Dynamic RSI and CCI Combined Multi factor Quantitative Trading Strategy

This strategy combines dynamic RSI, CCI and multiple MA moving averages to implement a multi-factor driven quantitative trading strategy. The strategy takes into account multiple dimensions such as trend, overbought…

Pine ScriptMean reversion Trend following RSI SMA Stochastic CCI

Author: ChaoZhang
Complexity: Intermediate · 93 lines
Parameters: 15
Backtest bar: 1m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

Technical Indicators

MA: Calculates average closing price over a period to determine price trend
RSI: Judges overbought and oversold levels
CCI: Judges overbought and oversold status
Stoch KDJ: Judges deviation of stochastic from main trend

Trading Signals

Buy signal: MA12 crosses over MA26, CCI below 100 (oversold), Stoch KDJ below 80 (oversold)

Sell signal: RSI crosses below dynamic threshold, Stoch KDJ above 80 (overbought)

Advantages

Multi-factor driven, comprehensive judgment, lower false signals
Dynamic threshold for sellable, real-time overbought and oversold detection
Combines trend, stochastic, mainstream technical indicators
Adopts multiple parameter tuning, high flexibility

Risks

Overly complex multi-factor combination, difficult parameter tuning
Performance highly related to parameter selection
Requires strict quantitative process for parameter optimization
High curve fitting risk

Optimization

More dataset testing for strategy robustness
Multiple parameter combination testing to find optimum
Add stop loss to reduce maximum drawdown
Add position sizing to avoid chasing and killing
Test adaptability across different products

Conclusion

This strategy combines multiple technical indicators and multi-factor driven judgments with parameter tuning and statistical validation to achieve good results. But higher complexity, need to prevent overfitting, and control position sizing and stop loss to reduce maximum drawdown. Can further expand strategy across products and timeframes.

Parameters

Name	Default	What it controls
v_input_1	12	Length
v_input_2_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_3	26	Length
v_input_4_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_5	3	smoothK_1
v_input_6	3	smoothD_1
v_input_7	14	lengthRSI
v_input_8	14	lengthStoch
v_input_9_close	0	RSI Source_1: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_10	4	smoothK_2
v_input_11	3	smoothD_2
v_input_12	5	lengthRSI_2
v_input_13	5	lengthStoch_2
v_input_14_close	0	RSI Source_2: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_15	true	buyCondition

Source Pine Script

/*backtest
start: 2023-11-19 00:00:00
end: 2023-11-26 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy(title="ATOM2.0", shorttitle="ATOM V2.0", overlay=false, default_qty_type=strategy.cash, currency=currency.USD, initial_capital=200, default_qty_type=strategy.cash, default_qty_value=100, pyramiding=10)

// Set Parameter MA12
len12 = input(12, minval=1, title="Length")
src12 = input(close, title="Source")
ma12 = sma(src12, len12)
//plot(ma12, color=color.blue, title="MA12")

// Set Parameter MA26
len26 = input(26, minval=1, title="Length")
src26 = input(close, title="Source")
ma26 = sma(src26, len26)
//plot(ma26, color=color.orange, title="MA12")

//Stochastic RSI 14,3,3
smoothK_1 = input(3, minval=1)
smoothD_1 = input(3, minval=1)
lengthRSI = input(14, minval=1)
lengthStoch = input(14, minval=1)
src_1 = input(close, title="RSI Source_1")

rsi1 = rsi(src_1, lengthRSI)
k = sma(stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK_1)
d = sma(k, smoothD_1)
//plot(k, color=color.red)
//plot(d, color=color.yellow)

//Stochastic RSI 5,4,3
smoothK_2 = input(4, minval=1)
smoothD_2 = input(3, minval=1)
lengthRSI_2 = input(5, minval=1)
lengthStoch_2 = input(5, minval=1)
src_2 = input(close, title="RSI Source_2")

rsi2 = rsi(src_2, lengthRSI_2)
k_2 = sma(stoch(rsi2, rsi2, rsi2, lengthStoch_2), smoothK_2)
d_2 = sma(k_2, smoothD_2)
//plot(k_2, color=color.white)
//plot(d_2, color=color.green)

// CCI
cci = cci(close,26)
//plot(cci,color=color.blue)

// Dynamic RSI
DZbuy = 0.1
DZsell = 0.1
Period = 14
Lb = 60

RSILine = rsi(close,Period)
jh = highest(RSILine, Lb)
jl = lowest(RSILine, Lb)
jc = (wma((jh-jl)*0.5,Period) + wma(jl,Period))
Hiline = jh - jc * DZbuy
Loline = jl + jc * DZsell
R = (4 * RSILine + 3 * RSILine[1] + 2 * RSILine[2] + RSILine[3] ) / 10

plot(R, title='R', color=color.white, linewidth=1, transp=0)
plot(Hiline, title='Hiline', color=color.yellow,  linewidth=1, transp=0)
plot(Loline, title='Loline', color=color.yellow, linewidth=1, transp=0)
plot(jc, title='Jc', color=color.purple,  linewidth=1, transp=50)

col_1 = R > Hiline ? color.red:na
col_2 = R < Loline ? color.green:na

fill(plot(R, title='R', color=color.white, linewidth=1, transp=0), plot(Hiline, title='Hiline', color=color.yellow,  linewidth=1, transp=0), color=col_1,transp=0)
fill(plot(R, title='R', color=color.white, linewidth=1, transp=0), plot(Loline, title='Loline', color=color.yellow, linewidth=1, transp=0), color=col_2,transp=0)
//------------------------------------------------------------------------------
// Calculate qty
// Parameter
fund = 10           // Fund per Contract in USD
leverage = 100     // Leverage
// Buy Condition
buyCondition = (ma12>ma26 and cci<100 and k<80 and d<80 and k_2<80 and d_2<80 and crossover(k_2, d_2))
buy = (buyCondition == input(1))
alertcondition(buy, title='time to Long', message='Long!!!')
//closeBuy = (cci>100 and cci<cci[1] and cci<cci[2])
closeBuy = (crossunder(R, Hiline) and k>80)
alertcondition(closeBuy, title='Time to Close', message='Close Long')

// Submit Orders
strategy.entry(id="Long", qty=(fund*leverage)/close, long=true, when=buyCondition)
strategy.close(id="Long", when=closeBuy)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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