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.
Komut dosyalarını "the strat" için ara
Bitcoin 30m Swing Trader Long/Short StrategyIntro
I want to share the results of my passionate hobby and the unstoppable chase for a profitable automated trading strategy. It has been created with the intention of trading only Bitcoin. Altcoins are not interesting for me, as I have discovered lots of issues with finding the right parameter values for experiencing a good performance. As altcoins typically follow the trend of bitcoin and characteristically have a high volatility that may cause stop-hunts, I decided to not over complicate this project. I was just aiming for a profitable trading strategy with an acceptable drawdown and enough confidence by a statistically significant number of trades beside a wide backtesting timespan (credits going out to TradingView: Deep Backtesting).
Total time spent on this is approximately 2 years.
Indicators used
RSI: Used for entries and trend reversal spots
MACD: Used for entry and exit optimiziation
ATR: Used for dynamic offsets in trend definition indicator
Custom trend indicator: Self-made indicator, based on simple price action of higher timeframes using pivot points to find support and resistance zones that have formerly been created
Strategy parameters
I have reduced the total parameters used to just a few. It took lots of working hours to find appropriate values along the trading algorithm and I don’t want to overcomplicate it to you.
This strategy is for those, who have been looking for a working strategy. No DIY kit.
Feel free to adapt Take profit or stop loss targets. But it’s not recommended to do so.
How it works
Entries:
I started with a kind of template that I have been using for strategies for a long time. This includes how to find the right Entries during a trend as well as spotting trend reverse opportunities. Here I combine simple indicators like RSI and MACD beside necessary trend conditions. If a target RSI Value is hit, it will enter a trade, after MACD histogram has stopped to fall/rise. Depends on long/short. While we are in a trade and trend reversed, it waits for a specific RSI target level to be hit, to reverse the trade. As simple as it is, it closes the open one and starts a trade in other direction.
Micro trend:
It starts to get more interesting when it comes to trend recognition, as it forms the core of the strategy and discovering appropriate values for it has been very hard. The final trend variable is defined by the responses over higher timeframes of my self-made trend indicator. Executed on the current timeframe, the trend indicator is quite interesting. But for a automated trading strategy it is necessary to deviate trading instructions from higher timeframes trends.
Macro trend:
The same process that happens for micro trend is also applied with much higher timeframes, like 3D or weekly. The basic assumption is, that if we are in a bull or bear run, where retail investors are flooding the markets, we are increasing our take profit targets respectively. This way we can catch bigger moves in bigger trends.
Exits:
Closing a trade generally happens when a TP target (in %) is hit, or the SL (in %) is hit. The strategy has a special treatment with SL’s. After it happens, the strategy is more careful about market conditions and typically waits for a countertrade. The third way of closing a trade has already been mentioned: the reverse trades. They happen during choppy market conditions. The strategy has also special awareness here and tracks, if reverse trades start to happen more often. After a while, it starts to be more restrictive in opening new reverse trades.
Performance
Capabilities and limitations:
As I have already mentioned the strategy is only optimized for bitcoin (Perpetual Futures). This does not mean, it can not be used on other markets, because the algorithm itself is universal appliable. A very hard task was about finding the right parameter values for the strategy performing like this. If you have a special wish to configure this strategy for a specific market, DM me. The strategy has been tested with different configurations on the following timeframes: 30, 15, 10, 5, 1. I have decided to publish the one for 30m TF, because its performance simply convinced me.
Repainting:
It has been tested lots of times against repainting.
Confidence:
The total backtesting performance reaches out to 2019-09-08. So the strategy has been managing to be successful since then, but this does not guarantee that the logic, this strategy follows, is going to continue this level in future.
Commission:
The algorithm is configured with 0.04% commission per trade, as it is on Binance (for Future Market orders).
Ordersize:
Its totally up to you, how much of your total equity should be traded. Nevertheless, I would personally recommend to not exceed 50% ordersize of your equity with this strategy. In the past, you would have had great performance beside a drawdown, that was from psychological point of view good to handle with. This strategy additionally uses STOP LOSSES, so you can never loose you whole ordersize at one trade.
Slippage:
You also must consider about getting slipped when trading this strategy on live markets. Statistically one could assume, that the slippage could be neutral, as it can be both positive or negative. It depends on your execution time, the exchange, on which you are executing trades and market conditions. But keep it in mind, as if you have too much slippage, this strategy would be unprofitable.
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers 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.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Advanced VWAP_Pullback Strategy_Trend-Template QualifierGeneral Description and Unique Features of this Script
Introducing the Advanced VWAP Momentum-Pullback Strategy (long-only) that offers several unique features:
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends. Mark Minervini, a 2x US Investment Champion, developed the Trend-Template, which covers eight different and independent characteristics that can be adjusted and optimized in this trend-following strategy to ensure the best results. The strategy will only trigger buy-signals in case the optimized qualifiers are being met.
2. Our strategy is based on the supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you are day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We have also integrated technical indicators such as the RSI and the MA / VWAP crossover into this strategy to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available in TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
This strategy can be applied to all timeframes from 5 min to daily.
The VWAP Momentum-Pullback Strategy
For the JS-TechTrading VWAP Momentum-Pullback Strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are recommended for algorithmic trading with this startegy.
A further prerequisite for generating a buy signals is that the individual value is in a short-term oversold state (RSI).
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.
Stop-loss limits and profit targets can be set variably. You also have the option to make use of the trailing stop exit strategy.
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
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 Jan 2020 until March 2023
- 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 combination of the Trend-Template and the RSI qualifiers results in a highly selective strategy which only considers 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.
- Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Cloud X MesoHello there fellow Traders!
Thanks for stopping by, so today I will be covering everything you need to to know about this TradingView strategy.
Below I will discuss everything you need to know about this strategy so you can get a full grasp of what the strategy is, the features, what it does, how it works, the benefits of how this strategy can help you, and the results.
What is Cloud X Meso?
-Cloud X Meso is a strategy that consists of 7 indicators to all line up for total confluence to take a buy or sell once all 6 indicators conditions are met. This strategy does not repaint and doesn't require any technical analysis to be used. The strategy can be used on any timeframe, and any instrument.
