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Strategy vault / Machine learning

MACD and RSI Based Long Short Trading Strategy

This strategy combines MACD and RSI indicators to implement long and short trading simultaneously, in order to obtain excess returns in unclear trend situations.

Author
ChaoZhang
Complexity
Intermediate · 101 lines
Parameters
11
Backtest bar
1h · intraday
Tested on
BTC/USDT · futures

Overview

This strategy combines MACD and RSI indicators to implement long and short trading simultaneously, in order to obtain excess returns in unclear trend situations.

Strategy Logic

  1. Calculate fast EMA (12-day) and slow EMA (26-day)
  2. Calculate MACD convergence divergence (fast EMA minus slow EMA)
  3. Calculate 9-day moving average of MACD as signal line
  4. Calculate 14-day RSI
  5. Go long when MACD<-0.1, RSI<27 and fast EMA below slow EMA
  6. Go short when MACD>0.125, RSI>81 and fast EMA above slow EMA
  7. Use take profit, stop loss, trailing stop loss to manage positions

Advantage Analysis

  1. Going both long and short can generate excess returns in non-trending markets
  2. Combining trend indicator EMA and reversal indicator RSI improves signal quality
  3. Using trailing stop loss to lock in profits effectively controls loss risk

Risk Analysis

  1. Trading both ways requires more capital to support margin requirements
  2. Prices may hit stop loss on both long and short positions when reversing sharply
  3. Improper parameter settings may cause over-trading

Risk Solutions:

  1. Sufficient capital to support position sizing
  2. Reasonable stop loss distance to avoid over-crowded stops
  3. Optimize parameters to reduce trading frequency

Optimization Directions

  1. Consider combining volatility indicators to improve entry timing
  2. Test different parameter combinations to find optimum
  3. Optimize stop loss strategy based on market conditions, such as trailing stop loss
  4. Use machine learning algorithms to auto-optimize parameters

Summary

This strategy implements dual-directional trading with MACD and RSI combination. Using trailing stop loss to lock in profits can generate excess returns in non-trending markets. The strategy can be further optimized on parameters, stop loss strategies etc. to obtain more consistent excess returns.

Parameters

NameDefaultWhat it controls
v_input_1falseInvert Trade Direction?
v_input_25From Month
v_input_323From Day
v_input_42021From Year
v_input_55To Month
v_input_625To Day
v_input_72021To Year
v_input_82500Take Profit
v_input_9600Stop Loss
v_input_10300Trailing Stop Loss
v_input_1150Trailing Stop Loss Offset

Source Pine Script

/*backtest
start: 2023-09-08 00:00:00
end: 2023-10-08 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
// Revision:        290
// Author:          @Hugo_Moriceau
//study("Moriceau_Crypto_strategies_Long_short_indicator_thesis",overlay=true)

// Pyramide 10 order size 100, every tick

strategy("Moriceau_Crypto_strategies_Long_short_indicator",overlay=true)

// === GENERAL INPUTS ===

fast = 12, slow = 26
fastMA = ema(close, fast)
slowMA = ema(close, slow)

macd = fastMA - slowMA
signal = sma(macd, 9)
rsi = rsi(close,14)

dataB = macd < -0.1  and rsi<27 and fastMA < slowMA
// data1 = macd > 0.125  and rsi>81 and fastMA> slowMA
dataS = macd > 0.125 and rsi > 81 and fastMA > slowMA

tradeInvert     = input(defval = false, title = "Invert Trade Direction?")

// === LOGIC ===

// is fast ma above slow ma?
Achat = macd < -0.1  and rsi < 27 and fastMA < slowMA ? true : false
vente = macd > 0.125 and rsi > 81 and fastMA > slowMA ? true : false

// are we inverting our trade direction?
tradeDirection = vente ? Achat ? false : true : Achat ? true : false

// === Plot Setting ===

plot(fastMA,color=red)
plot(slowMA,color=blue)
barcolor(color=iff(fastMA > slowMA, yellow, na))
barcolor(color=iff(fastMA < slowMA, black, na))
//barcolor(color=iff(macd > 0.12*close , fuchsia, na))
//barcolor(color=iff(macd < -0.1*close , lime, na))
plotchar(dataB, char='B',color=black,size = size.auto,location = location.belowbar,transp= 0)  
plotchar(dataS, char='S',color=black,size = size.auto,location = location.abovebar,transp= 0)

//fast = plot(maFast, title = "FastMA", color = yellow, linewidth = 2, style = line, transp = 50)
//slow = plot(maSlow, title = "SlowMA", color = black, linewidth = 2, style = line, transp = 50)

// === BACKTEST RANGE ===
FromMonth = input(defval = 05, title = "From Month", minval = 1)
FromDay   = input(defval = 23, title = "From Day", minval = 1)
FromYear  = input(defval = 2021, title = "From Year", minval = 2017)
ToMonth   = input(defval = 5, title = "To Month", minval = 1)
ToDay     = input(defval = 25, title = "To Day", minval = 1)
ToYear    = input(defval = 2021, title = "To Year", minval = 2017)


// === STRATEGY RELATED INPUTS ===+
// the risk management inputs
inpTakeProfit   = input(defval = 2500, title = "Take Profit", minval = 28)
inpStopLoss     = input(defval = 600, title = "Stop Loss", minval = 15)
inpTrailStop    = input(defval = 300, title = "Trailing Stop Loss", minval = 5)
inpTrailOffset  = input(defval = 50, title = "Trailing Stop Loss Offset", minval = 1)

// === RISK MANAGEMENT VALUE PREP ===

// if an input is less than 1, assuming not wanted so we assign 'na' value to disable it.

useTakeProfit   = inpTakeProfit  >= 1 ? inpTakeProfit  : na
useStopLoss     = inpStopLoss    >= 1 ? inpStopLoss    : na
useTrailStop    = inpTrailStop   >= 1 ? inpTrailStop   : na
useTrailOffset  = inpTrailOffset >= 1 ? inpTrailOffset : na


// === STRATEGY - LONG POSITION EXECUTION ===

enterLong() => not tradeDirection[1] and tradeDirection 
exitLong() => tradeDirection[1] and not tradeDirection
strategy.entry(id = "Achat", long = true, when = enterLong()) // use function or simple condition to decide when to get in
strategy.close(id = "TP 50% Sell", when = exitLong()) // ...and when to get out

// === STRATEGY - SHORT POSITION EXECUTION ===

enterShort() => tradeDirection[1] and not tradeDirection
exitShort() => not tradeDirection[1] and tradeDirection
strategy.entry(id = "Vente", long = false, when = enterShort())
strategy.close(id = "Vente", when = exitShort())

// === STRATEGY RISK MANAGEMENT EXECUTION ===

// finally, make use of all the earlier values we got prepped
strategy.exit("Vente", from_entry = "Vente", profit = useTakeProfit, loss = useStopLoss, trail_points = useTrailStop, trail_offset = useTrailOffset)
strategy.exit("Short", from_entry = "Achat", profit = useTakeProfit, loss = useStopLoss, trail_points = useTrailStop, trail_offset = useTrailOffset)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-10-09. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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