Diversification in the hedge fund industry

Tail risk of hedge funds: an extreme value application

This article focuses on the hedge fund industry, its specifics and impact on the financial system and, in particular on the rate of return, risk and performance produced by the sector. The rate of return, risk and performance of the hedge funds and other asset classes were derived from monthly returns, standard deviation and Sharpe ratios. The time periods 1997-2016 and 2000-2016 were considered. The hedge fund industry, compared to the stock market, the gold market, and the overall commodity market, brought a significantly higher return at a lower risk in the considered period. In the past years, as the two-dimensionally most powerful hedge funds in the short and long term appeared to be smaller funds managing assets up to 100 million USD, and in the medium term the largest funds managing assets over 1 billion USD. From the point of view of geographic asset allocation, the highest two-dimensional performance was shown by funds allocating their assets to North American markets.

Can We Really 'Clone' Hedge Fund Returns? Further Evidence M.Kooli & S. Sharma Hedge Fund Replication: Does Model Combination Help? J. Teiletche Factor-Based Hedge Fund Replication with Risk Constraints R.D.F.Harris & M. Mazibas Takeover Probabilities and the Opportunities for Hedge Funds and Hedge Fund Replication to Produce Abnormal Gains A.Ravi , P.Mayall & J. Simpson Benchmarking of Replicated Hedge Funds M.D.Wiethuechter & L. Nemeth Insight - Distributional Hedge Fund Replication via State Contingent Stochastic Dominance C.H. Glaffig Non-Parametric Hedge Funds and Replication Indices Performance Analysis: A Robust Directional Application L. Germain , N. Nalpas & A. Vanhems Hedge Fund Cloning through State Space Models R. Savona Hedge Fund Return Replication via Learning Models R. McFall Lamm, Jr Linear Model for Passive Hedge Fund Replication G. Barone-Adesi & S. Siragusa Can Hedge Fund-like Returns be Replicated in a Regulated Environment? I. Markov & N. Tuchschmid A Factor-based Application to Hedge Fund Replication M. Rossi & S.L. Rodriguez

Can Liquidity Risk Explain the Size-Performance Relationship for Hedge Funds?

Various studies have analyzed the determinants of hedge fund performance. The majority of them, however, come to contradictory conclusions with respect to the direction of influence of different factors on fund performance. The key reason for the inconsistencies is the highly dynamic nature of hedge funds. This paper specifically focuses on the dynamics of the relations between hedge fund performance and various microeconomic factors. It quantifies shifts in the average fund alpha that result from changes in hedge fund style, age, size, and fee structure and investigates the time variation of these shifts. The empirical results highlight the dynamic nature of the hedge fund industry. Hedge funds seem to generate a positive and significant alpha on average; however, the alpha level varies considerably over time. It is hard to predict the exact absolute alpha level based on the hedge fund micro-factors, but it seems to be possible to rank hedge funds using the micro-information. The results suggest that large funds with high relative inflow, charging higher than median management fees, are likely to deliver a higher alpha than their peers most of the time.KeywordsHedge FundHigh AlphaAbsolute FlowFund FlowAverage AlphaThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Macroeconomic Risk and Hedge Fund Returns

This chapter focuses on new trends in the hedge fund industry. The chapter begins by creating some historical context for the current perception and state of hedge funds. The remainder of this chapter focuses on the following trends and their potential impact on the industry: (1) growth in all areas of the industry, especially in terms of long-term capital flows from institutional investors; (2) uncertainty about growth in the short term; (3) ways hedge funds approach growth; (4) the need for more diversity among hedge fund managers, including more minorities and women; (5) diverging long-term objectives for larger and smaller hedge funds; (6) future cost savings to investors; (7) development of new investment options to address liquidity concerns for investors; (8) new regulations; and (9) the future role of technology in the hedge fund industry.

Noting that while hedge funds are well established in the United States and Europe, they have only begun to grow aggressively in Asia, the authors introduce a practical approach to analyzing the risk and performance of Asian hedge funds from the viewpoints of U.S. and Asia-Pacific based equity investors. They focus on the impact of including Asian hedge funds in these portfolios and examine whether the inclusion helps to insulate the overall portfolio when in down markets, capturing the upside and reducing the impact of market volatility during extreme events. They note that their approach alleviates the problems that can arise if hedge fund returns are skewed, leptokurtic, and non-linearly related to the market returns. They conclude that while all funds provided diversification in the sense that they were not perfectly correlated with market index returns, only 32 or 46% of the funds were negatively correlated with the S&amp;P 500 index returns in a down market (defined as the lowest return quartile of the S&amp;P 500). Their results also showed that very few of the funds provided downside protection, upside capture, and low volatility on the down-side. They also found that their results are sensitive to the choice of benchmark and conclude that this makes the methodology suitable for performance and risk measurement relative to existing investments. <b>TOPICS:</b>Real assets/alternative investments/private equity, emerging, statistical methods, performance measurement

