12/26-IT strategyBase of this Strategy is crossover of 12EMA on 26EMA.
Also multiple other criteria has to meet for buy signal, Criterias mentioned below
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There two entry option to select. Either one or both can be selected:
1. Only 12/26 Cross over
a. 12/26 crossover.
b. RSI (14) value to be between a range (RSI is inbuilt, but lower and upper range can be defined in settings)
c. MACD (12, 26) to be positive and above signal line (this is inbuilt)
2. Recent 12/26 Cross over and closing above pivot point(resistance)
a. 12/26 crossover has to be recent, CrossOverLookbackCandles value will look for crossover in # previous candles..
b. RSI (14) value to be between a range (RSI is inbuilt, but lower and upper range can be defined in settings)
c. MACD (12, 26) to be positive and above signal line (this is inbuilt)
d. closing above resistance line
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For Exit we have three options. you can select any SL as per your need, multiple SLs can also be selected
1. Trailing Stop Loss.
Source for TSL is adjustable(open, close, high or low), also you have to mention % below your source TSL has to be placed.
Once closing is below TSL, exit will be triggered.
2. Closing below 7SMA
After 7SMA SL is enabled, 7SMA will be plotted on chart and exit signal will be triggered when closing is below 7SMA.
Choose this option for LESS risk and rewards
3. 12/26 Crossdown
Once 12EMA crossdown below 26EMA, exit will be triggered.
Choose this option for HIGH risk and rewards
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Resistance line is plotted based on left and right candles, if 10(can be changed) is used for both left and right, indicator will look for 10 candles in left and 10 candles in right and if both left and right candle are lower then a line is plotted.
Source has to be selected (close or high)
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Qty mentioned in Buy trigger will be based on BUYVALUE entered
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Multiple Target option is available, if first target is matched how much percentage of qty to be sold can be defined.
If you wish to have only one Target, then exit qty in first target must be 100
Hareketli Ortalamalar
BankNifty_Bullish_Intraday
The script uses following mechanism to give a signal of BUY if multiple parameters evaluated are all passed.
ENTRY-
1. 5 min MACD should be more than its previous tick
2. 15 min MACD should be more than its previous tick
3. 60 min MACD should be more than its previous tick
4. ADX should be more than 12
5. RSI should be more than 60
6. Stochastic %k should have cross over with %d
7. Bollinger band upper band value should be more than previous tick
EXIT
If the 5 min bar price closes below 5 min EMA , it gives an exit signal.
BankNifty_Bearish_Intraday
The script uses following mechanism to give a signal of SELL if multiple parameters evaluated are all passed.
ENTRY-
1. 5 min MACD should be less than its previous tick
2. 15 min MACD should be less than its previous tick
3. 60 min MACD should be less than its previous tick
4. ADX should be more than 12
5. RSI should be less than 40
6. Stochastic %k should have negative cross over with %d
7. Bollinger band lower band value should be less than previous tick
EXIT
If the 5 min bar price closes above 5 min EMA , it gives an exit signal.
RSI and MA with Trailing Stop Loss and Take Profit (by Coinrule)The relative strength index is a momentum indicator used in technical analysis. It measures the speed and magnitude of a coin's recent price changes to evaluate overvalued or undervalued conditions in the price of that coin. The RSI is displayed as an oscillator (a line graph essentially) on a scale of zero to 100. When the RSI reaches oversold levels, it can provide a signal to go long. When the RSI reaches overbought levels, it can mark a good exit point or alternatively, an entry for a short position. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A moving average (MA) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. Essentially it is used to help smooth out price data by creating a constantly updated average price.
The Strategy enters and closes trades when the following conditions are met:
Entry Conditions:
RSI is greater than 50
MA9 is greater than MA50
RSI increases by 5
Exit Conditions:
Price increases by 1% trailing
Price decreases by 2% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
I11L - Meanreverter 4h---Overview---
The system buys fear and sells greed.
Its relies on a Relative Strength Index (RSI) and moving averages (MA) to find oversold and overbought states.
It seems to work best in market conditions where the Bond market has a negative Beta to Stocks.
Backtests in a longer Timeframe will clearly show this.
---Parameter---
Frequency: Smothens the RSI curve, helps to "remember" recent highs better.
RsiFrequency: A Frequency of 40 implies a RSI over the last 40 Bars.
BuyZoneDistance: Spacing between the different zones. A wider spacing reduces the amount of signals and icnreases the holding duration. Should be finetuned with tradingcosts in mind.
