We examine the problem of decision making using a probabilistic model when there is material uncertainty concerning the accuracy of the model coupled with limited information about it. Such conditions could hold, for example, for the user of a complex commercial model of natural catastrophe...

Factor analysis of security returns aims to decompose a return covariance matrix into systematic and specific risk components. To date, most commercially successful factor analysis has been based on fundamental models, although there is a large academic literature on statistical models. While...

In this paper we propose a novel application of Gaussian processes (GPs) to financial asset allocation. Our approach is deeply rooted in Stochastic Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert E. Fernholz that aims at flexibly analysing the performance of certain...

Standard mean-variance analysis is based on the assumption of normal return distributions. However, a growing body of literature suggests that the market oscillates between two different regimes – one with low volatility and the other with high volatility. In such a case, even if the return...

We develop scenario-based stochastic programming models for hedging the risks of international portfolios using options. The models provide an increasing level of integration in managing market and foreign exchange (FX) risks. We start with a single-stage model with currency options for...

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...

We propose a joint distribution that decomposes asset returns into two independent components: an elliptical innovation (Gaussian) and a systematic non-elliptical latent process. The paper provides a tractable approach to estimate the underlying parameters and, hence, the assets' exposures to...

In this paper we introduce uncertainty in the investment appraisal, managed through a new criterion called Average Internal Rate of Return (AIRR), introduced in Magni (2010). The consistency of the arithmetic of variables represented with intervals or fuzzy numbers makes it possible to apply the...

We study the impact of liquidity in optimal portfolio choice under leveraging to improve risk-adjusted and absolute returns. We consider a quasi-elastic market with continuous trading where temporary liquidity costs are sufficiently large relative to permanent impact. We show analytically that...