1,189 research outputs found
Do Sophisticated Investors Believe in the Law of Small Numbers?
Believers in the law of small numbers tend to overinfer the outcome of a random process after a small series of observations. They believe that small samples replicate the probability distribution properties of the population. We provide empirical evidence indicating that investors are mistakenly driven by this psychological bias when hiring or firing a fund manager after a successful (or losing) performance streak. Using quarterly data between 1994 and 2000 of 752 hedge funds, we analyze actual money flows into and out of hedge funds and their relationship with the length of the streak. We first show that persistence patterns have a predictive ability of future relative performance of a manager: the longer the winner streak, the larger the probability for a fund to remain a winner. Investors, in turn, appear to be aware of quality dispersion across managers and respond by following a momentum strategy: the longer the winning (losing) streak, the more likely they will invest in (divest from) that fund. Yet, we find that investors place excessive weight in the managers’ track record as a criterion for decision. Our model shows that the length of the streak has an economically and statistically significant impact on money flows beyond rationally expected performance, which confirms a “hot-hand†bias driving to a large extent momentum investing. Apparently, even sophisticated investors exhibit psychological biases that may have adverse effects on their wealth.Performance Persistence;Overreaction;Hedge Fund Investors;Hot-Hand Bias;Law of Small Numbers
Survival, Look-Ahead Bias and the Persistence in Hedge Fund Performance
Hedge funds databases are typically subject to high attrition ratesbecause of fund termination and self-selection. Even when all fundsare included up to their last available return, one cannot preventthat ex post conditioning biases a.ect standard estimates ofperformance persistence. In this paper we analyze the persistence inthe performance of U.S. hedge funds taking into account look-aheadbias (multi-period sampling bias). To do so, we model attrition ofhedge funds and analyze how it depends upon historical performance.Next, we use a weighting procedure that eliminates look-ahead bias inmeasures for performance persistence. The results show that the impactof look-ahead bias is quite severe, even though positive and negativesurvival-related biases are sometimes suggested to cancel out. Athorizons of one and four quarters, we find clear evidence of positivepersistence in hedge fund returns, also after correcting forinvestment style. At the two-year horizon, past winning funds tend toperform poorly in the future.survival;performance measurement;investments;individual profiles;hedge funds
Survival, Look-Ahead Bias and the Persistence in Hedge Fund Performance
Hedge funds databases are typicall subject to high attrition rates because of fund termination and self-selection.Even when all funds are included up to their last available return, one cannot prevent that ex post conditioning biases affect standard estimates of performance persistence.In this paper we analyze the persistence in the performance of U.S. hedge funds taking into account look-ahead bias (multi-period sampling bias).To do so, we model attrition of hedge funds and analyze how it depends upon historical performance.Next, we use a weighting procedure that eliminates look-ahead bias in measures for performance persistence.The results show that the impact of look-ahead bias is quitesevere, even though positive and negative survivalrelated biases are sometimes suggested to cancel out.At horizons of one and four quarters, we find clear evidence of positive persistence in hedge fund returns, also after correcting for investment style.At the two-year horizon, past winning funds tend to perform poorly in the future.hedging;performance measurement;investment trusts
A Portrait of Hedge Fund Investors: Flows, Performance and Smart Money
We explore the flow-performance interrelation by explicitly separating the investment and divestment decisions of hedge fund investors. The results show that different determinants and evaluation horizons underlie both decisions. While money inflows are sensitive to past long-run performance, outflows exhibit an immediate and sustained response to past performance in the short run. As a consequence, the shape of the flow-performance relation differs depending on the time horizon being analyzed. We find a weaker flow-performance relation for winning funds at quarterly horizons compared to annual horizons, which may explain why quarterly persistence in hedge fund performance is not competed away. Indeed, we also find evidence that most investors are unable to exploit the persistence of the winners. Conversely, investors are fast and successful in deallocating from the persistent losers, ensuring a disciplining mechanism for lowquality funds. Further, our findings do not support the existence of smart money
Do Sophisticated Investors Believe in the Law of Small Numbers?
