RSI CCI Fusion Strategy

The RSI-CCI Fusion strategy combines the strengths of the RSI and CCI indicators to form a powerful trading approach. It captures both momentum and cyclical dynamics for more comprehensive market assessment.

Author

ChaoZhang

Complexity

Starter · 62 lines

Parameters

Backtest bar

2h · intraday

Tested on

BTC/USDT · futures

Overview

Strategy Principle

Calculate RSI and CCI values.
Standardize RSI and CCI using z-score for better comparability.
Fuse standardized RSI and CCI with designated weights.
Compute dynamic upper and lower bands to identify overbought/oversold levels.
Consider short when fusion indicator crosses below upper band. Consider long when crossing above lower band.

Advantage Analysis

Compared to using RSI or CCI alone, advantages of this strategy include:

Integrates strengths of both indicators for better accuracy.
More scientific dynamic bands reduce false signals.
Standardization enables comparability, improving fusion.
Can assess both trend and overbought/oversold conditions.

Risk Analysis

Some risks of this strategy:

Improper parameters may miss key trade points.
Inadequate weights can weaken an indicator's role.
Ignoring overall trend may cause counter-trend trades.
Band settings too loose or too tight increase misjudgement risks.

Optimization Directions

It can be optimized by:

Finding optimal parameters through testing.
Adjusting weights based on market conditions.
Incorporating trend and volume indicators for better accuracy.
Setting stop loss/take profit to control risks.
Optimizing bands to balance sensitivity and noise.

Summary

The RSI-CCI fusion strategy improves judgement by consolidating indicators. With proper parameters and risk control, it generally outperforms single indicator strategies. But adjustments based on market conditions are still required.

Name	Default	What it controls
v_input_1	14	Length
v_input_float_1	0.5	RSI Weight
v_input_2	false	Enable Short Positions

Name

Default

What it controls

v_input_1

Length

v_input_float_1

0.5

RSI Weight

v_input_2

false

Enable Short Positions

/*backtest start: 2023-08-19 00:00:00 end: 2023-09-18 00:00:00 period: 2h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // © Julien_Eche //@version=5 // strategy("RSI-CCI Fusion Strategy", shorttitle="RSI-CCI Fusion Strategy", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=10) length = input(14, title="Length") rsi_weight = input.float(0.5, title="RSI Weight", minval=0.0, maxval=1.0) cci_weight = 1.0 - rsi_weight enableShort = input(false, "Enable Short Positions") src = close rsi = ta.rsi(src, length) cci = ta.cci(src, length) // Standardize the RSI and CCI values using z-score rsi_std = ta.stdev(rsi, length) rsi_mean = ta.sma(rsi, length) rsi_z = (rsi - rsi_mean) / rsi_std cci_std = ta.stdev(cci, length) cci_mean = ta.sma(cci, length) cci_z = (cci - cci_mean) / cci_std // Combine the standardized RSI and CCI combined_z = rsi_weight * rsi_z + cci_weight * cci_z // Rescale to the original scale rescaled = combined_z * ta.stdev(combined_z, length) + ta.sma(combined_z, length) // Calculate dynamic upper and lower bands upper_band = ta.sma(rescaled, length) + ta.stdev(rescaled, length) lower_band = ta.sma(rescaled, length) - ta.stdev(rescaled, length) // Buy and sell conditions buySignal = ta.crossover(rescaled, lower_band) sellSignal = ta.crossunder(rescaled, upper_band) // Enter long position if buySignal strategy.entry("Buy", strategy.long) // Exit long position if sellSignal strategy.close("Buy") // Enter short position if enabled if enableShort and sellSignal strategy.entry("Sell", strategy.short) // Exit short position if enabled if enableShort and buySignal strategy.close("Sell")

RSI CCI Fusion Strategy

Overview

Strategy Principle

Advantage Analysis

Risk Analysis

Optimization Directions

Summary

Parameters

Source Pine Script

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