Risk-Adjusted Performance

Beyond Binary Screens: A Continuous Shariah Compliance Index for Asset Pricing and Portfolio Design ArXiv ID: 2512.22858 “View on arXiv” Authors: Abdulrahman Qadi, Akash Sharma, Francesca Medda Abstract Binary Shariah screens vary across standards and apply hard thresholds that create discontinuous classifications. We construct a Continuous Shariah Compliance Index (CSCI) in $[“0,1”]$ by mapping standard screening ratios to smooth scores between conservative ``comfort’’ bounds and permissive outer bounds, and aggregating them conservatively with a sectoral activity factor. Using CRSP/Compustat U.S. equities (1999-2024) with lagged accounting inputs and monthly rebalancing, we find that CSCI-based long-only portfolios have historical risk-adjusted performance similar to an emulated binary Islamic benchmark. Tightening the minimum compliance threshold reduces the investable universe and diversification and is associated with lower Sharpe ratios. The framework yields a practical compliance gradient that supports portfolio construction, constraint design, and cross-standard comparisons without reliance on pass/fail screening. ...

Attention Factors for Statistical Arbitrage ArXiv ID: 2510.11616 “View on arXiv” Authors: Elliot L. Epstein, Rose Wang, Jaewon Choi, Markus Pelger Abstract Statistical arbitrage exploits temporal price differences between similar assets. We develop a framework to jointly identify similar assets through factors, identify mispricing and form a trading policy that maximizes risk-adjusted performance after trading costs. Our Attention Factors are conditional latent factors that are the most useful for arbitrage trading. They are learned from firm characteristic embeddings that allow for complex interactions. We identify time-series signals from the residual portfolios of our factors with a general sequence model. Estimating factors and the arbitrage trading strategy jointly is crucial to maximize profitability after trading costs. In a comprehensive empirical study we show that our Attention Factor model achieves an out-of-sample Sharpe ratio above 4 on the largest U.S. equities over a 24-year period. Our one-step solution yields an unprecedented Sharpe ratio of 2.3 net of transaction costs. We show that weak factors are important for arbitrage trading. ...

Re-evaluating Short- and Long-Term Trend Factors in CTA Replication: A Bayesian Graphical Approach ArXiv ID: 2507.15876 “View on arXiv” Authors: Eric Benhamou, Jean-Jacques Ohana, Alban Etienne, Béatrice Guez, Ethan Setrouk, Thomas Jacquot Abstract Commodity Trading Advisors (CTAs) have historically relied on trend-following rules that operate on vastly different horizons from long-term breakouts that capture major directional moves to short-term momentum signals that thrive in fast-moving markets. Despite a large body of work on trend following, the relative merits and interactions of short-versus long-term trend systems remain controversial. This paper adds to the debate by (i) dynamically decomposing CTA returns into short-term trend, long-term trend and market beta factors using a Bayesian graphical model, and (ii) showing how the blend of horizons shapes the strategy’s risk-adjusted performance. ...