AvgDownATRSum: The multiple of the Average ATR over 20 Bars * amount of opentrades for your average down. I choose the ATR over a fixed percent loss to find more signals in low volatility environments and less in high volatility environments.
---Some of my thoughts---
Be very careful about the good backtesting performance in many US-Stocks because the System had a favourable environment since 1970.
Be careful about the survivorship bias as well.
52% of stocks from the S&P500 were removed since 2000.
I discount my Annual Results by 5% because of this fact.
You will find yourself quite often with very few signals because of the high market correlation.
My testing suggests that there is no expected total performance difference between a signal from a bad and a signal from a good market condition but a higher volatility.
I am sharing this strategy because i am currently not able to implement it as i want to and i think that meanreversion is starting to be taken more serious by traders.
The challange in implementing this strategy is that you need to be invested 100% of the time to retrieve the expected annual performance and to reduce the fat tail risk by market crashes.
Wunder Trend Reversal botWunder Trend Reversal bot
1. Wunder Trend Reversal Bot - this has only one goal to find a reversal of the trend.
2. The strategy determines, based on the specified value for the filter, a market reversal based on the price actions of the previous bars.
3. A short EMA is used to filter false signals after the reversal signal was received. Crossing the EMA and changing its direction confirms the trend change.
4. There are 2 ways to calculate stop loss and take profit. You can choose one of them:
- Classic stop loss and take profit in a fixed percentage
- ATR stop loss and take pro
5. ATR uses risk reward (R:R) to calculate take profit. The script calculates the risk-reward based on a certain stop loss level and uses it to calculate the take profit
6. A function for calculating risk on the portfolio (your deposit) has been added to the script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
For example. Deposit - $1000, you set the risk to 1%. SL 5%. Entry volume will be $200. The loss at SL will be $10.10$ this is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contracts” option.
Fast EMA above Slow EMA with MACD (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average . An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the coin when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bullish
EMA8 is greater than EMA26
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include AXSUSDT on the 5-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly.
Additionally, the trailing stop loss and take profit conditions can also be changed to match your needs.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Strategy Myth-Busting #20 - HalfTrend+HullButterfly - [MYN]#20 on the Myth-Busting bench, we are automating the " I Found Super Easy 1 Minute Scalping System And Backtest It 100 Times " strategy from " Jessy Trading " who claims 30.58% net profit over 100 trades in a couple of weeks with a 51% win rate and profit factor of 1.56 on EURUSD .
This one surprised us quite a bit. Despite the title of this strategy indicating this is on the 1 min timeframe, the author demonstrates the backtesting manually on the 5 minute timeframe. Given the simplicity of this strategy only incorporating a couple of indicators, it's robustness being able to be profitable in both low and high timeframes and on multiple symbols was quite refreshing.
The 3 settings which we need to pay most attention to here is the Hull Butterfly length, HalfTrend amplitude and the Max Number Of Bars Between Hull and HalfTrend Trigger. Depending on the timeframe and symbol, these settings greatly impact the performance outcomes of the strategy. I've listed a couple of these below.
And as always, If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 3 open-source public indicators:
Hull Butterfly Oscillator by LuxAlgo
HalfTrend by Everget
Trading Rules
5 min candles but higher / lower candles work too.
Stop loss at swing high/low
Take Profit 1.5x the risk
Long
Hull Butterfly gives us green column, Wait for HalfTrend to present an up arrow and enter trade.
Short
Hull Butterfly gives us a red column , Wait for HalfTrend to present a down arrow and enter trade.
Alternative Trading Settings for different time frames
1 Minute Timeframe
Move the Hull Butterfly length from the default 11 to 9
Move the HalfTrend Amplitude from the default 2 to 1
Enabling ADX Filter with a 25 threshold
2 Hour Timeframe
Move the HalfTrend Amplitude from the default 2 to 1
Laddered Take Profits from 14.5% to 19% with an 8% SL
CM_SlingShotSystem+_CassicEMA+Willams21EMA13 htc1977 editionThis strategy is a combination of 2 indicators based on EMA(actually x3 EMAs and Williams ind.
We usin this to see where EMA fast is above EMA slow(for long), entry position when price hit fast EMA and exit if trend changes or price overbought, or by stoploss 1%.
The opposite for a short position.
For better result You can change every EMA's, stoploss, Willam's ind and other visualisation in settings.
If You find good combination - please, let me know(if You want).
