Printer Friendly

A law and finance analysis of hedge funds.

This paper empirically analyzes the impact of hedge .fund regulation on fund structure and performance. The data indicate restrictions on the location of key service providers and permissible distributions via wrappers" are associated with lower fund alphas, lower average monthly returns, and higher fixed fees. Furthermore, restrictions on the location of key service providers are associated with lower manipulation-proof performance measures, while wrapper distributions are associated with lower performance fees. As well, the data show standard deviations of monthly returns are lower among jurisdictions with restrictions on the location of key service providers and higher minimum capitalization requirements.

**********

"Hedge funds are not, should not be, and will not be unregulated!!" Christopher Cox (Chairman of SEC) in testimony before the Senate Banking Committee --Wall Street Journal, June 23, 2006

In the United States, hedge funds have been essentially an unregulated investment vehicle. By 2005 hedge funds collectively accumulated over a trillion dollars in assets, while at the peak in the summer of 2008 industry estimates suggest the market grew above $2.5 trillion in assets (Ineichen and Silberstein, 2008, pp. 16-17). With over a trillion dollars of capital under management and at 5% alphas sought/promised by most hedge funds, this implies that there needs to be at least an aggregate $50 billion above systematic-risk-justified return (and more than $125 billion in excess returns in 2008). Given the implausibility of over $50 billion being readily available for hedge fund investors and managers who aim to "beat the market," it seems highly likely that many hedge fund participants will be disappointed in the future. Furthermore, the increasingly large pool of hedge fund capital under management has the potential to move other markets and impact financial stability. As a result, the tremendous growth of the hedge fund asset class and potential systemic risk has attracted regulatory attention from the US Securities and Exchange Commission (SEC). (1)

Hedge fund registration in the United States commenced only in 2006 (Partnoy and Thomas, 2007; Brav et al., 2008a, 2008b). In other countries around the world, hedge funds face stricter regulations such as minimum capital requirements, marketing restrictions, and restrictions on retail investor participation, among other things. The growth of hedge funds worldwide has led regulators to reevaluate the suitability and effectiveness of their regulatory oversight (PriceWaterhouseCoopers, 2006, 2007). How has hedge fund regulation impacted hedge fund structure and performance?

The purpose of this study is to facilitate an understanding of the impact of hedge fund regulation on fund governance and performance. We measure fund performance along a variety of different metrics including a multifactor alpha (Fung and Hsieh, 2004), a manipulation-proof performance measure (MPPM) (Goetzmann et al., 2007) (as an alternative to the Sharpe ratio, which can be manipulated), and average monthly returns. With regard to fund structure, we focus on management and performance fees since hedge funds are best defined as a compensation scheme for a pool of money to be collectively managed and invested on behalf of the capital providers (Hodder and Jackwerth, 2007). (2)

In theory, there is an ambiguous correlation between hedge fund regulation and hedge fund structure and performance. On one hand, a lack of regulatory oversight may give rise to fund managers that disguise investment schemes and merely capture the fees. This view is consistent with theory and evidence in Bebchuk and Fried (2003), at least in other contexts, that the compensation structure is part of the agency problem rather than its solution. For instance, suppose there are two funds managed by the same group of fund managers. One has a strategy of shorting the Standard & Poor's 500 Index (S&P) while the other has a strategy of going long on the S&P. (3) The additional aspects of the hedge fund marketed to the hedge funds' investors hide the true nature of these hedge funds. In the end, half of the investors of these two hedge funds will lose, while the hedge fund managers reap the profits of the fixed management fees and carried interest performance fees of both hedge funds. The fund investors remain unaware of the scheme due to all of the "mumbo jumbo" of the marketing and promotional material of the hedge funds. Furthermore, without regulatory oversight and/or hedge fund registration requirements, regulatory authorities would also be unaware. Hedge fund registration and oversight would curb against this type of behaviour thereby improving hedge fund structure and average performance.

Alternatively, regulatory oversight may hamper fund performance where hedge fund managers and their investors lose freedom to contract and organize their resources in the way that they deem to be most efficient thereby exacerbating agency problems. The most common forms of regulation in different countries around the world include restrictions on minimum hedge fund size, restrictions on the location of key service providers, such as the administrator, custodian, investment advisor, auditors, legal and tax advisors, accountants, and consultants (as discussed in Section I), and limitations on the main market channels for hedge fund distribution. Such restrictions may constrain the fund to an inefficient scale, give rise to inefficient choices of human resources associated with fund management, create barriers to entry, and limit investor participation most suited to the particular hedge fund's strategy. If so, we would expect worse hedge fund performance and less efficient hedge fund structures (that do not as efficiently align the interests of investors and managers) in terms of higher management fees and lower performance fees.

These opposing views suggest the interaction between hedge fund regulation and hedge fund structure and performance is theoretically ambiguous and subject to whatever effect one believes dominates in the marketplace. Therefore, the purpose of this paper is to sort these issues out with an empirical analysis of pertinent data. In particular, we empirically examine the relationship between hedge fund performance, including Goetzmann et al. (2007) MPPMs, Fung and Hsieh (2004) multifactor alphas, average monthly returns and the standard deviation of returns, hedge fund structure (fixed management fees and carried interest performance fees), and various aspects of hedge fund regulation (minimum capitalization, restrictions on the location of key service providers, and restrictions on marketing channels) with an international data set of 3,782 hedge funds from 29 countries around the world (listed in Section I). We demonstrate results for data spanning the years 1994-2005 and show robustness for the subsample over 2003-2005.

At a broad level, the data indicate regulatory requirements in the form of restrictions on the location of key service providers and marketing channels that permit wrappers (securities that combine different products) are associated with lower alphas, lower average returns, and higher fixed fees. Related evidence confirms restrictions on location are also negatively related to MPPMs, while wrapper distributions are significantly negatively related to performance fees. There is further evidence that the standard deviation of returns is lower among jurisdictions with restrictions on the location of key service providers and higher minimum capitalization requirements.

In particular, in jurisdictions with restrictions regarding the location of key service providers, monthly returns are approximately 0.3% lower, MPPMs are approximately 0.2% lower (the MPPM is the average monthly welfare of a power utility investor in the portfolio over our sample periods), and seven-factor alphas are approximately 0.1% to 0.5% lower. These effects are statistically significant and robust to alternative specifications including alternative control variables, different sample periods (both 2003-2005 and 1994-2005), exclusion of funds-of-funds, and instrumental variable framework correcting for the endogeneity of regulations.

There is fairly robust evidence that minimum capitalization restrictions lower the standard deviation of returns. The data indicate that an increase in required minimum capitalization for a hedge fund from $1 to $2 million tends to be associated with a reduction in standard deviation of monthly returns by 0.02%. Minimum capitalization restrictions, however, are statistically unrelated to other aspects of fund performance.

The evidence indicates that jurisdictions with marketing via wrappers have lower monthly average returns by approximately 0.2% and seven-factor alphas 0.2% to 0.5% lower. These effects are economically large, ranging from 2.4% to 6.2% per year. Furthermore, wrapper distributions lower standard deviations of monthly returns by 0.9%. These effects are robust for the 1994-2005 period, but not for the 2003-2005 period.

Finally, there is evidence that jurisdictions permitting distributions via wrappers have lower performance fees by 0.43%. There is further evidence that jurisdictions with wrapper distributions and restrictions on the location of key service providers have higher fixed fees by 0.54% and 0.51%, respectively. Insofar as lower fixed fees and higher performance fees mitigate agency problems and better align the interests of fund managers and owners, this evidence is consistent with the related evidence demonstrating a negative association between performance and jurisdictions, which permit distribution via wrappers and have restrictions on location.

The analyses build on a large and growing literature on hedge fund structure and performance (Ackermann, McEnally, and Ravenscraft, 1999; Brown, Goetzmann, and Ibbotson, 1999; Liang, 1999, 2000, 2003; Agarwal and Naik, 2000a, 2000b, 2004; Brown, Goetzmann, and Park, 2001; Edwards and Caglayan, 2001; Amin and Kat, 2003; Brown and Goetzmann, 2003; Brunnermeier and Nagel, 2004; Getmansky, Lo, and Makarov, 2004; Baquero, Horst, and Verbeek, 2005; Cremers, Martijn, and Nair, 2005; Getmansky, 2005; Gupta and Liang, 2005; Agarwal, Daniel, and Naik, 2006; Teo, 2007: Boyson, 2010), as well as hedge fund activism (Bravet al., 2008a, 2008b; Klein and Zur, 2009). The analyses are also related to analyses of hedge fund share restrictions (Aragon, 2007) and hedge fund registration (Brown, Goetzmann, and Ibbotson, 2008). Prior evidence, however, has not considered a cross-country law and finance analysis of hedge fund regulation in relation to fund structure and performance in the spirit of La Porta et al. (1998, 2002, 2006). The analysis in this regard builds on evidence relating governance to hedge fund and mutual fund performance (Chevalier and Ellison, 1997; Elton, Gruber, and Blake, 2003; Cremers, Martijn, and Nair, 2005), and the structure of hedge funds and strategies (Fung and Hsieh, 1997, 2000, 2001; Jorion, 2000; Goetzmann, Ingersoll, and Ross, 2003; Ding et al., 2006).

This paper is organized as follows. Section I briefly describes hedge fund regulation in the countries considered. Section II introduces the data. Multivariate analyses are presented in Section III. Section IV discusses limitations and future research. Policy implications and concluding remarks follow in Section V.

I. Hedge Fund Regulation, Structure, and Performance

A. Hedge Fund Regulation

In the United States hedge funds are formed as limited partnerships whereby the investors are considered limited partners and the hedge fund managers are general partners. The limited partners are wealthy individuals and institutional investors. Compensation for hedge fund managers comprises a 1% to 2% fixed management fee based on hedge fund asset size and a 15% to 20% carried interest performance fee based on the profits. Incentive fees align interests of hedge fund managers as general partners and the investors as limited liability partners who only retain their limited liability by not taking part in any aspect of the management of the fund. Hedge funds are not allowed to advertise in the United States. There is no restriction on the minimum size to operate as a hedge fund, and no restrictions on the location of key service providers. Hedge funds in the United States can avoid the public disclosure requirements of the US Securities Act of 1933 by claiming the status of a private placement. (4) Hedge funds are also exempt from the US Investment Company Act of 1940 (which regulates mutual funds) by having no more than 499 investors with more than $5 million in assets, and by not making public offerings. (5) Prior to February 2006, hedge funds in the United States were also exempt from any registration requirement. Brown, Goetzmann, and Ibbotson (2008) analyze the impact of this registration requirement and find favorable quality signals are possible with registration. Verret (2007) gives specific commentary regarding hedge fund regulation and presents a model of self-regulation as a major theme of the policy recommendation.

[FIGURE 1 OMITTED]

In other countries around the world, unlike the United States, there are minimum capital requirements for hedge fund managers to operate a hedge fund, as well as different avenues for marketing (not merely private placements), and restrictions on the location of key service providers (see Figure 1) typically to be within the same jurisdiction. These regulations are summarized in Table I for 29 different countries (see PriceWaterhouseCoopers, 2006, 2007, for an extended discussion for most of these countries). (6) The focus is on the regulations in place in two periods, 2003-2005, which are stable for the regulations and countries enumerated in Table I, and 1994-2005, to be consistent with previous studies on hedge fund returns.

A typical hedge fund does not have any employees, but instead delegates different functions to service providers of the hedge fund (Figure 1). Outsourcing a hedge fund's functions minimizes the risk of collusion among hedge fund participants to perpetuate fraud, and also mitigates liability in the event the hedge fund participants are accused of improperly performing their management duties. A hedge fund's board of directors or trustee has a fiduciary duty to the investors to ensure that all parties involved in the fund can properly carry out their designated tasks. At issue in this paper is whether the form of regulatory oversight in the countries enumerated in Table I provides an additional level of governance and an additional check so that fraud is not perpetuated. If regulatory oversight facilitates additional value-added governance, then we would expect hedge funds in those jurisdictions to have higher alphas, MPPMs, and average returns. In the alternative, one may infer that restrictions on minimum capital requirements for managers, restrictions on the location of key service providers, and limitations on the main market channels for hedge fund distribution constrain the fund to an inefficient scale, give rise to inefficient choice of human resources associated with hedge fund management, create barriers to entry, and limit investor participation most suited to the particular hedge fund's strategy. (7) Thus, we would expect hedge funds in those jurisdictions to have worse performance.

The most common service providers include prime brokers, administrators, and distributors (Figure 1). Prime brokers lend money, act as counterparts to derivative contracts, lend securities in short sales, execute trades, and provide clearing, settlement, and custody services. Administrators issue and redeem interests and shares and calculate the net asset value of the fund. Distributors are responsible for marketing the fund to potential investors. Restrictions on location of key service providers typically require the presence of a local agent (PriceWaterhouseCoopers, 2006, 2007). The local agent, however, may not be of sufficient scale and/or employ the individuals that are most suited to the effective operation, management, and governance of the fund (Wilson, 2007). Practitioners often warn against using low-quality service providers (e.g., "... beware of the potential downside of using third-tier service providers. Furthermore, it is hard to garner the confidence of investors when you do not employ a top notch support network"). (8) The recent failure of hedge funds affiliated with Lehman Brothers, Bear Sterns, and Madoff has been attributable to low-quality, unreliable service providers (Wilson, 2007). Service providers are vitally important because they provide due diligence services for the fund, provide research on counterparty risk, and generally facilitate the execution of the fund's activities.

A fund's relationship with its service providers involves substantial human capital and asset specificity. Local or lower cost service providers can save on fees by up to 20%, but such cost savings can drastically hurt fund performance due to the reduction in auditor timing and support, inaccurate auditing services, enhanced counterparty risk, slower execution, delayed custody services, and conflicts of interest in marketing the fund. Market sentiment for a fund is particularly vulnerable to rumors of a fund using low-quality service providers (Wilson, 2007).