Believers in the law of small numbers tend to overinfer the outcome of a random process after a small series of observations. They believe that small samples replicate the probability distribution properties of the population. We provide empirical evidence indicating that investors are mistakenly driven by this psychological bias when hiring or firing a fund manager after a successful (or losing) performance streak. Using quarterly data between 1994 and 2000 of 752 hedge funds, we analyze actual money flows into and out of hedge funds and their relationship with the length of the streak. We first show that persistence patterns have a predictive ability of future relative performance of a manager: the longer the winner streak, the larger the probability for a fund to remain a winner. Investors, in turn, appear to be aware of quality dispersion across managers and respond by following a momentum strategy: the longer the winning (losing) streak, the more likely they will invest in (divest from) that fund. Yet, we find that investors place excessive weight in the managers’ track record as a criterion for decision. Our model shows that the length of the streak has an economically and statistically significant impact on money flows beyond rationally expected performance, which confirms a “hot-hand” bias driving to a large extent momentum investing. Apparently, even sophisticated investors exhibit psychological biases that may have adverse effects on their wealth
Survival, Look-Ahead Bias and the Persistence in Hedge Fund Performance
Hedge funds databases are typicall subject to high attrition rates because of fund termination and self-selection.Even when all funds are included up to their last available return, one cannot prevent that ex post conditioning biases affect standard estimates of performance persistence.In this paper we analyze the persistence in the performance of U.S. hedge funds taking into account look-ahead bias (multi-period sampling bias).To do so, we model attrition of hedge funds and analyze how it depends upon historical performance.Next, we use a weighting procedure that eliminates look-ahead bias in measures for performance persistence.The results show that the impact of look-ahead bias is quitesevere, even though positive and negative survivalrelated biases are sometimes suggested to cancel out.At horizons of one and four quarters, we find clear evidence of positive persistence in hedge fund returns, also after correcting for investment style.At the two-year horizon, past winning funds tend to perform poorly in the future
Formação de minicolônias de uruçu-cinzenta [Melipona fasciculata Smith 1858 (Apidae, Meliponini)].
On Hedge Fund Performance, Capital Flows and Investor Psychology
Guillermo Baquero (Quito, 1967) is assistant professor of Finance and Investments at the Rotterdam School of Management of Erasmus University Rotterdam since 2005. He holds a degree in mechanical engineering (Quito, 1992) and has a professional experience of several years in the field of hydraulic and pneumatic automation. Later he obtained an MBA from the Université Catholique de Louvain and an MSc in Economics from the Katholieke Universiteit Leuven, in Belgium. Between 1999 and 2001 he worked as a research associate at the Centre for Economic Studies (CES) of
the Katholieke Universiteit Leuven. In September 2001 he joined the Financial Management Department of the Rotterdam School of Management and the ERIM PhD program. Guillermo’s research has focused on the persistence of hedge funds and mutual funds, the behaviour of hedge fund investors, behavioural finance and experimental economics. The article at the basis of Chapter 3 of this book was awarded the prize for the best paper on hedge funds at the European Finance Association meetings in Zurich in 2006. The article at the basis of Chapter 2 was published in the Journal of Financial and Quantitative Analysis in 2005 and was awarded the prize for the second best paper on hedge funds at the European Finance Association meetings in Glasgow
in 2003. Guillermo’s teaching experience includes a number of courses in Corporate Finance,
Investments and Behavioural Finance, both at the bachelor and master level, and courses in Industrial Engineering at the executive level. He has worked as a
consultant for several firms and organizations in Belgium and Ecuador in matters related to Finance and Development. He is also a guest lecturer at the Latin-American Faculty of Social Sciences (FLACSO) in Quito, Ecuador.In a relatively short period of time, hedge funds have become major players in the financial markets. In 2004, the estimated total reached nearly 8000 funds, and the assets under management had risen to 100 billion in 1994. The client base for hedge funds has expanded beyond foundations and endowments to company pensions, public pensions, and to less “sophisticated” investors. However, the increasing and widespread acceptance of hedge funds as an alternative investment vehicle is disconcerting if we consider their limited transparency and the restricted liquidity conditions imposed to investors. On these grounds, serious questions arise about investors’ ability to make the right investment choices in hedge funds. This book speaks to these concerns. The four essays presented here examine the investment process of investors, the underlying factors determining their choices and the implications for investors’ wealth and for hedge funds’ performance. Four main conclusions follow. First, that hedge fund managers exhibit, on average, persistence in their performance at quarterly horizons, justifying to some extent an active search for skilled managers; however, large informational asymmetries prevent investors from taking timely decisions and exploiting the persistence of good performing funds while incurring high opportunity costs. In contrast, investors are able to divest swiftly from the poor performers, which may have a moderating effect on the risk-taking incentives of managers. Finally, investors appear to misread the information available and overreact to persistence patterns, both at the individual fund level and at the style level. Overall, this study confirms a potentially suboptimal allocation of capital flows across hedge funds, calling for higher levels of transparency in the demand side for capital, and more cautious due diligence and increased prudence in the supply side
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