This paper aims to analyze so-called anomalies or additional risk factors (other than market risk) on the Hong Kong stock exchange. To do so, we first select arbitrarily several factors that we a priori believe to be significant, we then collect the data and evaluate the returns associated with...

We re-examine US mutual fund performance persistence. We investigate persistence (i) using both “academic” factor models and “practitioner” index models, (ii) using decile-size recursive portfolios and also portfolios formed from smaller numbers of funds, (iii) using nonparametric...

We introduce artificial intelligence pricing theory (AIPT). In contrast with the APT's foundational assumption of a low dimensional factor structure in returns, the AIPT conjectures that returns are driven by a large number of factors. We first verify this conjecture empirically and show that...

A value investing strategy consists of purchasing stocks relatively undervalued to their funda-mental values and selling those relatively overvalued. Finding this kind of companies has been one of the most challenging goals for investors throughout the history. The main objective of this paper...

Sentiment indices based on investor sentiment surveys attempt to measure the stock market sentiment. The literature on these indices focusses mainly on whether investor sentiment influences the financial markets or not. But the term “sentiment” has never been defined in the literature....

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...

This paper introduces a simple and tractable sieve estimation of semiparametric conditional factor models with latent factors. We establish large-N-asymptotic properties of the estimators without requiring large T. We also develop a simple bootstrap procedure for conducting inference about the...