This paper examines to what extent stock market anomalies are driven by firm fundamentals in an investment-based asset pricing framework. Using Bayesian Markov Chain Monte Carlo (MCMC), we estimate a two-capital q-model to match firm-level stock returns, instead of matching portfolio-level...

Modern Algorithmic Trading ("Algo") allows institutional investors and traders to liquidate or establish big security positions in a fully automated or low-touch manner. Most existing academic or industrial Algos focus on how to "slice" a big parent order into smaller child orders over a given...

We develop a high frequency (HF) trading strategy where the HF trader uses her superior speed to process information and to post limit sell and buy orders. By introducing a multifactor mutually exciting process we allow for feedback effects in market buy and sell orders and the shape of the...

We develop and implement methods for determining whether introducing new securities or relaxing investment constraints improves the investment opportunity set for prospect investors. We formulate a new testing procedure for prospect spanning for two nested portfolio sets based on subsampling and...