I will check it with ML, and attach it here.
Original indicators will write in comments
Three Bars Play Strategy [JoseMetal]============
ENGLISH
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- Description:
This strategy is based on two simple candlestick patterns (you can pick between 2 variants) with an extra option to require trigger candles to be opposite to the closing one (explained below).
There are several customizable settings such as take profit, stop loss and break even (all based on ATR).
You can customize starting and ending date for the testings.
Other options such as allow switch position if strategy SHORTs when you are LONG and vice versa.
There's an additional optional EMA filter.
- LONG / SHORT ENTRY:
Original pattern: for LONG, current candle must close ABOVE the HIGH of previous candle and the candle 3 positions back, opposite conditions for SHORT.
Variant pattern: for LONG, the current candle must close ABOVE the HIGH of the previous candle and the candle before that one too, opposite conditions for SHORT.
Optional: require the trigger candles to be opposite, ex: for LONG you need the previous candles to be RED (bearish).
Optional: EMA filter, price must be ABOVE for LONGs, below for SHORTs.
- EXIT CONDITION:
Stop Loss or Take Profit, based on ATR.
- Visual:
The script prints the Take Profit as a GREEN line, Stop Loss as a RED line and entry price with a WHITE line.
If enabled, the Break Even required price is BLUE, and the new Stop Loss level (for break even or protecting profit) is AQUA.
- Recommendations:
This strategy is great on DAILY on most assets, including crypto, forex and gold.
12H seems to work in most cases, lower timeframes are worse.
- Customization:
You can customize indicator settings (ATR, EMA...).
Stop Loss and Take Profit ATR multipliers are also customizable.
The break even is optional, required level and break even levels (also based on ATR) are custom too.
Almost everything is customizable, for colors and plotting styles check the "Style" tab.
Enjoy!
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ESPAÑOL
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- Descripción:
Ésta estrategia se basa en dos patrones simples de velas (puedes elegir entre 2 variantes) con una opción extra para requerir que las velas de activación sean opuestas a la de cierre (se explica más adelante).
Hay varios ajustes personalizables como el take profit, el stop loss y el break even (todos basados en el ATR).
Puedes personalizar la fecha de inicio y finalización de las pruebas.
Otras opciones como permitir el cambio de posición si la estrategia cambie a SHORT cuando está LONG y viceversa.
Hay un filtro de EMA opcional adicional.
- ENTRADA LARGA / CORTA:
Patrón original: para LONG, la vela actual debe cerrar POR ENCIMA del ALTO de la vela anterior y de la vela 3 posiciones atrás, condiciones opuestas para SHORT.
Patrón variante: para LONG, la vela actual debe cerrar POR ENCIMA del ALTO de la vela anterior y la vela anterior a esa también, condiciones opuestas para SHORT.
Opcional: requiere que las velas de activación sean opuestas, por ejemplo: para LONG requiere que las velas anteriores sean ROJAS (bajistas).
Opcional: fltro EMA, el precio debe estar POR ENCIMA para los LONGs, por debajo para los SHORTs.
- CONDICIÓN DE SALIDA:
Stop Loss o Take Profit, basado en el ATR.
- Visual:
El script dibuja el Take Profit como una línea VERDE, el Stop Loss como una línea ROJA y el precio de entrada con una línea BLANCA.
Si está habilitado, el precio de break even requerido es AZUL, y el nuevo nivel de Stop Loss (para el break even o asegurar ganancias) es CELESTE.
- Recomendaciones:
Ésta estrategia es estupenda en DIARIO en la mayoría de los activos, incluyendo criptos, fórex y oro.
En 12H parece funcionar en la mayoría de los casos, las temporalidades inferiores son peores.
- Personalización:
Puedes personalizar la configuración de los indicadores (ATR, EMA...).
Los multiplicadores de Stop Loss y Take Profit ATR también son personalizables.
El break even es opcional, el nivel requerido y los niveles de break even (también basados en ATR) son personalizables también.
Casi todo es personalizable, para los colores y estilos de trazado compruebe la pestaña "Estilo".
¡Que lo disfrutes!
The Systems Lab: PRX StrategyLike the PRX Indicator (which is also available) this PRX Strategy includes all the elements necessary to run the PRX Trading System or to incorporate any of its elements into your own analysis. But since this is a strategy it also includes all of the system entry and exit orders which allows them to be displayed on the charts and backtested in different configurations to see how specific configurations of the system could have performed in the past.
