The moving average pullback strategy tracks the crossovers of price moving averages, and identifies pullback opportunities to make counter-trend trades when golden crosses occur. This strategy utilizes Fibonacci pullback lines to set entry and stop loss/profit taking levels to capture short-term price pullbacks.
The core of this strategy involves two moving averages - the 14-day EMA and the 56-day SMA. It triggers a buy signal when the 14-day EMA crosses above the 56-day SMA from below. Afterwards, the strategy looks back 20 days to find a swing low as support. Combined with the close price at crossover point, Fibonacci pullback lines are plotted, with 1.272 pullback line as entry and 0.618 as exit. Thus the strategy sets an entry point to go short after golden crosses, and takes profit if prices really pull back to 0.618 line.
The key steps of this strategy are:
The above explains the main workflow and logic behind this pullback strategy. It aims to capture opportunities when prices reverse short-term.
The key advantages of this moving average pullback strategy are:
In summary, this is very suitable for short-term mean-reversion style trading. It captures pullback chances to profit. The strategy is also simple and straightforward to implement.
Despite the pros, there are also certain risks to note for this strategy:
To mitigate the risks, we can set a short stop loss timeframe to control losses; also optimize the pullback line ranges to aim for reasonable profit targets.
There is still much room to optimize this moving average pullback strategy:
Test different parameter settings on items like moving average periods, lookback days, Fibonacci multiples etc to find optimum;
Add stop loss mechanisms like multiple stops or trailing stops to better control risks;
Introduce other indicators as FILTERS to avoid unsuitable market conditions;
Optimize position sizing and risk management rules.
Through rigorous testing and optimization, significant improvement can be achieved for this trading strategy.
The moving average pullback strategy is a very practical short-term trading strategy. It captures mean-reverting opportunities when prices pull back in the short run. The strategy idea is simple and easy to grasp. There are still risks that need addressing through optimization and risk control. Overall this is a promising quantitative strategy worthy of further research and application.
/*backtest start: 2022-12-12 00:00:00 end: 2023-12-18 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=2 strategy("MAC Pullback", overlay=true) // Setting up timeperiod for testing startPeriodYear = input(2014, "Backtest Start Year") startPeriodMonth = input(1, "Backtest Start Month") startPeriodDay = input(2, "Backtest Start Day") testPeriodStart = timestamp(startPeriodYear, startPeriodMonth, startPeriodDay, 0, 0) stopPeriodYear = input(2035, "Backtest Stop Year") stopPeriodMonth = input(12, "Backtest Stop Month") stopPeriodDay = input(30, "Backtest Stop Day") testPeriodStop = timestamp(stopPeriodYear, stopPeriodMonth, stopPeriodDay, 0, 0) // Moving Averages ema14 = ema(close, 14) ema28 = ema(close, 28) sma56 = sma(close, 56) // Plot plot(ema14, title="ema14", linewidth=2, color=green) plot(ema28, title="ema28", linewidth=2, color=red) plot(sma56, title="sma56", linewidth=3, color=blue) // Strategy goLong = cross(ema14, sma56) and ema14 > ema28 goShort = cross(ema14, sma56) and ema14 < ema28 // Locate Swing Lows leftBars = input(20) rightBars=input(20) swinglow = pivotlow(close, leftBars, rightBars) plot(swinglow, style=cross, linewidth=8, color=#00FF00, offset=-rightBars) if goLong == true and time >= testPeriodStart and time <= testPeriodStop // We try to make sure that we're catching the first Pullback after the crossover if ema14[12] < sma56[12] pivotpoint = lowest(40)[0] //lowest value of the month as our swing low // We calculate a Fib 1.272 extension (from the previous swing low to // the crossover long entry's open) and use this as our entry target to short the Pullback extensiontarget = ((close[1] - pivotpoint) * 1.27) + pivotpoint shorttarget = ((close[1] - pivotpoint) * 0.618) + pivotpoint strategy.order("Pullback", strategy.short, 5.0, limit=extensiontarget) // I would like to use a trailing stop but for know we just hope to get // filled if the pullback reaches all the way down to the 0.618. // We also place a tight stop loss since we trying to short an uptrend strategy.exit("Pullback Exit", "Pullback", limit=shorttarget, loss=400)template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6