This paper applies the Least Absolute Shrinkage and Selection Operator (LASSO) to make rolling 1-minute-ahead return forecasts using the entire cross section of lagged returns as candidate predictors. The LASSO increases both out-of-sample fit and forecast-implied Sharpe ratios. And, this...

This paper uses wavelets to decompose each stock's trading-volume variance into frequency-specific components. We find that stocks dominated by short-run fluctuations in trading volume have abnormal returns that are 1% per month higher than otherwise similar stocks where short-run fluctuations...

How do arbitrageurs find variables that predict returns? If a predictor lasts 30 days or more, then a clever arbitrageur can use his intuition to get the job done. But, what's an arbitrageur supposed to do if a predictor lasts 30 minutes or less? An arbitrageur's intuition is useless if the...

This paper introduces a new tool — the wavelet-variance estimator — that measures the fraction of trading activity at each investment horizon. We find substantial cross-sectional variation in horizons, even for stocks with the same volume, size, and liquidity. Moreover, the fraction of...

This paper proposes that computational complexity generates noise. The same asset is often held for completely different reasons by many funds following a wide variety of threshold-based trading rules. Under these conditions, we show it can be computationally infeasible to predict how these...