-I have optimized many different variations for different types of trading instruments of this strategy ready to be used. The difference of this strategy is that these variations do not need any reoptimization to keep up with recent market conditions since there are hardly any inputs used, which prevents common overfitting problems. The main goal was for this strategy to be automated, as well as plug and play or you can officially consider this as set and forever forget.
What does this strategy do?
-The main goal for this strategy is to catch long or short term trends by waiting for all 7 indicators to line up as well as using customized trading times to trade certain sessions where there is high amounts of volume in the market. This strategy doesn't always need to have a clear trending market, since it can also catch short term trends in choppy markets as well. Overall, the strategy tell you when it buys, sells, and exits after all conditions are met.
How does the strategy work?
-The way that this strategy works is when all of the indicators confluences are met. Next, a buy or sell label will print and the candles colors will color blue or red to show that the trade is in the buy or sell position followed along with a magenta colored line which is the trailing stop to follow the trade until the trade exits from the trailing stop being hit or if the strategies exit condition is met.
-The strategy does have a set Take Profit target since it relies on the trailing stop to end the trade. This is beneficial so you can catch any size of a trend move when the strategy is in high volume market sessions. You catch these trends by customizing the settings to toggle on or off certain indicators, functions, configuring a customized trading time, and toggling on or off certain trading days to make a specific approach for fine tuning a pair to trade in a certain time window with high amounts of volume to catch trending moves whether it be a long or short term trend.
Below I will explain each functionality of the strategy for you to better understand the different ways you can adjust the settings of this strategy.
Backtest Settings:
-You can use these settings to determine a start / end date of what results you would like to see in the strategy tester.
-You can determine the $ amount you would like to see on strategy testers results to be in terms of net profit and max drawdown.
-You can choose whether you want the strategy to take buys only, sells only, or buys and sells.
Automation:
-Compatible with Pine Connectors to fully automate this strategy for MT4/5
-It uses a % based risk when placing trades so you won't have to calculate a proper lot size or dollar amount.
-You can also put the symbol of what that strategy will be trading on so you know what pair its trading.
Custom Trading Times:
-When you customize a trading time for the strategy to trade in, the background will turn blue for that specific time window, and you can use the "Session Exit" function to have trades close once the time window ends when toggled on, or you can have the existing trades close on their own when "Session Exit" is toggled off.
Dynamic Trailing:
-The algorithm uses a volatility based indicator to determine proper stop loss placement depending on how volatile the market is. This will prevent you from guesstimating if your stop loss is too big or too small.
-When Dynamic trailing is off, then the strategy will use a Risk Reward based stop loss to trail everytime the trades hits a new Risk Reward target.
-You can also toggle on or off for the stop loss to go to break even once the trade hits a 1:1 Risk Reward.
Directional Bias Settings:
-This indicator is the main directional bias that uses a multi timeframe function to determine the directional bias, you can also use the Exponential Moving Average as a form of directional bias instead, or you can use both of them to work together to find the directional bias. You can also toggle each one on or off
Entry / Exit Settings:
-This indicator also uses a multi timeframe function but it determines the entry and exit for a trade when all confluences are met. You can also toggle the entry and exit functions on or off.
1 Candle Rule:
-This feature is inspired by No Nonsense Forex (NNFX) the main function of this is if your entry doesn't meet all the entry conditions, then the strategy will wait 1 more candle to meet all the entry conditions to take a trade.
No Trade Zone:
-This feature will uses a Volume based indicator to filter out low volume markets. The candles will turn grey to indicate the algorithm not to take trades, and you can also customize the sensitivity of how strong this indicator will filter out the low volume in the markets.
Indicator functions
Each indicator plays a certain role and also meets certain conditions when a buy or sell trade is placed. I will reveal 3 out of 7 of the indicators used to preserve the uniqueness of this strategy but overall, the logic of this strategies main goal is to ride long or short terms trends while getting dynamic Risk Reward trades.
-The first indicator that the strategy uses an Exponential Moving Average that is customizable, and is used as a form of a filter for either a long or short term directional bias to filter out false signals to help the algorithm trade with the trend.
-The second indicator that the strategy uses is an Oscillator which is the Wavetrend and this indicators functionality for the algorithm is used for the its buy and sell signals to line up with all the other indicators for confluence. This indicator can also be toggled on or off for you own preference
-The third indicator used is the Volume indicator, and this is used to give the other indicators the green light to enter a trade if there are high amounts of volume in the market.
What are the benefits of using this algorithm?
Stress Free Trading:
-Once automated, you will no longer need to stare at the charts all day, as well as trying to execute the trades on time or worried that you missed a setup. Or you can choose to take trades manually when a buy or sell signal comes up
Stress Free Risk Management:
-All you have to do is provide a risk % and the algorithm will do the rest of the work calculating the stop loss, exiting trades, etc. No more needing to find the right lot size, or dollar amount, all in all the strategy will manage the trades for you.
Psychology:
-when you choose to have a systematic trading approach, it eliminates a lot bad habits from human nature
What are the results like?
-I have multiple different variations of results of this strategy, but I will share one of the results.
Here is a screenshot below of what this strategy can do from just one of the variations.
The backtest below was done with another variation on simulating a 100k account risking 0.50% per trade.
Thank you for taking the time to read through this whole guide, and I hope this helped you better understand the strategy.
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
Macro Score (DFMA) and Donchian Cloud Score StrategyA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMA - Democratic Fibonacci Moving Average - is a separate indicator that we have released that takes 10 different Fibonacci MAs (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMA line. This helps by creating a consensus on the trend based on moving averages alone. Crossovers of the DFMA with the various Fib MA lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMA line/Fib MA (233) as well as the crosses of the Fib MA (3)/DFMA. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These four signals hold a lighter weight than the MA cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a blue momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score. Long and short thresholds can be determined by the user in the settings menu.
