In the presence of transaction costs, it is no longer possible to perfectly replicate the payoff of a European option by trading in the underlying stock. This paper develops a new option hedging strategy based on minimizing the expected cumulative hedging error and additional cost of rebalancing due to proportional transaction costs. We show that the resulting singular stochastic control proble...

Portfolio optimisation for a Fund of Hedge Funds (“FoHF”) has to address the asymmetric, non-Gaussian nature of the underlying returns distributions. Furthermore, the objective functions and constraints are not necessarily convex or even smooth. Therefore traditional portfolio optimisation methods such as mean-variance optimisation are not appropriate for such problems and global search optimis...

We develop an online algorithm called Component Hedge for learning structured concept classes when the loss of a structured concept sums over its components. Example classes include paths through a graph (composed of edges) and partial permutations (composed of assignments). The algorithm maintains a parameter vector with one non-negative weight per component, which always lies in the convex hu...

In this paper we apply data envelopment analysis (DEA) to evaluate the performance of hedge fund classifications. The purpose of alternative investment strategies such as hedge funds is to offer absolute returns, so using passive benchmarks to measure their performance could be ineffective. With the increasing number of hedge funds available, institutional investors, pension funds, and high net...

This study aimed at comparing the performances of distinct hedge fund strategies and assessing diversification opportunities using funds. paper analyses overall performance (as indices) for period 2001-2020. Hedge are compared alternative risk adjusted metrics; first, alpha based on four asset-pricing models (CAPM, Fama-French 3 factor, Carhart 5 factor models); then, Sharpe ratio. The findings...

This report was originally written as an industry white paper on Hedge Funds. This paper gives an overview to Hedge Funds, with a focus on risk management issues. We define and explain the general characteristics of Hedge Funds, their main investment strategies and the risk models employed. We address the problems in Hedge Fund modelling, survey current Hedge Funds available on the market and t...

Hedge funds have been the subject of media attention in the United States ("U.S.") and around the world given the pronounced growth of the hedge fund sector in recent years and the comparative dearth of regulations faced by hedge fund managers. The first part of this paper provides an overview of the potential agency problems associated with managing a hedge fund and the associated rationales f...

ince the early 1990s, hedge funds have become an increasingly popular asset class. The amount invested globally in hedge funds rose from approximately $50 billion in 1990 to approximately $1 trillion by the end of 2004.1 And because these funds characteristically use substantial leverage, they play a far more important role in the global securities markets than the size of their net assets indi...

Minimum-variance hedging of a contingent claim in discrete time is suboptimal when the contingent claim is hedged for multiple periods and the objective is to maximize the expected utility of cumulative hedging errors. This is because the hedging errors are not independent. The difference between a minimum-variance hedge and the optimal multiperiod hedge is called the hedging demand and depends...

We use Monte Carlo analysis to examine the potential of increased renewable generation to provide a hedge against variability in energy prices and costs. Fuel costs, electricity demand and wind generation are allowed to vary and a unit commitment and economic dispatch algorithm is employed to produce costminimising generation schedules under different levels of installed wind capacity. Increase...