The Double Moving Average Reversal strategy is a trend following strategy. It calculates moving averages of different periods to determine if the price trend reverses, in order to capture turning points and achieve buying low and selling high.
This strategy first calculates two sets of moving averages with different periods. One set is long-period moving averages, which is used to determine the overall trend. The other set is short-period moving averages, which is used to determine the local trend. By comparing the relationship between the two sets of moving averages, the strategy judges whether the overall trend has reversed.
Specifically, the strategy first calculates two long-period (e.g. 60-day) moving averages, which are the 60-day simple moving average and the 60-day weighted moving average. This set of moving averages is used to determine the overall trend. In addition, the strategy calculates two short-period (e.g. 5-day) moving averages, which are the 5-day simple moving average and the 5-day weighted moving average. This set of moving averages is used to determine the local trend.
When the short-term moving average crosses above the long-term moving average, it indicates the price has reversed from downtrend to uptrend. The strategy will open long positions. When the short-term moving average crosses below the long-term moving average, it indicates the price has reversed from uptrend to downtrend. The strategy will open short positions.
The specific steps are:
Calculate the 60-day simple moving average nma and 60-day weighted moving average n2ma
Calculate the 5-day simple moving average nma1 and 5-day weighted moving average n2ma1
Compare n2ma1 and nma1: if n2ma1 crosses above nma1, open long positions; if n2ma1 crosses below nma1, open short positions
Compare n2ma and nma: if n2ma crosses above nma and long position is opened, continue holding long; if n2ma crosses below nma and short position is opened, continue holding short
Close positions when price exceeds stop loss or reaches take profit
Repeat the above process to capture trend reversal and achieve buying low and selling high
The advantage of this strategy is that the double moving average combination can sensitively capture the reversal of price trend. The double moving average crossover is a classic technical indicator signal. Also, the combination of different period moving averages can judge both overall and local trends, achieving trend following.
The risk of this strategy is that the double moving average crossover may have false signals, causing mistiming entering or exiting positions, thus increasing trading risk. In addition, moving average systems are prone to wrong signals in range-bound markets. Finally, the double moving average system requires relatively long backtesting period to verify the stability of parameter settings.
The strategy can be optimized in the following aspects:
Optimize the moving average periods to find the best parameter combination
Add other technical indicator filters to avoid false breakouts
Add stop loss and take profit to control single trade risk
Combine with trend trading timing to avoid erroneous trades in sideways markets
Dynamically adjust position sizing to adapt to changing market volatility
In conclusion, the Double Moving Average Reversal strategy captures price trend turning points by comparing different period moving averages, in order to achieve buying low and selling high. Optimizing parameter settings, adding filters, and controlling risks are directions for improving the strategy. When used properly, it can be an effective tool to quantitatively capture trend reversals.
/*backtest start: 2022-10-10 00:00:00 end: 2023-06-08 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=2 // //////////////// Attempt to Reduced ReDraw version ///////////////////// // // Microcana.com strategy by pilotgsms - version 4.20b <<<< Edited by Seaside420 >>>> special thanks to 55cosmicpineapple // Hull_MA_cross added to script strategy("M&H_v420b", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100, calc_on_order_fills= true, calc_on_every_tick=true, pyramiding=0) dt = input(defval=0.0010, title="Decision Threshold", type=float, step=0.0001) dd = input(defval=1, title="Post Signal Bar Delay", type=float, step=1) df = input(defval=5, title="Close Position Bar Delay", type=float, step=1) keh=input(title="Double HullMA Cross",defval=7, minval=1) confidence=(request.security(syminfo.tickerid, 'D', close)-request.security(syminfo.tickerid, 'D', close[1]))/request.security(syminfo.tickerid, 'D', close[1]) prediction = confidence > dt ? true : confidence < -dt ? false : prediction[1] n2ma=2*wma(close,round(keh/2)) nma=wma(close,keh) diff=n2ma-nma,sqn=round(sqrt(keh)) n2ma1=2*wma(close[2],round(keh/2)) nma1=wma(close[2],keh) diff1=n2ma1-nma1,sqn1=round(sqrt(keh)) n1=wma(diff,sqn) n2=wma(diff1,sqn) openlong=prediction[dd] and n1>n2 and strategy.opentrades<1 if (openlong) strategy.entry("Long", strategy.long) openshort=not prediction[dd] and n2>n1 and strategy.opentrades<1 if (openshort) strategy.entry("Short", strategy.short) closeshort=prediction and close<low[df] if (closeshort) strategy.close("Short") closelong=not prediction and close>high[df] if (closelong) strategy.close("Long")