The performance of a given portfolio policy can in principle be evaluated by comparing its expected utility with that of the optimal policy. Unfortunately, the optimal policy is usually not computable, in which case a direct comparison is impossible. In this paper, we solve this problem by using the given portfolio policy to construct an upper bound on the unknown maximum expected utility. This...

Risk management in this paper is focused on multivariate risk-return decision making assuming time-varying estimation. Empirical research in risk management showed that the static "mean-variance" methodology in portfolio optimization is very restrictive with unrealistic assumptions. The objective of this paper is estimation of time-varying portfolio stocks weights by constraints on risk measure...

We describe a framework of a system for risk estimation and portfolio optimization based on stable distributions and the average value-at-risk risk measure. In contrast to normal distributions, stable distributions capture the fat tails and the asymmetric nature of real-world risk factor distributions. In addition, we make use of copulas, a generalization of overly restrictive linear correlatio...

Affine term structure models are widely used for studying the relationship between yields on assets of different maturities. However, it can be a helpful tool construction fixed-income portfolios. The monitoring these bond portfolios is great importance investor. purpose this work twofold. Firstly, we construct and optimize using Markowitz’s portfolio approach to multifactor Gaussian affine mod...

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 optimization problems based on the Markowitz (1952) mean/variance framework, where there is a trade-off be...

In this paper we construct robust models for active portfolio management in a market with transaction costs. The goal of these robust models is to control the impact of estimation errors in the values of the market parameters on the performance of the portfolio strategy. Our models can handle a large class of piecewise convex transaction cost functions and allow one to impose additional side co...

Efficient portfolio design is a principal challenge in modern computational finance. Optimization based on Markowitz two-objective mean-variance approach is computationally expensive for real financial world. Practical portfolio design introduces further complexity as it requires the optimization of multiple return and risk measures. Some of these measures are nonlinear and nonconvex. The probl...