2018/03/17 by Jize Zhang, Zhang, Jize, Tim Leung +3
Decision Sciences · Economics, Econometrics and Finance · #65K10 #90C30 #91G60 #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Economics and business #FOS: Mathematics #Financial Markets and Investment Strategies #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Portfolio Management (q-fin.PM) #Risk and Portfolio Optimization
paper · pdf · doi:10.48550/arxiv.1803.06460
openalex publication_date 2018/03/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We study an optimization-based approach to con- struct a mean-reverting portfolio of assets. Our objectives are threefold: (1) design a portfolio that is well-represented by an Ornstein-Uhlenbeck process with parameters estimated by maximum likelihood, (2) select portfolios with desirable characteristics of high mean reversion and low variance, and (3) select a parsimonious portfolio, i.e. find a small subset of a larger universe of assets that can be used for long and short positions. We present the full problem formulation, a specialized algorithm that exploits partial minimization, and numerical examples using both simulated and empirical price data.