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Mutual/Hedge Funds

Do investors in mutual funds and hedge funds get their fair share of returns, or are they perpetually disadvantaged by fees and underperforming fund managers? Are there ways to exploit fund behaviors? These blog entries relate to mutual funds and hedge funds.

Active ETF Performance

Do active exchange-traded funds (ETF), which realistically incorporate management costs and trading frictions, offer value to investors? In his June 2011 paper entitled “Active ETFs and Their Performance vis-à-vis Passive ETFs, Mutual Funds and Hedge Funds”, Panagiotis Schizas examines the returns and risks of the first active ETFs, including comparisons with alternative passive ETFs, mutual funds and hedge funds. The active ETFs [and passive counterparts] he considers are:

PowerShares Active Low Duration (PLK) [iShares Barclays 1-3 Year Treasury Bond (SHY)]
PowerShares Active Mega Cap (PMA) [SPDR S&P 500 (SPY)]
PowerShares Active AlphaQ (PQY) [PowerShares QQQ (QQQ)]
PowerShares Active Alpha Multi-Cap (PQZ) [SPDR S&P 500 (SPY)]
PowerShares Active U.S. Real Estate (PSR) [iShares FTSE NAREIT Real Estate 50 (FTY)]

Using matched ETF, mutual fund and hedge fund performance data (daily for ETFs and mutual funds and monthly for hedge funds) as available from active ETF inception (4/14/08 for the first four and 11/21/08 for the fifth) through 3/4/10, he finds that: Keep Reading

Focus on the Most Intensely Active Mutual Funds?

Are many mutual fund managers worldwide so fixated on benchmarks that they substantially emulate index funds, while charging shareholders “active” fees? In the April 2011 version of their paper entitled “The Mutual Fund Industry Worldwide: Explicit and Closet Indexing, Fees, and Performance”, Martijn Cremers, Miguel Ferreira, Pedro Matos and Laura Starks address the prevalence and consequences of index versus active investing in the mutual fund industry around the world. They focus on “closet index” funds that are nominally active but do not deviate much from benchmark compositions, applying an “Active Share” measurement to quantify the degree of deviation. Using data for large samples of alive and dead open-end equity mutual and exchange-traded funds across 30 countries during 2002 through 2007, they find that: Keep Reading

Hedge Fund Benchmark Bias?

Hedge fund databases are prone to: (1) self-selection bias (only good performers report); (2) backfill bias (only funds with good recent past performance retroactively report it); (3) survivorship bias (exclusion of dead fund performance); and; (4) liquidation bias (poor performers stop reporting but continue to operate for some period). Do hedge fund indexes therefore inaccurately portray industry performance? In the April 2011 revision of their paper entitled “Hedge Fund Biases After the Financial Crisis”, Dieter Kaiser and Florian Haberfelner estimate three of the four hedge fund database biases and explore how these biases evolved during the 2007-2009 financial crisis. They focus on liquidation bias, which leading commercial hedge fund databases do not attempt to control. Their principal analytic technique is to form hypothetical funds of hedge funds from actual single funds and compare the resulting hypothetical returns, after correcting for observable backfill and survivorship biases, with returns from real funds of hedge funds. Using data for 8,935 hedge funds (6,088 single funds and 2,847 funds of funds) for the period January 2002 through September 2010, they find that: Keep Reading

Taxonomy of Mutual Fund Fees, Expenses and Costs

The variety and sometime abstruseness of mutual fund fees and expenses suggest that fund manager incentives do not always align with the interest of fund investors in net return. In an April 2011 update entitled “Mutual Funds: Revised New Total Expense Ratio and Costs with Soft-Dollar Commissions and Rebates”, John Haslem notes that the SEC “regulatory scheme of expense ratio disclosure is short on transparency and long on opaque” and offers an alternative taxonomy of mutual fund costs intended to be transparent for investors. As described in the article, the categories/elements and typical magnitudes of annual fund expenses are: Keep Reading