The Donchian Cloud Score is derived from a set of 5 Donchian channels (upper, lower, and basis plotted) defaulted to lengths of 25, 50, 100, 150, and 200. A set of conditions associated with the channels aims to determine ranging versus trending markets. Weights are given to these conditions accordingly, then tallied up to determine the "cloud score", ranging between -25 and 25. In general, a ranging market is determined by a cloud score between -10 and 10, while a positive trending market has a score higher than 10 and a negative trending market has a score lower than -10. That said, long and short thresholds similar to the macro score itself are included in the user settings and set to a default of 5 or -5. The cloud score is plotted as a line in the underlay with coloration reflecting ranging or trending markets (green color above the long threshold, gray between the thresholds, and red below the short threshold). The cloud score is incorporated into the strategy syntax for long and short positions in that the score must be above or below the set threshold for a trade to be placed. A breakdown for the Donchian scoring is as follows:
- Broke the 25-length DC (DC(25)) upper band in the previous 3 bars - +1 if true, 0 if false
- Broke the DC(50) upper band in the previous 3 bars - +2 if true, 0 if false
- Broke the DC(100) upper band in the previous 3 bars - +3 if true, 0 if false
- Broke the DC(150) upper band in the previous 3 bars - +4 if true, 0 if false
- Broke the DC(200) upper band in the previous 3 bars - +5 if true, 0 if false
- Broke the DC(25) lower band in the previous 3 bars - -1 if true, 0 if false
- Broke the DC(50) lower band in the previous 3 bars - -2 if true, 0 if false
- Broke the DC(100) lower band in the previous 3 bars - -3 if true, 0 if false
- Broke the DC(150) lower band in the previous 3 bars - -4 if true, 0 if false
- Broke the DC(200) lower band in the previous 3 bars - -5 if true, 0 if false
- DC(25) basis line above the DC(50) basis line - +1 if true, -1 if false
- DC(25) basis line above the DC(100) basis line - +1 if true, -1 if false
- DC(25)basis line above the DC(150) basis line - +1 if true, -1 if false
- DC(25) basis line above the DC(200) basis line - +1 if true, -1 if false
- DC(50) basis line above the DC(100) basis line - +1 if true, -1 if false
- DC(50) basis line above the DC(150) basis line - +1 if true, -1 if false
- DC(50) basis line above the DC(200) basis line - +1 if true, -1 if false
- DC(100) basis line above the DC(150) basis line - +1 if true, -1 if false
- DC(100) basis line above the DC(200) basis line - +1 if true, -1 if false
- DC(150) basis line above the DC(200) basis line - +1 if true, -1 if false
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. The option for adding in a trailing stop has also been included, with options to choose between an ATR-based trail or a percentage-based trail. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview/Pineconnector Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else. If using Pineconnector, follow the same directions for setting up an alert, but use the ",buy,,risk=" syntax as noted in the tooltips.
Rocket Grid Algorithm - The Quant ScienceThe Rocket Grid Algorithm is a trading strategy that enables traders to engage in both long and short selling strategies. The script allows traders to backtest their strategies with a date range of their choice, in addition to selecting the desired strategy - either SMA Based Crossunder or SMA Based Crossover.
The script is a combination of trend following and short-term mean reversing strategies. Trend following involves identifying the current market trend and riding it for as long as possible until it changes direction. This type of strategy can be used over a medium- to long-term time horizon, typically several months to a few years.
Short-term mean reversing, on the other hand, involves taking advantage of short-term price movements that deviate from the average price. This type of strategy is usually applied over a much shorter time horizon, such as a few days to a few weeks. By rapidly entering and exiting positions, the strategy seeks to capture small, quick gains in volatile market conditions.
Overall, the script blends the best of both worlds by combining the long-term stability of trend following with the quick gains of short-term mean reversing, allowing traders to potentially benefit from both short-term and long-term market trends.
Traders can configure the start and end dates, months, and years, and choose the length of the data they want to work with. Additionally, they can set the percentage grid and the upper and lower destroyers to manage their trades effectively. The script also calculates the Simple Moving Average of the chosen data length and plots it on the chart.
The trigger for entering a trade is defined as a crossunder or crossover of the close price with the Simple Moving Average. Once the trigger is activated, the script calculates the total percentage of the side and creates a grid range. The grid range is then divided into ten equal parts, with each part representing a unique grid level. The script keeps track of each grid level, and once the close price reaches the grid level, it opens a trade in the specified direction.
The equity management strategy in the script involves a dynamic allocation of equity to each trade. The first order placed uses 10% of the available equity, while each subsequent order uses 1% less of the available equity. This results in the allocation of 9% for the second order, 8% for the third order, and so on, until a maximum of 10 open trades. This approach allows for risk management and can help to limit potential losses.
Overall, the Rocket Grid Algorithm is a flexible and powerful trading strategy that can be customized to meet the specific needs of individual traders. Its user-friendly interface and robust backtesting capabilities make it an excellent tool for traders looking to enhance their trading experience.
Macro Score - Dem. Fib. McGinley DynamicsA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMG - Democratic Fibonacci McGinley Dynamic - is a separate indicator that we have released that takes 10 different Fibonacci McGinley Dynamics (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMG line. This helps by creating a consensus on the trend based on these dynamic lines alone. Crossovers of the DFMG with the various McGinley lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMG line/McGinley(233) as well as the crosses of the McGinley(3)/DFMG. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These four signals hold a lighter weight than the McGinley cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a green momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to long and short thresholds for the macro score, defaulted to 5 and -5 respectively.
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. The option for adding in a trailing stop has also been included, with options to choose between an ATR-based trail or a percentage-based trail.
This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview/Pineconnector Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else. If using Pineconnector, follow the same directions for setting up an alert, but use the " ,buy, ,risk=" syntax as noted in the tooltips.
Default Properties for AVAX 20M:
DPO - 35 , uncentered
CMO - 25, open
K/D - 3/3
RSI Stoch Length - 3
Stoch Length - 4
Stoch Source - open
JVB Length - 14
JVB Smoothing - 2
DFMG source - close
Macro Length - 14
TP % - 1.5%
TTP % - 0.005%
SL % - 1.8%, no trail
Alex trading stragedyOverview
This script, named "ALEX TRADING STRATEGY", is a technical trading strategy designed for new investing groups. It uses a combination of various technical indicators to identify potential buying and selling opportunities in the market. The script includes the Relative Strength Index (RSI), Simple Moving Averages (SMA), Exponential Moving Averages (EMA), and Higher High Lower Low (HHLL) strategies to create a complete trading solution.
The user can change the position from long to short in the Input Settings. The script uses bar colors to indicate the current trading position. The script also has exit strategies to help manage the open trades. The user can also set the period for the various indicators used in the strategy.
The script provides various technical indicators and entry/exit signals to make the trading decision easier for the user. It also includes pivot lines, resistance and support levels to help the user make a more informed decision.
