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 #1” (fund “DropReasonID 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.
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.
The_Impact_of_Leverage_on_Hedge_Fund_Performance_(Wansoo_Choi).docx