We survey recent methodological contributions in asset pricing using factor models and machine learning. We organize these results based on their primary objectives: estimating expected returns, factors, risk exposures, risk premia, and the stochastic discount factor, as well as model comparison...

Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six international equity indices. We detect jumps in these estimators, construct the jump components of volatility and perform various tests on their properties. Then we use the class of...

This paper develops textual sentiment measures for China's stock market by extracting the textual tone of 60 million messages posted on a major online investor forum in China from 2008 to 2018. We conduct sentiment extraction by using both conventional dictionary methods based on customized word...

For stock market predictions, the essence of the problem is usually predicting the magnitude and direction of the stock price movement as accurately as possible. There are different approaches (e.g., econometrics and machine learning) for predicting stock returns. However, it is non-trivial to...

This article empirically investigates the volatility spillover of stock returns from the market to disaggregated industry sectors. Seventeen sectors from the US and UK stock markets are estimated by the GARCH technique based on daily data from 1973 to 2008. The key findings are two-fold. In the...

Here, we introduce a new approach for generating sequences of implied volatility (IV) surfaces across multiple assets that is faithful to historical prices. We do so using a combination of functional data analysis and neural stochastic differential equations (SDEs) combined with a probability...

With approximately 900 million observations we conduct, to our knowledge, the largest study ever of intraday stock return predictability using machine learning techniques finding consistent out-of-sample predictability across market, sector, and individual stock returns at various time horizons....

We consider the problems of derivative pricing and inference when the stochastic discount factor has an exponential-affine form and the geometric return of the underlying asset has a dynamics characterized by a mixture of conditionally Normal processes. We consider both the static case in which...

This study is an attempt to measure volatilities among regional stock markets and to establish a relationship between stock returns and volatility, and to rank these markets with respect to volatility. For this purpose, six markets are considered i.e. KSE100, Sensex, Nikkei225, Hangseng,...

This paper examines the co-movement between OPEC (Organization of Petroleum Exporting Countries) oil prices and the six largest African stock markets. We used wavelet coherence to analyze the evolution of this relationship both in time and by frequency. Our results show that the co-movement...