The primary concept is the identification of trends by way of a customized PSAR (Parabolic Stop and Reverse) calculation that uses linear regression to reduce market noise and highlight trends for longer using a method pioneered by Dr Ken Long. This means that price can penetrate the PSAR dots without causing a trend reversal to occur (flipping the dots over to the opposing side) which would normally occur with the traditional PSAR idea.
The intent is to help identify and stick with trends longer, adapt to changes in volatility by using linear regression as a noise filter and potentially capture large outlier moves. A linear regression curve is plotted as well in order to help identify when a change in trend will occur by it crossing the PSAR dots.
In order to make the trend as clear as possible the bars can be colored as either up-trend or down-trend with user selectable colors.
A moving average filter is also included as a longer term market condition filter in order to avoid periods when the market is against this average which is an inherent part of the system.
The strategy is currently long only (though we’re working on the short side) and includes standard entries along with a trailing stop using the customized PSAR. It also includes multiple options to re-enter with an existing trend if the trailing stop is hit but the trend remains in place.
Multiple parameters are available for customisation including the Linear Regression length, the Moving Average Filter lookback, enabling of the re-entry and continuation entry signals as well as a date range filter for more specific and repeatable backtesting over different markets and timeframes.
Risk Management is at the core of our system design principles and as such we set and limit the loss for every trade (which is also configurable as a parameter that defaults to $100/trade) and also trail the stop to both reduce risk and capture profit. The position size is calculated automatically and is volatility adjusted based on the initial stop.
Finally, there is a custom dashboard which shows all the relevant details for the current trade at a glance on the chart such as entry, initial stop (size and price), current trailing stop level and P/L in units of R-multiples (’R’ being the initial risk on the trade).
FFT Strategy Bi-Directional Stop/Profit/Trailing + VMA + AroonThis strategy uses the Fast Fourier Transform inspired from the source code of @tbiktag for the Fast Fourier Transform & @lazybear for the VMA filter.
If you are not familiar with the Fast Fourier transform it is a variation of the Discrete Fourier Transform. Veritasium on youtube has a great video on it with a follow up recommendation from 3brown1blue. In short it will extract all the frequencies from a set of data. @tbiktag laid the groundwork for creating the indicator which will allow you to isolate only those signals which are the most relevant and remove the noise. I recommend having @tbiktag's FFT Transform indicator side by side with this to understand what my variation is doing by setting similar settings .
Using this idea, you can then optimize a strategy to the frequencies that are best. The main entry signal is when the FFT Signal crosses above or below the 0 line .
Included with this strategy is the ability to optionally bi-directionally set:
Stop Loss
Trailing Stop Loss
Take Profit
Trailing Take Profit
Entries are optionally further filtered by use of the VMA using the algorithm from LazyBear which allows you to adjust a variable moving average with 3 market trend detections. Green represents upwards momentum; Blue sideways trading and Red downwards momentum. The idea being to filter out buy or sell entries unless the market is moving in that direction, and this makes a big difference as you can see for yourself when you turn it off or on. Turning it off will change the color of the FFT signal to orange instead of the green, blue, red colors .
I have added 2 custom stop loss types as well for experimentation:
1. VMA Filter stop loss to exit the trade if the VMA detects a market trend direction change matching the rules you have set. I have set this to off by default, but it is there so you can see what affect it may have on other tickers. It can increase the profit factor but usually at a cost of net profit.
2. The Aroon Filter stop loss with different lengths for the short or long direction. For the Aroon strategy (which is a trend change detector) it is considered bullish if the upper line (green in my code) is above 70 and the lower line (red in my code) is below 30 and the opposite for the bearish case. With this in mind, I have set it to filter by default only the extreme ends (99 and 1) to increase profit factor and net profit but I encourage you to try different settings and see how it affects things. Turning this off yields much higher net profit but at the cost of the profit factor and drawdown . To disable this just uncheck the 'Use Aroon Filter Long' (or short) and it will also hide the aroon graphics and crosses on the plot.
I will be adding more features in an attempt to lower the drawdown on this strategy but I hope you enjoy what I have so far!
Double Inside Bar & Trend Strategy - KaspricciDouble Inside Bar & Trend Strategy - Kaspricci
This strategy combines the Double Inside Bar candlestick pattern with a trend filter. Once the second inside bar closes and price is above trend moving average, a buy stop order is placed at high of the candle. If price is below trend moving average, a sell stop order is placed at the low of the candle.
