In this contribution we propose a dynamic tracking error problem and we consider the problem of monitoring at discrete point the shortfall of the portfolio below a set of given reference levels of wealth. We formulate and solve the resulting dynamic optimization problem using stochastic...

Portfolio optimization literature has come quite far in the decades since the first publication, and many modern models are formulated using second-order cone constraints and take discrete decisions into consideration. In this study, we consider both single-period and multi-period portfolio...

Dynamic programming is the essential tool in dynamic economic analysis. Problems such as portfolio allocation for individuals and optimal economic growth are typical examples. Numerical methods typically approximate the value function. Recent work has focused on making numerical methods more...

This paper develops an approximate closed-form optimal portfolio allocation formula for a spot asset whose variance follows a GARCH(1,1) process. We consider an investor with constant relative risk aversion (CRRA) utility who wants to maximize the expected utility from terminal wealth under a...

Using a multi-stage stochastic programming method, we suggest an optimal liability-driven investment(LDI) strategy for a closed defined-benefit pension fund including real assets. The objective is to jointly optimize contribution, funding ratio, and buyout cost, subject to a constraint on...

We study dynamic mean-variance optimization problems with multiple priors. We introduce two types of multiple priors, the priors for expected returns and the priors for covariances. Our framework suggests that the global minimum-variance portfolio is optimal when the investor strongly doubts the...

We identify decompositions of multi-period optimal portfolios, in which each subportfolio is dedicated to achieving a single investment target, in dynamic models with Von Neumann-Morgenstern preferences and diffusion asset returns (“Merton's problem”). These decompositions rest on...

An optimization method is developed for constructing investment portfolios which stochastically dominate a given benchmark for all decreasing absolute risk-averse investors, using Quadratic Programming. The method is applied to standard data sets of historical returns of equity price reversal...

Average Value-at-Risk (AVaR) is a potential alternative to Value-at-Risk in the financial regulation of banking and insurance institutions. To understand how AVaR influences a company's investment behavior, we study portfolio optimization under the AVaR constraint. Our main contribution is to...