Multi Timeframe RSI Moving Average Crossover Strategy

Pine ScriptTrend following Multi-timeframe Breakout RSI MACD EMA SMA

Author: ChaoZhang
Complexity: Intermediate · 132 lines
Parameters: 23
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The Multi-Timeframe RSI Moving Average Crossover Strategy is a trend following strategy across multiple timeframes. It uses RSI indicators on multiple timeframes and takes a weighted moving average of each timeframe's RSI. The final signals are generated by combining all RSI moving averages into two comprehensive indicators and trading the crossover signals, which is a typical dual moving average crossover system.

Principles

This strategy first calculates RSI indicators on multiple timeframes (1-min, 5-min, 15-min, etc). Then it takes 15-period VMA (weighted moving average) of the RSI for each timeframe to get the RSI moving average lines.

After that, all the RSI moving averages from different timeframes are combined equally into two signals - fast line and slow line. The fast line is a 100-period EMA and the slow line is a 150-period EMA.

When the fast line crosses above the slow line, a buy signal is generated. When the fast line crosses below the slow line, a sell signal is generated. By combining multi-timeframe RSI in this way, the crossover signals can effectively track trends while filtering out short-term market noise.

Advantages

Combining multiple timeframes can smooth price curves and avoid false breakouts effectively.
RSI indicates overbought/oversold levels, avoiding chasing new highs/lows.
Dual moving averages have better holding effect than a single moving average system.
Using VMA instead of SMA reduces the impact of short-term fluctuations.

Risks

Multi-timeframe strategies require extensive parameter tuning, improper settings may cause missing good entries or late entries.
Moving averages have poor curve fitting, underperform at trend turning points.
RSI divergence happens frequently, reversal signals should be watched.

Solutions: Optimize timeframe parameters; Combine with other indicators like MACD to determine trends; Watch out for RSI divergence signals.

Optimization Directions

Optimize the number of timeframes and parameter settings to better capture trends.
Consider adding stop loss to control risks.
Combine other indicators for better decision on trends and divergences.
Test different holding period parameters for best holding effect.

Conclusion

The Multi-Timeframe RSI Moving Average Crossover Strategy generates trading signals by combining RSI indicators from multiple timeframes using a moving average system, which is a typical multi-timeframe trend following strategy. Its strength lies in effectively tracking trends and filtering out noise, but parameter tuning and risk control need attention. With further optimization, it can become a robust trend following system.

Parameters

Name	Default	What it controls
v_input_1	1	Res 01
v_input_2	5	Res 0
v_input_3	15	Res 1
v_input_4	15	Res 2
v_input_5	15	Res 3
v_input_6	30	Res 4
v_input_7	45	Res 5
v_input_8	60	Res 6
v_input_9	15	lengthRSI
v_input_10	15	lengthMA
v_input_11	100	lengthFMA
v_input_12	150	lengthFMA2
v_input_13	true	Long trades 0 or 1
v_input_14	false	Short trades 0 or 1
v_input_15	true	From Month
v_input_16	true	From Day
v_input_17	2020	From Year
v_input_18	true	Thru Month
v_input_19	true	Thru Day
v_input_20	2112	Thru Year
v_input_21	true	Show Date Range
v_input_22	10	Long Stop Loss (%)
v_input_23	10	Short Stop Loss (%)

Source Pine Script

/*backtest
start: 2023-10-16 00:00:00
end: 2023-11-15 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy(title="RSI multitimeframe SMA crossover", shorttitle="RSI multitimeframe strategy", default_qty_type= strategy.percent_of_equity, margin_long=50, default_qty_value=150)

res1 = input(title="Res 01", type=input.resolution, defval="1")
res2 = input(title="Res 0", type=input.resolution, defval="5")
res3 = input(title="Res 1", type=input.resolution, defval="15")
res4 = input(title="Res 2", type=input.resolution, defval="15")
res5 = input(title="Res 3", type=input.resolution, defval="15")
res6 = input(title="Res 4", type=input.resolution, defval="30")
res7 = input(title="Res 5", type=input.resolution, defval="45")
res8 = input(title="Res 6", type=input.resolution, defval="60")



lengthRSI = input(15, minval=1)
lengthMA = input(15, minval=1)
lengthFMA = input(100, minval=1)
lengthFMA2 = input(150, minval=1)
Long_yes = input(defval=1, title="Long trades 0 or 1", minval=0, maxval=1)
Short_yes = input(defval=0, title="Short trades 0 or 1", minval=0, maxval=1)
src = close

