Keywords: heuristic optimization, portfolio optimization model, transaction costs.

In this thesis we extend the Markowitz Mean-Variance model to a rebalancing portfolio optimization problem incorporating realistic considerations such as transaction costs and a risk-free asset with short-selling allowed, and we apply the Tabu Search (TS) heuristic to solve practical portfolio problems. First of all, we propose a biobjective portfolio optimization model which we expect to yield a portfolio equilibrium by combining the two objectives: maximize the portfolioââ'¬â"¢s expected return and minimize its risk. For realistic portfolio problems we consider the multi-objective portfolio optimization models incorporating the risk-free asset and its short-selling and nonlinear transaction costs based on a single-period and a rebalancing portfolio optimization problem. Especially, to solve the rebalancing portfolio problem, we develop an adaptive, advanced TS algorithm having an evolutionary neighborhood structure, and we solve the problem with an iterative folding back procedure in the decision tree structure. Computational studies are performed with a risk-free asset and the number of risky assets to be 5, 10, 12, and 15 for both the single-period and rebalancing portfolio problems.

Portfolio Management with Heuristic Optimization consist of two parts. The first part (Foundations) deals with the foundations of portfolio optimization, its assumptions, approaches and the limitations when "traditional" optimization techniques are to be applied. In addition, the basic concepts of several heuristic optimization techniques are presented along with examples of how to implement them for financial optimization problems. The second part (Applications and Contributions) consists of five chapters, covering different problems in financial optimization: the effects of (linear, proportional and combined) transaction costs together with integer constraints and limitations on the initital endowment to be invested; the diversification in small portfolios; the effect of cardinality constraints on the Markowitz efficient line; the effects (and hidden risks) of Value-at-Risk when used the relevant risk constraint; the problem factor selection for the Arbitrage Pricing Theory.

Portfolio Management with Heuristic Optimization consist of two parts. The first part (Foundations) deals with the foundations of portfolio optimization, its assumptions, approaches and the limitations when "traditional" optimization techniques are to be applied. In addition, the basic concepts of several heuristic optimization techniques are presented along with examples of how to implement them for financial optimization problems. The second part (Applications and Contributions) consists of five chapters, covering different problems in financial optimization: the effects of (linear, proportional and combined) transaction costs together with integer constraints and limitations on the initital endowment to be invested; the diversification in small portfolios; the effect of cardinality constraints on the Markowitz efficient line; the effects (and hidden risks) of Value-at-Risk when used the relevant risk constraint; the problem factor selection for the Arbitrage Pricing Theory.

This monograph collects in one place the basic definitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework.

Control of an impartial balance between risks and returns has become important for investors, and having a combination of financial instruments within a portfolio is an advantage. Portfolio management has thus become very important for reaching a resolution in high-risk investment opportunities and addressing the risk-reward tradeoff by maximizing returns and minimizing risks within a given investment period for a variety of assets. Metaheuristic Approaches to Portfolio Optimization is an essential reference source that examines the proper selection of financial instruments in a financial portfolio management scenario in terms of metaheuristic approaches. It also explores common measures used for the evaluation of risks/returns of portfolios in real-life situations. Featuring research on topics such as closed-end funds, asset allocation, and risk-return paradigm, this book is ideally designed for investors, financial professionals, money managers, accountants, students, professionals, and researchers.

We provide a computational study of the problem of optimally allocating wealth among multiple stocks and a bank account, in order to maximize the infinite horizon discounted utility of consumption. We consider the situation where the transfer of wealth from one asset to another involves transaction costs that are proportional to the amount of wealth transferred. Our model allows for correlation between the price processes, which in turn gives rise to interesting hedging strategies. This results in a stochastic control problem with both drift-rate and singular controls, that can be recast as a free boundary problem in partial differential equations. Adapting the finite element method and using an iterative procedure that converts the free-boundary problem into a sequence of fixed boundary problems, we provide an efficient numerical method for solving this problem. We present computational results that describe the impact of volatility, risk aversion of the investor, level of transaction costs and correlation among the risky assets on the structure of the optimal policy. Finally we suggest and quantify some heuristic approximations.