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Bidirectional EMA Cross Quant Trading Strategy

Author: ChaoZhang, Date: 2024-01-24 17:31:41
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Overview

This strategy uses bidirectional EMA indicators to determine the main trend direction of the market, and combines the RSI indicator as the timing of entry selection, which belongs to the trend following algorithm trading strategy.

Strategy Principle

  1. Calculate multiple groups of EMA with different cycles to identify the main trend direction of the market in three dimensions: short-term, medium-term and long-term
  2. When the short-term EMA crosses above the medium-long term EMA, it is determined that a bullish trend has formed
  3. When the short-term EMA crosses below the medium-long term EMA, it is determined that a bearish trend has formed
  4. Combine the RSI indicator to find suitable entry timing. The RSI indicator can be used to determine overbought and oversold zones
  5. In an uptrend, go long when the RSI indicator is at low levels; In a downtrend, go short when the RSI indicator is at high levels

The above strategy mainly applies the bidirectional EMA indicator to determine the main trend direction, and uses the RSI indicator as the entry signal selection, which belongs to a typical trend following algorithm trading strategy.

Advantage Analysis

The biggest advantage of this strategy is that it can clearly determine the main trend direction of the market, and select a better entry timing based on the RSI indicator. Specific advantages are as follows:

  1. Use multiple sets of EMA to identify the main trend direction of the market under multiple time dimensions
  2. The EMA indicator calculation is simple with less noise, and it determines the main trend of the market accurately and reliably
  3. The RSI indicator can effectively determine entry and stop loss points to significantly optimize return retio
  4. The algorithm structure is clear and easy to understand and modify. It is a typical trend following strategy
  5. It can be flexibly combined with other technical indicators to further improve strategy performance

Risk Analysis

The strategy also has some risks, mainly in the following aspects:

  1. When the trend reverses, the stop loss point may be too idealized, thus increasing losses
  2. Unable to effectively determine the trend reversal point, possibly missing the opportunity to stop loss in time
  3. EMA parameters and RSI parameters need repeated testing and optimization, otherwise it may cause instability
  4. Cannot guarantee that every entry is the perfect timing, there may be unnecessary multiple repetitions
  5. It is difficult to effectively avoid major gaps under the influence of sudden events

To address the above risks, optimizations can be made in the following areas:

  1. Reasonably set stop loss points to prevent excessive losses
  2. Increase other indicators to determine trend reversal to ensure timely stop loss
  3. Optimize parameter combinations to adapt to wider market conditions
  4. Modify entry and stop loss logic to reduce the number of repetitions
  5. Increase exceptions judgment to avoid adverse effects of market gaps

Optimization Directions

From the advantages and risks of this strategy, we can get the following optimizable directions:

  1. On the existing bidirectional EMA framework, introduce indicators like MACD and BOLL for judging trend reversal points, thereby optimizing take profit and stop loss strategies
  2. Introduce machine learning models to predict trend reversal probability and further improve strategy performance
  3. Apply advanced filters to automatically identify abnormal market conditions and effectively prevent losses
  4. Use genetic algorithms, deep reinforcement learning and other methods to automatically optimize parameters so that strategies can adapt to more market types
  5. Add automatic stop loss module, can dynamically adjust stop loss points according to actual situation

Through introducing more indicators, prediction models, parameter optimization, risk control modules and other means, this strategy can be further improved to adapt to more complex and volatile market conditions.

Conclusion

This article detailed introduced the main content of the bidirectional EMA cross quantitative trading strategy. First, it outlined the main ideas and operating principles of the strategy. Then the advantages of the strategy were fully analyzed. At the same time, it also analyzed the main potential risks in the strategy. On this basis, several key optimizable directions were proposed. In summary, this strategy has the advantage of determining the main trend of the market, and also has some room for optimization, which is a typical quantitative trading strategy. Through continuous improvement and optimization, this strategy can become an important choice for investors’ algorithmic trading.

