Perspectives on Hedge Fund Herding: A Survey of Analytical Methods

Abstract

This article examines herding among hedge fund styles and uncovers new intuitions about the industry. By examining hedge fund style index returns using four techniques, we show that perceptions of herding may differ based on the choice of analytical method. Our analysis with independent component analysis is new, and we show that over time the various styles have evolved to meet the variance expectations of investors. We infer that hedge fund managers are adding value through techniques that deliver consistent returns derived from idiosyncratic factors that appear in higher moments.

An Empirical Study of Volatility Spillover Worldwide

“…The literature typically considers that diversification is found only in second order measures of dependence. However, Kumiega et al (2014) find that correlation may not necessarily be appropriate. They apply the five techniques to hedge fund index data and find the second-order techniques show evidence of herding, where funds mimic other funds.…”

Extraction of the Underlying Structure of Systematic Risk from Non-Gaussian Multivariate Financial Time Series Using Independent Component Analysis: Evidence from the Mexican Stock Exchange

“…(3) to manage investment portfolios [8]; (4) to allocate assets [32]; (5) to forecast financial time series [30]; (6) to compute improved portfolio risk measures such as VaR in banking sector [6,7]; (7) to explain the volatility of investment funds [45]; (8) to generate an equity sector classification [43]; (9) to improve bank performance evaluation [29]; (10) to produce multifactor index variance from the SPX sector ETF returns [38]; (11) to measure the dependency between stocks in the USA [17], and (12) to analyze herding among hedge fund styles [27].…”