Optimal Investment for Institutional Investors Under Value-at-Risk Constraints in Chinese Stock Markets

Value at Risk (VaR) is defined as the worst expected loss under normal market conditions over a specific time interval at a given confidence level. Given the widespread usage of VaR, it becomes increasingly important to study the effects of the portfolio optimization subject to the VaR constraint set by the fund manager. In this paper, we examine the classical portfolio optimization models and the most popular VaR methodologies. We show that the portfolio optimization models under VaR constraint provide the clear insight to the mean-variance decision. We also consider the problem with the extra tracking error constraint. Furthermore, we provide an empirical analysis on the model by using China's market data. VaR estimates are produced via Monte Carlo simulations