Hedge funds have a sponsor that is responsible for marketing the sponsor fund. To this end, it is noteworthy that a wrapper distribution channel has the potential to be associated with lower fund performance. Wrappers are securities whose returns tie together different financial products. In the case of wrappers, the sponsor distributes the offering materials for the sponsor fund as well as the disclosure materials for the affiliated wrapper products. There is a potential conflict of interest between the sponsor and the fund manager with respect to the disclosure of the wrapper relating to the fund manager (Gerstein, 2006). Wrapper constructions are often complex and inapprehensible for the average investor, thereby lowering the governance that hedge fund investors would otherwise provide. Empirical evidence confirms wrapper distributions are associated with a "flatter" or less sensitive flow-performance relationship (Cumming and Dai, 2009); that is, investors are less likely to withdraw from poor performers and enter better performers. Wrapper distributions are likewise associated with more frequent misreporting of returns (Cumming and Dai, 2008). Overall, we may expect fund managers have greater latitude for opportunistic behavior under wrapper distributions. This conflict of interest can lead to a negative association between wrappers and fund performance.

In sum, we expect restrictions regarding the location of hedge fund key service providers and wrapper distributions to be associated with poorer hedge fund performance and less efficient hedge fund structures (that do not as efficiently align the interests of investors and managers) in terms of higher management fees and lower performance fees. These predictions are the focus of the ensuing empirical analyses herein.

B. Hedge Fund Location

Hedge fund location depends on economic conditions and the proximity to the fund's investors, taxation, and regulatory burdens. The country of domicile of the fund managers may influence fund location particularly in reference to countries with restrictions on the location of key service providers. Additionally, fund managers that expect better performance may locate in jurisdictions with fewer regulatory burdens and lower taxes. For instance, offshore locations such as the Bahamas, Bermuda, and the Cayman Islands have few regulatory burdens and minimal tax for funds and their investors; therefore, many fund managers might choose to register in those jurisdictions despite regulations such as restrictions on location. The absence of regulatory oversight in these countries would render it difficult for fund managers without a track record to raise capital from institutional investors, while more established fund managers with a track record are less likely to experience fundraising difficulties depending on their fund strategy (Cumming and Johan, 2008).

In the empirical analyses below, we consider econometric models that account for nonrandom selection of location. In particular, we provide instrumental variable estimates of location choice. We also consider two-step Heckman corrections and treatment regressions (as well as other specifications that exclude selected countries). We find that the results are quite robust to alternative statistical treatment of location choice.

C. Hedge Fund Performance Measures

This paper uses Goetzmann et al.'s (2007) MPPM, Fung and Hsieh's (2004) multifactor alpha, average monthly hedge fund returns, and standard deviation of average monthly returns over our sample periods to measure hedge fund performance. We consider a variety of performance measures to demonstrate robustness as there is little consensus regarding the appropriate performance measurement for hedge funds among academics and practitioners (Baghi-Wadji and Klocker, 2007). The results pertaining to regulation are nevertheless quite robust to specifications reported and otherwise; alternative specifications are available upon request.

The MPPM is analogous to the Sharpe ratio, originally called the "reward-to-variability" ratio, and has traditionally been one of the most popular measures for risk-adjusted performance. However, it is now widely known that Sharpe ratio and other reward-to-risk measures may be manipulated with option-like strategies (Goetzmann et al., 2007). This type of manipulation may reasonably be expected to be commonplace among hedge funds. Therefore, we use the recently proposed MPPM by Goetzmann et al. (2007) for the hedge fund industry to remove bias from the potential manipulation of the Sharpe ratio (and results using the Sharpe ratio in an earlier draft of the paper were not materially different). The MPPM proposed by Goetzmann et al. (2007) is defined as follows:

[??] = 1/(1 - [rho])[DELTA]t ln (1/T T.summation over (t=1) [[[(1 + [r.sub.ft]).sup.-1] (1 + [r.sub.ft] + [x.sub.t]].sup.1-[rho]]), (1)

where [r.sub.ft] and n per period (not annualized) risk-free rate and the excess return of the fund over period t. The parameter p is the relative risk aversion; historically, this number ranges from two to four for the CRSP value-weighted market portfolio depending on the time and frequency of data used. The [??] can be interpreted as the annualized continuously compounded excess return of the portfolio (Goetzmann et al., 2007). The MPPM is interpreted as the average per period welfare of a power utility investor in the portfolio over the time period in question. We found the regression results to be very robust to MPPMs for Risk Aversions 2, 3, and 4. We report MPPM values for Risk Aversion 3, and results for alternative risk aversion parameters are available upon request.

A second performance measure considered in this paper is known as "alpha." Following the single-factor models, a variety of multifactor models have been developed and applied in the research of hedge funds (Fung and Hsieh, 1997, 2004; Getmansky et al., 2004; Lo, 2006). The multifactor models could be expressed in a general form as follows:

[r.sup.i.sub.t] = [[alpha].sup.i] + [K.summation over (k=1) [[beta].sup.i.sub.k][F.sub.k,i] + [[epsilon].sub.i,t], (2)

where [r.sup.i.sub.t] is the excess return (in excess of the risk-free rate) on hedge fund i for month t, [[alpha].sup.i] is the abnormal performance of hedge fund i over the regression time period, [[beta].sup.i.sub.k] is the factor loading of hedge fund i on factor k during the regression period, [F.sub.k,t] is the return for factor k for month t, and [[epsilon].sub.i,t] is the error term. The main difference among those models is the selection of factors. Fung and Hsieh (2004) have developed a seven-factor model, which has shown strong explanatory power in variation of hedge fund performance. The factors are the S&P 500 return minus the risk-free rate (SNPMRF), the Wilshire small cap minus the large cap return (SCMLC), the change in the constant maturity yield of the 10-year Treasury (BD 10RET), the change in the spread of Moody's Baa minus the 10-year Treasury (BAAMTSY), the bond PTFS (PTFSBD), the currency PTFS (PTFSFX), and the commodities PTFS (PTFSCOM), where PTFS denotes primitive trend following strategy. The estimated intercept [[??].sup.i] is the alpha performance measure or the abnormal performance of hedge fund i over the regression time period.

One challenge associated with multifactor models is that they might be sensitive to alternative specifications and benchmarks (Agarwal and Walk, 2000a). We take the three-month LIBOR converted into a monthly rate as the risk-free rate. Alternative benchmarks were also considered and did not materially affect the results; these are available upon request. Additionally, it is important to note that the results in a prior version of this paper made use of the single-factor Jensen's alpha, and demonstrated a consistent correlation between the regulation variables and the alphas as reported herein. Also, it is noteworthy that hedge funds have a variety of different strategies (the data, described in the next section, consider more than 20 strategies). We explicitly report results with strategy variables that are used to explain cross-sectional differences in hedge fund performance. Alternative approaches that account for strategy when estimating alphas and other performance metrics (such as grouping hedge funds into homogenous categories) did not materially influence the inferences drawn pertaining to legality and hedge fund performance.

D. Other Factors Pertinent to Hedge Fund Structure and Performance

In the empirical analyses in the subsequent sections, we control for a variety of characteristics other than hedge fund regulation that may impact hedge fund performance. First, the quality of investor protection and enforcement differs across countries of different legal origin; therefore, we consider the law and finance legal origin variables in the different countries (as in La Porta et al., 1998, 2002, 2006). We also control for international differences in GNP per capita in the countries considered.

Second, we control for a variety of hedge fund characteristics including the frequency with which investors may withdraw capital, hedge fund size, hedge fund age, minimum investment amounts per investor, and performance and management fees. These control variables are used in ways consistent with prior work measuring hedge fund performance (Ackermann, McEnally, and Ravenscraft, 1999; Brown, Goetzmann, and Ibbotson, 1999; Liang, 1999, 2000, 2003; Agarwal and Naik, 2000a, 2000b, 2004; Brown, Goetzmann, and Park, 2001; Edwards and Caglayan, 2001; Brown and Goetzmann, 2003; Brunnermeier and Nagel, 2004; Getmansky, Lo, and Makarov, 2004; Baquero, Horst, and Verbeek, 2005; Cremers, Martijn, and Nair, 2005; Getmansky, 2005; Agarwal, Daniel, and Naik, 2006, 2009). Additionally, in the data set considered (described immediately below), there are details regarding the primary fund strategy (24 different categories). In the multivariate empirical analyses, we indicate the robustness of the hedge fund regulation results to the inclusion/exclusion of all of these variables.

II. Data

A. Data Source

We use the data set from the Center for International Securities and Derivatives Markets (CISDM), a commonly used data set in the hedge fund literature (Bollen and Pool, 2009). The CISDM data comprise a total of 3,782 funds, both alive and defunct, over the 1994-2005 period (the same horizon studied by Bollen and Pool, 2009). Of these, 2,709 have performance statistics for 1994-2005, and 1,638 have performance statistics for 2003-2005. The total sample comprises funds registered in 29 different countries as enumerated in Table I. CISDM has data on funds from Israel and Panama; however, we could not locate reliable data regarding hedge fund regulations from those countries and, as such, dropped 35 funds from the sample. Summary statistics for the funds are provided in Table II.

Fung and Hsieh (2006) have demonstrated that only 3% of hedge funds appear in five of the major hedge fund databases (CISDM, TASS, EUR, MSCI, and HFR). The CISDM sample has 44.6% of the funds domiciled in the United States (and the combined CISDM/HFN sample has 68.1% of funds domiciled in the United States), while the TASS sample reported in International Financial Services (2006) has 34% of funds domiciled in the United States. The CISDM sample has 50.1% of funds domiciled in offshore jurisdictions, while the TASS sample has 55%. The CISDM sample has 6.0% of the funds from the European Union, while the TASS sample has 9%. While we cannot say whether the CISDM sample is representative of the worldwide population of hedge funds, we nevertheless consider robustness to including/excluding different countries, such as those with and without US funds, to demonstrate robustness to different samples. We explicitly confirm the results are very robust to these different subsamples and econometric methods.

B. Potential Biases

Hedge fund databases may exhibit biased performance results through selection bias, survivorship bias, and backfilling bias. Selection bias is present where databases do not comprise the universe of hedge funds. As with other prior research using single-country data sets, we cannot rule out selection bias. We nevertheless consider robustness of the results by excluding different countries, such as the United States, from the regression analyses. Survivorship bias is unlikely to be present due to the fact that we have defunct funds in our sample. Also, we consider the robustness of the results to the 1994-2005 period and the 2003-2005 subsample. Furthermore, in an earlier draft, we considered different populations of funds based on strategies and years and have found similar results (again, available upon request). Backfilling bias (funds start reporting to data vendors when they have successful returns in recent history) is likely mitigated by excluding the returns data for the first 18 months of returns data for each fund. Our results are robust to inclusion/exclusion of data with potential backfilling bias.

C. Summary Statistics and Univariate Correlations

Table II defines and summarizes the performance measures in the data for the January 1994-December 2005 and the January 2003-December 2005 periods, as well as the regulatory variables and variables for hedge fund characteristics. All returns calculations are expressed in decimals and on a monthly basis. The average hedge fund's alpha for 1994-2005 was 0.004 (median 0.003). MPPMs for 1994-2005 are largely left skewed, with significant outliers (seven very negative numbers for funds with almost -100% returns) associated with funds that almost failed in a given month and then failed shortly thereafter. After winsorizing the seven outliers, the average MPPM was 0.002 (median 0.003). The average monthly return was 0.009 (median 0.008). The average hedge fund size was $29.113 million (median $3.628 million) in 2005 US$, measured as the first observation during our sample period. The median fund in our data started in 1998, and our sample consists of all continuing and defunct funds in CISDM. We considered robustness to excluding funds with longer life spans, and our results are extremely robust. The average fixed fee for the hedge funds was 1.32% (median 1.00%) and the average performance fee was 17.24% (median 20.00%). Additional hedge fund statistics, as well as minimum and maximum values, are presented in Table II.

Table III provides a comparison of means and medians tests. Funds in jurisdictions without minimum capitalization restrictions have higher average and median returns, higher average and median standard deviation of returns, higher median MPPMs, higher average and median alphas, lower average and median fixed fees, and lower median performance fees. Note that MPPMs are significantly negatively skewed due to the calculation with fund failures, and have a high variance. This means the comparison of mean tests with MPPMs is insignificant (or possibly significant in the direction opposite that of the median test); therefore, we do not focus on the comparison of averages for MPPMs. Private placements are associated with higher average and median returns, higher median MPPMs, higher average and median alphas, lower median fixed fees, and higher average and median performance fees. Bank distributions are associated with lower average and median returns, lower average and median standard deviation of returns, lower median alphas, lower median MPPM, higher average and median fixed fees and lower median performance fees. Fund distribution company distributions are associated with lower average and median returns, lower median standard deviation of returns, lower median MPPMs, lower average and median alphas, higher average and median fixed fees, and lower average and median performance fees. Investment manager distributions are associated with lower average and median returns, lower median standard deviation of returns, lower median MPPMs, lower average and median alphas, higher average and median fixed fees and lower average and median performance fees. Wrapper distributions are associated with lower average and median returns, lower standard deviation of average and median returns, lower median MPPMs, lower average and median alphas, higher average and median fixed fees, and lower median performance fees. Distributions via other regulated financial intermediaries are associated with lower average and median returns, lower standard deviation of average and median returns, lower median MPPMs, lower average and median alphas, higher average and median fixed fees, and lower median performance fees. Distributions via nonregulated financial intermediaries are associated with lower median returns, lower median standard deviation of returns, lower median alphas, higher average and median fixed fees, and lower median performance fees and median. Jurisdictions that restrict the location of key service providers are associated with lower average and median returns, lower standard deviation of average and median returns, lower average and median alphas, and higher average fixed fees.

