We use a case study of a pension plan wishing to hedge the longevity risk in its pension liabilities at a future date. The plan has the choice of using either a customised hedge or an index hedge, with the degree of hedge effectiveness being closely related to the correlation between the value of the hedge and the value of the pension liability. The key contribution of this paper is to show how...

We initiate the study of hedge connectivity of undirected graphs, motivated by dependent edge failures in real-world networks. In this model, edges are partitioned into groups called hedges that fail together. The hedge connectivity of a graph is the minimum number of hedges whose removal disconnects the graph. We give a polynomial-time approximation scheme and a quasi-polynomial exact algorith...

Salvia divinorum is a new recreational drug where few studies have been conducted on its prevalence and predictors of use. Using a sample of undergraduate students, this study investigated these issues. While a small number reported experimenting with salvia, logistic regression models showed that demographics, marijuana use, and self-control are statistically significant predictors. The effect...

We analyze hedge fund performance using the stochastic discount factor (SDF) approach and imposing the arbitrage-free requirement to correctly value the derivatives and dynamic trading strategies used by hedge funds. Using SDFs of many asset-pricing models, we evaluate hedge fund portfolios based on style and characteristics. Without the arbitrage-free requirement, pricing errors are relatively...

We show that the Hedge Algorithm, a method widely used in Machine Learning, can be interpreted as a particular subgradient algorithm for minimizing a well-chosen convex function, namely a Mirror Descent Scheme. Using this reformulation, we can improve slightly the worstcase convergence guarantees of the Hedge Algorithm. Recently, Nesterov has introduced the class of Primal-Dual Subgradient Algo...

We use a new dataset of hedge fund returns from a separate account platform to examine (1) how much of hedge fund return smoothing is due to main-fund specific factors, such as managerial reporting discretion (2) the costs of removing hedge fund share restrictions. These accounts trade pari passu with matching hedge funds but feature third-party reporting and permissive share restrictions. We u...

This thesis applies a Partial Integral Differential Equation model, along with a Monte Carlo approach to quantitatively analyze the no arbitrage value of hedge fund performance fees. From a no-arbitrage point of view, the investor in a hedge fund is providing a free option to the manager of the hedge fund. The no-arbitrage value of this option can be locked in by the hedge fund manager using a ...

Hedge detection is used to distinguish uncertain information from facts, which is of essential importance in biomedical information extraction. The task of hedge detection is often divided into two subtasks: detecting uncertain cues and their linguistic scope. Hedge scope is a sequence of tokens including the hedge cue in a sentence. Previous hedge scope detection methods usually take all token...

This paper investigates hedge funds’ exposures to various financial and macroeconomic risk factors through alternative measures of factor betas and examines the performance of these factor betas in predicting the cross-sectional variation in hedge fund returns. The results indicate a positive and significant link between default premium beta (DEF beta) and future hedge fund returns as well as a...