This Pine script implements a multi-indicator trading strategy that combines several technical analysis techniques for making trading decisions. The script uses the Relative Strength Index (RSI) to determine overbought and oversold conditions in the market and plots the RSI values on the chart. The RSI values above 70 are considered overbought and plotted as red upward triangles, while the RSI values below 30 are considered oversold and plotted as green downward triangles.
The script also calculates Simple Moving Averages (SMAs) with the user-defined period and plots them along with the Exponential Moving Averages (EMAs) of 20, 50, and 100 periods. Based on the crossover of the close price and the moving averages, the script enters long or short trades. The script sets the trade exit conditions as the low or high crossing the lower or upper band, respectively.
In addition to the moving average crossover, the script uses the highest high and lowest low over a user-defined period to determine long and short entries. The script plots the long and short conditions on the chart as green upward and red downward triangles, respectively. The script allows the user to switch between long and short trades by changing the input settings.
Finally, the script changes the bar colors based on the trade direction, with green bars indicating a long trade, red bars indicating a short trade, and blue bars indicating no trade. Overall, this Pine script provides a comprehensive trading strategy that combines several technical analysis techniques to make informed trading decisions.
HOW TO USE
Input Settings: In the Input Settings section, you can change the long to short position. You can also change the period value (default is 10) used to calculate the Simple Moving Average (SMA) for the Keltner channel.
Indicators: The script uses RSI (Relative Strength Index) with 14 periods as well as multiple EMAs (Exponential Moving Averages) with periods 20, 50, and 100 to help in making trading decisions.
Entry Signals: The script uses two main entry signals: (1) Keltner Channel and (2) HHLL (High-Low). When the closing price crosses above the upper band of the Keltner channel, the script generates a long signal, and when the closing price crosses below the lower band of the Keltner channel, the script generates a short signal. The HHLL strategy generates a long signal when the current high crosses above the highest high of the last "nPeriod" bars, and generates a short signal when the current low crosses below the lowest low of the last "nPeriod" bars.
Exit Signals: The script uses two exit signals: (1) Stop Loss based on Keltner channel and (2) Profit Target based on Keltner channel. The script exits the long position when the closing price crosses below the lower band of the Keltner channel, and the script exits the short position when the closing price crosses above the upper band of the Keltner channel.
To use this script, you will need to have access to a trading platform that supports PineScript, such as TradingView, and attach the script to a chart. The script will then automatically generate entry and exit signals based on the rules described above. It's important to note that this script is just a tool and not a guarantee of profit. As with any trading strategy, it's important to thoroughly test and understand the script before using it for live trading.
Weird Renko StratThis strategy uses Renko, it generates a signal when there is a reversal in Renko. When using historical data, it provides a good entry and an okay exit. However, in a real-time environment, this strategy is subject to repaint and may produce a false signal.
As a result, the backtesting result should not be used as a metric to predict future results. It is highly recommended to forward-test the strategy before using it in real trading. I forward test it from 12/18/2022 to 12/21/2022 in paper trading, using the alert feature in Tradingview. I made 60 trades trading the BTCUSDT BINANCE 3 min with 26 as the param and under the condition that I use 20x margin, compounding my yield, and having 0 trading fee, a steady loss is generated: from $10 to $3.02.
This is quite interesting. As if I flip the signal from "Long" to "Short" and another way too, it will be a steady profit from $10 to $21.85. Hence, if I'm trying to anti-trade the real-time alert signal, the current "4 Days Result" will be good. Nevertheless, I still have to forward-test it for longer to see if it will fail eventually.
Dive into the setting of the strategy
- Margin is the leverage you use. 1 means 1x, 10 means 10x. It affects the backtest yield when you backtest
- Compound Yield button is for compound calculation, disable it to go back to normal backtesting
- Anti Strategy button is to do the opposite direction trade, when the original strat told you to "Long", you "Short" instead. Enable it to use the feature
- Param is the block size for the Renko chart
- Drawdown is just a visual tool for you in case you want to place a stop loss (represent by the semitransparent red area in the chart)
- From date Thru Date is to specify the backtest range of the strategy, This feature is turned off by default. It is controlled by the Max Backtest Timeframe which will be explain below
- Max Backtest Timeframe control the From date Thru Date function, disable it to enable the From Date Thru Date function
Param is the most important input in this strategy as it directly affects performance. It is highly recommended to backtest nearly all the possible parameters before deploying it in real trading. Some factors should be considered:
- Price of the asset (like an asset of 1 USD vs an asset of 10000 USD required different param)
- Timeframe (1-minute param is different than 1-month param)
I believe this is caused by the volatility of the selected timeframe since different timeframe has different volatility. Param should be fine-tuned before usage.
Here is the param I'm using:
BTCUSDT BINANCE 3min: 26
BTCUSDT BINANCE 5min: 28
BTCUSDT BINANCE 1day: 15
Background of the strategy:
- The strategy starts with $10 at the start of backtesting (customizable in setting)
- The trading fee is set to 0.00% which is not common for most of the popular exchanges (customizable in setting)
- The contract size is not a fixed amount, but it uses your balance to buy it at the open price. If you are using the compound mode, your balance will be your current total balance. If you are using the non-compound mode, it will just use the $10 you start with unless you change the amount you start with. If you are using a margin higher than 1, it will calculate the corresponding contract size properly based on your margin. (Only these options are allowed, you are not able to change them without changing the code)
Macro Score - DFMA-BasedA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMA - Democratic Fibonacci Moving Average - is a separate indicator that we have released that takes 10 different Fibonacci MAs (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMA line. This helps by creating a consensus on the trend based on moving averages alone. Crossovers of the DFMA with the various Fib MA lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMA line/Fib MA (233) as well as the crosses of the Fib MA (3)/DFMA. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These foursignals hold a lighter weight than the MA cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a blue momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score (-5/5).
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Default Properties, for AVAX 20M:
DPO - 40, uncentered
CMO - 25, open
K/D - 3/3
RSI Stoch Length - 3
Stoch Length - 4
Stoch Source - open
JVB Length - 25
JVB Smoothing - 2
DFMA source - close
Macro Length - 13
TP % - 1.5%
TTP % - 0.005%
SL % - 2%
MACD + RSI + ADX Strategy (ChatGPT-powered) by TradeSmartThis is a trading strategy made by TradeSmart, using the recommendations given by ChatGPT . As an experiment, we asked ChatGPT on which indicators are the most popular for trading. We used all of the recommendations given, and added more. We ended up with a strategy that performs surprisingly well on many crypto and forex assets. See below for exact details on what logic was implemented and how you can change the parameters of the strategy.
