When the MA crosses above the VWAP, it suggests that buying pressure is increasing, and it may be a good time to enter a long position. When the MA crosses below the VWAP, it suggests that selling pressure is increasing, and it may be a good time to exit a long position or enter a short position.
Traders typically use the MA VWAP crossover strategy in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions. As with any trading strategy, it is important to carefully consider the risks and potential rewards before making any trades.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MA/VWAP) can be adjusted and optimized as needed.
Backtesting Results
Backtesting gives outstanding results on all timeframes and drawdowns can be reduced to a minimum level. In this example, the hourly chart for MCFT has been used.
Settings for backtesting are:
- Period from April 2020 until April 2021 (1 yr)
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
- Slippage = 2 ticks
Other comments
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The RSI qualifier is highly selective and filters out the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• As a result, traders need to apply this strategy for a full watchlist rather than just one financial security.
Rebalance by StrategyThaiStrategy Rebalance
Rebalancing trade in the context of cryptocurrency refers to adjusting the composition of a cryptocurrency portfolio to maintain a desired allocation of different digital assets. As the market value of various cryptocurrencies changes over time, the proportion of each asset in the portfolio may deviate from the original target allocation. Rebalancing aims to restore the portfolio to its desired balance, ensuring it remains aligned with the investor's risk tolerance and investment goals.
Here are some steps to rebalance a cryptocurrency portfolio:
Assess your portfolio: Review your current cryptocurrency holdings and their respective market values. Determine the current allocation of each asset as a percentage of your total portfolio value.
Set target allocations: Decide on the target allocation for each cryptocurrency in your portfolio based on your investment goals, risk tolerance, and market outlook. This might involve allocating a higher percentage to more established cryptocurrencies like Bitcoin and Ethereum and a smaller percentage to newer or more volatile digital assets.
Calculate rebalancing amounts: Compare your current allocations with your target allocations. Calculate the amount of each cryptocurrency you need to buy or sell to achieve your target allocations.
Execute trades: Buy or sell the necessary amounts of each cryptocurrency to reach your target allocations. Keep in mind that transaction fees and taxes may apply, depending on your jurisdiction and the trading platform you use.
Monitor and adjust: Regularly review your cryptocurrency portfolio and market conditions. Rebalance as needed to maintain your target allocations and adapt to changing market dynamics.
Rebalancing a cryptocurrency portfolio can help manage risk and potentially enhance returns by ensuring that the portfolio remains diversified and aligned with the investor's objectives. However, it is important to consider the costs and tax implications of frequent rebalancing before implementing this strategy.
##########################################################################
Setting input
Start : start date
End : end date
----
Rebalance Mode :
Normal = Rebalance Always adjust the balance according to the preset proportions. , e.g. 50% of equity.
Fixed Asset = Fixed Asset value. e.g. always Fixed Asset 50% of capital
----
Proportion : Proportion 0.05 = 5% of capital or equity
Min Size Trade value : The minimum that the exchange allows to trade in usdt,usd
Range Price : distance openclose last price (0.01 = 1%)
Use indicator :
Indicator Period : Length
Moving Average Trap Strategy by D. BrigagliaThis is a strategy that follows the 200 periods moving average and fades the cross of ma3, ma5 and ma8. It is designed for profiting by mean reversion while at the same time respecting long term trend. It is designed for long term trending markets such as stocks and stock indices.
In this backtest, the strategy shows the ability to beat the S&P500 index with an average slippage set to 2 ticks. The number of trades is good (350), the profit factor is acceptable (1.67). The drawdowns are also reduced compared to the underlying asset.
Nothing of my content is financial advice.
Grospector DCA V.3This is system for DCA with strategy.
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Idea : Everything has average in its life. For bitcoin use 4 years for halving. I think it will be interesting price.
Default : I set MA is 365*4 days and average it again with 365 days.
Input :
len: This input represents the length of the moving average.
strongLen: This input represents the length of the moving average used to calculate the strong buy and strong sell zone.
shortMulti: This input represents the multiplier * moveing average used to calculate the short zone.
strongSellMulti: This input represents the multiplier used to calculate the strong sell signal.
sellMulti: This input represents the multiplier * moveing average used to calculate the sell zone.
strongBuyMulti: This input represents the multiplier used to calculate the strong sell signal.
longMulti: This input represents the multiplier * moveing average used to calculate the long zone.
*Diff sellMulti and strongBuyMulti which is normal zone.
useDerivative: This input is a boolean flag that determines whether to use the derivative display zone. If set to true, the derivative display zone will be used, otherwise it will be hidden.
zoneSwitch: This input determines where to display the channel signals. A value of 1 will display the signals in all zones, a value of 2 will display the signals in the chart pane, a value of 3 will display the signals in the data window, and a value of 4 will hide the signals.
price: Defines the price source used for the indicator calculations. The user can select from various options, with the default being the closing price.
labelSwitch: Defines whether to display assistive text on the chart. The user can select a boolean value (true/false), with the default being true.
zoneSwitch: Defines which areas of the chart to display assistive zones. The user can select from four options: 1 = all, 2 = chart only, 3 = data only, 4 = none. The default value is 2.
predictFuturePrice: Defines whether to display predicted future prices on the chart. The user can select a boolean value (true/false), with the default being true.
