In this paper we show, how Random Matrix Theory can be used to improve Markovitz's portfolio selection model. Detailed simulation study have been provided based on Warsaw Stock Exchange data using an automated trading system

We generalize the classic Grossman and Laroque (1990) (GL) model of optimal portfolio choice with housing and transaction costs by introducing predictability in house prices. As in the GL model, agents only move to more expensive (cheaper) houses when their wealth-to-housing ratios reach an...

In the fundamental paper on portfolio selection, Markowitz (1952) described via geometric reasoning his innovative theory and provided the explicit optimal selection for the cases of 3 and 4 assets. Merton (1972) obtained for the general case the efficient portfolio frontiers explicitly by using...

The recent crisis made it evident that replicating the performance of a benchmark is not a sufficient goal to meet the expectations of usually risk-averse investors. The manager should also consider that the investor are seeking for a downside protection when the benchmark performs poorly and...

Despite foreign reserves' strategic asset allocation relies mainly on Modern Portfolio Theory (MPT), the unique characteristics of central banks obliges them to articulate and reconcile typical optimization procedures with reserves' management objectives such as providing confidence regarding...

We examine the maximization problem of performance measure of financial structured products. For this purpose, we introduce the Kappa ratios, based on downside risk measures which take account of the asymmetry of the return probability distribution. First, we deal with the optimization of some...

Index tracking aims at determining an optimal portfolio that replicates the performance of an index or benchmark by investing in a smaller number of constituents or assets. The tracking portfolio should be cheap to maintain and update, i.e., invest in a smaller number of constituents than the...

In typical robust portfolio selection problems, one mainly finds portfolios with the worst-case return under a given uncertainty set, in which asset returns can be realized. A too large uncertainty set will lead to a too conservative robust portfolio. However, if the given uncertainty set is not...

In this work, we propose an ARMA(1,1)-GARCH(1,1) model with standard classical tempered stable (CTS) innovations for historical daily returns of 29 selected stocks. The non-Gaussian nature of the innovations captures the fat-tail property observed in data. The dependency between different assets...

In this article, we extend the Black-Litterman approach to a continuous time setting. We model analyst views jointly with asset prices to estimate the unobservable factors driving asset returns. The key in our approach is that the filtering problem and the stochastic control problem are...