Table IV provides univariate correlations across all of the variables enumerated in Table II. Hedge funds in jurisdictions that restrict the location of key service providers have significantly lower average returns and lower standard deviations of returns (correlations are -0.07 and -0.15, respectively). Jurisdictions that restrict the location of key service providers are positively correlated with MPPMs at 0.05, but this is attributable to the outliers with MPPMs as discussed above in conjunction with the comparison of means and medians tests in Table III. Hedge funds with higher performance fees have significantly higher average returns, standard deviations of returns, and alphas (correlations are 0.13, 0.23, and 0.14, respectively). Table IV also indicates high correlations across many of the variables; thus, we assess the robustness of the results to alternative specifications in the multivariate analyses.

III. Multivariate Analyses

The multivariate empirical tests are presented in Table V encompassing 15 regressions in three panels. Panels A and B consider, as dependent variables, the different performance (average monthly returns, standard deviation of monthly returns, MPPMs, and seven-factor alphas) measures over the 1994-2005 and 2003-2005 periods, respectively. Panel C considers the further robustness checks for the performance measures over 1994-2005, as well as the determinants of fixed fees and performance fees. The dependent variables in the MPPM regressions for the 1994-2005 period are winsorized at the 95% level due to outliers in the left tail, as discussed in Section II. We include fund-of-funds in the Panel A and B regressions but exclude fund-of-funds in the Panel C regressions. Results relating regulation to performance are invariant to including or excluding different types of fund structures and fund-of-funds, as regulations pertaining to funds also apply to fund-of-funds (PriceWaterhouseCoopers, 2006, 2007). We exclude fund-of-funds for regressions determining fees, as fee structures are materially different for fund-of-funds. The central focus of the following discussion is on the impact of regulation on hedge fund performance and structure. Robustness to inclusion/exclusion of control variables for legal origin, GNP per capita, and various hedge fund characteristics is also considered. As discussed further below, alternative sets of explanatory variables and treatment of error terms, such as clustering, econometric methods, subsets of the data, etc, did not materially impact the results, and additional specifications not presented are available upon request.

In Models 5 and 10, we present the second step of a two-stage IV regression. The first step involves a logit regression on a dummy variable equal to one for restrictions on the location of key service providers, and an OLS regression with the log of minimum capitalization. For these regressions, we include explanatory variables that include fund characteristics, legal origin, and more than two dozen explanatory variables for the fund's primary strategy, as well as explanatory variables for fund characteristics such as the number of funds and the year of first establishment of the funds in explaining jurisdiction choice. One important identifying fund characteristic is the "master-feeder" structure. (9) A master-feeder structure allows funds to market a fund to both onshore and offshore investors, and, as such, it is possible that this structure explains, in part, jurisdiction choice, but will not necessarily be directly correlated with returns. Overall, the first-step regressions model "hedge fund forum shopping" (hedge fund choice of law; Cumming and Johan, 2008). Cumming and Johan (2008) rank the risks associated with different strategies and find some evidence of an alignment of interests between hedge fund managers and their investors in terms of jurisdiction choice. As considered in Cumming and Johan (2008), there are three possibilities that give rise to a relationship between fund strategy and jurisdiction: 1) a race to the bottom (hedge fund managers pursuing riskier strategies and strategies for which potential agency problems are more pronounced select jurisdictions that have less onerous regulatory oversight), 2) neutrality (the association between hedge fund strategies and hedge fund regulation is random, and 3) an alignment of interests (hedge funds pursuing risky investment strategies select jurisdictions with more onerous regulation). Legal origin dummy variables are included to account for potential fund manager preferences for the legal system (La Porta et al., 1998; a dummy variable for the more flexible English legal system countries is suppressed to avoid collinearity). We had considered taxation variables, but tax benefits for different jurisdictions depend on fund strategies and characteristics and are not easily quantified into a few variables; whereas, fund strategies and asset location are intuitively related to hedge fund forum shopping (Cumming and Johan, 2008).

For a similar and comparable method to deal with endogeneity and selection, as reported in an earlier draft of the paper, we considered two-step regressions in the spirit of Heckman (1976, 1979) with the first step selecting an offshore jurisdiction. Fund managers, in practice, typically register in the country in which they are domiciled or offshore (Wilson, 2007). By first running the logit regression as a nonrandom choice, we control for the nonrandom distribution of offshore registrants. Therefore, the two-step method is an improvement over an alternative approach of simply restricting the sample to the offshore subsample. (10) The results were extremely similar to those reported herein and are available upon request.

At a broad level, the data indicate regulatory requirements in the form of restrictions regarding the location of key service providers and permissible distributions via wrappers are associated with lower MPPMs, lower fund alphas, lower average monthly returns, and higher fixed fees. Wrapper distributions are significantly negatively related to performance fees. Also, the data show standard deviations of monthly returns are lower among jurisdictions with restrictions on the location of key service providers and higher minimum capitalization requirements. Specific details are summarized below.

A. Restrictions on Location

The data indicate that jurisdictions with restrictions on the location of key service providers (see Figure 1 and the accompanying text) have poorer performance results. Table V, Panel A indicates average monthly returns are lower by 0.003 (Model 1), MPPMs are lower by 0.002 (Model 3), and alphas are lower by 0.002 (Models 4 and 5) among jurisdictions that restrict location. These results are invariant to controls for endogeneity (Model 4 vs. Model 5). In other words, this is equivalent to a reduction in alpha by 2% per year, so the effect is not only statistically significant but also economically large. We observe a similar effect for the subsample of data for 2003-2005 in Models 6, 8, 9, and 10. The results excluding fund-of-funds in Models 11-13 indicate monthly alphas are lower by 0.002, 0.003, and 0.005, respectively, in jurisdictions that restrict location. That is, the economic significance is largest in Model 13, where annualized alphas are lower by 6% per year.

Note that the standard deviation of monthly returns is lower by 0.005 (Model 2) and 0.004 (Model 7) for jurisdictions that restrict location, but that reduction is not sufficient to compensate for the reduction in returns, as MPPMs are lower with restrictions on location. The implication of the data is that a location restriction inefficiently constrains the human capital availed to a hedge fund thereby leading to poorer performance. There is no net corporate governance benefit to a geographic proximity between a hedge fund's service providers and the hedge fund's regulatory body.

There is a positive and significant correlation between fixed management fees and restrictions on the location of key service providers. Fixed fees are 0.51% higher among jurisdictions that restrict location, which is economically significant given that Table II indicates the median fixed fee is 1.2% and the mean is 1.3%. (11) However, there is no statistically significant relationship between restrictions on location and performance fees.

B. Minimum Capitalization Requirements

The data indicate some evidence that restrictions on minimum capitalization in a jurisdiction are associated with a reduction in the standard deviation of monthly returns. Table V confirms that an increase in required minimum capitalization for a hedge fund from $1 to $2 million is associated with a reduction in standard deviation of monthly returns by 0.02% to 0.03% in Models 2 and 4.

The minimum capitalization restriction is generally insignificant in the other tables apart from it being marginally significant at the 10% level in Model 6 demonstrating that minimum capitalization lowers monthly returns for the subsample for 2003-2005. The economic significance is such that a raise in minimum capitalization from $1 to $2 million is associated with a lowering in monthly returns by 0.01% (or 0.12% per year). One limitation with regard to minimum capitalization (as indicated in Table II) is that proxies are needed for some countries since the requirements are not exact. Note that minimum capitalization requirements appear binding on only a small portion of the sample (i.e., some funds in countries without minimum capitalization are smaller than the minimum capitalization levels in other countries); nevertheless, it is possible that some funds face problems associated with first achieving the minimum capitalization hurdle when they first start the fund.

C. Permissible Hedge Fund Distribution Channels

The data indicate that jurisdictions that permit distributions via wrappers show significantly lower average monthly returns by 0.002 in Model 1, and lower alphas by 0.002 in Model 4 and 0.005 in Model 13. These effects are economically large, ranging from 2.4% to 6.2% per year. This evidence is consistent with the conflicts of interest associated with wrappers, as discussed in detail in Section I.A. Note, however, that these effects are not robust to the restricted sample for 2003-2005 in Table V, Panel B. We do observe that wrappers are also associated with lower standard deviations of monthly returns in Model 2 by 0.009, and there is no significant association between wrappers and MPPMs.

Wrapper distributions are associated with significantly higher fixed fees by 0.54% in Model 14. Also, wrapper distributions are associated with significantly lower performance fees by 0.43% in Model 15. In other words, fund managers appear able to extract higher fixed fees and require less performance-based compensation when the fund is marketed in combination with other products.

There is evidence at the 10% level of significance that marketing via nonregulated financial institutions is associated with a higher standard deviation in returns in Model 2 by 0.010. That is, riskier unregulated distributions are associated with riskier actions by hedge fund managers. However, there is no significant association between nonregulated distributions and fund performance.

There is a positive relationship between fund alphas and private placements in Model 13 by 0.010 or 12.7% per year. This effect is significant regardless of inclusion or exclusion of the US subsample, which comprises a significant portion of the private placements. This result is consistent with the comparison tests in Table III. As well, note that Models 14 and 15 demonstrate both higher fixed and higher performance fees associated with private placements and other financial institutions. Again, these results are robust to excluding the US subsample. The included variables for distribution channels were selected based on minimizing correlations with other variables as indicated in Table IV. When other distribution variables are included, the results tend to exhibit less statistical significance.

D. Control Variables

A number of the control variables are significant, such as legal origin variables. As in La Porta et al. (1998, 2002, 2006), a dummy variable for English legal origin is suppressed to avoid perfect collinearity. The results, however, vary depending on the time period (e.g., compare Panel A vs. Panel B for German legal origin). We do not have a good explanation for these legal results. The data indicate hedge fund regulations are more consistently related to performance than legal origin.

There is evidence that hedge fund characteristics impact performance and structure. Share redemption restrictions at one year are rather consistently associated with better hedge fund performance, which can be attributed to greater flexibility in meeting liquidity requirements for investors. The relationship between performance fees and returns is not evidenced in our regressions, unlike Ackermann, McEnally, and Ravenscraft (1999). For subsets of different fund strategies, we do see a correlation between performance fees and performance, but these subsets of the data do not materially affect our inferences between regulation and performance. Other variables were also considered, but not reported as they were insignificant or immaterial to the results pertaining to the regulatory variables of interest. Other specifications are available upon request.

IV. Extensions and Future Research

This paper introduced, for the first time, a cross-country law and financial analysis of the impact of hedge fund regulation on hedge fund performance. The data were based on 29 countries and focused on performance measures from January 1994-December 2005, as well as January 2003-December 2005. The data indicate hedge fund regulation in the form of restrictions regarding the location of key service providers and marketing via wrapper distributions are negatively correlated to hedge fund performance and positively related to fixed fees. Wrapper distributions are also negatively related to performance fees.

One potential concern with the analysis of the relationship between hedge fund regulation and governance and performance relates to nonrandom location choice, as discussed in Section III. We explicitly confirm the robustness of the results to endogeneity of forum shopping. Due to space restrictions, we exclude a number of robustness checks that are available upon request (and many of which were presented in an earlier draft). For instance, in separate regressions, we excluded onshore funds, offshore funds, and US funds from the sample. We also ran two-step regressions with Heckman-like selection effects for offshore registrants in the first step (e.g., using the treatreg function in Stata). Furthermore, we considered excluding funds of different ages, such as excluding funds more than five years old. These regressions all produced results that were not materially different insofar as presenting hedge fund regulation impacts performance and fee structures.

A second potential concern is that tax differences for offshore versus onshore funds drive differences in performance. In specifications not presented, but available upon request, we demonstrate robustness to exclusion of offshore funds. Hence, our findings are not likely attributable to tax differences.

A third potential concern is in respect to the robustness to alternative data sets. In this paper, we have demonstrated robustness to different subsets of the CISDM data set. We have considered robustness to the subset of onshore versus offshore funds and to the exclusion of US funds. We reported results that exclude the first 18 months of fund performance (for a possible backfilling bias). These and other robustness checks are available upon request.

Generalizations from the data are constrained to the markets and market conditions from which the data are drawn. The analyses focused on performance over 1994-2005 and over 2003-2005. It may be the case that hedge fund regulation plays a more favorable role on performance in times of market crashes, such as the 2008-2009 (current) financial meltdown. Hedge fund regulation may also play a more favorable role in other countries. Further research regarding other time periods and other countries is warranted. Further research could also investigate the interaction between hedge fund regulation and hedge fund activism (for US evidence, see Brav et al., 2008a, 2008b; Klein and Zur, 2009) and other similar forms of financial intermediation.

Finally, it is worth noting that we do not provide a normative evaluation about the desirability of regulations that give rise to lower performance measures for investors. Policy objectives may weight more heavily reductions in the standard deviation of returns than anything to do with performance, for example. Further research could assess governmental or societal objectives to appropriately consider suitable hedge fund regulations for different countries. The analysis has been confined to assessing the impact of fund regulation on riskadjusted performance for investors, and fund structure in terms of fixed and performance fees.

V. Concluding Remarks

This paper empirically analyzed the impact of hedge fund regulation on fund structure and performance using a cross-country data set of 3,782 hedge funds from 29 countries from January 1994 to December 2005. The focus of the analysis involved regulatory requirements in the form of minimum capitalization imposed on hedge fund managers, restrictions on the location of key service providers and permissible distribution channels in relation to hedge fund alphas, MPPMs, average monthly returns, fixed fees, and performance fees.

