This study develops a portfolio optimization method based on the Stochastic Dominance (SD) decision criterion and the Empirical Likelihood (EL) estimation method. SD and EL share a distribution-free assumption framework which allows for dynamic and non-Gaussian multivariate return distributions....

A stochastic bound is a portfolio which stochastically dominates all alternatives in a reference portfolio set instead of a single alternative portfolio. An approximate bound is a portfolio which comes as close as possible to this ideal. To identify and analyze exact or approximate bounds,...

We derive a limit theorem for appropriately centered and scaled martingale transforms of the form sum_{i=1}^{n}\xi_{i}V_{i} to mixed-stable limits when (\xi_{i})_{i\in\mathbb{Z}} is an iid sequence in the domain of attraction of an alpha-stable distribution where alpha\in(0,2]. Using the...

We provide a CLT for martingale transforms that holds even when the second moments are infinite. Compared to an analogous result in Hall and Yao [Econometrica 71 (2003) 285-317] we impose minimal assumptions and utilize the Principle of Conditioning to verify a modified version of the...

We derive a limit theorem for appropriately centered and scaled martingale transforms \sum_{i=1}^{n}\xi_{i}V_{i} to mixed-stable limits when \left(\xi_{i}\right) is an iid sequence in the domain of attraction of an \alpha-stable distribution where \alpha\in(0,2]. Using the Principle of...