The strategy is a Christmas special , this is how we would like to thank the support of our followers.
The strategy has performed well on Forex, tested on 43 1-hour pairs and turned a profit in 21 cases. Also it has been tested on 51 crypto pairs using the 1-hour timeframe, and turned a profit in 45 cases with a Profit Factor over 1.4 in the top-5 cases. Tests were conducted without commission or slippage, unlike the presented result which uses 0.01% commission and 5 tick slippage.
Some of the top performers were:
SNXUSDT
SOLUSDT
CAKEUSDT
LINKUSDT
EGLDUSDT
GBPJPY
TRYJPY
USDJPY
The strategy was implemented using the following logic:
Entry strategy:
Long entry:
Price should be above the Simple Moving Average (SMA)
There should be a cross up on the MACD (indicated by the color switch on the histogram, red to green)
RSI should be above the 50 level
Volume is above the selected volume-based Exponential Moving Average (EMA)
ADX should also agree to this position: below 50 and over 20, and above the Regularized Moving Average (REMA)
Short entry:
Price should be under the Simple Moving Average (SMA)
There should be a cross down on the MACD (indicated by the color switch on the histogram, red to green)
RSI should be below the 50 level
Volume is above the selected volume-based Exponential Moving Average (EMA)
ADX should also agree to this position: below 50 and over 20, and above the Regularized Moving Average (REMA)
Exit strategy:
Stop Loss will be placed based on ATR value (with 1.5 Risk)
Take profit level will be placed with a 2.5 Risk/Reward Ratio
Open positions will be closed early based on the Squeeze Momentum (Long: change to red, Short: change to green)
NOTE! : The position sizes used in the example is with 'Risk Percentage (current)', according which the position size will be determined such
that the potential loss is equal to % of the current available capital. This means that in most of the cases, the positions are calculated using leverage.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Allow early TP/SL plots: false by default, Checking this option will result in the TP and SL lines to be plotted also on the signal candle rather than just the entry candle. Consider this only when manual trading, since backtest entries does not happen on the signal candle.
Entry Signal:
Fast Length: 12 by default
Slow Length: 26 by default
Source: hlcc4 by default
Signal Smoothing: 9 by default
Oscillator MA Type: EMA by default
Signal Line MA Type: EMA by default
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 14 by default
ATR Smoothing (of the SL): EMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier. Please select only one active stop loss. Default value (if nothing or multiple stop losses are selected) is the 'ATR Based Stop Loss'.
Candle Lookback (of the SL): 10 by default
Base Risk Multiplier: 1.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 2.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exit based on Squeeze Momentum: true by default, a Long position will be closed when Squeeze Momentum turns red inside an open position and a Short position will be closed when Squeeze Momentum turns green inside an open position
BB Length: 20 by default
BB Mult Factor: 1.0 by default
KC Length: 20 by default
KC Mult Factor: 1.5 by default
Use True Range (KC): Yes by default
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 1.5 by default
Order Type: Risk Percentage (current) by default, allows adjustment on how the position size is calculated: Cash: only the set cash ammount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade Risk Percentage (current): position size will be determined such that the potential loss is equal to % of the current available capital Risk Percentage (initial): position size will be determined such that the potential loss is equal to % of the initial capital
Trend Filter:
Use long trend filter: true by default, only enter long if price is above Long MA
Show long trend filter: true by default, plot the selected MA on the chart
MA Type (Long): SMA by default
MA Length (Long): 100 by default
MA Source (Long): close by default
Use short trend filter: true by default, only enter long if price is under Short MA
Show short trend filter: false by default, plot the selected MA on the chart
MA Type (Short): SMA by default
MA Length (Short): 100 by default
MA Source (Short): close by default
Simple RSI Limiter:
Limit using Simple RSI: true by default, if set to 'Normal', only enter long when Simple RSI is lower then Long Boundary, and only enter short when Simple RSI is higher then Short Boundary. If set to 'Reverse', only enter long when Simple RSI is higher then Long Boundary, and only enter short when Simple RSI is lower then Short Boundary.
Simple RSI Limiter Type:
RSI Length: 14 by default
RSI Source: hl2 by default
Simple RSI Long Boundary: 50 by default
Simple RSI Short Boundary: 50 by default
ADX Limiter:
Use ADX Limiter: true by default, only enter into any position (long/short) if ADX value is higher than the Low Boundary and lower than the High Boundary.
ADX Length: 5 by default
DI Length: 5 by default
High Boundary: 50 by default
Low Boundary: 20 by default
Use MA based calculation: Yes by default, if 'Yes', only enter into position (long/short) if ADX value is higher than MA (ADX as source).
MA Type: REMA by default
MA Length: 5 by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: EMA by default
MA Length: 10 by default
Session Limiter:
Show session plots: false by default, show crypto market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Date Range:
Limit Between Dates: false by default
Start Date: Jul 01 2021 00:00:00 by default
End Date: Dec 31 2022 00:00:00 by default
Trading Time:
Limit Trading Time: false by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 1234567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 1234567 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 0930-1600 by default, hours between which the trades can happen. The time is always in the exchange's timezone
Fine-tuning is highly recommended when using other asset/timeframe combinations.
Macro Score -- User-Customized Scores and SignalsA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger. This particular strategy allows the user to choose between 18 different signals to be used in scoring as well as allowing the user to determine the individual weights of each score as well as the overall threshold to determine long or short signals. Weights for each score range between 1 and 5, with 5 being the greatest weight. The overall threshold for long or short is dependent on the total possible weights added together (i.e. if your weights total -10 or +10, a threshold within this range must be used).
The macro score itself is printed in an underlay as a white line that goes between the maximum positive and negative values for all weights added together for this strategy. In addition to the macro score line, a green momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score. The length of the Macro Score's momentum line can be found in the settings.