This strategy is for educational purposes only! It is not meant to be a financial advice.
Settings
Trend source, type of moving average and length for calculating trend
Stop Loss Type - default: ATR. You can switch between stop loss calculation based on Average True Range value or fixed value.
ATR Length / Factor / TP Ratio - default: 14 / 2.0 / 2.0. Used to calculate the Stop Loss as ATR * Factor and Take Profit as Stop Loss * TP Ratio.
FIX Stop Loss / Take Profit - default: 10 pips / 20 pips. In case you select Stop Loss Type = FIX, these value swill be used.
Risk in % - default: 1%, option to adjust the quantity of a trade based on a defined risk percentage. If enabled, it will overwrite the quantity parameter of the strategy settings.
On top you can filter trades by start and end date as well as time of the day.
EMA RSI Strategy
Simple strategy
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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.
Linear EDCA v1.2Strategy Description:
Linear EDCA (Linear Enhanced Dollar Cost Averaging) is an enhanced version of the DCA fixed investment strategy. It has the following features:
1. Take the 1100-day SMA as a reference indicator, enter the buy range below the moving average, and enter the sell range above the moving average
2. The order to buy and sell is carried out at different "speed", which are set with two linear functions, and you can change the slope of the linear function to achieve different trading position control purposes
3. This fixed investment is a low-frequency strategy and only works on a daily level cycle
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Strategy backtest performance:
BTCUSD (September 2014~September 2022): Net profit margin 26378%, maximum floating loss 47.12% (2015-01-14)
ETHUSD (August 2018~September 2022): Net profit margin 1669%, maximum floating loss 49.63% (2018-12-14)
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How the strategy works:
Buying Conditions:
The closing price of the day is below the 1100 SMA, and the ratio of buying positions is determined by the deviation of the closing price from the moving average and the buySlope parameter
Selling Conditions:
The closing price of the day is above the 1100 SMA, and the ratio of the selling position is determined by the deviation of the closing price and the moving average and the sellSlope parameter
special case:
When the sellOffset parameter>0, it will maintain a small buy within a certain range above the 1100 SMA to avoid prematurely starting to sell
The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
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Version Information:
Current version v1.2 (the first officially released version)
v1.2 version setting parameter description:
defInvestRatio: The default fixed investment ratio, the strategy will calculate the position ratio of a single fixed investment based on this ratio and a linear function. The default 0.025 represents 2.5% of the position
buySlope: the slope of the linear function of the order to buy, used to control the position ratio of a single buy
sellSlope: the slope of the linear function of the order to sell, used to control the position ratio of a single sell
sellOffset: The offset of the order to sell. If it is greater than 0, it will keep a small buy within a certain range to avoid starting to sell too early
maxSellRate: Controls the maximum sell multiple. The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
maxBuyRate: Controls the maximum buy multiple. The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
maPeriod: the length of the moving average, 1100-day MA is used by default
smoothing: moving average smoothing algorithm, SMA is used by default
useDateFilter: Whether to specify a date range when backtesting
settleOnEnd: If useDateFilter==true, whether to close the position after the end date
startDate: If useDateFilter==true, specify the backtest start date
endDate: If useDateFilter==true, specify the end date of the backtest
investDayofweek: Invest on the day of the week, the default is to close on Monday
intervalDays: The minimum number of days between each invest. Since it is calculated on a weekly basis, this number must be 7 or a multiple of 7
The v1.2 version data window indicator description (only important indicators are listed):
MA: 1100-day SMA
RoR%: floating profit and loss of the current position
maxLoss%: The maximum floating loss of the position. Note that this floating loss represents the floating loss of the position, and does not represent the floating loss of the overall account. For example, the current position is 1%, the floating loss is 50%, the overall account floating loss is 0.5%, but the position floating loss is 50%
maxGain%: The maximum floating profit of the position. Note that this floating profit represents the floating profit of the position, and does not represent the floating profit of the overall account.
