As a result of the recent financial crises, equity markets have performed poorly in the last five years or so. In consequence, equity long-only strategies have generally been unattractive over this period. This motivates the investigation on whether better performance can be achieved by...

We propose a robust portfolio optimization approach based on Value-at-Risk (VaR) adjusted Sharpe ratios. Traditional Sharpe ratio estimates based on limited historical return data are subject to estimation errors. Portfolio optimization based on traditional Sharpe ratios ignores this uncertainty...

We propose a novel linear approximation of expected utility. The approximation guides us as we transfer the traditional quadratic dependence of third-order stochastic dominance (TSD) into an equivalent linear system. The finding also shows a dual relationship between traditional low partial...

We develop a novel Mean-Max Drawdown portfolio optimization approach using buy-and-hold portfolios. The optimization is performed utilizing a multi-objective evolutionary algorithm on a sample of S&P 100 constituents. Our optimization procedure provides portfolios with better Mean-Max Drawdown...

Robust optimization considers uncertainty in inputs to address the shortcomings of mean-variance optimization. We investigate the mechanisms by which robust optimization achieves its goal and give practical guidance regarding its parametrization. We show that quadratic uncertainty sets are...

In this paper, first we study a stochastic volatility market model for which an explicit candidate solution to the problem of maximizing utility function of terminal wealth is obtained. Applying this result, we present a complete solution for the Heston model which is a particular case of the...

Overall, 72 subjects invest their endowment in four risky assets. Each com-bination of assets yields the same expected return and variance of returns. Illusion of expertise prevails when one prefers nevertheless the self-selected portfolio. After being randomly assigned to groups of four...

This paper treats the risk-averse optimal portfolio problem with consumption in continuous time for a stochastic-jump-volatility, jump-diffusion (SJVJD) model of the underlying risky asset and the volatility. The new developments are the use of the SJVJD model with...

Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the ``error maximization'' problem where inaccuracy in parameter estimation...