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...

In this paper, we proposed a hedge detection method with average perceptron, which was used in the closed challenge in CoNLL-2010 Shared Task. There are two subtasks: (1) detecting uncertain sentences and (2) identifying the in-sentence scopes of hedge cues. We use the unified learning algorithm for both subtasks since that the hedge score of sentence can be decomposed into scores of the words,...

We test the hypothesis that capacity constraints significantly influence hedge fund families’ decision to open new funds. Hedge fund families face diseconomies of scale because of the non-scalability of their investment strategies. We propose that as the existing funds approach critical size, hedge fund families may prefer opening new funds rather than accepting new investment in the existing f...

This paper presents a system which adopts a standard sequence labeling technique for hedge detection and scope finding. For hedge detection, we formulate it as a hedge labeling problem, while for hedge scope finding, we use a two-step labeling strategy, one for hedge labeling and the other for scope finding. In particular, various kinds of syntactic dependencies are systemically exploited and e...

We assess the use of hedge phrases in “affective” NLG texts. A simple experiment suggests non-native speakers prefer texts that contain hedge phrases, but native speakers prefer texts that do not contain hedge phrases.

This paper re-examines the ability of the factor model approach to evaluate the performance of the Equity Hedge, Event Driven, Macro, Relative Value, and Funds of Hedge Funds styles. As Hedge Fund returns are not normally distributed, we assign a premium to higher-order comoments of Hedge Fund returns with the US market aggregate. In addition to traditional asset(conditioned by the levels of so...