positionPercent%: position percentage
positionAvgPrice: position average holding cost
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策略说明：
Linear EDCA（Linear Enhanced Dollar Cost Averaging）是一个DCA定投策略的增强版本，它具有如下特性：
1. 以1100日SMA均线作为参考指标，在均线以下进入定买区间，在均线以上进入定卖区间
2. 定买和定卖以不同的“速率”进行，它们用两条线性函数设定，并且你可以通过改变线性函数的斜率，以达到不同的买卖仓位控制的目的
3. 本定投作为低频策略，只在日级别周期工作
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策略回测表现：
BTCUSD（2014年09月~2022年09月）：净利润率26378%，最大浮亏47.12%（2015-01-14）
ETHUSD（2018年08~2022年09月）：净利润率1669%，最大浮亏49.63%（2018-12-14）
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策略工作原理：
买入条件：
当日收盘价在 1100 SMA 之下，由收盘价和均线的偏离度，以及buySlope参数决定买入仓位比例
卖出条件：
当日收盘价在 1100 SMA之上，由收盘价和均线的偏离度，以及sellSlope参数决定卖出仓位比例
特例：
当sellOffset参数>0，则在 1100 SMA以上一定范围内还会保持小幅买入，避免过早开始卖出
单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
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版本信息：
当前版本v1.2（第一个正式发布的版本）
v1.2版本设置参数说明：
defInvestRatio: 默认定投比例，策略会根据此比例和线性函数计算得出单次定投的仓位比例。默认0.025代表2.5%仓位
buySlope: 定买的线性函数斜率，用来控制单次买入的仓位倍率
sellSlope: 定卖的线性函数斜率，用来控制单次卖出的仓位倍率
sellOffset: 定卖的偏移度，如果大于0，则在一定范围内还会保持小幅买入，避免过早开始卖出
maxSellRate: 控制最大卖出倍率。单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
maxBuyRate: 控制最大买入倍率。单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
maPeriod: 均线长度，默认使用1100日MA
smoothing: 均线平滑算法，默认使用SMA
useDateFilter: 回测时是否要指定日期范围
settleOnEnd: 如果useDateFilter==true，在结束日之后是否平仓所持有的仓位平仓
startDate: 如果useDateFilter==true，指定回测开始日期
endDate: 如果useDateFilter==true，指定回测结束日期
investDayofweek: 每次在周几定投，默认在每周一收盘
intervalDays: 每次定投之间的最小间隔天数，由于是按周计算，所以此数字必须是7或7的倍数
v1.2版本数据窗口指标说明（只列出重要指标）：
MA：1100日SMA
RoR%: 当前仓位的浮动盈亏
maxLoss%: 仓位曾经的最大浮动亏损，注意此浮亏代表持仓仓位的浮亏情况，并不代表整体账户浮亏情况。例如当前仓位是1%，浮亏50%，整体账户浮亏是0.5%，但仓位浮亏是50%
maxGain%: 仓位曾经的最大浮动盈利，注意此浮盈代表持仓仓位的浮盈情况，并不代表整体账户浮盈情况。
positionPercent%: 仓位持仓占比
positionAvgPrice: 仓位平均持仓成本
Simple RSI and SMA Long and Short (by Coinrule)The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A simple moving average ( SMA ) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range.
The Strategy enters and closes the trade when the following conditions are met:
LONG
SMA100 is greater than SMA150
RSI is greater than 50
SHORT
SMA100 is less than SMA150
RSI is less than 50
When a long position is opened, it remains open until the conditions for a short are met at which point the long position is closed and the short position is opened. Then, when the conditions for the long position are met, the short will be closed and a long will be opened.
This strategy is back tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Power Trend v1.0Background to the tool
The tool was built out of frustration. Having traded for many years with a reasonable level of success I was always frustrated that my trading never went up a level. The world of trading is filled with people having so much more success than me and this level of FOMO really bothered me and resulted in inconsistency and countless hours sitting in front of a screen, hoping for the best. I also became a little bit of an indicator junkie - was there a holy grail indicator out there for me? I always felt that as a retail trader I was behind the curve. I started to investigate how the major market participants trade and make money and I was astounded at the level of success that they get from creating strategies and sticking to it. The market is driven largely by a "black boxes" which, for us retail traders are outside of our ability to access. I wanted to build a tool that could give me a traders edge.
Another factor that has always bothered me was when reading investing books there is a general assumption that a standard entry, say 8/13 cross over, works on all stocks. However, it is not the case and it can be frustrating for a trader using a set up and not realizing that the set up was/is the problem, not the trader. This realization alone has made a huge impact on my trading. The big boxes that control the market know this already.
Also, a lot of indicators that are available don’t take advantage of the backtesting capability provided in Tradingview. It is fairly simple to find 8-9 trades where a set up worked and then fall into the trade of assuming that it cannot fail. Knowing which set ups work and how frequently it will print will change the way that you trade.