Restrictions on the location of a hedge fund's key service providers give rise to poorer performance in terms of lower MPPMs, lower alphas, lower average monthly returns, and higher fixed fees. Overall, hedge fund regulation, in terms of locational restrictions of key service providers, has hampered fund performance and distorted efficient fund compensation structures. We also found that distribution via wrappers was associated with lower performance results (albeit with some sensitivity to the time period considered), higher fixed fees, and lower performance fees, which may reflect conflicts of interest associated with the marketing and distribution of companion products. Nevertheless, we did see some evidence that distributions via wrappers, as well as minimum capital requirements and restrictions on location of key service providers, tend to be associated with lower standard deviations of returns. Hence, while hedge fund regulation tends to inhibit performance and incentive fees, it also has the potential to lower risks in the market. Therefore, the current evidence from hedge fund regulation does offer guidance for the ongoing policy debates regarding hedge fund regulation. Further research is warranted as more data and natural experiments arise with the likely upcoming changes in the regulatory environment around the world.

References

Ackermann, C., R. McEnally, and D. Ravenscraft, 1999, "The Performance of Hedge Funds: Risk, Return and Incentives," Journal of Finance 54, 833-874.

Agarwal, V., N. Daniel, and N.Y. Naik, 2006, "Flows, Performance, and Managerial Incentives in the Hedge Fund Industry," London Business School Working Paper.

Agarwal, V., N. Daniel, and N. Naik, 2009, "Role of Managerial Incentives and Discretion in Hedge Fund Performance," Journal of Finance 64, 2221-2256.

Agarwal, V. and N.Y. Naik, 2000a, "Multi-Period Performance Persistence Analysis of Hedge Funds," Journal of Financial and Quantitative Analysis 35, 327-342.

Agarwal, V. and N.Y. Naik, 2000b, "On Taking the Alternative Route: Risks, Rewards and Performance Persistence of Hedge Funds," Journal of Alternative Investments 2, 6-23.

Agarwal, V. and N.Y. Naik, 2004, "Risks and Portfolio Decisions Involving Hedge Funds," Review of Financial Studies 17, 63-98.

Amin, G.S. and H.M. Kat, 2003, "Hedge Fund Performance 1990-2000: Do the 'Money Machines' Really Add Value?" Journal of Financial & Quantitative Analysis 38, 251-274.

Aragon, G.O., 2007, "Share Restrictions and Asset Pricing: Evidence from the Hedge Fund Industry," Journal of Financial Economies 83, 33-58.

Baghai-Wadji, R. and S. Klocker, 2007. "Performance and Style Shifts in the Hedge Fund Industry," London Business School Working Paper.

Baquero, G., J.T. Horst, and M. Verbeek, 2005, "Survival, Look-Ahead Bias, and Persistence in Hedge Fund Performance," Journal of Financial & Quantitative Analysis 40, 493-517.

Bebchuk, L.A. and J.M. Fried, 2003, "Executive Compensation as an Agency Problem," Journal of Economic Perspectives 17, 71-92.

Bollen, N.P.B. and V.K. Pool, 2009, "Do Hedge Fund Managers Misreport Returns? Evidence from the Pooled Distribution," Journal of Finance 64, 2257-2288.

Boyson, N.M, 2010, "Implicit Incentives and Reputational Herding by Hedge Fund Managers," Journal of Empirical Finance 17, 283-299.

Brav, A., W. Jiang, F. Partnoy, and R. Thomas, 2008a, "Hedge Fund Activism, Governance and Firm Performance," Journal of Finance 63, 1729-1775.

Bray, A., W. Jiang, F. Partnoy, and R. Thomas, 2008b, "The Returns to Hedge Fund Activism," Financial Analysts Journal 64, 45-61.

Brown, S.J. and W.N. Goetzmann, 2003, "Hedge Funds with Style," Journal of Portfolio Management 29, 101-112.

Brown, S.J., W.N. Goetzmann, and R.G. Ibbotson, 1999, "Offshore Hedge Funds: Survival and Performance 1989-1995," Journal of Business 72, 91-117.

Brown, S.J., W.N. Goetzmann, B. Liang, and C. Schwarz, 2008, "Lessons from Hedge Fund Registration," Journal of Finance 63, 2785-2815.

Brown, S.J., W.N. Goetzmann, and J. Park, 2001, "Careers and Survival: Competition and Risk in the Hedge Fund and CTA Industry," Journal of Finance 56, 1869-1886.

Brunnermeier, M.K. and S. Nagel, 2004, "Hedge Funds and the Technology Bubble," Journal of Finance 59, 2013-2040.

Butler, M.G., C.M. Callahan, and R.E. Smith, 2007, "Human Resource Outsourcing: Performance of Service Providers," AAA 2008 MAS Meeting Paper. Available at SSRN: http://ssrn.com.abstract=1003945.

Chevalier, J. and G. Ellison, 1997, "Risk Taking by Mutual Funds as a Response to Incentives," Journal of Political Economy 105, 1167-1200.

Cremers, K., J. Martijn, and V. Nair, 2005, "Governance Mechanisms and Equity Prices," Journal of Finance 60, 2859-2875.

Cumming, D. and N. Dai, 2008, "Hedge Fund Regulation and Misreported Returns," European Financial Management, forthcoming.

Cumming, D. and N. Dai, 2009, "Capital Flows and Hedge Fund Regulation," Journal of Empirical Legal Studies 6, 843-873.

Cumming, D. and S. Johan, 2008, "Hedge Fund Forum Shopping," University of Pennsylvania Journal of Business and Employment Law 10, 783-831.

Ding, B., M. Getmansky, B. Liang, and R. Wermers, 2006, "Market Volatility, investor Flows, and the Structure of Hedge Fund Markets," University of Massachusetts Working Paper.

Edwards, F.R. and M.O. Caglayan, 2001, "Hedge Fund Performance and Manager Skill," Journal of Futures Markets 21, 1003-1028.

Elton, E.J., M.J. Gruber, and C.R. Blake, 2003, "Incentive Fees and Mutual Funds," Journal of Finance 58, 779-804.

Fung, W. and D.A. Hsieh, 1997, "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," Review of Financial Studies 10, 275-302.

Fung, W. and D.A. Hsieh, 2000, "Performance Characteristics of Hedge Funds and CTA Funds: Natural versus Spurious Biases," Journal ofFinancial and Quantitative Analysis 35, 291-307.

Fung, W. and D.A. Hsieh, 2001, "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," Review of Financial Studies 14, 313-341.

Fung, W. and D.A. Hsieh, 2004, "Hedge Fund Benchmarks: A Risk Based Approach," Financial Analyst Journal 60, 65-80.

Fung, W. and D.A. Hsieh, 2006, "Hedge Funds: An Industry in Its Adolescence," Federal Reserve Bank of Atlanta Economic Review (Fourth Quarter), 1-34.

Gerstein, K.S., 2006. "Hedge Fund Distribution: Regulatory Hot Buttons," Schulte Roth & Zabel, LLP.

Getmansky, M., 2005, "The Life Cycle of Hedge Funds: Fund Flows, Size and Performance," University of Massachusetts Working Paper.

Getmansky, M., A.W. Lo, and I. Makarov, 2004, "An Econometric Model of Serial Correlation and Illiquidity in Hedge Fund Returns," Journal of Financial Economics 74, 529-609.

Goetzmann, W.N., J.E. Ingersoll, and S.A. Ross, 2003, "High-Water Marks and Hedge Fund Management Contracts," Journal of Finance 58, 1685-1717.

Goetzmann, W.N., J.E. Ingersoll, M.I. Spiegel, and I. Welch, 2007, "Portfolio Performance Manipulation and Manipulation-Proof Performance Measures," Review of Financial Studies 20, 1503-1546.

Gupta, A. and B. Liang, 2005, "Do Hedge Funds have Enough Capital? A Value-at-Risk Approach," Journal of Financial Economics 77, 219-253.

Heckman, J., 1976, "The Common Structure of Statistical Models of Truncation, Sample Selection, and Limited Dependent Variables and a Simple Estimator for Such Models," Annals of Economic and Social Measurement 5,475-492.

Heckman, J., 1979, "Sample Selection Bias as a Specification Error," Econometrica 47, 153-161.

Hodder, J.E. and J.C. Jackwerth, 2007, "Incentive Contracts and Hedge Fund Management," Journal of Financial and Quantitative Analysis 42, 811-826.

Ineichen, A. and K. Silberstein, 2008, "AIMA's Roadmap to Hedge Funds," Alternative Investment Management Association. Available at: http://www.aima.org/download.cfm/docid/ 6133E854-63FF-46FC-95347B445AE4ECFCC.

International Financial Services, 2006, "Hedge Funds: City Business Services (March 2006)." Available at: http://www.ifsl.org.uk/uploads/CBS_Hedge_Funds_2006.pdf.

Jorion, P., 2000, "Risk Management Lessons from Long-Term Capital Management," European Financial Management 6, 277-300.

Khorana, A., H. Servaes, and P. Tufano, 2005, "Explaining the Size of the Mutual Fund Industry around the World," Journal of Financial Economics 78, 145-185.

Khorana, A., H. Servaes, and P. Tufano, 2009, "Mutual Fund Fees around the World," Review of Financial Studies 22, 1279-1310.

Klein, A. and E. Zur, 2009, "Entrepreneurial Shareholder Activism: Hedge Funds and Other Private Investors," Journal of Finance 64, 187-229.

La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R. Vishny, 1998, "Law and Finance," Journal of Political Economy 106, 1113-1155.

La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R. Vishny, 2002, "Investor Protection and Corporate Valuation," Journal of Finance 57, 1147-1170.

La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R. Vishny, 2006, "What Works in Securities Laws?" Journal of Finance 61, 1-32.

Liang, B., 1999, "On the Performance of Hedge Funds," Financial Analysts Journal 55, 72-85.

Liang, B., 2000, "Hedge Funds: The Living and the Dead," Journal of Financial and Quantitative Analysis 35, 309-326.

Liang, B., 2003, "The Accuracy of Hedge Fund Returns," Journal of Portfolio Management 29, 111-122.

Liang, B. and H. Park., 2008, "Share Restrictions, Liquidity Premium, and Offshore Hedge Funds," University of Massachusetts, Amherst Working Paper.

Lo, A., 2006, "Where Do Alphas Come From?: A New Measure of the Value of Active Investment Management," Massachusetts Institute of Technology Working Paper.

Partnoy, F. and R.S. Thomas, 2007, "Gap Filling, Hedge Funds, and Financial Innovation," in Y. Fuchita and R.E. Litan, Eds. Brookings-Nomura Papers on Financial Services, Washington, DC, Brookings Institution Press.

PriceWaterhouseCoopers, 2006, "The Regulation, Taxation and Distribution of Hedge Funds in Europe: Changes and Challenges," London, UK, PriceWaterhouseCoopers.

PriceWaterhouseCoopers, 2007, "Under the Spotlight: The Regulation, Taxation and Distribution of Hedge Funds around the Globe," London, UK, PriceWaterhouseCoopers.

Teo, M., 2009, "The Geography of Hedge Funds," Review of Financial Studies 22, 3531-3561.

Verret, J.W., 2007, "Dr. Jones and the Raiders of Lost Capital: Hedge Fund Regulation, Part II," Delaware Journal of Corporate Law 32, 799-841.

White, H., 1980, "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica 48, 817-838.

Wilson, R. 2007, Hedge Fund Blog Book. Available at: http://hedgefundgroup.org/Hedge-Fund-Book.pdf.

(1) http://www.sec.gov/news/speech/spchl 11704hjg.htm. For industry perspectives regarding hedge fund regulation, see http://www.hedgeco.net/hedge-fund-regulations.htm and http://www.hedgefundregulation.com/.

(2) Hedge funds may further be categorized by their strategic focus, and in this paper, we control for a variety of different strategies. For related work on fees in the mutual fund industry, see Khorana, Servaes, and Tufano (2005, 2009).

(3) This example was provided in a discussion at the DeGroote Microstructure Conference by Professor Larry Harris in November 2006 but does not necessarily reflect his views of the hedge fund industry.

(4) In a private placement, there typically are not more than 35 "accredited" investors, whereby an accredited investor is someone with more than $1 million in wealth or who earned more than $200,000 in the previous two years.

(5) Formerly, the maximum was 99; now, there is a maximum in the Investment Company Act or the rules thereunder, so the default maximum is the 500-person trigger under the Securities and Exchange Act (Partnoy and Thomas, 2007).

(6) The majority of countries and years are available in PriceWaterhouseCoopers (2006). For countries/years not available in PriceWaterhouseCoopers (2006), we obtained information regarding regulation on the hedge funds in a survey sent to selected funds. It is noteworthy that the broad regulatory categories we use have been stable over time (distribution channels, size, and restrictions on location are rarely modified restrictions), but there have been changes to other areas, particularly taxation.

(7) An alternative interpretation is as follows. It is possible that jurisdictions with more stringent hedge fund regulation also have more active regulators that monitor hedge fund manager activities. Klein and Zur (2009) find that activist hedge fund managers achieve their target returns by extracting cash from the investee firms from which they acquire at least a 5% stake by forcing increased investee debt capacity and higher dividends. If regulatory oversight curtails this type of activist investment, one may infer that it will also lower expected returns.

(8) Source: http://www.hedgefundlaunch.com/how-to-start-a-hedge-fund-part-l/- In other nonhedge fund contexts, service providers have been shown to be very important for performance (Butler, Callahan, and Smith, 2007).

(9) We identify master-feeder funds using the method in Liang and Park (2008) where if there exist both onshore and offshore funds with the same investment style managed by the same company, then these funds are identified as master-feeder funds.

(10) Heckman selection regressions, treatment regressions (using the treatreg function in Stata), and regressions with restricted subsample (such as excluding onshore funds or excluding US funds) all provided similar results to those reported.

