RSI-CCI Fusion Strategy

Author: ChaoZhang, Date: 2023-09-19 16:42:18


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.

Strategy Principle

  1. Calculate RSI and CCI values.

  2. Standardize RSI and CCI using z-score for better comparability.

  3. Fuse standardized RSI and CCI with designated weights.

  4. Compute dynamic upper and lower bands to identify overbought/oversold levels.

  5. 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:

  1. Integrates strengths of both indicators for better accuracy.

  2. More scientific dynamic bands reduce false signals.

  3. Standardization enables comparability, improving fusion.

  4. Can assess both trend and overbought/oversold conditions.

Risk Analysis

Some risks of this strategy:

  1. Improper parameters may miss key trade points.

  2. Inadequate weights can weaken an indicator’s role.

  3. Ignoring overall trend may cause counter-trend trades.

  4. Band settings too loose or too tight increase misjudgement risks.

Optimization Directions

It can be optimized by:

  1. Finding optimal parameters through testing.

  2. Adjusting weights based on market conditions.

  3. Incorporating trend and volume indicators for better accuracy.

  4. Setting stop loss/take profit to control risks.

  5. Optimizing bands to balance sensitivity and noise.


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.

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

// 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

// Enter short position if enabled
if enableShort and sellSignal
    strategy.entry("Sell", strategy.short)

// Exit short position if enabled
if enableShort and buySignal