scholarly journals Home Bias and Local Contagion: Evidence from Funds of Hedge Funds

2019 ◽  
Vol 33 (10) ◽  
pp. 4771-4810 ◽  
Author(s):  
Clemens Sialm ◽  
Zheng Sun ◽  
Lu Zheng
Keyword(s):  
Market Segmentation ◽  
Hedge Funds ◽  
Hedge Fund ◽  
Home Bias ◽  
Fund Performance ◽  
Superior Performance ◽  
Local Bias ◽  
Funds Of Hedge Funds ◽  
Hedge Fund Performance ◽  
Funds Of Funds

Abstract Our paper analyzes the geographical preferences of hedge fund investors and the implication of these preferences for hedge fund performance. We find that funds of hedge funds overweigh their investments in hedge funds located in the same geographical areas and that funds with a stronger local bias exhibit superior performance. Local bias also gives rise to excess flow comovement and extreme return clustering within geographic areas. Overall, our results suggest that while funds of funds benefit from local advantages, their local bias also creates market segmentation that can destabilize the underlying hedge funds.

Financial Industry Affiliation and Hedge Fund Performance

2021 ◽  
Author(s):  
Lingling Zheng ◽  
Xuemin (Sterling) Yan
Keyword(s):  
Initial Public Offerings ◽  
Hedge Funds ◽  
Negative Impact ◽  
Hedge Fund ◽  
Seasoned Equity Offerings ◽  
Fund Performance ◽  
Financial Industry ◽  
Internal Conflicts ◽  
Industry Affiliation ◽  
Hedge Fund Performance

Affiliation with a financial conglomerate may provide hedge funds with superior information about the conglomerate’s lending, investment banking, and brokerage clients; such affiliation can also lead to potential conflicts with the other units of the conglomerate and exacerbate the conflict between hedge fund companies and hedge fund investors. We find that affiliated funds significantly underperform unaffiliated funds. A difference-in-difference analysis confirms the negative relation between financial industry affiliation and hedge fund performance. Affiliated funds pursue asset-gathering strategies, overweight their conducted initial public offerings/seasoned equity offerings clients’ stocks, are more likely to commit legal and regulatory violations, and tend to exhibit a greater number of internal conflicts. Our results are consistent with conflict of interest exerting a negative impact on the performance of affiliated hedge funds. However, it is possible that lack of skill also contributes to the underperformance of affiliated funds. This paper was accepted by Karl Diether, finance.

Style and Skill: Hedge Funds, Mutual Funds, and Momentum

2020 ◽  
Vol 66 (12) ◽  
pp. 5505-5531 ◽  
Author(s):  
Mark Grinblatt ◽  
Gergana Jostova ◽  
Lubomir Petrasek ◽  
Alexander Philipov
Keyword(s):  
Mutual Funds ◽  
Hedge Funds ◽  
Mutual Fund ◽  
Hedge Fund ◽  
Fund Performance ◽  
Short Sales ◽  
Fund Managers ◽  
Liquidity Provision ◽  
Stock Picking ◽  
Hedge Fund Performance

Classifying mandatory 13F stockholding filings by manager type reveals that hedge fund strategies are mostly contrarian, and mutual fund strategies are largely trend following. The only institutional performers—the two thirds of hedge fund managers that are contrarian—earn alpha of 2.4% per year. Contrarian hedge fund managers tend to trade profitably with all other manager types, especially when purchasing stocks from momentum-oriented hedge and mutual fund managers. Superior contrarian hedge fund performance exhibits persistence and stems from stock-picking ability rather than liquidity provision. Aggregate short sales further support these conclusions about the style and skill of various fund manager types. This paper was accepted by Tyler Shumway, finance.

Can Liquidity Risk Explain Diseconomies of Scale in Hedge Funds?