(11) The economic significance for the OLS regressions in Table V, Panel C, Models 14 and 15 can be calculated by transforming the regression ln(Y/(l_Y) = X[beta] to Y = [e.sup.X][beta] / (1 + [e.sup.X][beta]).

Douglas Cumming and Na Dai *

We owe thanks to the Bill Christie (the editor) and an anonymous referee for extremely helpful and timely feedback. Sofia Johan, Andrew Karolyi, and Michael King provided very helpful comments and suggestions, and Li Que provided research assistance. Also, we owe thanks to the seminar participants at Hofstra University, Vanderbilt Law School the American Law and Economics Association Annual Conference at Harvard Law School, the Western Finance Association Annual Conference, the Northern Finance Association Conference, the DeGroote Conference on Market Structure and Market Integrity, the Financial Intermediation Research Society Conference, the Amsterdam Conference on Financial Intermediation at the Crossroads, and the European Financial Management Symposium at the University of Cambridge Judge Institute of Management. Also, we thank Wendy Jennings for copyediting.

* Douglas Cumming is a Professor and the Ontario Research Chair in the Schulich School of Business at York University in Toronto, Ontario, Canada. Na Dai is an Assistant Professor in the School of Business at SUNY-Albany in Albany, NY.
Table I. Regulation of and Channels for Distribution of Hedge
Funds by Country

This table summarizes by country the regulation of hedge funds
across 29 countries including the minimum capital requirements,
permissible marketing channels, and whether there exists
restrictions on the location of key service providers (Figure 1).
The minimum capital requirements to operate as a hedge fund
manager vary 1n some countries depending on fund characteristics
and, as such, are proxied, as summarized in this table, for the
purpose of empirical analyses in the subsequent tables (and the
results are robust to alternative proxies).

Country         No. of      No. of      Proxy for
               Funds in    Funds in      Minimum
               Data Set    Data Set      Capital
               1994-2005   2003-2005   Requirement
                                       to Operate
                                        as Hedge
                                          Fund
                                         Manager
                                       (2005 US$)

Australia             1        1                 0
Austria               1        1        $6,750,000
BWI,                 11       11          $500,000
  Anguilla
Bahamas             113       44           $25,000
Bermuda             281      179                $0
Brazil                4        4          $362,000
British             497      260          $500,000
  Virgin
  Inlands
Canada               20       15                $0
Cayman              889      609          $500,000
  Islands
Channel              78       76           $44,077
  Islands
France               14       14          $168,750
Germany               2        2          $373,617
Gibraltar             1        1          $155,674
Guernsey             17        0           $45,517
Hong Kong             1        0        $2,275,000
Ireland              77       56           $67,500
Isle of Man          21       18          $142,500
Italy                 5        5        $1,245,390
Jersey                3        0           $45,517
Luxembourg           78       57          $168,750
Malta                 2        2          $155,674
Mauritius             2        2                $0
Netherlands           4        1          $303,750
Netherlands          34       16                $0
  Antilles
New                   1        0                $0
  Zealand
Sweden                2        2          $155,674
Switzerland          13       11        $4,300,000
United            1,602      827                $0
  States
United                6        1           $67,500

Country                  Main Marketing Channels

               Banks       Fund       Wrappers    Private
                       Distribution              Placements
                        Companies

Australia        1          1            1           1
Austria          1          1            1           0
BWI,             1          0            0           1
  Anguilla
Bahamas          0          0            0           1
Bermuda          1          0            0           1
Brazil           1          1            0           1
British          1          0            0           1
  Virgin
  Inlands
Canada           1          1            1           1
Cayman           1          0            0           1
  Islands
Channel          1          1            1           1
  Islands
France           0          1            1           1
Germany          1          0            0           0
Gibraltar        1          0            0           0
Guernsey         1          1            1           1
Hong Kong        1          1            0           1
Ireland          1          0            0           1
Isle of Man      0          1            1           1
Italy            0          0            0           1
Jersey           1          1            1           1
Luxembourg       1          0            0           0
Malta            1          1            0           1
Mauritius        0          0            0           1
Netherlands      0          0            1           0
Netherlands      0          0            0           1
  Antilles
New              1          1            1           1
  Zealand
Sweden           1          1            0           0
Switzerland      1          1            1           0
United           0          0            0           1
  States
United           1          0            1           1

Country                        Main Marketing Channels

               Investment      Other       Nonregulated     Total
                Managers     Regulated      Financial     Number of
                             Financial     Intermedia-    Marketing
                              Service          ries       Channels
                            Institutions

Australia          1             1              0             6
Austria            0             0              0             3
BWI,               1             0              0             3
  Anguilla
Bahamas            1             0              0             2
Bermuda            1             0              0             3
Brazil             1             1              0             5
British            1             0              0             3
  Virgin
  Inlands
Canada             1             1              0             6
Cayman             0             0              0             2
  Islands
Channel            1             1              1             7
  Islands
France             1             0              0             4
Germany            0             1              1             3
Gibraltar          1             1              0             3
Guernsey           1             1              1             7
Hong Kong          1             1              0             5
Ireland            0             1              0             3
Isle of Man        1             0              0             4
Italy              0             0              0             1
Jersey             1             1              1             7
Luxembourg         0             1              0             2
Malta              0             1              0             4
Mauritius          0             0              0             1
Netherlands        1             1              0             3
Netherlands        0             0              0             1
  Antilles
New                1             1              0             6
  Zealand
Sweden             1             1              0             4
Switzerland        1             1              0             5
United             0             0              0             1
  States
United             1             0              0             4

Country        Restrictions           Legal Origin
               on Location
                  of Key      English   French   German
                 Service
                Providers?

Australia           0            1        0        0
Austria             0            0        0        1
BWI,                1            1        0        0
  Anguilla
Bahamas             1            1        0        0
Bermuda             1            1        0        0
Brazil              1            0        1        0
British             1            1        0        0
  Virgin
  Inlands
Canada              0            1        0        0
Cayman              1            1        0        0
  Islands
Channel             0            1        0        0
  Islands
France              0            0        1        0
Germany             1            0        0        1
Gibraltar           1            0        0        1
Guernsey            0            1        0        0
Hong Kong           0            1        0        0
Ireland             1            1        0        0
Isle of Man         1            1        0        0
Italy               1            0        1        0
Jersey              0            0        1        0
Luxembourg          0            0        1        0
Malta               1            0        1        0
Mauritius           1            1        0        0
Netherlands         1            0        1        0
Netherlands         1            0        1        0
  Antilles
New                 0            1        0        0
  Zealand
Sweden              1            0        0        0
Switzerland         1            0        0        1
United              0            1        0        0
  States
United              0            1        0        0

Country        Legal Origin     GDP per
                                Capita
               Scandinavian   (2005 USE)

Australia           0            $30,700
Austria             0            $31,300
BWI,                0            $24,500
  Anguilla
Bahamas             0            $17,700
Bermuda             0            $36,000
Brazil              0             $8,100
British             0            $24,500
  Virgin
  Inlands
Canada              0            $31,500
Cayman              0            $32,300
  Islands
Channel             0            $35,264
  Islands
France              0            $28.700
Germany             0            $30,635
Gibraltar           0            $38,200
Guernsey            0            $44,600
Hong Kong           0            $34,200
Ireland             0            $31,900
Isle of Man         0            $35,000
Italy               0            $28,108
Jersey              0            $57,000
Luxembourg          0            $58,900
Malta               0            $14,686
Mauritius           0            $12,800
Netherlands         0            $29,500
Netherlands         0            $11,400
  Antilles
New                 0            $23,200
  Zealand
Sweden              1            $28,400
Switzerland         0            $33,800
United              0            $40,100
  States
United              0            $29,600
  Kingdom

Table II. Definition of Variables and Summary Statistics

This table defines the main variables used in the paper. Summary
statistics are also provided for each variable. Data source:
Center for International Securities and Derivatives Markets.

Variable         Definition                         Mean      Median

Performance Variables

Average          Average monthly return, 1994-      0.009      0.008
returns 1994-    2005, adjusted for backdating
2005             (removing the first 18 months
                 of the fund's reported
                 returns)

Average          Average monthly return, 2003-      0.010      0.008
returns 2003-    2005, adjusted for backdating
2005

Standard         Average standard deviation of      0.038      0.027
deviation of     returns, 1994-2005, adjusted
returns 1994-    for backdating
2005

Standard         Average standard deviation of      0.023      0.016
deviation of     returns, 2003-2005, adjusted
returns 2003-    for backdating
2005

Manipulation-    MPPM (Goetzmann et al., 2007),    -0.117      0.040
proof            1994-2005, adjusted for
performance      backdating
measure (MPPM)
1994-2005

MPPM 2003-2005   MPPM (Goetzmann et al., 2007),     0.082      0.066
                 2003-2005, adjusted for
                 backdating

Alpha 1994-      Alpha of multifactor model         0.004      0.003
2005             (Fung and Hsieh, 2004), 1994-
                 2005, adjusted for backdating

Alpha 2003-      Alpha of multifactor model         0.003      0.002
2005             (Fung and Hsieh, 2004), 2003-
                 2005, adjusted for backdating

Hedge Fund Regulation Variables

Log minimum      The log of the minimum             6.216        0
capitalization   capitalization required to
                 operate as a hedge fund
                 manager in 2005 US$

Marketing        A dummy variable equal to one      0.973        1
private          where the country allows fund
placement        distribution via private
                 placements

Marketing bank   A dummy variable equal to one      0.530        1
                 where the country allows fund
                 distribution via banks (as
                 defined in Table I)

Marketing fund   A dummy variable equal to one      0.048        0
distribution     where the country allows fund
company          distribution via fund
                 distribution companies

Marketing        A dummy variable equal to one      0.290        0
investment       where the country allows fund
manager          distribution via investment
                 managers

Marketing via    A dummy variable equal to one      0.048        0
wrappers         where the country allows fund
                 distribution via wrappers

Marketing        A dummy variable equal to one      0.081        0
other            where the country allows fund
regulated        distribution via other
financial        regulated financial
institution      institutions

Marketing        A dummy variable equal to one      0.027        0
nonregulated     where the country allows fund
financial        distribution via other
institution      nonregulated financial
                 institutions

Restrictions     A dummy variable equal to one      0.514        1
on location of   where the country imposes
key service      restrictions on the location
providers        of key service providers
                 (Figure 1)

Country GNP and Legal Origin

French legal     A dummy variable equal to one      0.030        0
origin           for French legal origin
                 countries (La Porta et al.,
                 1998)

German legal     A dummy variable equal to one      0.005        0
origin           for German legal origin
                 countries (La Porta et al.,
                 1998)

Log GNP per      Log of the country's GNP per      10.441     10.491
capita           capita, expressed in 2004 US$

Fund Characteristics

Yearly capital   A dummy variable equal to one      0.092        0
redemptions      if capital redemptions are
                 possible only on an annual
                 basis

Log assets       The log of the fund's assets      12.707     15.104
                 in millions of 2005 US$ as
                 measured at the start date of
                 the fund

Minimum          The minimum investment             2.22E      2.50E
investment       required for the fund               + 6        + 6

Management fee   The fixed fee in percentages       1.324       1.2
                 for management compensation

Performance      The carried interest              17.241       20
fee              performance fee in percentages
                 for management compensation

Misreporting     A dummy variable equal to one      0.698        1
fund             if the firm misreports monthly
                 returns by reporting at least
                 50% of marginally negative
                 returns as marginally positive
                 (Bollen and Pool, 2009)

Master feeder    A dummy variable equal to one      0.218        0
                 if the fund is a master feeder
                 structure

Number of        The number of funds operated       3.534        2
funds            by the fund manager at the
                 time of the fund's operations

Year of fund     The year in which the fund was   1997.540     1998
establishment    established

Variable           SD      Minimum   Maximum   No. of
                                               Observations

Performance Variables

Average           0.009    -0.059     0.253     2,709
returns 1994-
2005

Average           0.008    -0.019     0.059     1,638
returns 2003-
2005

Standard          0.044     0.001     1.505     2,709
deviation of
returns 1994-
2005

Standard          0.020     0.000     0.233     1,638
deviation of
returns 2003-
2005

Manipulation-     3.411    -90.174    0.508     2,709
proof
performance
measure (MPPM)
1994-2005

MPPM 2003-2005    0.088    -0.697     0.556     1,638

Alpha 1994-       0.008    -0.066     0.176     2,709
2005

Alpha 2003-       0.008    -0.044     0.064     1,638
2005

Hedge Fund Regulation Variables

Log minimum       6.369       0      15.725     3,747
capitalization

Marketing         0.162       0         1       3,747
private
placement

Marketing bank    0.499       0         1       3,747

Marketing fund    0.213       0         1       3,747
distribution
company

Marketing         0.454       0         l       3,747
investment
manager

Marketing via     0.213       0         l       3,747
wrappers

Marketing         0.273       0         1       3,747
other
regulated
financial
institution

Marketing         0.161       0         1       3,747
nonregulated
financial
institution

Restrictions      0.500       0         1       3,747
on location of
key service
providers

Country GNP and Legal Origin

French legal      0.170       0         1       3,747
origin

German legal      0.067       0         l       3,747
origin

Log GNP per       0.225     9.000    10.984     3,747
capita

Fund Characteristics

Yearly capital    0.289       0         1       3,782
redemptions

Log assets        6.286       0      22.575     3,782

Minimum           8.26E       0       5.00E     3,700
investment         + 7                + 09

Management fee    0.701       0        15       3,721

Performance       6.024       0        50       3,642
fee

Misreporting      0.459       0         1       3,782
fund

Master feeder     0.413       0         1       3,432

Number of         5.240       1        46       3,782
funds

Year of fund      4.048     1967      2006      3,754
establishment

Table III. Comparison of Means and Medians Tests

This table presents a comparison of means and medians tests for
differences in performance and fees for different regulatory
conditions. The sample covers the 1994-2005 period. The fee tests
are presented excluding fund-of-funds. The manipulation-proof
performance measure (MPPM) tests are presented with winsorized
results (at the 95% level) in order to exclude extreme outliers
in the left-hand tail. The fund performance data are presented
for all funds as the results are robust to inclusion or exclusion
of fund-of-funds.