DCA: Defines the dollar amount to use for dollar-cost averaging (DCA) trades. The user can input an integer value, with a default value of 5.
WaitingDCA: Defines the amount of time to wait before executing a DCA trade. The user can input a float value, with a default value of 0.
Invested: Defines the amount of money invested in the asset. The user can input an integer value, with a default value of 0.
strategySwitch: Defines whether to turn on the trading strategy. The user can select a boolean value (true/false), with the default being true.
seperateDayOfMonth: Defines a specific day of the month on which to execute trades. The user can input an integer value from 1-31, with the default being 28.
useReserve: Defines whether to use a reserve amount for trading. The user can select a boolean value (true/false), with the default being true.
useDerivative: Defines whether to use derivative data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
useHalving: Defines whether to use halving data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
extendHalfOfHalving: Defines the amount of time to extend the halving date. The user can input an integer value, with the default being 200.
Every Zone : It calculate percent from top to bottom which every zone will be splited 10 step.
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
Kitchen [ilovealgotrading]
OVERVIEW:
Kitchen is a strategy that aims to trade in the direction of the trend by using supertrend and stochRsi data by calculating at different time values.
IMPLEMENTATION DETAILS – SETTINGS:
First of all, let's understand the supertrend and stocrsi indicators.
How do you read and use Super Trend for trading ?
The price is often going upwards when it breaks the super trend line while keeping its position above the indication level.
When the market is in a bullish trend, the indicator becomes green. The indicator level will act as trendline support in such a scenario. The color of the indicator changes to red to indicate a negative trend once the price crosses the support line. The price uses the super trend level as a trendline resistance during a bearish move.
In our strategy, if our 1-hour and 4-hour supertrend lines show the up or down train in the same direction at the same time, we can assume that a train is forming here.
Why do I use the time of 1 hour and 4 hours ?
When I did a backtest from the past to the present, I discovered that the most accurate and consistent time zones are the 1 hour and 4 hour time zones.
By the way we can change our short term timeframe(1H) and long term timeframe(4H) from settings panel.
How do you read and use the Stoch-RSI Indicator?
This indicator analyzes price dynamics automatically to detect overbought and oversold locations.
The indicator includes:
- The primary line, which typically has values between 0 and 100;
- Two dynamic levels for overbought and oversold conditions.
IF our stoch-rsi indicator value has fallen below our lower boundary line, the oversold event has been observed in the price, if our stoch-rsi value breaks up our bottom line after becoming oversold, we think that the price will start the recovery phase.(The case is also true for the opposite.)
However, this does not always apply and we need additional approvals, Therefore, our 1H and 4H supertrrend indicator provides us with additional confirmation.
Buy Condition:
Our 1H(short term) and 4H(long term) supertrrend indicator, has given the buy signal(green line and yellow line), and if our stochrsi indicator has broken our oversold line up on the past 15 bars, the buy signal is formed here.
Sell Condition:
Our 1H(short term) and 4H(long term) supertrrend indicator, has given the sell signal(red line and orange line), and if our stochrsi indicator has broken our overbuy line down on the past 15 bars, the sell signal is formed here.
Stop Loss or Take Profit Conditions:
Exit Long Senerio:
All conditions are completed, the buy signal has arrived and we have entered a LONG trade, the 1-hour supertrend line follows the price rise(yellow line), if the price breaks below the 1-hour super trend line and a sell condition occurs for 1H timeframe for supertrend indcator, LONG trade will exit here.
Exit Short Senerio:
All conditions are completed, the Sell signal has arrived and we have entered a SHORT trade, the 1-hour supertrend line follows the price down(orange line), if the price breaks up the 1-hour super trend line and a buy condition occurs for 1H timeframe for supertrend indcator, SHORT trade will exit here.
What can you change in the settings panel?
1-We can set Start and End date for backtest and future alarms
2-We can set ATR length and Factor for supertrend indicator
3-We can set our short term and long term timeframe value
4-We can set StochRsi Up and Low limit to confirm buy and sell conditions
5-We can set stochrsi retroactive approval length
6-We can set stochrsi values or the length
7-We can set Dollar cost for per position
8- We can choose the direction of our positions, we can set only LONG, only SHORT or both directions.
9-IF you want to place automatic buy and sell orders with this strategy, you can paste your codes into the Long open-close or Short open-close message sections.
For example
IF you write your alert window this code {{strategy.order.alert_message}}.
When trigger Long signal you will get dynamically what you pasted here for Long Open Message
ALSO:
Please do not open trades without properly managing your risk and psychology!!!
If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
