This strategy utilizes the principle of exponential moving average (EMA) crossovers, combined with the RSI indicator, to determine trend direction for entries and exits.
The strategy uses 3 EMA lines with different periods - fast, medium and slow lines. A buy signal is generated when the fast EMA crosses above the medium EMA, and a sell signal is generated when the fast EMA crosses below the medium EMA.
The strategy also incorporates the RSI indicator to gauge overbought and oversold conditions. The RSI calculates a ratio of average up days to average down days over a period to show the relative strength of an asset. Values above the overbought threshold signal overbought conditions, while values below the oversold threshold signal oversold conditions.
The buy conditions for the strategy are:
The sell conditions are:
Using EMA crossovers to determine trend direction combined with RSI to identify short-term reversal opportunities, this strategy makes use of both trend following and mean reversion concepts.
This strategy combines EMA crossovers and RSI to gauge both trend and overbought/oversold levels, filtering out false breakouts and noisy trades. Using 3 EMA lines gives a clear trend bias.
The RSI settings allow the strategy to time entries and exits at advantageous overbought/oversold areas.
The requirement for price to break all 3 EMA lines before entering trades helps avoid being whipsawed.
Like all backtested strategies, this strategy faces the risk of backtest overfitting. Changing market conditions in live trading may render the optimized parameters unsuitable.
In ranging markets, the strategy may generate false signals and suffer losses.
Poor RSI parameter tuning may lead to missed opportunities or false signals.
Consider adding validation on higher timeframes to avoid noise.
Wait for retest of EMA lines before entering trades to validate signal.
Incorporate other indicators like MACD, Bollinger Bands for combined signal confirmation.
Use machine learning to optimize parameters for robustness.
Consider adding stop loss to exit uncertain trends quickly.
This strategy combines EMA crossovers and RSI to identify trend while taking advantage of short-term reversals. It utilizes both trend following and mean reversion concepts efficiently. There is scope for optimization via signal validation, parameter tuning, stop losses etc. But backtest overfitting needs to be considered, and live performance should be evaluated. Overall, this serves as a useful reference for learning, but requires further validation in live markets.
/*backtest start: 2023-09-24 00:00:00 end: 2023-10-24 00:00:00 period: 1h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/ // © chadsadachai //@version=5 strategy("EMA Cross V1", overlay= true) //rsi length = input.int(title = "Rsi Lenght" , defval=26 , minval=1, maxval=50) overS = input.int(title = "Rsi OVS line" , defval=30 , minval=1, maxval=40) overB = input.int(title = "Rsi OVB line" , defval=70 , minval=1, maxval=100) mLine = input.int(title = "Rsi Medium line" , defval=42 , minval=1, maxval=60) price = close vrsi = ta.rsi(price, length) co = vrsi >= mLine and vrsi < overB cu = ta.crossunder(vrsi, overB) //ema F = input.int(title = "EMA Fast" , defval=17 , minval=1, maxval=50) M = input.int(title = "EMA Medium" , defval=35, minval=1, maxval=100) S = input.int(title = "EMA Slow" , defval=142, minval=1, maxval=200) emaF = ta.ema(price , F) emaM = ta.ema(price , M) emaS = ta.ema(price , S) //plot plot(emaF , color = color.green , linewidth=1) plot(emaM , color = color.yellow , linewidth=1) plot(emaS , color = color.red , linewidth=1) //Time Stamp start = timestamp(input.int(title = "Start Year" , defval=2011 , minval=2011, maxval=2025), input.int(title = "Start Month" , defval=1 , minval=1, maxval=12), input.int(title = "Start Day" , defval=1 , minval=1, maxval=31), 0, 0) end = timestamp(input.int(title = "End Year" , defval=2025 , minval=2011, maxval=2025), input.int(title = "End Month" , defval=1 , minval=1, maxval=12), input.int(title = "End Day" , defval=1 , minval=1, maxval=31), 0, 0) // years = input.int(title = "Year" , defval=2018 , minval=2011, maxval=2025) // months = input.int(title = "Month" , defval=1 , minval=1, maxval=12) // days = input.int(title = "Day" , defval=1 , minval=1, maxval=31) //longCondition Default // longCondition1 = EMA_Fast >= EMA_Slow and EMA_Fast >= EMA_Medium//ta.crossover(EMA_Fast, EMA_Slow) EMA_Fast > EMA_Slow and EMA_Medium > EMA_Slow // longCondition3 = price >= EMA_Medium and price > EMA_Slow // longCondition2 = vrsi >= overSold and vrsi <= overBought //longCondition & shortCondition ETHUSD // 1.price > emaF > emaM > emaS // 2.rsi overcross overS longC1 = price > emaF and price > emaM and price > emaS // longC1 = ta.crossover(emaF, emaM) longC2 = if longC1 co // shortC1 = EMA_Fast < EMA_Medium //and EMA_Fast < EMA_Slow and EMA_Medium < EMA_Slow //and cu // shortC2 = overBought > vrsi //and vrsi < overBought //overSold < vrsi and vrsi < mediumLine // exitLong Condition // 1.price < emaF < emaM < emaS // 2.rsi overcross mediumLine exitLong1 = ta.crossunder(emaF, emaM) //or emaF < emaM//and price < emaM and price < emaF exitLong2 = ta.crossunder(vrsi,mLine) //exitLong3 = price < emaM //strategy.entry if time >=start and time <=end strategy.entry("Buy", strategy.long , when = longC1 and longC2) // if(exitLong1 or exitLong2) strategy.close("Buy" , when = exitLong1 or exitLong2) // exitShort1 = EMA_Fast > EMA_Medium // //exitShort2 = ta.crossover(vrsi , mediumLine) // exitShort2 = ta.crossunder (vrsi,mediumLine) // strategy.close("Short" , when = exitShort1 or exitShort2) // //shortCondition = cu // //if (shortCondition1 and shortCondition2) // //strategy.entry("My Short Entry Id", strategy.short)template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6