                               Mean      Median       SD      Minimum

                                     No Minimum Capitalization

Average returns 1994-2005      0.009      0.008      0.008     -0.056
Standard deviation of          0.041      0.031      0.036      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.004      0.012     -0.126
7-factor alpha, 1994-2005      0.004      0.004      0.008     -0.053
Management fee                 1.233      1.000      0.770      0.000
Performance fee               19.222     20.000      4.568      0.000

                                     No Private Placements

Average returns 1994-2005      0.006      0.006      0.005     -0.005
Standard deviation of          0.032      0.024      0.029      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.000      0.002      0.007     -0.030
7-factor alpha, 1994-2005      0.002      0.001      0.005     -0.015
Management fee                 1.283      1.000      0.716      0.120
Performance fee               17.814     20.000      6.407      0.000

                                    No Bank Distributions

Average returns 1994-2005      0.009      0.009      0.008     -0.041
Standard deviation of          0.042      0.032      0.036      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.004      0.012     -0.100
7-factor alpha, 1994-2005      0.004      0.004      0.008     -0.066
Management fee                 1.222      1.000      0.790      0.000
Performance fee               19.317     20.000      4.507      0.000

                            No Fund Distribution Company Distributions

Average returns 1994-2005      0.009      0.008      0.009     -0.059
Standard deviation of          0.038      0.027      0.045      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.004      0.003      0.009     -0.066
Management fee                 1.310      1.000      0.780      0.000
Performance fee               19.281     20.000      4.461      0.000

                                 No Investment Manager Distributions

Average returns 1994-2005      0.009      0.008      0.008     -0.031
Standard deviation of          0.039      0.028      0.035      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.004      0.011     -0.114
7-factor alpha, 1994-2005      0.004      0.004      0.008     -0.046
Management fee                 1.301      1.000      0.828      0.000
Performance fee               19.431     20.000      4.124      0.000

                                       No Wrapper Distributions

Average returns 1994-2005      0.009      0.008      0.009     -0.059
Standard deviation of          0.039      0.027      0.045      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.004      0.003      0.009     -0.066
Management fee                 1.311      1.000      0.781      0.000
Performance fee               19.304     20.000      4.415      0.000

                            No Other Regulated Financial Intermediary
                                            Distributions

Average returns 1994-2005      0.009      0.008      0.009     -0.059
Standard deviation of          0.039      0.028      0.045      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.004      0.003      0.009     -0.066
Management fee                 1.310      1.000      0.790      0.000
Performance fee               19.294     20.000      4.413      0.000

                                   No Other Nonregulated Financial
                                      Intermediary Distributions

Average returns 1994-2005      0.009      0.008      0.009     -0.059
Standard deviation of          0.038      0.027      0.044      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.004      0.003      0.009     -0.066
Management fee                 1.316      1.000      0.783      0.000
Performance fee               19.286     20.000      4.442      0.000

                                      No Restrictions on Location

Average returns 1994-2005      0.009      0.008      0.008     -0.031
Standard deviation of          0.041      0.031      0.036      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.004      0.012     -0.100
7-factor alpha, 1994-2005      0.004      0.004      0.008     -0.046
Management fee                 1.228      1.000      0.796      0.000
Performance fee               19.242     20.000      4.729      0.000

                              Maximum         Number
                                                of
                                           Observations

                            No Minimum Capitalization

Average returns 1994-2005      0.054            1458
Standard deviation of          0.252            1458
  average returns,
  1994-2005
MPPM, 1994-2005                0.033            1456
7-factor alpha, 1994-2005      0.064            1458
Management fee                15.000            1446
Performance fee               50.000            1446

                             No Private Placements

Average returns 1994-2005      0.033             102
Standard deviation of          0.131             102
  average returns,
  1994-2005
MPPM, 1994-2005                0.019             102
7-factor alpha, 1994-2005      0.026             102
Management fee                 4.800              59
Performance fee               33.000              59

                              No Bank Distributions

Average returns 1994-2005      0.054            1355
Standard deviation of          0.252            1355
  average returns,
  1994-2005
MPPM, 1994-2005                0.033            1352
7-factor alpha, 1994-2005      0.064            1355
Management fee                15.000            1341
Performance fee               50.000            1339

                               No Fund Distribution
                               Company Distributions

Average returns 1994-2005      0.253            2579
Standard deviation of          1.505            2579
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            2572
7-factor alpha, 1994-2005      0.176            2579
Management fee                15.000            2561
Performance fee               50.000            2543

                               No Investment Manager
                                   Distributions

Average returns 1994-2005      0.054            1901
Standard deviation of          0.260            1901
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            1898
7-factor alpha, 1994-2005      0.064            1901
Management fee                15.000            2039
Performance fee               50.000            2022

                               No Wrapper Distributions

Average returns 1994-2005      0.253            2579
Standard deviation of          1.505            2579
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            2572
7-factor alpha, 1994-2005      0.176            2579
Management fee                15.000            2560
Performance fee               50.000            2542

                            No Other Regulated Financial
                             Intermediary Distributions

Average returns 1994-2005      0.253            2514
Standard deviation of          1.505            2514
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            2507
7-factor alpha, 1994-2005      0.176            2514
Management fee                15.000            2493
Performance fee               50.000            2479

                            No Other Nonregulated Financial
                              Intermediary Distributions

Average returns 1994-2005      0.253            2640
Standard deviation of          1.505            2640
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            2633
7-factor alpha, 1994-2005      0.176            2640
Management fee                15.000            2597
Performance fee               50.000            2578

                             No Restrictions on Location

Average returns 1994-2005      0.054            1396
Standard deviation of          0.252            1396
  average returns,
  1994-2005
MPPM, 1994-2005                0.033            1394
7-factor alpha, 1994-2005      0.064            1396
Management fee                15.000            1350
Performance fee               50.000            1346

                               Mean      Median       SD      Minimum

                                    Minimum Capitalization >0

Average returns 1994-2005      0.008      0.007      0.010     -0.059
Standard deviation of          0.034      0.024      0.052      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.010     -0.114
7-factor alpha, 1994-2005      0.003      0.003      0.009     -0.066
Management fee                 1.421      1.500      0.776      0.000
Performance fee               19.352     20.000      4.275      0.000

                                         Private Placements

Average returns 1994-2005      0.009      0.008      0.009     -0.059
Standard deviation of          0.038      0.027      0.044      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.004      0.003      0.009     -0.066
Management fee                 1.319      1.000      0.780      0.000
Performance fee               19.314     20.000      4.379      0.000

                                          Bank Distributions

Average returns 1994-2005      0.008      0.007      0.010     -0.059
Standard deviation of          0.034      0.024      0.050      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.003      0.003      0.009     -0.055
Management fee                 1.418      1.500      0.753      0.000
Performance fee               19.242     20.000      4.368      0.000

                              Fund Distribution Company Distributions

Average returns 1994-2005      0.008      0.006      0.007     -0.005
Standard deviation of          0.032      0.021      0.031      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.010     -0.075
7-factor alpha, 1994-2005      0.003      0.002      0.007     -0.031
Management fee                 1.557      1.500      0.674      0.000
Performance fee               19.268     20.000      3.695     10.000

                                  Investment Manager Distributions

Average returns 1994-2005      0.008      0.007      0.011     -0.059
Standard deviation of          0.036      0.025      0.060      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.001      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.003      0.003      0.010     -0.066
Management fee                 1.376      1.500      0.575      0.000
Performance fee               18.773     20.000      5.332      0.000

                                        Wrapper Distributions

Average returns 1994-2005      0.007      0.006      0.006     -0.004
Standard deviation of          0.031      0.020      0.031      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.001      0.003      0.009     -0.075
7-factor alpha, 1994-2005      0.003      0.002      0.007     -0.031
Management fee                 1.550      1.500      0.663      0.000
Performance fee               18.554     20.000      5.092      0.000

                                      Other Regulated Financial
                                      Intermediary Distributions

Average returns 1994-2005      0.007      0.006      0.006     -0.005
Standard deviation of          0.030      0.019      0.030      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.001      0.003      0.009     -0.075
7-factor alpha, 1994-2005      0.002      0.002      0.007     -0.031
Management fee                 1.454      1.500      0.545      0.000
Performance fee               19.041     20.000      4.856      0.000

                                     Other Nonregulated Financial
                                      Intermediary Distributions

Average returns 1994-2005      0.008      0.007      0.007     -0.004
Standard deviation of          0.033      0.021      0.035      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.001      0.003      0.011     -0.075
7-factor alpha, 1994-2005      0.003      0.002      0.008     -0.031
Management fee                 1.420      1.500      0.485      0.000
Performance fee               18.936     20.000      4.291     10.000

                                      Restrictions on Location

Average returns 1994-2005      0.008      0.007      0.010     -0.059
Standard deviation of          0.035      0.025      0.051      0.001
  average returns,
  1994-2005
MPPM, 1994-2005                0.002      0.003      0.011     -0.126
7-factor alpha, 1994-2005      0.003      0.003      0.009     -0.066
Management fee                 1.412      1.500      0.748      0.000
Performance fee               19.320     20.000      4.112      0.000

                             Maximum       Number         Difference
                                             of            in Means
                                         Observations    (t-Statistic)

                            Minimum Capitalization >0

Average returns 1994-2005      0.253            1284       3.735 ***
Standard deviation of          1.505            1284       4.198 ***
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            1279      -0.796
7-factor alpha, 1994-2005      0.176            1284       2.723 ***
Management fee                15.000            1201      -6.24 ***
Performance fee               50.000            1179      -0.754

                                Private Placements

Average returns 1994-2005      0.253            2640      -4.090 ***
Standard deviation of          1.505            2640      -1.965 **
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            2633      -1.916 *
7-factor alpha, 1994-2005      0.176            2640      -4.121 ***
Management fee                15.000            2588      -0.389
Performance fee               50.000            2566      -1.789 *

                                 Bank Distributions

Average returns 1994-2005      0.253            1387       4.406 ***
Standard deviation of          1.505            1387       4.480 ***
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            1383      -0.030
7-factor alpha, 1994-2005      0.176            1387       3.399 ***
Management fee                15.000            1306      -6.519 ***
Performance fee               50.000            1286       0.437

                                 Fund Distribution
                               Company Distributions

Average returns 1994-2005      0.035             163       1.476
Standard deviation of          0.179             163       2.490 **
  average returns,
  1994-2005
MPPM, 1994-2005                0.025             163       0.153
7-factor alpha, 1994-2005      0.030             163       1.498
Management fee                 4.800              86      -3.312 ***
Performance fee               30.000              82       0.029

                                 Investment Manager
                                   Distributions

Average returns 1994-2005      0.253             841      -2.361 **
Standard deviation of          1.505             841      -1.040
  average returns,
  1994-2005
MPPM, 1994-2005                0.025             837       0.915
7-factor alpha, 1994-2005      0.176             841      -2.843 ***
Management fee                 4.000             608       2.509 **
Performance fee               50.000             603      -2.794 ***

                               Wrapper Distributions

Average returns 1994-2005      0.035             163       2.301 **
Standard deviation of          0.179             163       3.024 ***
  average returns,
  1994-2005
MPPM, 1994-2005                0.025             163       0.374
7-factor alpha, 1994-2005      0.030             163       2.151 **
Management fee                 4.800              87      -3.294 ***
Performance fee               30.000              83       1.325

                                No Other Regulated
                              Financial Intermediary
                                  Distributions

Average returns 1994-2005      0.035             228       3.542 ***
Standard deviation of          0.179             228       4.232 ***
  average returns,
  1994-2005
MPPM, 1994-2005                0.025             228       0.637
7-factor alpha, 1994-2005      0.030             228       3.568 ***
Management fee                 2.750             154      -3.089 ***
Performance fee               33.000             146       0.615

                                Other Nonregulated
                              Financial Intermediary
                                  Distributions

Average returns 1994-2005      0.035             102       0.692
Standard deviation of          0.179             102       1.400
  average returns,
  1994-2005
MPPM, 1994-2005                0.025             102       0.665
7-factor alpha, 1994-2005      0.030             102       1.001
Management fee                 2.250              50      -1.480
Performance fee               30.000              47       0.554

                            Restrictions on Location

Average returns 1994-2005      0.253            1346       3.853 ***
Standard deviation of          1.505            1346       3.353 ***
  average returns,
  1994-2005
MPPM, 1994-2005                0.042            1341      -0.418
7-factor alpha, 1994-2005      0.176            1346       2.996 ***
Management fee                15.000            1297      -6.141 ***
Performance fee               50.000            1279      -0.448

                              Difference
                              in Medians
                            (Chi-Square)

Average returns 1994-2005     28.003 ***
Standard deviation of         39.592 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 5.605 **
7-factor alpha, 1994-2005      25.613 ***
Management fee                178.42 ***
Performance fee                14.713 ***

Average returns 1994-2005      27.506 ***
Standard deviation of          16.200 ***
  average returns,
  1994-2005
MPPM, 1994-2005                12.511 ***
7-factor alpha, 1994-2005      25.007 ***
Management fee                  0.256
Performance fee                16.869 ***

Average returns 1994-2005      31.867 ***
Standard deviation of          44.228 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 4.688 **
7-factor alpha, 1994-2005      31.867 ***
Management fee                209.808 ***
Performance fee                 9.478 ***

Average returns 1994-2005      20.213 ***
Standard deviation of          15.653 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 4.657 **
7-factor alpha, 1994-2005      18.628 ***
Management fee                 32.084 ***
Performance fee                14.282 ***

Average returns 1994-2005      17.028 ***
Standard deviation of           8.198 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 5.560 **
7-factor alpha, 1994-2005      14.361 ***
Management fee                 29.785 ***
Performance fee                 4.716**

Average returns 1994-2005      23.576 ***
Standard deviation of          20.213 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 5.466 **
7-factor alpha, 1994-2005      21.862 ***
Management fee                 33.161 ***
Performance fee                 9.593 ***

Average returns 1994-2005      34.520 ***
Standard deviation of          27.883 ***
  average returns,
  1994-2005
MPPM, 1994-2005                10.227
7-factor alpha, 1994-2005      39.963 ***
Management fee                 33.083 ***
Performance fee                31.469 ***

Average returns 1994-2005      10.845 ***
Standard deviation of          22.627 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 0.729
7-factor alpha, 1994-2005       9.278 ***
Management fee                 27.991 ***
Performance fee                21.334 ***

Average returns 1994-2005      18.424 ***
Standard deviation of          23.364 ***
  average returns,
  1994-2005
MPPM, 1994-2005                 1.437
7-factor alpha, 1994-2005      14.655 ***
Management fee                179.403 ***
Performance fee                 1.708

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.

