This paper evaluates a logistic regression-based trading strategy (LRST) that generates annualized returns of 24.61%, outperforming the S&P 500 over the sample period.

However, the strategy also exhibits high volatility and a Sharpe ratio below 1, indicating that the excess returns come with substantial risk and an imperfect risk-return profile.

Recent underperformance suggests that the strategy may struggle under changing market structure conditions, including the rise of algorithmic trading and macroeconomic regime shifts.

The findings reinforce that strong historical returns alone are insufficient; trading systems must continuously adapt to evolving market dynamics to remain effective.

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