The goal with the tool is to identify setups that have worked in the past with a high degree of profitability, high profit factor and low drawdown and using the planning tool allows you to customize the setup to find exactly what you are looking for across any tradeable asset on TradingView.
Over the past 20 years I have realized the following:
1) Not all entries and signals work the same on all stocks and knowing the historical performance of a strategy is critical
2) Not having a plan in advance lowers your probability of success
3) Developing consistency in analysis is critical
4) Developing confidence in your own plan is more important than whose trades you try to copy
5) Having 30 indicators does not help you trade better - it leads to more frustration
So here is the product of these realisations:
1) The tool looks across the most common entry strategies (RMA / EMA / SMA / HMA / WMA cross on 5 dimensions of type and 5 common crossovers) and can be used on 19 different time frames giving you guidance on what the best set up is for the stock you are analysing
2) It incorporates volatility into the strategy – when stocks are trading outside of a predetermined volatility band, a trade will not be entered. This accommodates traders who tend to get shaken out of trades too early.
3) It looks at the impact of “buying the dip” – often a common strategy employed by many traders which now can be backtested and reviewed to see if it actually helped or hindered the trade.
4) It measures your trade plan against your R – what you are willing to risk – and calculates your target profit based on your R multiple
5) It provides a non repaint signal on your base strategy and provides you with signals to trade smaller or shorter signals within the bigger strategy.
There are some additional visual tools:
• Squeeze signals - I am a big fan of the TTM squeeze however the Squeeze by itself can be hard to trade. Seeing a squeeze fire long on a chart can add to trade confidence.
• Seeing zones of support and resistance rather than single lines can also give you some leeway in terms of not getting pushed out of a trade too soon.
The backtester is always reviewed on a multi year period to get an understanding of win rate %, profit ratio and average duration of trade. As an option trader knowing that a high probability move is playing out allows me to make sure that I don’t undercut the time frame for the expiration of the option relative to the historical average duration of a trade. Backtesting on shorter times is unrealistic.
Key benefits
1) It will save you a ton of time. I don’t have to sit in front of a screen watching ticks each day. I can plan for an entry, set an alert for a trade and when the conditions are met the TradingView system sends me a message and I will go and confirm a trade, execute it, set my alerts for control and move on with my life.
2) It allows me to review trade ideas in a consistent manner using the best trade plan and set up for a stock.
3) It forces me to be patient and not panic (always a good thing). With an adjustable volatility feature I can modify the volatility band in the trade plan to accommodate choppy market conditions.
4) It looks at both sides of the market (long and short) and you can calculate the impact of being market neutral or having a directional bias.
I hope this tool helps you to achieve some degree of peace in your trading.
Gaussian Filter ModifiedAn effort to enhance auto-trading based on Gaussian Filter with Standard Deviation Filtering, Trading True Range and Smoothed SMA was added to remove noise contributing to ranging markets and unwanted entries against established trend.
Gaussian parameters need to be adjusted for different asset pair to find its own "signature", then filter out bad entry with TTR and SMA.
*Credits to Loxx for his work on Gaussian Filter
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!
Strategy Based on Percent of Stocks Above/Below Key MovingThis Strategy looks to buy the market after the percentage of stocks below the 20 SMA moving average drops below 30% and crosses back above it. The strategy outperforms buy and hold on the S&P and more importantly only has a max draw down of 11% which gives it a much better risk adjusted performance then buy and hold alone.
It has three sell rules, 1. When the same indicator crosses into overbought territory. 2. Index Closes below the 200 SMA. 3. Stop Loss is triggered (default is Trailing stop loss).
The indicator used can be found here :
The Strategy has been coded so that all the variables can be adjusted so you can tweak it to get the best performance to whatever market you like. I have hard coded the best variables I could find to trade the AMEX:SPY .
You can track market breadth on the following markets :
Market Tickers Available = SP500 , DJI, NQ, NQ100, R2000, R3000, SP500 Financials, SP500 Materials, SP500 Energy, SP500 Staples, SP500 Discretionary, SP500 Industrials , SP500 Real Estates, Overall Market
The strategy can be used on any of these moving averages : 20, 50, 100, 150, 200
You can adjust the greed and fear levels to change when the strategy takes trades at Overbought and Oversold Levels
Stop Loss
Two Stop losses are available a fixed stop loss based on an ATR value or a trailing % Stop Loss
Regime Filters
Two Regime filters are available:
1. a simple moving average (Strategy wont take trades under the 200 SMA)
2. Advance/Decline Filter Details can be found here:
Date Filter
[Sniper] SuperTrend + SSL Hybrid + QQE MODHi. I’m DuDu95.