Table IV. Correlation Matrix

This table presents correlations across the variables defined in Table
11. Correlations significant at the 5% level are highlighted in
underline font.

                           1        2         3       4        5

 l Average returns          1.00
   1994-2005

 2 Standard deviation of    0.54#    1.00
   returns 1994-2005

 3 Manipulation-proof       0.54#   -0.31#    1.00
   performance
   measure 1994-2005

 4 Alpha 1994-2005          0.85     0.40#    0.51#    1.00

 5 Log minimum             -0.06#   -0.14#    0.04    -0.01     1.00
   capitalization

 6 Marketing private        0.08#    0.07#    0.03     0.06#   -0.15#
   placement

 7 Marketing bank          -0.11#   -0.19#    0.02    -0.07#    0.78#

 8 Marketing fund           0.01     0.00    -0.01     0.01     0.09#
   distribution
   company

 9 Marketing investment    -0.03    -0.05#    0.00    -0.04     0.22#
   manager

10 Marketing via           -0.02    -0.02    -0.03    -0.03     0.09#
   wrappers

11 Marketing other         -0.07#   -0.08#   -0.04    -0.06#    0.17#
   regulated financial
   institution

12 Marketing               -0.02    -0.03    -0.04    -0.02     0.11#
   nonregulated
   financial institution

13 Restrictions on         -0.07#   -0.15#    0.05#   -0.03#    0.75#
   location of key
   service providers

14 French legal origin     -0.05#   -0.05#   -0.01    -0.04     0.16#

15 German legal origin      0.04     0.04     0.02     0.05     0.04

16 Log GNP per capita      -0.06#    0.01    -0.08#   -0.06#   -0.61#

17 Yearly capital           0.07#    0.03     0.04     0.05#   -0.21#
   redemptions

18 Log assets               0.00     0.06#   -0.03     0.00    -0.07#

19 Minimum investment      -0.02#   -0.03     0.00    -0.01     0.02

20 Management fee           0.06#    0.01     0.03     0.07     0.11#

21 Performance fee          0.13#    0.23#    0.00     0.14#   -0.03

22 Misreporting fund       -0.13#   -0.28#    0.06#   -0.09#    0.05#

23 Master feeder           -0.11#   -0.08#   -0.04    -0.07#    0.10#

24 Number of funds         -0.10#   -0.12#   -0.02    -0.12#    0.16#

25 Year of fund            -0.07#   -0.20#    0.14#   -0.07#    0.14#
   establishment

                           6        7        8        9        10

 1 Average returns
   1994-2005

 2 Standard deviation of
   returns 1994-2005

 3 Manipulation-proof
   performance
   measure 1994-2005

 4 Alpha 1994-2005

 5 Log minimum
   capitalization

 6 Marketing private        1.00
   placement

 7 Marketing bank          -0.13#    1.00

 8 Marketing fund           0.01     0.14#    1.00
   distribution
   company

 9 Marketing investment     0.09     0.45#    0.32#    1.00
   manager

10 Marketing via           -0.01     0.13#    0.96#    0.32#    1.00
   wrappers

11 Marketing other         -0.53#    0.25#    0.62#    0.12#    0.60#
   regulated financial
   institution

12 Marketing                0.02     0.15#    0.77#    0.26#    0.77#
   nonregulated
   financial institution

13 Restrictions on          0.15     0.83#   -0.17#    0.44#   -0.19#
   location of key
   service providers

14 French legal origin     -0.88#    0.10#    0.13#   -0.03     0.09#

15 German legal origin     -0.17#    0.02     0.13#   -0.02     0.13#

16 Log GNP per capita      -0.35#   -0.45#   -0.08#   -0.60#   -0.03

17 Yearly capital           0.05#   -0.25#   -0.07#   -0.17#   -0.07#
   redemptions

18 Log assets               0.07#   -0.12#   -0.02    -0.11#   -0.01

19 Minimum investment       0.01     0.01    -0.02    -0.04    -0.02

20 Management fee          -0.01     0.12#    0.10#    0.09#    0.10#

21 Performance fee          0.02    -0.06#   -0.05#   -0.12#   -0.05#

22 Misreporting fund        0.00     0.06     0.03     0.07#    0.03

23 Master feeder            0.05#    0.10#   -0.06#    0.01    -0.05#

24 Number of funds         -0.02     0.19#    0.03     0.18#    0.03

25 Year of fund            -0.06#    0.16#    0.04    -0.06#    0.05#
   establishment

                           11       12       13       14       15

 l Average returns
   1994-2005

 2 Standard deviation of
   returns 1994-2005

 3 Manipulation-proof
   performance
   measure 1994-2005

 4 Alpha 1994-2005

 5 Log minimum
   capitalization

 6 Marketing private
   placement

 7 Marketing bank

 8 Marketing fund
   distribution
   company

 9 Marketing investment
   manager

10 Marketing via
   wrappers

11 Marketing other          1.00
   regulated financial
   institution

12 Marketing                0.57#   1.00
   nonregulated
   financial institution

13 Restrictions on         -0.15#   -0.17#    1.00
   location of key
   service providers

14 French legal origin      0.52#   -0.03#   -0.14#    1.00

15 German legal origin     -0.01     0.00    -0.03     0.00     1.00

16 Log GNP per capita       0.13#    0.02    -0.70#    0.23#   -0.01

17 Yearly capital          -0.09#   -0.05#   -0.23#   -0.06#   -0.01
   redemptions

18 Log assets              -0.06#    0.01    -0.12#   -0.07#    0.00

19 Minimum investment      -0.02    -0.01     0.01    -0.01     0.00

20 Management fee           0.05#    0.04     0.10     0.02     0.12#

21 Performance fee         -0.07#   -0.11#   -0.04     0.00     0.01

22 Misreporting fund        0.02     0.04     0.04     0.01    -0.04

23 Master feeder           -0.09#   -0.02     0.12#   -0.06#   -0.01

24 Number of funds          0.04     0.05#    0.16#    0.02    -0.01

25 Year of fund             0.09#    0.03#    0.12#    0.05#   -0.01
   establishment

                           16       17       18       19      20

 l Average returns
   1994-2005

 2 Standard deviation of
   returns 1994-2005

 3 Manipulation-proof
   performance
   measure 1994-2005

 4 Alpha 1994-2005

 5 Log minimum
   capitalization

 6 Marketing private
   placement

 7 Marketing bank

 8 Marketing fund
   distribution
   company

 9 Marketing investment
   manager

10 Marketing via
   wrappers

11 Marketing other
   regulated financial
   institution

12 Marketing
   nonregulated
   financial institution

13 Restrictions on
   location of key
   service providers

14 French legal origin

15 German legal origin

16 Log GNP per capita       1.00

17 Yearly capital           0.16#    1.00
   redemptions

18 Log assets               0.07#    0.01     1.00

19 Minimum investment       0.00    -0.01     0.02     1.00

20 Management fee          -0.11#   -0.07#   -0.02    -0.01    1.00

21 Performance fee          0.04     0.02     0.15#   -0.01    0.06#

22 Misreporting fund       -0.04     0.02     0.00     0.03    0.02

23 Master feeder           -0.06#   -0.02    -0.04     0.05    0.04

24 Number of funds         -0.14#   -0.08#   -0.08    -0.01    0.01

25 Year of fund             0.01    -0.14#   -0.09#    0.01    0.04
   establishment

                           21       22       23       24

 l Average returns
   1994-2005

 2 Standard deviation of
   returns 1994-2005

 3 Manipulation-proof
   performance
   measure 1994-2005

 4 Alpha 1994-2005

 5 Log minimum
   capitalization


 6 Marketing private
   placement

 7 Marketing bank

 8 Marketing fund
   distribution
   company

 9 Marketing investment
   manager

10 Marketing via
   wrappers

11 Marketing other
   regulated financial
   institution

12 Marketing
   nonregulated
   financial institution

13 Restrictions on
   location of key
   service providers

14 French legal origin

15 German legal origin

16 Log GNP per capita

17 Yearly capital
   redemptions

18 Log assets

19 Minimum investment

20 Management fee

21 Performance fee          1.00

22 Misreporting fund       -0.12#    1.00

23 Master feeder            0.11#    0.01     1.00

24 Number of funds         -0.03     0.00     0.14#    1.00

25 Year of fund            -0.01    -0.05#    0.10#    0.06#
   establishment

Note: Correlations significant at the 5% level are indicated with #.

Table V. Regression Analyses of Hedge Fund Performance and
Compensation Structure

This table presents OLS regression analyses of the determinants
of the average monthly return, standard deviation of the average
monthly return, manipulation-proof performance measure (MMPM)
(Goetzmann et al., 2007), and the seven-factor fund alpha (Fang
and Hsieh, 2004) for the cross-section of funds in the data.
Explanatory variables are as defined in Table II. Dummy variables
are included for the funds' primary strategy (30 dummy variables
in total). Panel A presents the results for performance measures
using all CISDM data over the range 1994-2005 including defunct
funds. Performance data are used for all available months. Model
3 winsorizes the left-hand-side variable at the 95% level,
which results in removal of outliers in the left tail of the
distribution. Panel B, Models 6-10 include only funds with
performance data from 2003-2005. Models 5 and 10 demonstrate the
second step of a two-step regression. The first step involves a
logit regression on a dummy variable equal to one for
restrictions on location and an OLS regression for log (minimum
capitalization). The second step uses the fitted values of those
variables. Panel C, Models 11-13, presents results for 1994-2005
and demonstrates robustness of the determinants of the
multifactor alphas to different explanatory variables, as well as
reporting results for the determinants of fixed fees (Model 14)
and performance fees (Model 15). The logistic transformation is
applied to the dependent variables in Models 14 and 15 so that
the values are not bounded between zero and one, and OLS can be
applied without bias. Models 1-10 include fund-of-funds with
dummy variables for fund-of-fund strategies, while Models 11-15
exclude funds-of-funds to illustrate robustness. White's (1980)
heteroskedasticity-consistent covariance matrix estimator is used
in all regressions.

Panel A. Performance Measures 1994-2005

Variable                          Model 1: Average
                                  Monthly Returns
                            Coefficient     t-Statistic

Constant                     0.052 **          3.398

Hedge Fund Regulation

Variables

Log minimum                 -2.690E-06        -0.052
capitalization

Marketing via wrappers       -0.002 *         -1.935

Marketing nonregulated
financial institution          0.002           1.178

Restrictions on location
of key service
providers                   -0.003 ***        -3.764

Country GNP and Legal
Origin

French legal origin           -0.001          -1.285

German legal origin          0.011 ***         6.291

Log GNP per capita          -0.004 ***        -2.965

Fund Characteristics

Yearly capital
redemptions                  0.001 **          2.358

Log assets                 -8.0151E-05 **     -2.439

Minimum investment           8.295E-13         0.199

Management fee                0.0003           1.482

Performance fee            -.959592D-05       -0.140

Misreporting fund            -0.001 *         -1.792

Strategy dummy
variables?                      Yes

Number of observations         2,525

Adjusted [R.sup.2]             0.061

F-statistic                  4.90 ***

Variable                        Model 6: Average
                                Monthly Returns
                            Coefficient     t-Statistic
Endogenous)

Constant                     0.073 ***         4.501

Hedge Fund Regulation

Variables

Log minimum                -7.982E-05 *       -1.649
capitalization

Marketing via wrappers        -0.001          -0.880

Marketing nonregulated        -0.001          -0.506
financial institution

Restrictions on location
of key service
providers                   -0.003 ***        -4.139

Country GNP and Legal

Origin

French legal origin           -0.0003         -0.299

German legal origin           -0.002          -0.980

Log GNP per capita          -0.006 ***        -3.865

Fund Characteristics

Yearly capital
redemptions                  0.001 **          2.109

Log assets                  -2.702E-05        -0.998

Minimum investment          3.683E-12 *        1.813

Management fee               0.0004 **         2.020

Performance fee            -.6513850-04 **    -2.291

Misreporting fund           -0.002 ***        -3.733

Strategy dummy
variables?                      Yes

Number of observations         1,435

Adjusted [R.sup.2]             0.339

F-Statistic                  19.00 ***

Variable                        Model 11: Fund Alpha
                            Coefficient     t-Statistic

Constant                       0.028           1.353

Hedge Fund Regulation

Variables

Log minimum
capitalization               1.168E-05         0.160

Marketing via private
placements

Marketing bank

Marketing fund
distribution
companies

Marketing via wrappers

Marketing other
financial institution

Marketing nonregulated
financial institution

Restrictions on location
of key service
providers                    -0.002 *         -1.894

