In the previous sections, we saw that - to a certain extent - funds’ characteristics explain a part of the difference in realized performance between hedge funds. Are there groups of investors which systematically differ in their demand for certain characteristics? In the flavor ofBerk and van Binsbergen(2016), I take the perspective of a revealed preferences approach and estimate the preferences of hedge fund investors for a hedge fund’s characteristics. Taking the allocations of the investors as given, I estimate the preferences for fund characteristics which are compatible with these observed allocations. I estimate the preferences for the
control variables used in the previous Section: management fee (MgmtFee); performance fee (PerfFee); age of the fund, measured as the number of years passed since the first entry of the fund in any database (Age); assets under management in millions USD (AuM); length of the lockup period in days (LockupPeriod); a dummy equal to one if the fund has a high-water mark in place (High-high-waterMark); a dummy equal to one if the fund uses leverage (Leverage). To measure the risk tolerance of the groups of investors, I include the standard deviation of the funds’ returns, measured over the full sample period (σ) as a proxy for risk.
Additionally, I control for the investment styles of the funds by including dummy variables.
For every class of investor k, I estimate the following cross-sectional regression:
PercentageAllocationi,k =β0+Xiβk+ Stylei+εi,k, (3.3)
where Xi denotes the vector of characteristics of fund i. PercentageAllocationi,k denotes the allocation by investor class k into fund i. I measure the time-varying characteristics (age, assets under management) and the allocations at the beginning of the sample (May 2012). Stylei is a set of style dummies. I cluster the standard errors at the level of the managing company. Table 3.6 shows estimates for OLS regressions weighted by the assets under management.7
7The dependent variable, being a percentage, is bounded. See the robustness Section3.7 for a model and estimation results taking into account the bounded support of the dependent variable.
Table 3.6: Revealed preferences
This table shows estimates for the following regression:
PercentageAllocationi,k=β0+Xiβk+ Stylei+εi,k.
PercentageAllocationi,k denotes the allocation by investor class k into fund i in May 2012. Xi denotes a vector of the following fund characteristics: management fee (MgmtFee); performance fee (PerfFee); age of the fund measured as the number of years passed since the first entry of the fund in any database (Age);
assets under management in millions USD (AuM); length of the lockup period in years (LockupPeriod); a dummy equal to one if the fund has a high-water mark in place (High-waterMark); a dummy equal to one if the fund uses leverage (Leverage); standard deviation of the fund’s returns during the full sample period (σ). I measure the time-varying characteristics (age, assets under management) in May 2012. Stylei is a set of style dummies. The regression is weighted by the funds’ average assets under management during the full sample period. T-statistics, based on standard errors clustered at the level of the managing company, appear in parenthesis below the estimates. Statistical significance at the 1%, 5%, and 10% level is denoted by ***,**, * respectively.
Individuals Pension and Business State or municipal Other investment profit sharing plans development companies government entities advisers
MgmtFee -0.005 -0.018 -0.001 -0.012 0.021
Charities Corporations Insurance High net worth Banking or or other businesses companies individuals thrift institutions
MgmtFee -0.047*** 0.087* 0.019 -0.028* -0.016
Turning to the preferences of the groups of investors for specific fee structures, I find that Charities seem to prefer lower management and performance fees. An increase by 1% in the management fee leads to a decrease of -4.7% in the relative holding of charities. The effect of the fund’s performance fee is only statistically significant at the 5% level and economically not relevant. Corporations or other businesses seem to tolerate higher fees. An increase by 1% in the management fee translates to an increase equal to 8.7% in the relative holding of Corporations and other businesses. The effect of the performance fee is significant at the 5% level but economically not significant. High net worth individuals seem to prefer lower management fees. An increase by 1% in the management fee results in a decrease of -2.8%
in the relative holding of High net worth individuals.
Turning to the age and the size of the funds - both closely related to how well-established the funds are - reveals that Individuals, Charities, and High net worth individuals prefer smaller funds. The assets under management of the funds are measured in millions and all coefficients are virtually equal to zero. Thus, the effect is likely economically negligible. High
net worth individuals tend to invest in older funds, while Insurance companies are willing to invest into younger funds. An increase by ten years in the age of the fund leads to a decrease equal to -3% and an increase by 5% in the holdings by Insurance companies and High net worth individuals.
High net worth individuals seem to accept longer lockup periods. An increase in the lockup period by 30 days results in an increase in the holding of High net worth individuals of approximately 6%. Banking or thrift institutions prefer shorter lockup periods. However, with a coefficient being virtually equal to zero this effect is economically irrelevant.
Charities seem to prefer funds which have a high-water mark in place. The presence of a high-water mark increases the relative holding of Charities by 5.6%. This effect is significant at the 5% level.
As conjectured in Section3.4.3, State or municipal government entities indeed seem to prefer funds which are less risky. A 1% increase in the monthly standard deviation of the fund’s returns decreases the relative holding of State or municipal government entities by -1.4%.
Summarizing, there is heterogeneity in the preferences of the groups of investors for fund characteristics. Charities and High net worth individuals are sensitive with respect to the management fees they are charged and prefer smaller funds. On the other hand, Corporations or other businesses are willing to pay higher fees and invest in larger funds. Insurance companies are willing to invest into younger funds, while High net worth individuals prefer older funds. Compatible with evidence from prior Sections, State or municipal government entities prefer funds which are less risky. Charities prefer funds with high-water marks in place.
This Section establishes that hedge fund investors differ in their investment objectives and therefore choose different funds based on their characteristics. In the next Section, I study whether hedge fund investors not only choose different funds but also influence the investment strategies employed by the funds.