Machine learning (ML) is progressively reshaping the fields of quantitative finance and
algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers …

We theoretically and empirically study portfolio optimization under transaction costs and
establish a link between turnover penalization and covariance shrinkage with the …

We study how to best combine the sample mean-variance portfolio with the naive equally
weighted portfolio to optimize out-of-sample performance. We show that the seemingly …

This paper studies a dynamic asset-liability management problem of a company with market
frictions. Specifically, the asset prices are modeled by a multivariate geometric Brownian …

We derive a closed-form solution to a continuous-time optimal portfolio selection problem
with return predictability and transaction costs. Specifically, we assume that asset returns are …

We study a dynamic mean–variance portfolio selection problem with return predictability and
trading frictions from price impact. Applying mean-field type control theory, we provide a …

Why Naive 1/N Diversification Is Not So Naive, and How to Beat It? Page 1 JOURNAL OF
FINANCIAL AND QUANTITATIVE ANALYSIS © THE AUTHOR(S), 2023. PUBLISHED BY …

This textbook shows how to bring theoretical concepts from finance and econometrics to the
data. Focusing on coding and data analysis with R, we show how to conduct research in …

This paper studies a portfolio choice problem of a utility-maximizing investor with return
predictability and small liquidity costs. By adopting a logarithmic-return assumption, our …

This paper investigates portfolio selection in the presence of transaction costs and ambiguity
about return predictability. By distinguishing between ambiguity aversion to returns and to …