/*backtest
start: 2023-01-23 00:00:00
end: 2024-01-23 00:00:00
period: 4h
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/
// © Investoz
// Indikatorn är byggd som ett utbildningsyfte och är därför ingen rekommendation för köp/sälj av aktier. Tanken är att skapa en visuell form i en graf
// som visar om det finns någon trend såväl positiv som negativ. En dialogruta med en varning talar om vilken trend som råder. I koden finns en möjlighet
// att ta position eller gå ur position om man vill skapa en startegi kring denna trendindikator. Rekommenderar dock starkt att inte enbart förlita sig på denna
// indikator som beslut för köp/sälj då resultaten blir negativa om man köper på psoitiv trend och säljer på negativ trend. Det måste kombineras med andra idéer
// och därför fungerar denna skript mer som ett komplement till sin egen strategi.
// Det är fritt fram för vem som helst att använda sig av denna indikator.  
//@version=4
//Skapar en strategiskript med 5 % av eget kapital som ett exempel. Detta går att ändra i skriptets inställningar, välj egenskaper och sedan ändra orderstorlek
//till ett annat värde av % på eget kapital.
strategy("© Investoz trendvarningar", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=5)
//Lägger till inmatningar till skriptindikatorn. Användaren kan se och redigera inmatningar i objektdialogen efter eget val.
ema1 = input(21, minval=1, maxval=500, title="Lila linje")
valema1=input(true, title="Visa lila linje")
ema2 = input(34, minval=1, maxval=500, title="Blå linje")
valema2=input(true, title="Visa blå linje")
ema3 = input(55, minval=1, maxval=500, title="Grön linje")
valema3=input(true, title="Visa grön linje")
ema4 = input(89, minval=1, maxval=500, title="Gul linje")
valema4=input(true, title="Visa gul linje")
ema5 = input(141, minval=1, maxval=500, title="Orange linje")
valema5=input(true, title="Visa orange linje")
ema6 = input(230, minval=1, maxval=500, title="Röd linje")
valema6=input(true, title="Visa röd linje")
ema7 = input(371, minval=1, maxval=500, title="Röd linje")
valema7=input(true, title="Visa röd linje")
//Inmatningar för antal staplar
startbar = input(1, minval=1, maxval=1, title="Första stapeln")
Endbar = bar_index
//Källa input, stängning. Användaren kan själv byta till vilken källa som önskas.
src = input(close, title="Source")
//Antal staplar sedan den längsta ema började och framåt. 
tid=Endbar + startbar - 371
//EMA loop
aema1 = ema(src, ema1)
bema2 = ema(src, ema2)
cema3 = ema(src, ema3)
dema4 = ema(src, ema4)
eema5 = ema(src, ema5)
fema6 = ema(src, ema6)
gema7 = ema(src, ema7)
//Skriver ut linjer i diagrammet om förhållandet är sant, annars falskt.
h=plot(valema1 ? aema1 : na, title="Lila linje", style=plot.style_line, linewidth=1, color=color.purple)
i=plot(valema2 ? bema2 : na, title="Blå linje", style=plot.style_line, linewidth=1, color=color.blue)
j=plot(valema3 ? cema3 : na, title="Grön linje", style=plot.style_line, linewidth=1, color=color.green)
k=plot(valema4 ? dema4 : na, title="Gul linje", style=plot.style_line, linewidth=1, color=color.yellow)
l=plot(valema5 ? eema5 : na, title="Orange linje", style=plot.style_line, linewidth=1, color=color.orange)
m=plot(valema6 ? fema6 : na, title="Röd linje", style=plot.style_line, linewidth=1, color=color.red)
n=plot(valema7 ? gema7 : na, title="Brun linje", style=plot.style_line, linewidth=1, color=color.maroon)
//Fyller bakgrunden mellan två linjer med en viss färg.