Country GNP and Legal
Origin

French legal origin           -0.002          -1.250

German legal origin          0.011 ***         6.555

Log GNP per capita            -0.002          -1.244

Fund Characteristics

Yearly capital
redemptions                  0.001  **         2.514

Log assets                  -3.035E-05        -0.725

Minimum investment          .427196D-11        0.666

Management fee               4.100E-04         1.363

Performance fee              1.200E-04         1.221

Misreporting fund            -4.70E-04        -0.922

Strategy dummy
variables?                      Yes

Number of observations         1,837

Adjusted [R.sup.2]             0.052

F-statistic                  2.75 ***

Variable                        Model 2: SD of
                                Average Returns
                            Coefficient     t-Statistic

Constant                     0.237 ***         3.884

Hedge Fund Regulation

Variables

Log minimum                -4.385E-04 **      -2.401
capitalization

Marketing via wrappers       -0.009 **        -2.366

Marketing nonregulated
financial institution         0.010 *          1.721

Restrictions on location
of key service
providers                    -0.005 **        -2.315

Country GNP and Legal
Origin

French legal origin            0.001           0.326

German legal origin          0.025 ***         3.536

Log GNP per capita          -0.018 ***        -3.481

Fund Characteristics

Yearly capital
redemptions                   -0.0004         -0.239

Log assets                  -2.535E-04        -1.505

Minimum investment          -4.234E-11        -1.099

Management fee                0.0003           0.023

Performance fee               -0.0001         -0.418

Misreporting fund           -0.009 ***        -4.897

Strategy dummy
variables?                      Yes

Number of observations         2,525

Adjusted [R.sup.2]             0.041

F-statistic                  12.68 ***

Variable                        Model 7: SD of
                                Average Returns
                            Coefficient     t-Statistic

Constant                     0.139 ***         4.521

Hedge Fund Regulation

Variables

Log minimum                -2.802E-04 ***     -2.899
capitalization

Marketing via wrappers        -0.004          -1.345

Marketing nonregulated        -0.0001         -0.042
financial institution

Restrictions on location
of key service
providers                   -0.004 ***        -3.332

Country GNP and Legal

Origin

French legal origin            0.002           0.600

German legal origin          0.025 ***         5.398

Log GNP per capita          -0.011 ***        -3.899

Fund Characteristics

Yearly capital
redemptions                   0.0001           0.079

Log assets                   3.30E-02          0.610

Minimum investment          -1.341E-12        -0.092

Management fee                0.002 *          1.835

Performance fee               0.0001           1.298

Misreporting fund           -0.007 ***        -5.577

Strategy dummy
variables?                      Yes

Number of observations         1,435

Adjusted [R.sup.2]             0.320

F-Statistic                  17.57 ***

Variable                        Model 12: Fund Alpha
                            Coefficient     t-Statistic

Constant                      (1.043           1.634

Hedge Fund Regulation

Variables

Log minimum
capitalization              -1.667E-05        -0.226

Marketing via private
placements

Marketing bank                 0.001           0.995

Marketing fund
distribution
companies                     -0.001          -0.462

Marketing via wrappers

Marketing other
financial institution

Marketing nonregulated
financial institution

Restrictions on location
of key service
providers                    -0.003 *         -1.852

Country GNP and Legal
Origin

French legal origin           -0.002          -1.429

German legal origin          0.011 ***         4.380

Log GNP per capita            -0.004          -1.579

Fund Characteristics

Yearly capital
redemptions                  0.002 **          2.537

Log assets                  -2.83E-i15        -0.687

Minimum investment          .449960D-11        0.696

Management fee              4.1 00E-04         1.362

Performance fee              1.200E-04         1.262

Misreporting fund           -4.900E-04        -0.974

Strategy dummy
variables?                      Yes

Number of observations         1,837

Adjusted [R.sup.2]             0.053

F-statistic                  2.63 ***

Variable                          Model 3: MPPM

                            Coefficient     t-Statistic

Constant                       0.024           1.378

Hedge Fund Regulation

Variables

Log minimum                  1.068E-04         1.399
capitalization

Marketing via wrappers         0.001           0.329

Marketing nonregulated
financial institution         -0.003          -1.255

Restrictions on location
of key service
providers                    -0.002 *         -1.726

Country GNP and Legal
Origin

French legal origin           -0.002          -1.146

German legal origin          0.009 ***         3.295

Log GNP per capita            -0.002          -1.354

Fund Characteristics

Yearly capital
redemptions                    0.001           1.342

Log assets                  -4.776E-05        -1.609

Minimum investment           8.525E-12         0.823

Management fee                0.0002           0.349

Performance fee               0.0001           1.018

Misreporting fund              0.001           1.392

Strategy dummy
variables?                      Yes

Number of observations         2,518

Adjusted [R.sup.2]             0.051

F-statistic                  3.18 ***

Variable                          Model 8: MPPM

                            Coefficient     t-Statistic

Constant                     0.058 ***         4.227

Hedge Fund Regulation

Variables

Log minimum                 -5.063E-05        -1.222
capitalization

Marketing via wrappers      -2.500E-04         -210

Marketing nonregulated        -0.001          -0.815
financial institution

Restrictions on location
of key service
providers                   -0.002 ***        -3.147

Country GNP and Legal

Origin

French legal origin           -0.001          -0.391

German legal origin         -0.006 ***        -2.926

Log GNP per capita          -0.005 ***        -3.681

Fund Characteristics

Yearly capital
redemptions                  0.001 ***         2.629

Log assets                  -2.964E-05        -1.266

Minimum investment           4.073E-12         1.233

Management fee                -0.0001         -0.034

Performance fee            -8.333E-05 ***     -2.757

Misreporting fund          -1.167E-03 ***     -2.641

Strategy dummy
variables?                      Yes

Number of observations         1,478

Adjusted [R.sup.2]             0.309

F-Statistic                 16.71  ***

Variable                        Model 13: Fund Alpha
                            Coefficient     t-Statistic

Constant                      (1.(133          1.219

Hedge Fund Regulation

Variables

Log minimum
capitalization              -1.053E-05        -0.149

Marketing via private
placements                   0.010 **          2.366

Marketing bank                 0.003           1,569

Marketing fund
distribution
companies

Marketing via wrappers       -0.005 **        -2.384

Marketing other
financial institution         -0.001          -0.720

Marketing nonregulated         0.005           1.318
financial institution

Restrictions on location
of key service
providers                    -0.005 **        -2.147

Country GNP and Legal
Origin

French legal origin          0.0115 *          1.872

German legal origin          0.023 ***         4.645

Log GNP per capita            -0.004          -1.594

Fund Characteristics

Yearly capital
redemptions                  0.001 **          2.399

Log assets                  -2.907E-05        -0.705

Minimum investment         .404473D-1 1        0.636

Management fee               4.100E-04         1.365

Performance fee              1.100E-04         1.212

Misreporting fund           -4.700E-04        -0.937

Strategy dummy
variables?                      Yes

Number of observations         1,837

Adjusted [R.sup.2]             0.057

F-statistic                  2.65 ***

Variable                        Model 4: Fund Alpha

                            Coefficient     t-Statistic

Constant                      0.028 *          1.806

Hedge Fund Regulation

Variables

Log minimum                  2.11E-05          0.414
capitalization

Marketing via wrappers       -0.002 *         -1.852

Marketing nonregulated
financial institution          0.001           0.719

Restrictions on location
of key service
providers                   -0.002 ***        -3.086

Country GNP and Legal
Origin

French legal origin           -0.002          -1.515

German legal origin          0.013 ***         7.293

Log GNP per capita           -0.003 *         -1.761

Fund Characteristics

Yearly capital
redemptions                   0.001 *          1.875

Log assets                   -2.5E-05         -(1.845

Minimum investment           4.63E-12          0.679

Management fee                0.00t *          1.846

Performance fee              9.00E-05          1.533

Misreporting fund            -2.90E-04        -0.714

Strategy dummy
variables?                      Yes

Number of observations         2,482

Adjusted [R.sup.2]             0.060

F-statistic                  3.79 ***

Variable                        Model 9: Fund Alpha
                            Coefficient     t-Statistic

Constant                     0.052 **"         2.808

Hedge Fund Regulation

Variables

Log minimum                 -3.031E-05        -0.5(16
capitalization

Marketing via wrappers        -0.002          -1.580

Marketing nonregulated         0.002           0.880
financial institution

Restrictions on location
of key service
providers                    -0.001 **        -2.326

Country GNP and Legal

Origin

French legal origin            0.002           1.291

German legal origin         -0.013 ***        -6.456

Log GNP per capita          -0.005 ***        -2.663

Fund Characteristics

Yearly capital
redemptions                  2.700E-04         0.406

Log assets                  -3.248E-05        -1.321

Minimum investment           2.817E-12         0.542

Management fee               2.300E-04         1.132

Performance fee            -6.000E-05 *       -1.879

Misreporting fund             -0.001          -1.604

Strategy dummy
variables?                      Yes

Number of observations         1,435

Adjusted [R.sup.2]             0.204

F-Statistic                  9.99 ***

Variable                       Model 14: Fixed Fees
                            Coefficient     t-Statistic

Constant                    -4.522 ***        -10.270

Hedge Fund Regulation

Variables

Log minimum
capitalization               8.112E-04         0.573

Marketing via private
placements                   0.221 **          2.200

Marketing bank

Marketing fund
distribution
companies

Marketing via wrappers       0.146 ***         3.172

Marketing other
financial institution        0.073 ***         2.690

Marketing nonregulated        -0.100          -1.463
financial institution

Restrictions on location
of key service
providers                    0.076 ***         4.181

Country GNP and Legal
Origin

French legal origin            0.059           0.732

German legal origin           0.409 *          1.849

Log GNP per capita             0.044           1.196

Fund Characteristics

Yearly capital
redemptions                  -0.040 **        -2.331

Log assets                  -2.543E-04        -0.335

Minimum investment

Management fee

Performance fee

Misreporting fund             -0.006          -0.650

Strategy dummy
variables?                      Yes

Number of observations         2,601

Adjusted [R.sup.2]             0.100

F-statistic                  7.69 ***

Variable                          Model 5: Fund Alpha
                                (Hedge Fund Regulation
                                 Variables Endogenous)
                            Coefficient     t-Statistic

Constant                       0.026           0.610

Hedge Fund Regulation

Variables

Log minimum                  3.34E-05          0.147
capitalization

Marketing via wrappers

Marketing nonregulated
financial institution

Restrictions on location
of key service
providers                   -0.002 ***        -3.103

Country GNP and Legal
Origin

French legal origin           -0.002          -0.657

German legal origin          0.013 ***         6.762

Log GNP per capita            -0.002          -0.576

Fund Characteristics

Yearly capital
redemptions                  0.001 **          2.445

Log assets                   -4.00E-05        -1.388

Minimum investment           4.34E-12          0.662

Management fee              5.10E-04 *         1.736

Performance fee              8.00E-05          1.274

Misreporting fund            -3.40E-04        -0.762

Strategy dummy
variables?                      Yes

Number of observations         2,237

Adjusted [R.sup.2]             0.063

F-statistic                  3.79 ***

Variable                        Model 10: Fund Alpha
                               (Hedge Fund Regulation
                                Variables Endogenous)
Coefficient
                            Coefficient     t-Statistic

Constant                       0.046           1.199

Hedge Fund Regulation

Variables

Log minimum                 -1.214E-05        -0.070
capitalization

Marketing via wrappers

Marketing nonregulated
financial institution

Restrictions on location
of key service
providers                    -0.001 **        -2.275

Country GNP and Legal

Origin

French legal origin            0.002           0.678

German legal origin         -0.014 ***        -7.035

Log GNP per capita            -0.(104         -1.162

Fund Characteristics

Yearly capital
redemptions                  3.000E-04         0.449

Log assets                  -3.087E-05        -1.220

Minimum investment           2.627E-12         0.505

Management fee               2.400E-04         1.192

Performance fee            -6.000E-05 *       -1.896

Misreporting fund            -0.001 *         -1.743

Strategy dummy
variables?                      Yes

Number of observations         1,431

Adjusted [R.sup.2]             0.226

F-Statistic                 10. 16 ***

Variable                        Model 15: Performance
                                       Fees
                            Coefficient     t-Statistic
Constant                    -3.734 ***        -3.908

Hedge Fund Regulation

Variables

Log minimum
capitalization               4.883E-03         1.314

Marketing via private        0.727 ***         3.375
placements

Marketing bank

Marketing fund
distribution
companies

Marketing via wrappers       -0.291 *         -1.861

Marketing other
financial institution        0.128 **          2.318

Marketing nonregulated         0.220           1.955
financial institution

Restrictions on location
of key service
providers                      0.003           0.061

Country GNP and Legal
Origin

French legal origin          0.381 ***         3.372

German legal origin          0.621 **          2.542

Log GNP per capita            0.141 *          1.784

Fund Characteristics

Yearly capital
redemptions                  0.076 **          2.163

Log assets                 1.595E-02 ***       5.403

Minimum investment

Management fee

Performance fee

Misreporting fund             -0.001          -0.030

Strategy dummy
variables?                      Yes

Number of observations         2,541

Adjusted [R.sup.2]             0.052

F-statistic                  4.82 ***

*** Significant at the 0.01 level.

** Significant at the 0.05 level.

* Significant at the 0.10 level.
COPYRIGHT 2010 Financial Management Association
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2010 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Cumming, Douglas; Dai, Na
Publication:Financial Management
Article Type:Report
Geographic Code:1USA
Date:Sep 22, 2010
Words:18201
Previous Article:Hedging affecting firm value via financing and investment: evidence from property insurance use.
Next Article:What drives the issuance of putable convertibles: risk-shifting, asymmetric information, or taxes?
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters