We propose a one-month market-timing model constructed from 15 diverse variables. We use weighted least squares with stepwise variable selection to build a predictive model for the one-month-ahead market excess returns. From our statistical model, we transform our forecasts into investable...

The fair value of an option is given by breakeven volatility, the value of implied volatility that sets the profit and loss of a delta-hedged option to zero. We calculate breakeven volatility for 400,000 options traded on the S&P 500 Index, and we build a predictive model for these volatility...

Revisiting the issue of return predictability, we show there is substantial predictive power in combining forecasting variables. We apply correlation screening to combine twenty variables that have been proposed in the return predictability literature, and demonstrate forecasting power at a...

Commonality in idiosyncratic volatility cannot be completely explained by time-varying volatility. We decompose the common factor in idiosyncratic volatility (CIV) of Herskovic et al. (2016) into two components: idiosyncratic volatility innovations (VIN) and time-varyingidiosyncratic volatility...

This paper demonstrates how deep learning can be used to price and calibrate models of credit risk. Deep neural networks can learn structural and reduced-form models with high degrees of accuracy. For complex credit risk models, whose closed-form solutions are not available, deep learning offers...

We present novel evidence of factor timing in the Chinese stock market. Actively managed Chinese stock mutual funds have larger exposure on the size factor when it performs well and smaller exposure when it performs poorly. By constructing a proxy for the size preference of active stock funds,...

This paper takes a cross-country and cross-sector perspective to investigate the drivers of commodity momentum strategies. Commodity momentum strategies deployed in the U.S. and Chinese markets generate positive average returns with non-negligible correlations, but their premia are primarily...

We revisit a series of popular anomalies: seasonal, announcement and momentum. We comment on statistical significance and persistence of these effects and propose useful investment strategies to incorporate this information. We investigate the creation of a seasonal anomaly and trend model...

We study the risk-reversal premium, where out-of-the-money puts are over-priced relative to out-of-the-money calls. This effect is driven by investors’ utility preferences which lead them to over-pay for the risk reduction benefits of long puts instead of valuing options on the basis of...

Filtered consumption growth, constructed from a broad set of macro variables, improves cross-sectional asset pricing on portfolios formed on size, book-to-market equity, and past performance compared to observed consumption growth. I use two methods to construct measures of filtered consumption...