Hedging the exchange rate risk in international portfolio diversification : currency forwards versus currency options

As past research suggest, currency exposure risk is a main source of overall risk of international diversified portfolios. Thus, controlling the currency risk is an important instrument for controlling and improving investment performance of international investments. This study examines the effectiveness of controlling the currency risk for international diversified mixed asset portfolios via different hedge tools. Several hedging strategies, using currency forwards and currency options, were evaluated and compared with each other. Therefore, the stock and bond markets of the, United Kingdom, Germany, Japan, Switzerland, and the U.S, in the time period of January 1985 till December 2002, are considered. This is done form the point of view of a German investor. Due to highly skewed return distributions of options, the application of the traditional mean-variance framework for portfolio optimization is doubtful when options are considered. To account for this problem, a mean-LPM model is employed. Currency trends are also taken into account to check for the general dependence of time trends of currency movements and the relative potential gains of risk controlling strategies

The joint distribution of stock returns is not elliptical

Using a large set of daily US and Japanese stock returns, we test in detail the relevance of Student models, and of more general elliptical models, for describing the joint distribution of returns. We find that while Student copulas provide a good approximation for strongly correlated pairs of stocks, systematic discrepancies appear as the linear correlation between stocks decreases, that rule out all elliptical models. Intuitively, the failure of elliptical models can be traced to the inadequacy of the assumption of a single volatility mode for all stocks. We suggest several ideas of methodological interest to efficiently visualise and compare different copulas. We identify the rescaled difference with the Gaussian copula and the central value of the copula as strongly discriminating observables. We insist on the need to shun away from formal choices of copulas with no financial interpretation.Comment: 12 figure

Microscopic models of financial markets

This review deals with several microscopic models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power-law with index around three), it became clear that financial markets dynamics give rise to some kind of universal scaling laws. Showing similarities with scaling laws for other systems with many interacting subunits, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic was pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavors of multi-agent models that have appeared by now, we discuss the Cont-Bouchaud, Solomon-Levy-Huang and Lux-Marchesi models. Open research questions are discussed in our concluding section. --

Coherent Asset Allocation and Diversification in the Presence of Stress Events

We propose a method to integrate frequentist and subjective probabilities in order to obtain a coherent asset allocation in the presence of stress events. Our working assumption is that in normal market asset returns are sufficiently regular for frequentist statistical techniques to identify their joint distribution, once the outliers have been removed from the data set. We also argue, however, that the exceptional events facing the portfolio manager at any point in time are specific to the each individual crisis, and that past regularities cannot be relied upon. We therefore deal with exceptional returns by eliciting subjective probabilities, and by employing the Bayesian net technology to ensure logical consistency. The portfolio allocation is then obtained by utility maximization over the combined (normal plus exceptional) distribution of returns. We show the procedure in detail in a stylized case.Stress tests, asset allocation, Bayesian Networks

Multivariate concave and convex stochastic dominance

Stochastic dominance permits a partial ordering of alternatives (probability distributions on consequences) based only on partial information about a decision maker’s utility function. Univariate stochastic dominance has been widely studied and applied, with general agreement on classes of utility functions for dominance of different degrees. Extensions to the multivariate case have received less attention and have used different classes of utility functions, some of which require strong assumptions about utility. We investigate multivariate stochastic dominance using a class of utility functions that is consistent with a basic preference assumption, can be related to well-known characteristics of utility, and is a natural extension of the stochastic order typically used in the univariate case. These utility functions are multivariate risk averse, and reversing the preference assumption allows us to investigate stochastic dominance for utility functions that are multivariate risk seeking. We provide insight into these two contrasting forms of stochastic dominance, develop some criteria to compare probability distributions (hence alternatives) via multivariate stochastic dominance, and illustrate how this dominance could be used in practice to identify inferior alternatives. Connections between our approach and dominance using different stochastic orders are discussed.decision analysis: multiple criteria, risk; group decisions; utility/preference: multiattribute utility, stochastic dominance, stochastic orders