RSI Indicator Based Stock Trading Pyramiding Strategy

This article mainly introduces a stock trading pyramiding strategy designed based on the Relative Strength Index (RSI) indicator. The strategy uses the RSI indicator to determine overbought and oversold areas of…

Pine ScriptMean reversion Volatility RSI

Author: ChaoZhang
Complexity: Intermediate · 107 lines
Parameters: 5
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

Use the RSI indicator to judge whether the stock has entered the overbought or oversold area. RSI below 25 is oversold, and above 80 is overbought.
When the RSI enters the oversold area, start going long. When the RSI enters the overbought area, start going short.
Adopt the pyramiding method, with up to 7 additional purchases. Set take profit and stop loss points after each additional purchase.

Advantage Analysis

Using the RSI indicator to determine the overbought and oversold areas can capture larger price reversal opportunities.
The pyramiding method can obtain relatively better returns when the market moves correctly.
Setting take profit and stop loss after each additional purchase can control risks.

Risk Analysis

The effect of RSI indicator to determine overbought and oversold areas is unstable, and wrong signals may occur.
The number of additional purchases needs to be set reasonably, too many additional purchases will increase risks.
The setting of stop loss points needs to consider volatility, cannot be set too small.

Optimization Directions

Consider combining other indicators to filter RSI signals and improve the accuracy of determining overbought and oversold statuses. Such as KDJ, BOLL and other indicators.
Can set floating stop loss to track price. Adjust dynamically according to volatility and risk control requirements.
Consider using adaptive parameters based on market conditions (bull market, bear market, etc.).

Summary

This strategy combines the RSI indicator with the pyramiding strategy. While judging the overbought and oversold statuses, it can obtain more returns through additional purchases. Although the accuracy of RSI judgment needs to be improved, through reasonable parameter optimization and combination with other indicators, it can form an effective trading strategy. This strategy has some universality and is a relatively simple and straightforward quantitative trading method.

Parameters

Name	Default	What it controls
v_input_1	80	OverBought
v_input_2	25	OverSold
v_input_3	5	RSI Length
v_input_4	3	ProfitTarget_Percent
v_input_5	10	LossTarget_Percent

Source Pine Script

/*backtest
start: 2023-12-30 00:00:00
end: 2024-01-29 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © RafaelZioni

strategy(title='Simple RSI strategy', overlay=false)

SWperiod = 1
look = 0
OverBought = input(80, minval=50)
OverSold = input(25, maxval=50)

bandmx = hline(100)
bandmn = hline(0)

band1 = hline(OverBought)
band0 = hline(OverSold)
//band50 = hline(50, color=black, linewidth=1)
fill(band1, band0, color=color.purple, transp=98)


src = close
len = input(5, minval=1, title="RSI Length")
up = rma(max(change(src), 0), len)
down = rma(-min(change(src), 0), len)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - 100 / (1 + up / down)

p = 100

//scale
hh = highest(high, p)
ll = lowest(low, p)
scale = hh - ll

//dynamic OHLC
dyno = (open - ll) / scale * 100
dynl = (low - ll) / scale * 100
dynh = (high - ll) / scale * 100
dync = (close - ll) / scale * 100

//candle color
color_1 = close > open ? 1 : 0

//drawcandle
hline(78.6)
hline(61.8)
hline(50)
hline(38.2)
hline(23.6)
plotcandle(dyno, dynh, dynl, dync, title="Candle", color=color_1 == 1 ? color.green : color.red)
plot(10, color=color.green)
plot(55, color=color.black)
plot(80, color=color.black)
plot(90, color=color.red)

long = rsi <= OverSold ? 5 : na

//Strategy
golong = rsi <= OverSold ? 5 : na

longsignal = golong  
//based on https://www.tradingview.com/script/7NNJ0sXB-Pyramiding-Entries-On-Early-Trends-by-Coinrule/
//set take profit

ProfitTarget_Percent = input(3)
Profit_Ticks = close * (ProfitTarget_Percent / 100) / syminfo.mintick

//set take profit

LossTarget_Percent = input(10)
Loss_Ticks = close * (LossTarget_Percent / 100) / syminfo.mintick


//Order Placing

strategy.entry("Entry 1", strategy.long, when=strategy.opentrades == 0 and longsignal)

strategy.entry("Entry 2", strategy.long, when=strategy.opentrades == 1 and longsignal)

strategy.entry("Entry 3", strategy.long, when=strategy.opentrades == 2 and longsignal)

strategy.entry("Entry 4", strategy.long, when=strategy.opentrades == 3 and longsignal)

strategy.entry("Entry 5", strategy.long, when=strategy.opentrades == 4 and longsignal)

strategy.entry("Entry 6", strategy.long, when=strategy.opentrades == 5 and longsignal)

strategy.entry("Entry 7", strategy.long, when=strategy.opentrades == 6 and longsignal)



if strategy.position_size > 0
    strategy.exit(id="Exit 1", from_entry="Entry 1", profit=Profit_Ticks, loss=Loss_Ticks)
    strategy.exit(id="Exit 2", from_entry="Entry 2", profit=Profit_Ticks, loss=Loss_Ticks)
    strategy.exit(id="Exit 3", from_entry="Entry 3", profit=Profit_Ticks, loss=Loss_Ticks)
    strategy.exit(id="Exit 4", from_entry="Entry 4", profit=Profit_Ticks, loss=Loss_Ticks)
    strategy.exit(id="Exit 5", from_entry="Entry 5", profit=Profit_Ticks, loss=Loss_Ticks)
    strategy.exit(id="Exit 6", from_entry="Entry 6", profit=Profit_Ticks, loss=Loss_Ticks)
    strategy.exit(id="Exit 7", from_entry="Entry 7", profit=Profit_Ticks, loss=Loss_Ticks)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-30. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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