Thursday, September 20, 2007

The Economics of Private Equity Funds

The Economics of Private Equity Funds

Metrick, Andrew and Yasuda, Ayako, (September 9, 2007)

This paper analyzes the economics of the private equity industry using a novel model and dataset. We obtain data from a large investor in private equity funds, with detailed records on 238 funds raised between 1992 and 2006. Fund managers earn revenue from a variety of fees and profit-sharing rules. We build a model to estimate the expected revenue to managers as a function of these rules, and we test how this estimated revenue varies across the characteristics of our sample funds. Among our sample funds, about 60 percent of expected revenue comes from fixed-revenue components which are not sensitive to performance. We find major differences between venture capital (VC) funds and buyout (BO) funds – the two main sectors of the private equity industry. In general, BO fund managers earn lower revenue per managed dollar than do managers of VC funds, but nevertheless these BO managers earn substantially higher revenue per partner and per professional than do VC managers. Furthermore, BO managers build on their prior experience by raising larger funds, which leads to significantly higher revenue per partner and per professional, despite the fact that these larger funds have lower revenue per dollar. Conversely, while prior experience by VC managers does lead to higher revenue per partner in later funds, it does not lead to higher revenue per professional. Taken together, these results suggest that the BO business is more scalable than the VC business

Wednesday, September 19, 2007

Factor Funds, Mean-Variance Efficiency, and the Gains From International Diversification

Factor Funds, Mean-Variance Efficiency, and the Gains From International Diversification

Eun, Cheol S., Lai, Sandy and Zhang, Zhe, (August 2007)

We propose a new investment strategy employing “factor funds” to systematically enhance the mean-variance efficiency of international diversification. Our approach is motivated by evidence from the empirical asset pricing literature and the direct link between factor-based asset pricing tests and investors' portfolio allocation problem. The success of size (SMB), book-to-market (HML), and momentum (MOM) factors in explaining stock returns and the country-specific properties of these factors imply that international factor funds can significantly enhance portfolio efficiency beyond what can be achieved by country market indices alone. Using data from ten developed countries over 1981-2004, we show that the Sharpe ratio of the “augmented” optimal portfolio involving international factor funds (0.76) far exceeds that of the “benchmark” optimal portfolio comprising country market indices only (0.19), strongly rejecting the intersection hypothesis which posits that the international factor funds do not span investment opportunities beyond what country market indices do. Among the three classes of factor funds, HML funds contribute most to the efficiency gains. The added gains from international factor diversification are significant for both in- and out-of-sample periods, and for a realistic range of additional investment costs for factor funds, and remain robust over time

This post has been added to Asset Class Reader: International Stocks

Monday, September 03, 2007

Asset Class Correlation

Two papers in this ongoing series of studies on asset class correlation are available at the FPA Journal:

The Volatility of Correlation: Important Implications for the Asset Allocation Decision

William J. Coaker II, senior investment officer of equities for the San Francisco City-County Employees Retirement System.

Executive Summary

* The severity of how much correlation changes, even over longer periods of time, has not been adequately understood.

* This paper analyzes the changing correlation of 15 asset classes measured against the S&P 500 over a 35-year period, and the impact of those changes on asset allocation decisions. It measures the correlations in rolling one-, three-, five-, and ten-year time series, from 1970 to 2004.

* The article also evaluates whether 15 asset classes have helped or hurt in years the S&P 500 has declined, and whether growth or value styles are more correlated to the index.

* The average variance in correlation measured 0.98 over one year and 0.25 over ten years. In short, the relationship among many of the asset classes appears to be inherently unstable.

* Large value provides more diversification benefits than large growth, and small value provides more diversification than small blend or small growth. Emerging markets may provide higher returns and greater diversification than developed nations. But the low correlations of small value and real estate may not hold up during the next broad market decline.

* Correlations exhibit uniqueness, meaning periods are distinct from previous time periods. For example, international stocks' correlation to the S&P 500 was 0.48 from 1970 to 1997, but 0.83 from 1998 to 2002.

* Rather than rely on historical correlations, a more comprehensive and dynamic approach is needed in making asset allocation decisions.

Emphasizing Low-Correlated Assets: The Volatility of Correlation

William J. Coaker II, senior investment officer of equities for the San Francisco City-County Employees Retirement System.

Executive Summary

• The fact that correlations change is well known. But the severity of change, and which relationships are subject to change, needs to be better understood because it has important implications for containing risk.

• This study evaluates the volatility of correlation among 18 asset classes to each other to determine the consistency or inconsistency of relationships. It provides not only the long-term correlations of the assets, but the standard deviation of correlation and the range of correlations based on two standard deviations from the average correlation. It also summarizes the correlations in a probability distribution.

• In the asset allocation process, some assets often are used together even though diversification benefits have been very low. For example, the correlations of the S&P 500 to large growth, mid-blend to mid-growth, small blend to small growth, and large value to mid-value, have been very strong.

• Several assets often are neglected in the asset allocation decision, even though their diversification benefits have been very high. Natural resources, global bonds, and long-short, for example, stand out as having consistently low correlations to all the other assets in this study.

• Growth and blend styles are highly correlated, and using them together does little to reduce risk.

• Real estate, high-yield bonds, U.S. bonds, and long-short are more closely linked to value investing than growth. Emerging markets are somewhat more connected to growth than value.

• The asset allocation decision should emphasize low-correlated assets that satisfy return objectives.Two sample portfolios for different style investors show how risk and return are improved by combining lower-correlated assets.