[Archives] Arbitrage At Its Limits: Hedge Funds And The Technology Bubble

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Arbitrage at its Limits: Hedge Funds and the Technology Bubble via Yale University.

Markus K. Brunnermeier

Princeton University

Stefan Nagel

London Business School

This version: October 2002

Abstract:

Classical finance theory maintains that rational arbitrageurs would find it optimal to attack price bubbles and thus exert a correcting force on prices. We examine stock holdings of hedge funds during the time of the technology bubble on the NASDAQ. Counter to the classical view, we find that hedge fund portfolios were heavily tilted towards (overpriced) technology stocks. This does not seem to be the result of unawareness of the bubble: At an individual stock level these investments were well timed. On average, hedge funds started to reduce their exposure in the quarter prior to price peaks of individual technology stocks, and their overall stock holdings in the technology segment outperformed characteristics-matched benchmarks. Our findings are consistent with models in which arbitrage is limited, because arbitrageurs face constraints, are unable to temporally coordinate their strategies, and investor sentiment is predictable. Our results also suggest that frictions such as short-sales constraints are not sufficient to explain why the presence of sophisticated investors failed to contain the bubble.

Arbitrage At Its Limits: Hedge Funds And The Technology Bubble – Introduction

Technology stocks on NASDAQ rose to unprecedented levels during the two years leading up to March 2000. Ofek and Richardson (2001) estimate that, at the peak, the entire internet sector, comprising several hundred stocks, was priced as if the average future earnings growth rate of these firms would exceed the growth rates experienced by some of the fastest growing firms in the past, and, at the same time, the required rate of return would be zero percent for several decades. By almost any standard, such valuation levels are so outrageous that this period appears to be another episode in the history of asset price bubbles.

Shiller (2000) argues that the stock price increase was driven by irrational euphoria among individual investors, fed by an emphatic media, which maximized TV-ratings and catered to investor demand for pseudo-news. Of course, only few economists doubt that there are both rational and irrational market participants. However, there are two opposing views about whether rational traders correct the price impact of behavioral traders. The classic efficient market hypothesis (Friedman 1953, Fama 1965) predicts that sophisticated rational traders will undo any mispricing caused by “irrational exuberance”. The literature on limits of arbitrage questions this claim. It argues that various factors such as market timing incentives, noise trader risk, and transactions costs constrain arbitrage.

Our objective in this paper is to empirically characterize the response of “rational arbitrageurs” to the growth of the technology bubble. Specifically, we examine stock holdings of hedge funds during the 1998 to 2000 period. Our choice to look at hedge funds is motivated by the fact that hedge funds are highly sophisticated investors, who should come closest to the ideal of “rational arbitrageurs” in classical finance theory. By observing their trading behavior, we are able to examine whether hedge funds were indeed a correcting force during the bubble period, and it also allows us to provide empirical evidence on limits to arbitrage.

Our study is unusual in that we look at hedge fund holdings directly. In general, data on hedge funds is very difficult to obtain, since hedge funds are not regulated by the SEC. However, like other institutional investors, hedge funds with large holdings in U.S. equities do have to report their quarterly equity long positions to the SEC on form 13F. We extract hedge fund holdings from these data, including those of well-known managers such as Soros, Tiger, Tudor, and others. To the best of our knowledge, our paper is the first to use holdings data to analyze the trading activities of hedge funds. To assess the effect of short positions and derivatives, we also look at returns of hedge funds.

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