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This is the script for the series called "Sniper".
*** What is "Sniper" Series? ***
"Sniper" series is the project that I’m going to start.
In "Sniper" Series, I’m going to "snipe and shoot" the youtuber’s strategy: to find out whether the youtuber’s video about strategy is "true or false".
Specifically, I’m going to do the things below.
1. Implement "Youtuber’s strategy" into pinescript code.
2. Then I will "backtest" and prove whether "the strategy really works" in the specific ticker (e.g. BTCUSDT) for the specific timeframe (e.g. 5m).
3. Based on the backtest result, I will rate and judge whether the youtube video is "true" or "false", and then rate the validity, reliability, robustness, of the strategy. (like a lie detector)
*** What is the purpose of this series? ***
1. To notify whether the strategy really works for the people who watched the youtube video.
2. To find and build my own scalping / day trading strategy that really works.
**********************************************************************************
*** Strategy Description ***
This strategy is from " QQE MOD + supertrend + ssl hybrid" by korean youtuber "코인투데이".
"코인투데이" claimed that this strategy will make you a lot of money in any crypto ticker in 15 minute timeframe.
### Entry Logic
1. Long Entry Logic
- Super Trend Short -> Long
- close > SSL Hybrid baseline upper k
- QQE MOD should be blue
2. Short Entry Logic
- Super Trend Long -> Short
- close < SSL Hybrid baseline lower k
- QQE MOD should be red
### Exit Logic
1. Long Exit Logic
- Super Trend Long -> Short
2. Short Entry Logic
- Super Trend Short -> Long
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
3. SuperTrend and SSL Hybrid Baseline is by default drawn on the chart.
4. If you check EMA filter, EMA would be drawn on the chart.
5. Should add QQE MOD indicator manually if you want to see QQE MOD.
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*** Rating: True or False?
### Rating:
→ 3.5 / 5 (0 = Trash, 1 = Bad, 2 = Not Good, 3 = Good, 4 = Great, 5 = Excellent)
### True or False?
→ True but not a 'perfect true'.
→ It did made a small profit on 15 minute timeframe. But it made a profit so it's true.
→ It worked well in longer timeframe. I think super trend works well so I will work on this further.
### Better Option?
→ Use this for Day trading or Swing Trading, not for Scalping. (Bigger Timeframe)
→ Although the result was not good at 15 minute timeframe, it was quite profitable in 1h, 2h, 4h, 8h, 1d timeframe.
→ Crypto like BTC, ETH was ok.
→ The result was better when I use EMA filter.
### Robust?
→ Yes. Although result was super bad in 5m timeframe, backtest result was "consistently" profitable on longer timeframe (when timeframe was bigger than 15m, it was profitable).
→ Also, MDD was good under risk management option on.
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*** Conclusion?
→ I recommend you not to use this on short timeframe as the youtuber first mentioned.
→ In my opinion, I can use on longer timeframe like 2h or bigger with EMA filter, stoploss and risk management.
Davin's 10/200MA Pullback on SPY Strategy v2.0Strategy:
Using 10 and 200 Simple moving averages, we capitalize on price pullbacks on a general uptrend to scalp 1 - 5% rebounds. 200 MA is used as a general indicator for bullish sentiment, 10 MA is used to identify pullbacks in the short term for buy entries.
An optional bonus: market crash of 20% from 52 days high is regarded as a buy the dip signal.
An optional bonus: can choose to exit on MA crossovers using 200 MA as reference MA (etc. Hard stop on 50 cross 200)
Recommended Ticker: SPY 1D (I have so far tested on SPY and other big indexes only, other stocks appear to be too volatile to use the same short period SMA parameters effectively) + AAPL 4H
How it works:
Buy condition is when:
- Price closes above 200 SMA
- Price closes below 10 SMA
- Price dumps at least 20% (additional bonus contrarian buy the dip option)
Entry is on the next opening market day the day after the buy condition candle was fulfilled.
Sell Condition is when:
- Prices closes below 10 SMA
- Hard stop at 15% drawdown from entry price (adjustable parameter)
- Hard stop at medium term and long term MA crossovers (adjustable parameters)
So far this strategy has been pretty effective for me, feel free to try it out and let me know in the comments how you found :)
Feel free to suggest new strategy ideas for discussion and indicator building
