Quantitative research analysts (Quants) produce in-depth quantitative and econometric modeling of market anomalies to assist sell-side analysts and institutional clients with stock selection strategies. Quants are associated with more efficient analyst forecasting behavior on anomaly predictors...

We use a proprietary dataset to test the implications of several asymmetric information models on how short-lived private information affects trading strategies and liquidity provision. Our identification rests on information acquisition before analyst recommendations are publically announced....

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...

We provide a new framework for modeling trends and periodic patterns in high-frequency financial data. Seeking adaptivity to ever-changing market conditions, we enlarge the Fourier flexible form into a richer functional class: both our smooth trend and the seasonality are non-parametrically...

We propose a bivariate component GARCH-MIDAS model to estimate the long- and short-run components of the variances and covariances. The advantage of our model to the existing DCC-based models is that it uses the same form for both the variances and covariances and that it estimates these moments...

We present a two-factor volatility model to study the impact of news arrival and trading volume on stock returns variance. The model can explicitly account for the association between volatility and volume, as well as the persistence in equity variance. Unlike the standard "Mixture of...

This study presents and empirically tests a simple framework that examines the effects of market liquidity (the ease with which stocks are traded) and funding liquidity (the ease with which market participants can obtain funding) on stock market bubbles. Three key findings emerge from this...

This paper provides tractable expressions for broad classes of standard transforms for the case of affine jump diffusions. Extending and unifying existing results, these include expressions for exponential, polynomial-log-linear, and polynomial transforms of a state vector in both conditional...

We propose a nonparametric method to test which characteristics provide independent information for the cross section of expected returns. We use the adaptive group LASSO to select characteristics and to estimate how they affect expected returns nonparametrically. Our method can handle a large...