2017 ◽  
Vol 07 (02) ◽  
pp. 1750002
Author(s):  
Hany A. Shawky ◽  
Ying Wang
Keyword(s):  
Hedge Funds ◽  
Hedge Fund ◽  
Liquidity Risk ◽  
Fund Performance ◽  
Diseconomies Of Scale ◽  
Liquidity Crises ◽  
Using Data ◽  
Asset Size ◽  
Hedge Fund Performance

Using data from the Lipper TASS hedge fund database over the period 1994–2012, we examine the role of liquidity risk in explaining the relation between asset size and hedge fund performance. While a significant negative size-performance relation exists for all hedge funds, once we stratify our sample by liquidity risk, we find that such a relationship only exists among funds with the highest liquidity risk. Liquidity risk is found to be another important source of diseconomies of scale in the hedge fund industry. Evidently, for high liquidity risk funds, large funds are less able to recover from the relatively more significant losses incurred during market-wide liquidity crises, resulting in lower performance for large funds relative to small funds.

scholarly journals The Effect of Investment Constraints on Hedge Fund Investor Returns

2018 ◽  
Vol 54 (4) ◽  
pp. 1539-1571 ◽  
Author(s):  
Juha Joenväärä ◽  
Robert Kosowski ◽  
Pekka Tolonen
Keyword(s):  
Real World ◽  
Hedge Funds ◽  
Liquidity Constraints ◽  
Hedge Fund ◽  
Fund Performance ◽  
Performance Persistence ◽  
Investor Returns ◽  
Fund Size ◽  
Hedge Fund Performance ◽  
Investment Constraints

This paper examines the effect of real-world, investor-level investment constraints, including several that have not been studied before, on hedge fund performance and its persistence. Using a large consolidated database, we demonstrate that hedge fund performance persistence is significantly reduced when rebalancing rules reflect fund size restrictions and liquidity constraints but remains statistically significant at higher rebalancing frequencies. Hypothetical investor portfolios that incorporate additional minimum diversification constraints, minimum investment requirements, and focus on open funds suggest that the performance and its persistence documented in earlier studies of hedge funds is not easily exploitable, especially by large investors.

Beta Active Hedge Fund Management

2018 ◽  
Vol 53 (6) ◽  
pp. 2525-2558 ◽  
Author(s):  
Jun Duanmu ◽  
Alexey Malakhov ◽  
William R. McCumber
Keyword(s):  
Hedge Funds ◽  
Common Factor ◽  
Explanatory Power ◽  
Hedge Fund ◽  
Superior Performance ◽  
Time Varying ◽  
Fund Managers ◽  
Out Of Sample ◽  
Hedge Fund Performance

We reconsider whether hedge funds’ time-varying risk factor exposures are predictive of superior performance. We construct an overall measure (BA) of fund managers and present evidence that top beta active managers deliver superior long-term out-of-sample performance compared to top alpha active managers. BA captures the time-varying nature of beta exposures and can be interpreted as a common factor of both systematic risk (SR) and (1 - R2) measures. BA also compares favorably to extant measures of market timing, capturing the explanatory power of such measures of hedge fund performance.

scholarly journals New Evidence On Hedge Fund Performance Measures

2011 ◽  
Vol 8 (11) ◽  
Author(s):  
Komlan Sedzro
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Measures ◽  
Hedge Funds ◽  
Hedge Fund ◽  
Fund Performance ◽  
Sharpe Ratio ◽  
Data Envelopment ◽  
Sharpe Ratios ◽  
Hedge Fund Performance ◽  
New Evidence

Hedge funds are still relatively unfamiliar to most investors despite the intense popularity they have enjoyed in recent years. Measuring the performance of these financial instruments using traditional methods is, however, problematic, since their returns do not follow a normal distribution. In this study, we consider rankings obtained with the Stochastic Dominance (SD) method and compare them with ranks produced using Sharpe Ratios, Modified Sharpe Ratios, and Data Envelopment Analysis. We also explore the advantages highlighted by the literature of the Data Envelopment Analysis (DEA) method in relation to traditional measures like Sharpe ratio and Modified Sharpe ratio. Our results show that classic performance measures are better correlated with SD than DEA results.

Benchmarking and Bias in Hedge Funds

2017 ◽  
Author(s):  
Jeffrey S. Smith ◽  
Kenneth Small ◽  
Phillip Njoroge
Keyword(s):  
Selection Bias ◽  
Hedge Funds ◽  
Hedge Fund ◽  
Academic Research ◽  
Fund Performance ◽  
Measurement Bias ◽  
Return Smoothing ◽  
Survivorship Bias ◽  
Hedge Fund Returns ◽  
Hedge Fund Performance

This chapter discusses investment benchmarking and measurement bias in hedge fund performance. A good benchmark should be unambiguous, investible, measurable, appropriate, reflective of current investment opinions, specified in advance, and accountable. Additionally, a good benchmark should be simple, easily replicable, comparable, and representative of the market that the benchmark is trying to capture. Several biases, such as database selection bias, survivorship bias, style classification bias, backfill bias, self-reporting bias, and return-smoothing bias exist that impede the process of creating a benchmark. These biases increase the difficulty of studying hedge fund returns and managerial skill. However, most of the academic research on hedge fund returns report positive alphas for hedge funds.

