In this paper, we study an investor's asset allocation problem with a recursive utility and with tradable volatility that follows a two-factor stochastic volatility model. Consistent with Liu and Pan (2003) and Egloff, Leippold, and Wu's (2009) finding under the additive utility, we show that...

On 9 October 2007, the Dow Jones Industrial Average reached a high of 14,164.53; by 9 March 2009, it had dropped about 54 percent, to a low of 6,547.05. Former Fed chairman Alan Greenspan called this a “once-in-a-century” crisis. The authors show that the probability of a stock market drop of...

In practice, traders, such as high-frequency and day traders, rely in part or primarily on moving averages to predict market directions, but their equilibrium impact is unknown. This paper presents a model to analyze how such technical traders compete trading with informed investors and how they...

We propose a 4-factor model for the Chinese stock market by adding a trend factor into the market, size, and value of Liu, Stambaugh, and Yuan's (2019) 3-factor model. Because of up to 80% of individual trading, the trend factor captures salient relevant price and volume trends, and earns a...

Automated machine learning extends the search space to include hyperparameters and algorithm selection. We apply automated machine learning (AutoML) to cross sectional stock return prediction with factors. We formulate factor dimension reduction and hyperparameter tuning in conventional ML...

Automated machine learning extends the search space to include hyperparameters and algorithm selection. We apply automated machine learning (AutoML) to cross sectional stock return prediction with factors. We formulate factor dimension reduction and hyperparameter tuning in conventional ML...