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January 31, 2025

CaseyC% Oscillator: A Smarter Mean Reversion Strategy for SP500 Traders

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Written by Ali Casey, founder of StatOasis and AlgoChef, creator of the Algo Trading Masterclass (ATM), with over 10 years of experience building systematic trading tools - building algorithmic strategies, testing ideas with data, and teaching traders how to build structured, portfolio-based trading workflows.

Published January 31, 2025 · Updated June 17, 2025

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Table of contents▾
  • What is the CaseyC% Oscillator?
  • RSI2 vs. CaseyC%: Key Differences
  • Testing Five Mean Reversion Strategies on SPY ETF (1995-2024)
  • Why Diversifying CaseyC% Variations is Better Than Increasing Position Size
  • Portfolio of 5 Uncorrelated Strategies: (All CaseyC% Variations Together)
  • Conclusion: Smarter Trading with CaseyC%
  • Frequently Asked Questions (FAQs)

The short version

Discover how CaseyC% oscillator can diversify your mean reversion strategies and improve portfolio performance in SP500 trading.

Tired of RSI(2) failing in volatile markets? Meet CaseyC%—a smarter oscillator designed to smooth equity curves and improve your mean reversion strategy.

Mean reversion trading has long been a profitable approach, relying on price reverting to historical averages after extreme movements.

However, traditional indicators like the Relative Strength Index (RSI2) often struggle with false signals and whipsaws.

Unlike RSI2, which only considers short-term price movements, CaseyC% integrates momentum ranking and smoothing to produce more reliable signals

In this article, we’ll compare RSI2 vs. CaseyC%, analyze different variations of CaseyC%, and explain why diversifying strategies beats increasing position size.

Before we dive into CaseyC%, I’ve previously explored how a volume filter improved RSI2 strategy returns by 48%. Let's see how CaseyC% further enhances mean reversion.

What is the CaseyC% Oscillator?

A Smarter Mean Reversion Indicator

Developed by Ali Casey from StatOasis, CaseyC% is a momentum-based ranking oscillator designed for mean reversion and quantitative trading. Unlike RSI(2), which only measures overbought/oversold conditions based on short-term price action, CaseyC%:

✅ Ranks price changes over a chosen period

✅ Normalizes momentum within a range of 0 to 100

✅ Smooths the result for more reliable signals

✅ Available for multiple platforms for free. download code from StatOasis Community

How CaseyC% Works (Step-by-Step)

1️⃣ Momentum Calculation: Measures price change over ChangeLen periods.
2️⃣ Ranking Mechanism: Normalizes the momentum within a RankLen window, scaling it from 0 to 100.
3️⃣ Smoothing: Applies a moving average (SmoothLen) to reduce noise and improve signal quality.

RSI2 vs. CaseyC%: Key Differences

Indicator Strengths

  • RSI(2) Simple, widely used, easy to implement
  • CaseyC% Adaptive ranking, reduces false signals, customizable parameters

Indicator Weaknesses

  • RSI(2) High whipsaw rate, struggles in volatile markets
  • CaseyC% Requires parameter tuning

Testing Five Mean Reversion Strategies on SPY ETF (1995-2024)

To validate CaseyC%'s effectiveness, we tested five different mean reversion strategies on the SPY ETF (1995-2024):

Strategy 1: RSI2 Mean Reversion

  • Buy SPY when RSI(2) is below a threshold.
  • Exit after 4 bars.

Strategy 2: Regular CaseyC% Mean Reversion

  • Buy SPY when CaseyC% is below a threshold.
  • Exit after 4 bars.

Strategy 3: Cumulative CaseyC% (Stronger Mean Reversion Filter)

  • Buy when the sum of the last 3 CaseyC% values is below a threshold.
  • Exit after 4 bars.

Strategy 4&5: Dynamic CaseyC% (Adaptive Buy/Sell Levels)

  • Buy when the Cumulative CaseyC% is at its lowest value over the past X bars.
  • Exit after 4 bars.

Why Diversifying CaseyC% Variations is Better Than Increasing Position Size

Diversification is the only free lunch in trading—use it wisely.

Instead of simply increasing position size on a single strategy, traders can achieve better results by combining multiple CaseyC% strategies:

✅ Reduces correlation between trades

✅ Lowers drawdowns and smooths returns

✅ Maintains stable profitability in different market conditions

Instead of increasing position size, we tested a portfolio approach, combining RSI2 and CaseyC% variations into a diversified strategy

Portfolio of 5 Uncorrelated Strategies: (All CaseyC% Variations Together)

  • Combines RSI2, Regular CaseyC%, Cumulative CaseyC%, and Dynamic CaseyC% into a multi-strategy portfolio.
  • Each strategy trades independently, reducing risk and smoothing returns.
  • Even with relatively high correlations, the portfolio is still better than any single strategy.
Don’t put all your capital into one strategy. Build a portfolio of uncorrelated edges.

Conclusion: Smarter Trading with CaseyC%

The CaseyC% oscillator and its variations (Cumulative & Dynamic CaseyC%) offer a superior alternative to RSI2 for mean reversion trading. By using multiple variations, traders can:

✅ Reduce risk & drawdowns
✅ Achieve smoother equity curves
✅ Boost long-term returns without overexposing capital

📌 Next Steps:
✅ Download CaseyC% and backtest your own strategies.
✅ Test Regular, Cumulative, and Dynamic CaseyC% together.
✅ Focus on diversification over position size.

Frequently Asked Questions (FAQs)

What is Cumulative CaseyC%?

  • Cumulative CaseyC% is the sum of the last three CaseyC% values, making it a stronger mean reversion filter that smooths out noisy signals.

How does Dynamic CaseyC% work?

  • Dynamic CaseyC% adjusts buy/sell levels dynamically using past values, adapting to market conditions instead of relying on fixed thresholds.

Can CaseyC% be used on assets other than SPY ETF?

  • Yes! CaseyC% works on stocks, forex, and crypto, but you may need to adjust parameters based on the asset’s volatility and liquidity.

How can I prevent overfitting CaseyC% to past data?

  • Avoid excessive parameter tweaking and validate strategies on out-of-sample data and different market conditions.

Is increasing position size the best way to boost returns?

  • No. Instead of increasing size, run multiple uncorrelated strategies to reduce risk and improve equity curve stability.

This study makes no claim to the StatOasis research standard, which took effect on August 3, 2026. See how studies are run now →

Historical backtest results are not a guarantee of future returns. This content is for educational purposes only and is not investment advice. Hypothetical performance disclosure (CFTC Rule 4.41).

Read the Strategies, Backtested hub
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Table of contents

  • What is the CaseyC% Oscillator?
  • RSI2 vs. CaseyC%: Key Differences
  • Testing Five Mean Reversion Strategies on SPY ETF (1995-2024)
  • Why Diversifying CaseyC% Variations is Better Than Increasing Position Size
  • Portfolio of 5 Uncorrelated Strategies: (All CaseyC% Variations Together)
  • Conclusion: Smarter Trading with CaseyC%
  • Frequently Asked Questions (FAQs)

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StatOasis is calm, evidence-based algorithmic-trading education, founded by Ali Casey. Ali builds systematic trading strategies and teaches the workflow behind them: research, build, test, combine, deploy. He writes the Overfit newsletter, published since 2024, and runs the Algo Trading Masterclass.

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