MACD Histogram Strategy of RSI

Author: ChaoZhang, Date: 2023-12-25 11:45:10



This strategy generates trading signals based on the MACD of RSI indicator. It combines the RSI indicator’s ability to judge overbought and oversold levels in the market, as well as MACD’s advantage in determining market trend and momentum changes, to design a strategy that utilizes multiple indicators to provide trading signals.

Strategy Logic

The strategy first calculates the RSI indicator, then computes the MACD based on the RSI indicator. The RSI indicator can determine the overbought and oversold conditions in the market, while the MACD captures changes in market trend and momentum.

Specifically, the strategy first calculates the 14-period RSI indicator. Then based on the RSI, the MACD indicator is computed, including 12 and 26-period EMAs, as well as a 9-period signal line. The MACD histogram is then calculated.

When the MACD histogram crosses above 0, a buy signal is generated. When the MACD histogram crosses below 0, a sell signal is triggered. This way, the strategy utilizes RSI to judge overbought/oversold levels, while also using MACD to determine trend and momentum changes, to generate trade signals.

Advantages of the Strategy

This strategy combines the strengths of both RSI and MACD indicators, allowing for a more comprehensive judgment of market conditions, resulting in more reliable signals.

  1. Using RSI to judge overbought/oversold levels helps with stock selection and preventing false breakouts.

  2. MACD’s judgment of trend and momentum changes makes trade signals clearer.

  3. The combination of RSI and MACD, with judgments based on multiple factors, helps filter out false signals.

Risks of the Strategy

  1. Parameter settings for RSI and MACD affect strategy performance and require tuning and optimization.

  2. The combination of multiple indicators increases strategy complexity and the probability of errors.

  3. MACD trade signals may lag and need to be complemented by other indicators.

Optimization Directions

  1. Optimize RSI and MACD parameters to find best parameter combinations.

  2. Incorporate other indicators like KDJ, Bollinger Bands to form an indicator cluster and improve signal accuracy.

  3. Incorporate stop loss strategies to control per trade loss.

  4. Optimize entry and exit logic to prevent conflicting signals.


This strategy utilizes the combined strengths of RSI and MACD indicators to form trade signals, judging overbought/oversold levels while also considering trend and momentum factors, effectively filtering out false signals and providing quality signals. Next steps involve further enhancements like parameter optimization, stop loss, adding more indicators etc. to improve signal accuracy and reliability.

start: 2022-12-18 00:00:00
end: 2023-12-24 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]


strategy(title = "MACD of RSI", overlay = false)
//////////////////////// RSI ///////////////////////////

src = close, len = input(14, minval=1, title="Length")

up = sma(max(change(src), 0), len)

down = sma(-min(change(src), 0), len)

rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))

//////////////////////// RSI   //////////////////////////

//////////////// MACD  ////////////////////////////

sourcemacd = rsi

fastLength = input(12, minval=1), slowLength=input(26,minval=1)


fastMA = ema(sourcemacd, fastLength)

slowMA = ema(sourcemacd, slowLength)

macd = fastMA - slowMA

signal = ema(macd, signalLength)


swap1 = delta>0?green:red


p1 = plot(macd,color=blue,title='MACD Line')

p2 = plot(signal,color=red,title='Signal')

fill(p1, p2, color=blue)


/////////////////////////MACD  //////////////////////////

// Conditions

longCond = na

sellCond = na

longCond :=  crossover(delta,0)

sellCond :=  crossunder(delta,0)

monthfrom =input(6)

monthuntil =input(12)



if (  longCond   )

    strategy.entry("BUY", strategy.long, stop=close, oca_name="TREND", comment="BUY")



if ( sellCond   )