Hedge Fund Pricing

2017 ◽  
Author(s):  
David Hampton
Keyword(s):  
Asset Pricing ◽  
Hedge Funds ◽  
Hedge Fund ◽  
Theory Of The Firm ◽  
Fund Managers ◽  
Asset Pricing Theory ◽  
Funds Of Hedge Funds ◽  
Pricing Theory ◽  
Computational Platform ◽  
Hedge Fund Performance

The two main differentiating features of hedge fund managers compared to traditional investment managers are their ability to leverage and to take both short and long positions. Asset-pricing models used in traditional investment management appraisal have evolved to take these two features into account to correctly specify the pricing of hedge funds. Modern hedge fund asset-pricing theory has its roots in two venerable fields of financial economics research: capital asset pricing and the theory of the firm. This chapter presents the theory and intuition behind the most widely used models for hedge fund performance analysis. MATLAB is used as a computational platform for examples in the chapter using 10 hypothetical hedge fund return vectors. Quants and managers of funds of hedge funds deal mostly with data as presented in net monthly column vectors typically in a Microsoft Excel format.

Hedge Funds Fundamentals

2017 ◽  
Author(s):  
H. Kent Baker ◽  
Greg Filbeck
Keyword(s):  
Hedge Funds ◽  
Hedge Fund ◽  
Fund Performance ◽  
Investment Strategies ◽  
Intended Audience ◽  
History Of ◽  
Background Material ◽  
Fund Investment ◽  
Hedge Fund Performance ◽  
Distinguishing Features

This chapter provides background material for understanding the multifaceted nature of hedge funds. The first section begins by defining a hedge fund, followed by a discussion of distinguishing characteristics, benefits and risks, history of hedge funds, hedge fund investment strategies, funds of funds, hedge fund performance, and hedge fund biases, including selection bias, survivorship bias, backfill bias, and liquidation bias. The next section discusses the purpose of the book followed by sections on its distinguishing features and the intended audience. The chapter then outlines the six major parts of the book, including an abstract for each of the remaining 29 chapters. These six parts are (1) background, (2) structure of hedge funds, (3) investment strategies of hedge funds, (4) risk and regulation, (5) hedge fund performance, and (6) issues, trends, and future prospects of hedge funds. The final section offers a summary and conclusions.

scholarly journals Hedge Fund Performance during and after the Crisis: A Comparative Analysis of Strategies 2007–2017

2019 ◽  
Vol 7 (1) ◽  
pp. 15
Author(s):  
Nicola Metzger ◽  
Vijay Shenai
Keyword(s):  
Hedge Funds ◽  
Factor Model ◽  
Practical Knowledge ◽  
Hedge Fund ◽  
Fund Performance ◽  
Fixed Income ◽  
Return Distributions ◽  
Passive Strategies ◽  
Hedge Fund Performance ◽  
Better Than

The performance of hedge funds is of interest to investors looking for ways of generating value over passive strategies, particularly in bad times. This study used the Hedge Index database with over 9500 hedge funds to analyse, in depth, the performance of ten major strategies, during and after the financial crisis (June 2007–January 2017). To the best of our knowledge, such a study covering the last ten years has not been published. Performance of the various strategies was analysed, using correlations, the Carhart’s four factor model, persistence of performance, and reward-risk ratios. The findings are that some hedge fund strategies which have persistent performances are also able to outperform the benchmark in some periods. In the crisis period, value-wise, all strategies did better than the S&P500, thereby, conserving value for investors, better than passive investment in the S&P500. Over the entire period of the research (June 2007–January 2017), seven strategies performed better than the S&P500: Global Macro, Multi Strategy, Emerging Markets, Long/Short Equity, Event Driven, Convertible Arbitrage, and Fixed Income Arbitrage. As hedge funds typically have skewed return distributions, performance was analysed in different periods, within conventional and downside risk frameworks. This research contributes to the advancement of knowledge on the outcomes of hedge fund strategies in different market conditions and the reliability of alternative risk frameworks in their evaluation. Apart from the theoretical implications, this research provides practical knowledge to managers and investors on which strategies hold better value and in what circumstances.

Sign in / Sign up

Export Citation Format

Share Document