Abstract In this paper, the effect of leverage on hedge fund performance is measured. TASS data from 1994 to 2016 are used to measure the impact of leverage on hedge fund performance. Three hedge fund performance measurements are regressed on degree of leverage with eight control variables including fund size, strategies, and use of derivatives. The results show that for strategy-adjusted return as a performance measurement, hedge fund leverage has a negative impact on fund performance. Also there is evidence of diseconomies of scale where funds with medium-sized assets under management (AUM) tend to show better performance than funds with high AUM. No significant relation between use of leverage and performance is observed for other performance measurements, including the Fung and Hsieh seven and eight-factor alpha and style-adjusted return. Acknowledgements I like to express the deepest appreciation to my thesis advisor professor David M. Smith for his continuous support of this research, and for providing me with all the necessary data for the research. His office was always opened for guidance, and his patience allowed this paper to be my own work, but steered in the right direction when needed. I would also like to thank professor Rita Biswas for her insightful comment which leaded me to have wide perspective for my research. I am also grateful for her warm encouragement. I take this opportunity to express gratitude to all of the Finance Department faculty members who are always ready to help students. Without their excellence in teaching, this paper would have never been accomplished.
strategies that display high leverage use in dissolved funds but low leverage use in live funds. 46.15% of dedicated short bias in dissolved funds used leverage whereas only 16.67% are using leverage in live funds. Options strategy as well, used relatively high leverage (46.65%) in dissolved funds, yet only 9.09% are using leverage in live funds. However, since the Live category does not contain enough number of dedicated short bias and options strategy, it is hard to conclude that two strategies have inconsistent weight of leverage. Table 1 Summary statistics of leverage use across various hedge fund strategies Graveyard 2016 Funds Leveraged Funds Unleveraged Convertible Arbitrage 195 (73.9%) 69 (26.1%) Dedicated Short Bias 24 (46.2%) 28 (53.8%) Emerging Markets 516 (60.7%) 334 (39.3%) Equity Market Neutral 356 (57.9%) 259 (42.1%) Event Driven 365 (52.3%) 333 (47.7%) Fixed Income Arbitrage 262 (64.5%) 144 (35.5%) Fund of Funds 1830 (36.1%) 3243 (63.9%) Global Macro 584 (69.5%) 256 (30.5%) Long/Short Equity Hedge 1922 (58.6%) 1356 (41.4%) Managed Futures 638 (68.3%) 296 (31.7%) Multi-Strategy 867 (54.4%) 727 (45.6%) Options Strategy 21 (45.7%) 25 (54.3%) SUM 7580 (51.7%) 7070 (48.3%) Live 2016 Funds Leveraged Funds Unleveraged Convertible Arbitrage 34 (82.9%) 7 (17.1%) Dedicated Short Bias 1 (16.7%) 5 (83.3%) Emerging Markets 118 (50.0%) 118 (50.0%) Equity Market Neutral 70 (56.0%) 55 (44.0%) Event Driven 89 (52.0%) 79 (47.0%) Fixed Income Arbitrage 77 (65.3%) 41 (34.7%) Fund of Funds 634 (37.5%) 1056 (62.5%) Global Macro 154 (60.4%) 101 (39.6%)
survivorship bias that is reported by Liang (2000). Furthermore, frequently observed extreme dispersion of hedge fund returns is likely to distort the shape of return sample. Thus, to avoid misrepresentation from outliers, winsorizing is needed. Winsorizing is a transformation of extreme returns into an upper and lower percentile (e.g., the 1st and 99th percentiles), so that extreme outliers do not excessively influence the results. Methodology To address the question of whether individual funds’ use of leverage is stable over the years, TASS data between 2009 and 2016 are examined. Only those funds for which leverage is stable throughout this period are retained in the sample. TASS data on leverage usage was not available prior to 2009, so this study assumes that average leverage was stable even prior to that time. Following the method of Chen (2011), this study only includes funds with inception date after 1994 in order to mitigate survivorship bias reported by Brown, Goetzmann, Ibbotson, and Ross (1992) since TASS database does not report the returns of dissolved funds prior to 1994. Also in order to avoid backfilling bias and incubation bias, return data before the initial reporting date are excluded based on the ideas of Ackerman, McEnally, and Ravenscraft (1999) and Evans (2010). Among numerous graveyard fund data, only funds with “DropReasonID #1” (fund liquidated) are considered to exclude other reasons for drop out (e.g., fund no longer reporting, unable to contact fund, fund closed to new investment, etc.) and to induce meaningful use of dissolved funds. The forementioned three performance measurements including Fung and Hsieh’s (2004) seven and eight-factor alpha, strategy-adjusted return, and style-adjusted return are used.