The current signals to choose from include:
- ADX Threshold - if the Average Directional Index is above a set threshold, signal positive or negative
- CMF Threshold - if the Chaikin Money Flow oscillator is above 0, signal positive; otherwise, signal negative
- CMO > TSI Signal - signal positive if there is a cross of the Chande Momentum Oscillator and the True Strength Index signal line
- CMO Threshold - if the Chande Momentum Oscillator is above 0, signal positive; otherwise, signal negative
- DPO Threshold - if the Detrended Price Oscillator is above 0, signal positive; otherwise, signal negative
- EOM Threshold - if the Ease of Money Oscillator is above 0, signal positive; otherwise, signal negative
- Jurik Threshold - if the Jurik price line (from the Jurik Volatility Bands) is above 0, signal positive; otherwise, signal negative
- MACD Threshold - if the MACD signal line is above 0, signal positive; otherwise, signal negative
- McGinley Cross - a crossover of a fast McGinley Dynamic length line and a slow McGinley Dynamic line signals positive; otherwise, signal negative
- PSAR - if the direction of the PSAR is heading long, signal positive; otherwise, signal negative
- ROC Threshold - if the Rate of Change oscillator is above 0, signal positive; otherwise, signal negative
- RSI Threshold - if the Relative Strength Index is above 50, signal positive; otherwise, signal negative
- Stoch RSI Threshold - if the Stoch RSI is above 50, signal positive; otherwise, signal negative
- Supertrend - if the Supertrend determines long, signal positive; otherwise, signal negative
- TSI Cross - a crossover of the True Strength Index value line and the TSI signal line signals positive; otherwise, signal negative
- TSI Signal Threshold - if the TSI signal line is above 0, signal positive; otherwise, signal negative
- Williams Alligator Cross - if the Williams Alligator lips cross the teeth and jaw, signal positive; otherwise, signal negative
- Williams %R - if the Williams %R is above -50, signal positive; otherwise, signal negative
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Sample setup for SOLUSDT 30M:
- Score 1 - Value 4, PSAR (0.05 start, 0.02 increment, 0.2 max value; sourced open)
- Score 2 - Value 4, Jurik Threshold (JVB Length 25, JVB Smoothing 6, JVB Price Threshold 0)
- Score 3 - Value 5, DPO Threshold (DPO Length 40, uncentered)
- Score 4 - Value 5, CMO Threshold (CMO Length 40, sourced open)
- Score 5 - Value 2, MACD Threshold (Fast Length 12, Slow Length 30, sourced open)
- Macro Length 21
- Long Threshold - -3
- Short Threshold - +3
- Take Profit % - 0.9/0.9
- Trail % - 0.005
- Stop Loss % - 1.4
Sample setup for AVAXUSDT 20M:
- Score 1 - Value 3, TSI Cross (Long Length 25, Short Length 16, Signal Length 17)
- Score 2 - Value 2, TSI Signal Threshold (same settings as the TSI Cross)
- Score 3 - Value 2, Jurik Threshold (JVB Length 20, JVB Smoothing 8, JVB Price Threshold 0)
- Score 4 - Value 2, DPO Threshold (DPO Length 40, uncentered)
- Score 5 - Value 1, Stoch Threshold (K/D 3, RSI (Stoch) Length 10, Stochastic Length 4, sourced open)
- Macro Length 13
- Long Threshold - +5
- Short Threshold - -5
- Take Profit % - 1.2/1.2
- Trail % - 0.005
- Stop Loss % - 1.5
Macro Score - TSI-BasedA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to various TSI (True Strength Index) signals, including a crossover/crossunder of TSI signal and TSI value, a threshold for the TSI Signal (above or below 0), and a crossover/crossunder of the CMO (Chande Momentum Oscillator) and the TSI signal line. Additionally, there are thresholds for DPO (Detrended Price Oscillator, above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These three signals hold a lighter weight than the three TSI signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a red momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score (-6/6).
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
EMA RSI Strategy
Simple strategy
=============
If the last two closes are in ascending order, the rsi is below 50 and ascending, and the current candle is above 200 ema, then LONG. If the last two closes are in descending order, the rsi is above 50 and descending, and the current candle is below 200 ema, then SHORT.
LONG Exit strategy:
ATR: Last 14 day
Lowest: The lowest value of the last 14 candles
Limit points = (Trade Price - Lowest + ATR) * 100000
trail_points : Limit/2
trail_offset = Limit/2
SHORT Exit strategy:
ATR: Last 14 day
Highest: The higher value of the last 14 candles
Limit points = (Trade Price - Highest + ATR) * 100000
trail_points : Limit/2
trail_offset = Limit/2
Backtest results for the AUDUSD pair gave positive results over the last three months.
I am testing this strategy using a python bot in a real environment this week and will update the results at the end of the week.
Disclaimer
This is not financial advice. You should seek independent advice to check how the strategy information relates to your unique circumstances.
We are not liable for any loss caused, whether due to negligence or otherwise arising from the use of, or reliance on, the information provided directly or indirectly by this strategy.
rt maax EMA cross strategythis just sample of our strategies we published with open source, to learning our investor the way of trading and analysis, this strategy just for study and learning
in this strategy we use expontial moving avarage 20 , 50 , 200 and the we build this strategy when the price move up ema 200 and ema 20,50 cross up the 200 ema in this conditions the strargey will open long postion
and the oppisit it is true for short postion in this sitation the price should be under ema 200 and the ema 20 , 50 should cross under 200 ema then the strategy will open the short postion
we try this strategy on forex ,crypto and futures and it give us very good result ,, also we try this postion on multi time frame we find the stragey give us good result on 1 hour time frame .
in the end our advice for you before you use any stratgy you should have the knowledg of the indecators how it is work and also you should have information about the market you trade and the last news for this market beacuse it effect so much on the price moving .
so we hope this strategy give you brefing of the way we work and build our strategy
Multi Trend Cross Strategy TemplateToday I am sharing with the community trend cross strategy template that incorporates any combination of over 20 built in indicators. Some of these indicators are in the Pine library, and some have been custom coded and contributed over time by the beloved Pine Coder community. Identifying a trend cross is a common trend following strategy and a common custom-code request from the community. Using this template, users can now select from over 400 different potential trend combinations and setup alerts without any custom coding required. This Multi-Trend cross template has a very inclusive library of trend calculations/indicators built-in, and will plot any of the 20+ indicators/trends that you can select in the settings.
