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Multi-EMA Crossover Trend Following Strategy

Author: ChaoZhang, Date: 2024-01-04 16:22:07
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Overview

The Multi-EMA Crossover Trend Following Strategy combines multiple EMA lines with different parameters to identify trend directions based on crossover signals, aiming to follow trends in the market. It utilizes 7 EMA lines, including periods of 12, 26, 50, 100, 200, 89 and 144, by comparing their crossover situations.

Strategy Logic

The core logic of this strategy is based on the crossover principles of EMA lines. Among EMAs, shorter period EMAs are more sensitive to recent price changes and can reflect near-term trends, while longer period EMAs are less sensitive and represent long-term trends. When a shorter EMA crosses above a longer EMA from below, a “golden cross” is formed, indicating the short-term trend is turning bullish. A “death cross” appears when a shorter EMA crosses below a longer EMA from above, signaling a bearish trend reversal.

This strategy monitors 7 groups of EMA crossovers simultaneously, including 12&26, 12&50, 12&100, 12&200, 12&89 and 12&144 periods. For example, when the 12-day EMA crosses above the 26-day EMA, the strategy will open a long position. It will close the long position when a death cross happens. The same logic applies to other EMA pairs.

Advantage Analysis

The biggest advantage of this strategy is the ability to capture trends across multiple timeframes. By combining multiple EMAs, it can identify both short-term and long-term trends, realizing multi-timeframe trend following. In addition, the strategy performance can be optimized by adjusting EMA parameters.

Risk Analysis

The main risk of this strategy is overfrequent crossover signals when using multiple EMAs together. For example, crossovers between 12-day and 26-day EMAs happen more often than those between 12-day and 200-day lines. Frequent entries and exits may increase trading costs and slippage. Also, EMAs have lagging nature, which may cause untimely trade signals.

To mitigate the risks, EMA periods can be optimized to control crossover frequency at proper levels. Limiting max daily entry numbers or setting stop loss may also restrict risks.

Improvement Directions

The main optimization space lies in adjusting EMA parameters, such as experimenting with more period combinations or trying other moving averages like SMA. Additional filters can also be added to improve signal quality, for example, volume or volatility indicators. Furthermore, stop loss strategies may be used to reduce the impact of market turbulence.

Conclusion

The Multi-EMA Crossover Trend Following Strategy identifies trend directions by comparing crossover situations among multiple EMAs, capturing trends across timeframes. Its advantage is the flexibility to tweak parameters and catch trends on different levels. The drawback is potentially overfrequent signals and increased trading costs. Further improvements can be achieved through parameter optimization and adding supplementary conditions.

/*backtest
start: 2023-12-27 00:00:00
end: 2024-01-03 00:00:00
period: 30m
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
strategy("EMA Trades", overlay=true, pyramiding=4)

src = input(close, title="Source")

shortestLine = input(12, minval=1, title="Shortest Line")
shorterLine = input(26, minval=1, title="Shorter Line")
shortLine = input(50, minval=1, title="Short Line")
middleLine = input(100, minval=1, title="Middle Line")
longLine = input(200, minval=1, title="Long Line")
longerLine = input(89, minval=1, title="Longer Line")
longestLine = input(144, minval=1, title="Longest Line")

shortestLineOutput = ema(src, shortestLine)
shorterLineOutput = ema(src, shorterLine)
shortLineOutput = ema(src, shortLine)
middleLineOutput = ema(src, middleLine)
longLineOutput = ema(src, longLine)
longerLineOutput = ema(src, longerLine)
longestLineOutput = ema(src, longestLine)

//plot(shortestLineOutput, title="Shortest EMA", color=#ffffff)
//plot(shorterLineOutput, title="Shorter EMA", color=#e54fe6)
//plot(shortLineOutput, title="Short EMA", color=#4e6bc3)
//plot(middleLineOutput, title="Middle EMA", color=#1dd6d8)
//plot(longLineOutput, title="Long EMA", color=#d0de10)
//plot(longerLineOutput, title="Longer EMA", color=#ef6a1a)
//plot(longestLineOutput, title="Longest EMA", color=#ff0e0e)

longEnrtyCondition_1 = crossover(shortestLineOutput[1], shorterLineOutput[1]) and shortestLineOutput > shorterLineOutput
longEntryCondition_2 = crossover(shortestLineOutput[1], shortLineOutput[1]) and shortestLineOutput > shortLineOutput
longEnrtyCondition_3 = crossover(shortestLineOutput[1], middleLineOutput[1]) and shortestLineOutput > middleLineOutput
longEntryCondition_4 = crossover(shortestLineOutput[1], longLineOutput[1]) and shortestLineOutput > longLineOutput

shortEnrtyCondition_1 = crossunder(shortestLineOutput[1], shorterLineOutput[1]) and shortestLineOutput < shorterLineOutput
shortEntryCondition_2 = crossunder(shortestLineOutput[1], shortLineOutput[1]) and shortestLineOutput < shortLineOutput
shortEnrtyCondition_3 = crossunder(shortestLineOutput[1], middleLineOutput[1]) and shortestLineOutput < middleLineOutput
shortEntryCondition_4 = crossunder(shortestLineOutput[1], longLineOutput[1]) and shortestLineOutput < longLineOutput

if (longEnrtyCondition_1)
    strategy.entry("Buy1", strategy.long)
    strategy.exit("Sell1")

if (longEntryCondition_2)
    strategy.entry("Buy2", strategy.long)
    strategy.exit("Sell2")

if (longEnrtyCondition_3)
    strategy.entry("Buy3", strategy.long)
    strategy.exit("Sell3")

if (longEntryCondition_4)
    strategy.entry("Buy4", strategy.long)
    strategy.exit("Sell4")

if (shortEnrtyCondition_1)
    strategy.entry("Sell1", strategy.short)
    strategy.exit("Buy1")

if (shortEntryCondition_2)
    strategy.entry("Sell2", strategy.short)
    strategy.exit("Buy2")

if (shortEnrtyCondition_3)
    strategy.entry("Sell3", strategy.short)
    strategy.exit("Buy3")

if (shortEntryCondition_4)
    strategy.entry("Sell4", strategy.short)
    strategy.exit("Buy4")
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