Did the STOCK Act impact the performance, risk and flow of hedge funds?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Laleh Samarbakhsh ◽  
Meet Shah

PurposeThis research aims to examine hedge funds’ performance, risk and flow before and after the implementation of the Stop Trading on Congressional Knowledge (STOCK) Act.Design/methodology/approachThis paper includes the use of different factor models to highlight the performance and risk of hedge funds before and after the implementation of the STOCK Act. Hedge fund holdings are retrieved from Thomson Reuters Lipper Hedge Fund Database (TASS).FindingsThis study finds significant differences before and after the implementation of the STOCK Act. The results for the entire sample period indicate that hedge funds suffered lower-alpha, standard deviation and idiosyncratic risk after the implementation of the STOCK Act.Originality/valueThe paper’s originality and value lie in addressing the relationship gap between the STOCK Act and hedge fund performance.

2017 ◽  
Vol 11 (3) ◽  
pp. 387-414 ◽  
Author(s):  
Zachary Alexander Smith ◽  
Muhammad Zubair Mumtaz

Purpose The purpose of this paper is to examine whether there is significant evidence that hedge fund managers engage in deceptive manipulation of their reported performance results. Design/methodology/approach A model of hedge fund performance has been developed using standard regression analysis incorporating dependent lagged variables and an autoregressive process. In addition, the extreme bounds analysis technique has been used to examine the robustness and sensitivity of the explanatory variables. Finally, the conditional influence of the global stock market’s returns on hedge fund performance and the conditional return behavior of the Hedge Fund Index’s performance have been explored. Findings This paper begins by identifying a model of hedge fund performance using passive index funds that is well specified and robust. Next, the lag structure associated with hedge fund returns has been examined and it has been determined that it seems to take the hedge fund managers two months to integrate the global stock market’s returns into their reported performance; however, the lagged variables were reduced from the final model. The paper continues to explore the smoothing behavior by conditioning the dependent lagged variables on positive and negative returns and find that managers are conservative in their estimates of positive performance events, but, when experiencing a negative result, they seem to attempt to rapidly integrate that effect into the return series. The strength of their integration increases as the magnitude of the negative performance increases. Finally, the performance of returns for both the Hedge Fund Index and the passive indices were examined and no significant differences between the conditional returns were found. Research limitations/implications The results of this analysis illustrate that hedge fund performance is not all that different from the performance of passive indices included in this paper, although it does offer investors access to a unique return distribution. From a management perspective, we are reminded that we need to be cautious about hastily arriving at conclusions about something that looks different or feels different from everything else, because, at times, our preconceived notions will cause us to avoid participating in something that may add value to our organizations. From an investment perspective, sometimes having something that looks and behaves differently from everything else, improves our investment experience. Originality/value This paper provides a well-specified and robust model of hedge fund performance and uses extreme bounds analysis to test the robustness of this model. This paper also investigates the smoothing behavior of hedge fund performance by segmenting the returns into two cohorts, and it finds that the smoothing behavior is only significant after the hedge funds produce positive performance results, the strength of the relationship between the global stock market and hedge fund performance is more economically significant if the market has generated a negative performance result in the previous period, and that as the previous period’s performance becomes increasingly negative, the strength of the relationship between the Hedge Fund Index and the global stock market increases.


2018 ◽  
Vol 21 (03) ◽  
pp. 1850016 ◽  
Author(s):  
Yao Zheng ◽  
Eric Osmer

We examine the dynamic effect of aggregate stock market sentiment on the performance of various hedge fund styles. We find that hedge funds typically perform better during periods of optimistic sentiment and that for different hedge fund styles there is a differential response of hedge fund returns to positive and negative sentiment shocks. We also find that changes in aggregate investor sentiment have a larger effect on hedge fund performance during periods of high conditional volatility. Our results suggest there is a strong asymmetry in the relationship between hedge fund performance and investor sentiment.


2021 ◽  
Author(s):  
Lingling Zheng ◽  
Xuemin (Sterling) Yan

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.


2020 ◽  
Vol 66 (12) ◽  
pp. 5505-5531 ◽  
Author(s):  
Mark Grinblatt ◽  
Gergana Jostova ◽  
Lubomir Petrasek ◽  
Alexander Philipov

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.


2019 ◽  
Vol 33 (10) ◽  
pp. 4771-4810 ◽  
Author(s):  
Clemens Sialm ◽  
Zheng Sun ◽  
Lu Zheng

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.


2017 ◽  
Vol 07 (02) ◽  
pp. 1750002
Author(s):  
Hany A. Shawky ◽  
Ying Wang

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.


2018 ◽  
Vol 54 (4) ◽  
pp. 1539-1571 ◽  
Author(s):  
Juha Joenväärä ◽  
Robert Kosowski ◽  
Pekka Tolonen

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.


Author(s):  
Komlan Sedzro

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.


Author(s):  
Jeffrey S. Smith ◽  
Kenneth Small ◽  
Phillip Njoroge

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.


Author(s):  
H. Kent Baker ◽  
Greg Filbeck

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.


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