How it works : Simple trend cross strategies go long when the fast trend crosses over the slow trend, and/or go short when the fast trend crosses under the slow trend. Options for either trend direction are built-in to this strategy template. The script is also coded in a way that allows you to enable/modify pyramid settings and scale into a position over time after a trend has crossed.
Use cases : These types of strategies can reduce the volatility of returns and can help avoid large market downswings. For instance, those running a longer term trend-cross strategy may have not realized half the down swing of the bear markets or crashes in 02', 08', 20', etc. However, in other years, they may have exited the market from time to time at unfavorable points that didn't end up being a down turn, or at times the market was ranging sideways. Some also use them to reduce volatility and then add leverage to attempt to beat buy/hold of the underlying asset within an acceptable drawdown threshold.
Special thanks to @Duyck, @everget, @KivancOzbilgic and @LazyBear for coding and contributing earlier versions of some of these custom indicators in Pine.
This script incorporates all of the following indicators. Each of them can be selected and modified from within the indicator settings:
ALMA - Arnaud Legoux Moving Average
DEMA - Double Exponential Moving Average
DSMA - Deviation Scaled Moving Average - Contributed by Everget
EMA - Exponential Moving Average
HMA - Hull Moving Average
JMA - Jurik Moving Average - Contributed by Everget
KAMA - Kaufman's Adaptive Moving Average - Contributed by Everget
LSMA - Linear Regression , Least Squares Moving Average
RMA - Relative Moving Average
SMA - Simple Moving Average
SMMA - Smoothed Moving Average
Price Source - Plotted based on source selection
TEMA - Triple Exponential Moving Average
TMA - Triangular Moving Average
VAMA - Volume Adjusted Moving Average - Contributed by Duyck
VIDYA - Variable Index Dynamic Average - Contributed by KivancOzbilgic
VMA - Variable Moving Average - Contributed by LazyBear
VWMA - Volume Weighted Moving Average
WMA - Weighted Moving Average
WWMA - Welles Wilder's Moving Average
ZLEMA - Zero Lag Exponential Moving Average - Contributed by KivancOzbilgic
Disclaimer : This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
3Commas Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures , options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
The difference between core script and this interpretation is that this strategy is specially designed for 3Commas bots
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Strength Volatility Killer - The Quant ScienceStrength Volatility Killer - The Quant Science™ is based on a special version of RSI (Relative Strength Index), created with the simple average and standard deviation.
DESCRIPTION
The algorithm analyses the market and opens positions following three different volatility entry conditions. Each entry has a specific and personal exit condition. The user can setting trailing stop loss from user interface.
USER INTERFACE SETTING
Configures the algorithm from the user interface.
AUTO TRADING COMPLIANT
With the user interface, the trader can easily set up this algorithm for automatic trading.
BACKTESTING INCLUDED
The trader can adjust the backtesting period of the strategy before putting it live. Analyze large periods such as years or months or focus on short-term periods.
NO LIMIT TIMEFRAME
This algorithm can be used on all timeframes.
GENERAL FEATURES
Multi-strategy: the algorithm can apply long strategy or short strategy.
Built-in alerts: the algorithm contains alerts that can be customized from the user interface.
Integrated indicator: indicator is included.
Backtesting included: quickly automatic backtesting of the strategy.
Auto-trading compliant: functions for auto trading are included.
ABOUT BACKTESTING
Backtesting refers to the period 13 June 2022 - today, ticker: AVAX/USDT, timeframe 5 minutes.
Initial capital: $1000.00
Commission per trade: 0.03%
3C Reversal Filter v1In essence, this strategy is a heavily smoothed range filter.
This strategy includes a backtester and ability to connect it with your 3 commas bot(See adviced settings below)
The calculation steps below gives an example on how signals are made:
1. Calculating the price movement using ATR, % change, standard deviation etc..
2. Obtaining the smoothed price using SMA.
3. Obtaining the absolute value of the bar-to-bar change.
4. Applying EMA, twice, to the values in step 3.
5. Obtaining the slow trailing line by multiplying the result of step 4 by 1.618.
Think of it as a heavily smoothed price range
If the 1.618 value looks familiar, that’s because it’s used in Fibonacci sequences. You can of course experiment with other values. I’ve seen good results with both 2.618 and 4.236
What does the strategy do?
1. Determine Trend Detection
2. Detect Short-Term Momentum
3commas settings:
-For now you can only use simple bots.
-Create LONG and SHORT bots for the coins you like to trade and set up alerts(You can send long and short signal from the same alert)
-Set TP to 50% the strategy will handle buys and exits based on your inputs.
-Set safety orders to 0. I might add DCA to the strategy if testing proves that to be a good solution.
-When you have made the bots input the bot ID and token adress in the settings of the strategy.
-When creating the alert use this webhook :https://3commas.io/trade_signal/trading_view
-In the message field you use {{strategy.order.alert_message}} as the placeholder.
Statistical Correlation Algorithm - The Quant ScienceStatistical Correlation Algorithm - The Quant Science™ is a quantitative trading algorithm.
ALGORITHM DESCRIPTION
This algorithm analyses the correlation ratios between two assets. The main asset (on the chart), and the secondary asset (set by the user). Then apply the long or short trading strategy.
The algorithm divides trading work into three parts:
1. Correlation analysis
2. Long or short entry
3. Closing trades
Inside the strategy: the algorithm analyses the percentage change yields from a previous session, of the secondary asset. If the variation meets the set condition then it will open a long or short position, on the primary asset. The open position is closed after 'x' number of sessions. Stop loss and take profit can be added to the trade exit parameters.
Logic: analyses the correlation between two assets and looks for a statistical advantage within the correlation.
INDICATOR DESCRIPTION
The algorithm includes a quantitative indicator. This indicator is used for correlation analysis and offers a quick reading of the quantitative data. The blue area shows the correlation ratio values. The yellow histograms show the percentage change in the yields of the main asset. Purple histograms show the percentage change in secondary asset yields.
GENERAL FEATURES
Multi time-frame: the user can set any time-frame for the secondary asset.
Multi asset: the user analyses the conditions on a second asset.
Multi-strategy: the algorithm can apply either the long strategy or the short strategy.
Built-in alerts: the algorithm contains alerts that can be customized from the user interface.
Integrated indicator: the quantity indicator is included.
Backtesting included: automatic backtesting of the strategy is generated based on the values set.