// === INPUT BACKTEST RANGE ===
fromMonth = input(defval = 1,    title = "From Month",      type = input.integer, minval = 1, maxval = 12)
fromDay   = input(defval = 1,    title = "From Day",        type = input.integer, minval = 1, maxval = 31)
fromYear  = input(defval = 2020, title = "From Year",       type = input.integer, minval = 1970)
thruMonth = input(defval = 1,    title = "Thru Month",      type = input.integer, minval = 1, maxval = 12)
thruDay   = input(defval = 1,    title = "Thru Day",        type = input.integer, minval = 1, maxval = 31)
thruYear  = input(defval = 2112, title = "Thru Year",       type = input.integer, minval = 1970)

// === INPUT SHOW PLOT ===
showDate  = input(defval = true, title = "Show Date Range", type = input.bool)

// === FUNCTION EXAMPLE ===
start     = timestamp(fromYear, fromMonth, fromDay, 00, 00)        // backtest start window
finish    = timestamp(thruYear, thruMonth, thruDay, 23, 59)        // backtest finish window
window()  => time >= start and time <= finish ? true : false       // create function "within window of time"



// stop loss 
longLossPerc = input(title="Long Stop Loss (%)", type=input.float, minval=0.0, step=0.5, defval=10) * 
   0.01
longStopPrice = strategy.position_avg_price * (1 - longLossPerc)

shortLossPerc = input(title="Short Stop Loss (%)", type=input.float, minval=0.0, step=0.5, defval=10) * 
   0.01
shortStopPrice = strategy.position_avg_price * (1 + shortLossPerc)


rsi1 = rsi(src, lengthRSI)
MA1 = vwma(rsi1, lengthMA)






outD1 = security(syminfo.tickerid, res1, MA1)
outD2 = security(syminfo.tickerid, res2, MA1)
outD3 = security(syminfo.tickerid, res3, MA1)
outD4 = security(syminfo.tickerid, res4, MA1)
outD5 = security(syminfo.tickerid, res5, MA1)
outD6 = security(syminfo.tickerid, res6, MA1)
outD7 = security(syminfo.tickerid, res7, MA1)
outD8 = security(syminfo.tickerid, res8, MA1)




//plot_d0 = outD0
//plot_d1 = outD1
//plot_d2 = outD2
//plot_d3 = outD3
//plot_d4 = outD4
//plot_d5 = outD5
//plot_d6 = outD6

out_multi = ema(outD1+outD2+outD3+outD4+outD5+outD6+outD7+outD8, lengthFMA)
out_multi2 = ema(outD1+outD2+outD3+outD4+outD5+outD6+outD7+outD8, lengthFMA2)
//out_multi1 = outD2+outD3+outD4
//out_multi2 = outD4+outD5+outD6

//col0 = outD0 < 20 ? color.lime : outD0 > 80 ? color.red : color.blue
//col1 = outD1 < 20 ? color.lime : outD1 > 80 ? color.red : color.blue
//col2 = outD2 < 20 ? color.lime : outD2 > 80 ? color.red : color.blue
//col3 = outD3 < 20 ? color.lime : outD3 > 80 ? color.red : color.blue
//col4 = outD4 < 20 ? color.lime : outD4 > 80 ? color.red : color.blue
//col5 = outD5 < 20 ? color.lime : outD5 > 80 ? color.red : color.blue
//col6 = outD6 < 20 ? color.lime : outD6 > 80 ? color.red : color.blue


// plot(plot_d0,linewidth=2, color=col0)
// plot(plot_d1, linewidth=2, color=col1)
// plot(plot_d2,linewidth=2, color=col2)
// plot(plot_d3,linewidth=2, color=col3)
// plot(plot_d4,linewidth=2, color=col4)
// plot(plot_d5,linewidth=2, color=col5)
// plot(plot_d6,linewidth=2, color=col6)

long=(out_multi/8)
short=(out_multi2/8)

plot(long, linewidth=1, color=color.green)
plot(short, linewidth=1, color=color.red)

long1=crossover(long,short)
short1=crossunder(long,short)

h0 = hline(65, "Upper Band", color=color.red, linestyle=hline.style_solid, linewidth=2 )
h1 = hline(35, "Lower Band", color=color.green, linestyle=hline.style_solid, linewidth=2)


strategy.entry("buy", strategy.long, when=long1 and window() and Long_yes > 0) 
if strategy.position_size > 0
    strategy.exit(id="XL STP", stop=longStopPrice)
strategy.close("buy",when=short1 )

strategy.entry("sell", strategy.short, when=short1 and window() and Short_yes > 0) 
if strategy.position_size < 0
    strategy.exit(id="XS STP", stop=shortStopPrice)
strategy.close("buy",when=long1 )

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-16. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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