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...

This paper provides a novel five-component decomposition of optimal dynamic portfolio choice. It reveals the simultaneous impacts from market incompleteness and wealth-dependent utilities. The decomposition leads to implementation via either closed-form solutions or Monte Carlo simulations. With...

In this paper, we propose a multivariate market model with returns assumed to follow a multivariate normal tempered stable distribution. This distribution, defined by a mixture of the multivariate normal distribution and the tempered stable subordinator, is consistent with two stylized facts...

In the paper, we consider the application of the theory of probability metrics in several areas in the eld of nance. First, we argue that specially structured probability metrics can be used to quantify stochastic dominance relations. Second, the methods of the theory of probability metrics can...

We consider classes of reward-risk optimization problems that arise from different choices of reward and risk measures. In certain examples the generic problem reduces to linear or quadratic programming problems. We state an algorithm based on a sequence of convex feasibility problems for the...

This paper sets out a new approach to sovereign wealth and risk management, based on the theory of contingent claim analysis (CCA). To manage sovereign risk, it is essential to analyse the sovereign's balance sheet. The state has to solve an asset-liability management (ALM) problem between its...

This paper explores the application of contingent claims analysis (CCA) to two quot;hotquot; issues in life-cycle finance: (1) investing for retirement and (2) deciding when, if ever, to switch careers. Participants in individual retirement accounts do not have the time or the knowledge to make...