fill(h, i, color = color.purple,transp=34)
fill(i, j, color = color.blue,transp=34)
fill(j, k, color = color.green,transp=34)
fill(k, l, color = color.yellow,transp=34)
fill(l, m, color = color.orange,transp=34)
fill(m, n, color = color.red,transp=34)
//Skapa en algoritm för positiv trend
PositivTrend = crossover(aema1,gema7)?1:0
TrendPositiv = ema(close,1) > aema1 and aema1 > bema2?1:0
//Skapa en algoritm för negativ trend
NegativTrend = crossunder(aema1,gema7)?1:0
TrendNegativ = ema(close,1) < aema1 and aema1 < bema2?1:0
//Skapar en textruta med varningstext för positiv trend
varningtextpositiv = "Varning för positiv trend."+"\n" + "Leta efter att ta position!"
// if PositivTrend
//     varningpositiv=label.new(
//      bar_index, 
//      low,  
//      xloc=xloc.bar_index, 
//      yloc=yloc.price,
//      color=color.black, 
//      textcolor=color.green,
//      text=varningtextpositiv,
//      style=label.style_label_down,
//      textalign=text.align_left)
//Skapar en textruta med varningstext för negativ trend
varningtextnegativ = "Varning för negativ trend."+"\n" + "Leta efter utgången!"
// if NegativTrend
//     varningnegativ=label.new(
//      bar_index, 
//      low,  
//      xloc=xloc.bar_index, 
//      yloc=yloc.price,
//      color=color.black, 
//      textcolor=color.red,
//      text=varningtextnegativ,
//      style=label.style_label_up,
//      textalign=text.align_left)
//Köp om positiv trend
if (PositivTrend) 
    strategy.entry("Ta position", strategy.long, when = PositivTrend)
//Sälj om negativ trend
if (NegativTrend)
    strategy.close("Ta position", when = NegativTrend, comment="Gå ur position")
//Beräkning av positiv trend
vspositiv(positiv)=>valuewhen(Endbar==startbar,positiv,0)
vepositiv(positiv)=>valuewhen(Endbar==Endbar,positiv,0)
positivmean(TrendPositiv)=>
    csumpositiv = cum(TrendPositiv)
//Slut//   
    a = vepositiv(csumpositiv)
//Start//
    b = vspositiv(csumpositiv)
//Slut - Start// 
    (a - b)/(tid)
positivmeanpositiv = positivmean(TrendPositiv) 
//Beräkning av negativ trend
vsnegativ(negativ)=>valuewhen(Endbar==startbar,negativ,0)
venegativ(negativ)=>valuewhen(Endbar==Endbar,negativ,0)
negativmean(TrendNegativ)=>
    csumnegativ = cum(TrendNegativ)
//Slut//   
    a = venegativ(csumnegativ)
//Start//
    b = vsnegativ(csumnegativ)
//Slut - Start// 
    (a - b)/(tid)
negativmeannegativ = negativmean(TrendNegativ) 
//Inmatning av text som ska in i texruta som visar antal staplar i trend
logga = "© Investoz: Trend i tid"+ "\n"
streck = "--------------------------------------------------------"
totalastaplar = "\n" + "Dagar totalt: " + tostring(tid)+ " dagar "+"\n"+ streck + "\n"
totalpositiv = "Dagar totalt i positiv trend "+" 📈 : "  +tostring(positivmeanpositiv*tid, "##.##") +" dagar " + "\n"
totalnegativ = "\n" + "Dagar totalt i negativ trend" + " 📉 : "  +tostring(negativmeannegativ*tid, "##.##") +" dagar " 
//Textruta för antal staplar i trend
// if barstate.ishistory
//     barcountlbl=label.new(
//      bar_index, 
//      low,  
//      xloc=xloc.bar_index, 
//      yloc=yloc.price,
//      color=color.black, 
//      textcolor=color.yellow,
//      text=logga+streck+totalastaplar+totalpositiv+streck+totalnegativ,
//      style=label.style_label_lower_left,
//      textalign=text.align_left)
//     label.delete(barcountlbl[1])
//////////////////////////////////
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