Systemic Risk and Hedge Funds

Hedge funds increasingly are becoming a focus of investors and U.S. regulatory agencies including the U.S. Securities and Exchange Commission (the “SEC”), the U.S. Treasury Department, the National Association of Securities Dealers, and the Commodity Futures Trading Commission as enhanced regulatory attention is forcing the hedge fund industry for the first time since the near‐collapse of Long‐Term Capital Management, L.P. in late 1998 to examine itself more closely. In light of the dismal performance of U.S. stock market indices over the past several years, investors are turning to “absolute” return vehicles, such as hedge funds, that are able to generate current positive returns in a market that has returned consistently laggard results. Investors’ ability to invest in hedge funds has been further enhanced by the increase of hedge funds‐of‐funds registered under the U.S. Investment Company Act of 1940, as amended (the “1940 Act”). Simultaneously, over the past 18 months, the SEC has become increasingly concerned with a multitude of industry occurrences including (i) the widening access of investors to hedge funds, (ii) the unregulated nature of hedge funds, potentially leading to fraud or conflicts of interest with their investors, and (iii) the impact of hedge funds on the markets, especially in relation to their use of short selling. As U.S. regulatory attention remains focused on the hedge fund industry and industry practice and the themes of potential new regulations become apparent, it has become a cautionary period for hedge fund sponsors and investment managers.

This paper models hedge fund exposure to risk factors and examines time-varying performance of hedge funds. From existing models such as asset-based style (ABS)-factor model, standard asset class (SAC)-factor model, and four-factor model, we extract the best six factors for each hedge fund portfolio by investment strategy. Then, we find combinations of risk factors that explain most of the variance in performance of each hedge fund portfolio based on investment strategy. The results show instability of coefficients in the performance attribution regression. Incorporating a time-varying factor exposure feature would be the best way to measure hedge fund performance. Furthermore, the optimal models with fewer factors exhibit greater explanatory power than existing models. Using rolling regressions, our customized investment strategy model shows how hedge funds are sensitive to risk factors according to market conditions.

A Total Risk Measurement Framework for Hedge Funds and Funds of Funds

Capacity constraints, investor information, and hedge fund returns

THOMAS SCHNEEWEIS is a professor at the School of Management of the University of Massachusetts at Amherst. R ecent events in financial markets have focused interest on the existence and operations of a relatively new form of investment entity, the hedge fund. While many definitions for hedge funds exist, they are basically ‘‘loosely regulated private pooled investment vehicles that can invest in both cash and derivative markets on a leveraged basis for the benefits of its investors.’’ Unfortunately, there are a number of myths surrounding hedge funds and the risk and return opportunities that hedge funds offer. In a short comment one cannot cover in detail all of the misconceptions about the performance of hedge funds or other alternative investments. In fact, journals such as The Journal of Alternative Investments exist to permit a better long term understanding of many of the new alternative investment forms. However, despite a wide range of research conducted on hedge funds and their performance, the following are a number of popular misconceptions.

Since 1997, the hedge fund industry has grown at a compounded annual growth rate of 16.07%, resulting in a 26-fold increase from its original value to its present value of $3.1 trillion Assets Under Management. This study researched the varying investment strategies used by hedge funds to determine the strategy that provides the highest returns for its investors. From the previous literature, the study identified Long/Short Equity, Global Macro, Arbitrage, Event Driven, and Cross-Asset Multi-Strategy as viable and relevant investment approaches. Using hedge fund index data from Bloomberg, Hedge Fund Research, Eureka Hedge, Barclay’s, and Credit Suisse, returns for each respective strategy were collected and compared against the Bloomberg Global Hedge Fund (BHEDGE) Index and the S&amp;P 500 Index. Alpha adjusted returns for each strategy were later calculated and plotted against the average weighted returns of each individual strategy. The results of this study show that the L/S Equity strategy provided the highest returns for its investors. Specifically, only the L/S Equity strategy outperformed the BHEDGE Index by a narrow margin, while all other strategies provided negative alpha figures. All hedge fund strategies outperformed the overall equity market on a year-to-date basis, however, provided negative alpha returns when compared to the S&amp;P 500 1-Year market gains. This deficit between hedge funds and the overall equity market can be attributed to the COVID-19 pandemic and its inflationary effects through low interest rates, market stimulus packs, and an increased money supply.