Auto-trading compliant: functions for auto trading are included.
USER INTERFACE SETTINGS
Through the intuitive user interface, you can manage all the parameters of this algorithm without any programming experience. The user interface is extremely descriptive and contains all the information needed to understand the logic of the algorithm and to configure it correctly.
1. Date range: through this function you can adjust the analysis and working period of the algorithm.
2. Asset: through this function you can adjust the secondary asset and its time-frame. You can enter any type of asset, even indices and economic indicators.
3. Asset details: this function is used to adjust the percentage change to be analyzed on the secondary asset. The analysis and input conditions are also chosen.
4. Active long or short strategy: this function is used to set the type of strategy to be used, long or short.
5. Setting algo trading alert: with this function, users can manage alerts for their web-hook.
6. Exit&Money management: with this function the user can adjust the exit periods of each trade and activate or deactivate any stop losses and take profits.
7. Data Value Analysis: this function is used to adjust the parameters for the quantity indicator.
VIDYA Trend StrategyOne of the most common messages I get is people reaching out asking for quantitative strategies that trade cryptocurrency. This has compelled me to write this script and article, to help provide a quantitative/technical perspective on why I believe most strategies people write for crypto fail catastrophically, and how one might build measures within their strategies that help reduce the risk of that happening. For those that don't trade crypto, know that these approaches are applicable to any market.
I will start off by qualifying up that I mainly trade stocks and ETFs, and I believe that if you trade crypto, you should only be playing with money you are okay with losing. Most published crypto strategies I have seen "work" when the market is going up, and fail catastrophically when it is not. There are far more people trying to sell you a strategy than there are people providing 5-10+ year backtest results on their strategies, with slippage and commissions included, showing how they generated alpha and beat buy/hold. I understand that this community has some really talented people that can create some really awesome things, but I am saying that the vast majority of what you find on the internet will not be strategies that create alpha over the long term.
So, why do so many of these strategies fail?
There is an assumption many people make that cryptocurrency will act just like stocks and ETFs, and it does not. ETF returns have more of a Gaussian probability distribution. Because of this, ETFs have a short term mean reverting behavior that can be capitalized on consistently. Many technical indicators are built to take advantage of this on the equities market. Many people apply them to crypto. Many of those people are drawn down 60-70% right now while there are mean reversion strategies up YTD on equities, even though the equities market is down. Crypto has many more "tail events" that occur 3-4+ standard deviations from the mean.
There is a correlation in many equities and ETF markets for how long an asset continues to do well when it is currently doing well. This is known as momentum, and that correlation and time-horizon is different for different assets. Many technical indicators are built based on this behavior, and then people apply them to cryptocurrency with little risk management assuming they behave the same and and on the same time horizon, without pulling in the statistics to verify if that is actually the case. They do not.
People do not take into account the brokerage commissions and slippage. Brokerage commissions are particularly high with cryptocurrency. The irony here isn't lost to me. When you factor in trading costs, it blows up most short-term trading strategies that might otherwise look profitable.
There is an assumption that it will "always come back" and that you "HODL" through the crash and "buy more." This is why Three Arrows Capital, a $10 billion dollar crypto hedge fund is now in bankruptcy, and no one can find the owners. This is also why many that trade crypto are drawn down 60-70% right now. There are bad risk practices in place, like thinking the martingale gambling strategy is the same as dollar cost averaging while also using those terms interchangeably. They are not the same. The 1st will blow up your trade account, and the 2nd will reduce timing risk. Many people are systematically blowing up their trade accounts/strategies by using martingale and calling it dollar cost averaging. The more risk you are exposing yourself too, the more important your risk management strategy is.
There is an odd assumption some have that you can buy anything and win with technical/quantitative analysis. Technical analysis does not tell you what you should buy, it just tells you when. If you are running a strategy that is going long on an asset that lost 80% of its value in the last year, then your strategy is probably down. That same strategy might be up on a different asset. One might consider a different methodology on choosing assets to trade.
Lastly, most strategies are over-fit, or curve-fit. The more complicated and more parameters/settings you have in your model, the more likely it is just fit to historical data and will not perform similar in live trading. This is one of the reasons why I like simple models with few parameters. They are less likely to be over-fit to historical data. If the strategy only works with 1 set of parameters, and there isn't a range of parameters around it that create alpha, then your strategy is over-fit and is probably not suitable for live trading.
So, what can I do about all of this!?
I created the VIDYA Trend Strategy to provide an example of how one might create a basic model with a basic risk management strategy that might generate long term alpha on a volatile asset, like cryptocurrency. This is one (of many) risk management strategies that can reduce the volatility of your returns when trading any asset. I chose the Variable Index Dynamic Average (VIDYA) for this example because it's calculation filters out some market noise by taking into account the volatility of the underlying asset. I chose a trend following strategy because regressions are capturing behaviors that are not just specific to the equities market.
The more volatile an asset, the more you have to back-off the short term price movement to effectively trend-follow it. Otherwise, you are constantly buying into short term trends that don't represent the trend of the asset, then they reverse and loose money. This is why I am applying a trend following strategy to a 4 hour chart and not a 4 minute chart. It is also important to note that following these long term trends on a volatile asset exposes you to additional risk. So, how might one mitigate some of that risk?
One of the ways of reducing timing risk is scaling into a trade. This is different from "doubling down" or "trippling down." It is really a basic application of dollar cost averaging to reduce timing risk, although DCA would typically happen over a longer time period. If it is really a trend you are following, it will probably still be a trend tomorrow. Trend following strategies have lower win rates because the beginning of a trend often reverses. The more volatile the asset, the more likely that is to happen. However, we can reduce risk of buying into a reversal by slowly scaling into the trend with a small % of equity per trade.
Our example "VIDYA Trend Strategy" executes this by looking at a medium-term, volatility adjusted trend on a 4 hour chart. The script scales into it with 4% of the account equity every 4-hours that the trend is still up. This means you become fully invested after 25 trades/bars. It also means that early in the trade, when you might be more likely to experience a reversal, most of your account equity is not invested and those losses are much smaller. The script sells 100% of the position when it detects a trend reversal. The slower you scale into a trade, the less volatile your equity curve will be. This model also includes slippage and commissions that you can adjust under the "settings" menu.
This fundamental concept of reducing timing risk by scaling into a trade can be applied to any market.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
