Risk-Adjusting Forecasts for Increased Portfolio Performance
This paper decomposes the Sharpe-ratio gap — the performance cost of estimation error in mean-variance investing — into a mean-forecast error (RAFE) and a precision-alignment error …
This paper decomposes the Sharpe-ratio gap — the performance cost of estimation error in mean-variance investing — into a mean-forecast error (RAFE) and a precision-alignment error …
Regional and global factor momentum signals outperform local factors in forecasting risk premiums and revitalize momentum investing in less-integrated markets like Japan.
We offer a novel approach that aims at mitigating the crippling effects that parameter uncertainty and estimation errors have on the out-of-sample perforance of mean-variance …
We document a cross-country factor momentum anomaly, which we term 'Factor Chasing'. Specialized style mutual funds chase factor returns across countries, but their trades are …
We analyze event risk premia in an expected utility framework and provide closed-form solutions under both quadratic and power utility for four different cases: …
This paper introduces break-age, a novel measure for parameter uncertainty caused by structural breaks, and demonstrates its significance in stock pricing.
We estimate crypto-related risk for U.S. banks using historical covariance with bitcoin returns, focusing on contagion from FTX's failure.
Unsupervised ML clustering of assets into equally weighted sub-portfolios dominates both plug-in minimum variance and equally weighted benchmarks, with optimal cluster count around …
Correcting for survivorship and delisting bias substantially overturns published cryptocurrency anomaly evidence: size is overstated, while momentum and market beta no longer price …