Modified Relative Strength Index Trend Following Strategy

This strategy captures market trends based on the Modified Relative Strength Index (Modified RSI). The main idea of the strategy is to use the crossover signals and histogram signals of the Modified RSI indicator to…

Pine ScriptTrend following RSI EMA

Author: ChaoZhang
Complexity: Intermediate · 77 lines
Parameters: 10
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

Calculate the EMA of price as the input for Modified RSI
Calculate the Modified RSI indicator
Calculate the EMA of Modified RSI as the signal line
Calculate the difference between Modified RSI and signal line as the histogram
When Modified RSI crosses above the signal line and the histogram is greater than 0, generate a buy signal
When Modified RSI crosses below the signal line and the histogram is less than 0, generate a sell signal

Strategy Advantages

The Modified RSI indicator can better capture trends compared to the traditional RSI indicator
Combining the crossover signals and histogram signals of Modified RSI can effectively filter out false signals
Parameters are adjustable and applicable to different markets and timeframes
The program is concise and computationally efficient

Strategy Risks

The Modified RSI indicator is prone to generating false signals in range-bound markets
The capture of trend turning points may have a lag
A single indicator is easily affected by price noise

Strategy Optimization Directions

It can be combined with other trend indicators such as moving averages to improve signal reliability
A stop-loss and take-profit module can be added to control single transaction risk
Parameters can be optimized based on different market characteristics
A position management module can be added to dynamically adjust positions

Summary

This strategy utilizes the characteristics of the Modified RSI indicator to build a trading system from the perspective of trend following. The Modified RSI indicator overcomes some of the defects of the traditional RSI indicator and has relatively strong trend capture ability. However, strategies based on a single indicator often have limitations and need to be improved in combination with other technical means. By optimizing strategy parameters, enriching signal sources, adding risk control modules, and other methods, the stability and profitability of this strategy can be further improved.

Parameters

Name	Default	What it controls
v_input_int_1	13	Price_EMA
v_input_int_2	14	RSI_Period
v_input_int_3	5	RSI_Avg_EMA
v_input_int_4	20	Fast_EMA
v_input_int_5	50	Slow_EMA
v_input_source_1_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_1	#02ac11	(?Histogram)Above Grow
v_input_2	#6ee47d	Fall
v_input_3	#e5939b	Below Grow
v_input_4	#dd0000	Fall

Source Pine Script

/*backtest
start: 2023-03-23 00:00:00
end: 2024-03-28 00:00:00
period: 1d
basePeriod: 1h
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/
// © YogirajDange

//@version=5


// Verical lines


// // Define the times
// t1 = timestamp(year, month, dayofmonth, 09, 15) // 9:15
// t2 = timestamp(year, month, dayofmonth, 11, 15) // 11:15
// t3 = timestamp(year, month, dayofmonth, 13, 15) // 1:15
// t4 = timestamp(year, month, dayofmonth, 15, 25) // 3:25

// // Check if the current bar is on the current day
// is_today = (year(time) == year(timenow)) and (month(time) == month(timenow)) and (dayofmonth(time) == dayofmonth(timenow))

// // Draw a vertical line at each time
// if is_today and (time == t1 or time == t2 or time == t3 or time == t4)
//     line.new(x1 = bar_index, y1 = low, x2 = bar_index, y2 = high, extend = extend.both, color=color.red, width = 1)

strategy('Modified RSI')
col_grow_above = input(#02ac11, "Above   Grow", group="Histogram", inline="Above")
col_fall_above = input(#6ee47d, "Fall", group="Histogram", inline="Above")
col_grow_below = input(#e5939b, "Below Grow", group="Histogram", inline="Below")
col_fall_below = input(#dd0000, "Fall", group="Histogram", inline="Below")
EMA_length = input.int(13, 'Price_EMA', minval=1)
RSI_length = input.int(14, 'RSI_Period', minval=1)
Avg_length = input.int(5, 'RSI_Avg_EMA', minval=1)
fastMA = ta.ema(close, EMA_length)
modrsi = ta.rsi(fastMA, RSI_length)
RSIAVG = ta.ema(modrsi, Avg_length)
plot(modrsi, color=color.rgb(38, 0, 255), linewidth=2)
plot(RSIAVG, color=color.rgb(247, 0, 0))
rsiUpperBand = hline(60, 'RSI Upper Band', color=#099b0e)
//hline(50, "RSI Middle Band", color=color.new(#787B86, 50))
rsiLowerBand = hline(40, 'RSI Lower Band', color=#e90101)

RSI_hist = modrsi - RSIAVG

//plot(RSI_hist,"RSI_Histogram", color = #c201e9, style = plot.style_columns,linewidth= 5)

plot(RSI_hist, title="RSI_Histogram", style=plot.style_columns, color=(RSI_hist>=0 ? (RSI_hist[1] < RSI_hist ? col_grow_above : col_fall_above) : (RSI_hist[1] < RSI_hist ? col_grow_below : col_fall_below)))


/////// Moving Averages 20 50 EMA

fast_ma = input.int(20, minval=2, title="Fast_EMA")
slow_ma = input.int(50, minval=2, title="Slow_EMA")

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

out = ta.ema(src, fast_ma)
out1 = ta.ema(src, slow_ma)

//plot(out, title="20 EMA", color=color.rgb(117, 71, 247), linewidth = 2)
//plot(out1, title="50 EMA", color=color.rgb(0, 0, 0), linewidth = 2)


longCondition = ((ta.crossover(modrsi, RSIAVG)) and (RSI_hist > 0))
if longCondition
    strategy.entry('B', strategy.long)

shortCondition = ((ta.crossunder(modrsi, RSIAVG)) and (RSI_hist < 0))
if shortCondition
    strategy.entry('S', strategy.short)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-03-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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