Holdings Return Skewness as a Luck-Skill Discriminator

Can investors discriminate between lucky and skillful equity fund managers by examining the distribution of returns across fund holdings? In the September 2010 preliminary draft of their paper entitled “Home-Run Sluggers vs. Contact Hitters: Stock Performance Distribution inside Mutual Funds and Fund Managers’ Stock Picking Ability”, Peter Chung and Thomas Kim relate the skewness of the return distribution of equity mutual fund holdings to performance persistence. Specifically, they calculate the skewness of the distribution of four-factor (adjusted for market, size, book-to-market, momentum) alphas of individual fund holdings weighted according to position size. A fund manager who consistently picks outperforming stocks (gets lucky with one big winner) would have a negatively (positively) skewed distribution of alphas. Using reported holdings for 1,604 U.S. equity mutual funds and data to calculate the lagged six-month alphas for each of these holdings from the end of July 2002 through February 2006, they find that: Keep Reading

Institutional Ownership, Idiosyncratic Volatility and Stock Returns

Is the number of institutional owners of a stock, arguably a proxy for general investor awareness and demand, an important factor in current and future pricing of the stock? In their February 2011 paper entitled “What Makes Stock Prices Move? Fundamentals vs. Investor Recognition”, Scott Richardson, Richard Sloan and Haifeng You investigate the role of institutional ownership breadth in size-adjusted stock price dynamics. They focus on institutional investors with greater than $100 million in equity holdings, as reported quarterly to the SEC via Form 13F. They measure institutional ownership breadth as the number of institutions holding a particular stock relative to the number of institutions holding any given stock. They measure firm size based on total assets. They impose a three-month lag on data to ensure calculations use only publicly available information. Using stock returns, institutional ownership data and accounting data for a broad sample of U.S. firms over the period 1986 through 2008 (35,526 firm years), they find that: Keep Reading

Mutual Fund Investors Causing Their Own Demise?

Do mutual fund investors in aggregate exhibit good, bad or indifferent market timing? In their January 2011 article entitled “Past Performance is Indicative of Future Beliefs”, Philip Maymin and Gregg Fisher investigate how the aggregated timing of buying and selling by mutual fund investors affects their average returns. Using monthly returns and assets for approximately 25,000 mutual funds over the period November 1995 through October 2010, they find that: Keep Reading

Outperformance of Hedge Funds: Timing or Asset Selection?

Does hedge fund outperformance derive from systematically superior timing or from superior asset selection? In the December 2010 version of her paper entitled “Can Factor Timing Explain Hedge Fund Alpha?”, Hyuna Park decomposes alpha generated by hedge funds into security selection and timing with respect to eight risk factors (including U.S. and emerging equity risk premiums). Her essential measure of  factor timing performance is degree of fund success in raising (lowering) exposure to a factor when the factor’s return is high (low). For example, a fund with a high equity market beta when stock returns are high and low equity market beta when stock returns are low demonstrates good timing of the equity risk premium. She gives special attention to relatively illiquid hedge funds to ensure that frequent trading does not obscure factor timing ability and considers both aggregate and individual fund performances. Using net returns and other characteristics for 6,114 live and dead hedge funds during 1994-2008, she finds that: Keep Reading

Diversifying within Versus across Hedge Strategies

Funds of hedge funds (FoF) diversify investments across hedge funds to achieve steady return streams. Some FoFs diversify within a single hedge fund strategy (category), while others diversify both within and across hedge fund categories. Does the latter enhanced approach to diversification outperform the former? In their December 2010 paper entitled “Diversification Strategies and the Performance of Funds of Hedge Funds”, Na Dai and Hany Shawky contrast the performances of FoFs that diversify within one category versus those that diversify both within and across categories. Using monthly performance data for two broad samples of live and dead FoFs with different diversification metrics spanning 1994 through 2008, they find that: Keep Reading

Dividend Tax Drag on European Funds

Do European-listed equity index funds predictably underperform their benchmarks by the amount of total expenses, as do U.S.-listed counterparts? In the May 2010 update of their paper entitled “The Performance of European Index Funds and Exchange-Traded Funds”, David Blitz, Joop Huij and Laurens Swinkels investigate the magnitude and sources of underperformance of European index mutual funds and exchange-traded funds (ETF) relative to benchmark indexes. Using return and expense data for a sample of 40 European-listed passive funds of interest to global equity investors, and their underlying indexes, spanning January 2003 through December 2008, they find that: Keep Reading

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