Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for November 2024 (Final)
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Momentum Investing Strategy (Strategy Overview)

Allocations for November 2024 (Final)
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Investing Expertise

Can analysts, experts and gurus really give you an investing/trading edge? Should you track the advice of as many as possible? Are there ways to tell good ones from bad ones? Recent research indicates that the average “expert” has little to offer individual investors/traders. Finding exceptional advisers is no easier than identifying outperforming stocks. Indiscriminately seeking the output of as many experts as possible is a waste of time. Learning what makes a good expert accurate is worthwhile.

Pension Fund Real Estate Allocation, Cost and Performance

How do pension funds, arguably representative of sophisticated and conservative investors, use real estate as an alternative investment? In their January 2012 paper entitled “Value Added From Money Managers in Private Markets? An Examination of Pension Fund Investments in Real Estate”, Aleksandar Andonov, Piet Eichholtz and Nils Kok investigate the allocation, costs and performance of pension funds with respect to real estate investments. Using self-reported investment data for 884 U.S., Canadian, European and Australian/New Zealand pension funds during 1990 through 2009, they find that: Keep Reading

All-Americans: The Best Picks?

Do stock analysts elected to All-American (AA) status by institutional voters (via Institutional Investor magazine) reliably out-pick other analysts? In the December 2011 update of their paper entitled “Are Stars’ Opinions Worth More? The Relation Between Analyst Reputation and Recommendation Values”, Lily Fang and Ayako Yasuda examine the average performance of stock recommendations of AA analysts and other analysts as distinct groups. They further differentiate top-rank AAs (first and second place winners) from bottom-rank AAs (third-place and runners-up). They define “strong buy” and “buy” stock ratings as buy recommendations and “hold,” “sell” and “strong sell” ratings as sell recommendations. They focus on distinguishing skill from luck and information value from pure influence. They consider adjustments for five risk factors: market, size, book-to-market, momentum and technology sector. Competing portfolios hold recommended stocks for fixed intervals relative to public release dates with equal recommendation weighting and daily rebalancing. Using analyst recommendation data and associated stock returns for 1994 through 2009 (roughly 3,000 analysts and 20,000 stock recommendations per year), they find that: Keep Reading

University Endowment Performance: Strategic versus Tactical Allocation

Is strategic asset class allocation or active management paramount for U.S. university endowment investment performance? In the October 2011 draft of their paper entitled “Do (Some) University Endowments Earn Alpha?”, Brad Barber and Guojun Wang explore the investment performance of U.S. university endowments with regard to overall alpha, performance persistence and sources of superior performance. They assess three groups of universities: Ivy League; other elite universities based on high average math SAT entrance scores; and, the balance of universities. They measure alpha as the residual return (from specific asset selection and tactical asset class allocation) after accounting for the combined returns of best-fit constant (strategic) asset class allocations to five indexes representing U.S. stocks (S&P 500 Index), non-U.S. stocks (MSCI non-U.S.), U.S. bonds (Barclays Capital Aggregate Bond Index), hedge funds (Hedge Fund Research Fund‐Weighted Composite Index) and private equity (Cambridge Associates U.S. Private Equity Index). Using annual voluntarily reported university endowment investment returns, benchmark index returns and math SAT score statistics for incoming freshmen during 1991 through 2010 (279 endowments report in all 20 years), they find that: Keep Reading

SumZero Participant Trading Acumen

Do analysts who work for hedge funds make good calls? In their November 2011 paper entitled “Do Buy-side Recommendations Have Investment Value?”, Steven Crawford, Wesley Gray, Bryan Johnson and Richard Price III profile analysts employed by mutual funds, hedge funds and other investment firms and examine whether these experts make good trading recommendations. Using personal data and 2,135 long and short U.S. common stock investment propositions from over 1,100 participants in the SumZero community of buy-side investment professionals (mostly associated with hedge funds) during March 2008 through December 2010, and contemporaneous institutional holdings from SEC Form 13F filings, they find that: Keep Reading

Impact of Free, Unbiased Investing Advice

How do individual investors respond to an offer of free, unbiased investment advice? In their August 2010 paper entitled “Is Unbiased Financial Advice To Retail Investors Sufficient? Answers from a Large Field Study”, Utpal Bhattacharya, Andreas Hackethal, Simon Kaesler, Benjamin Loos and Steffen Meyer evaluate the responses of 8,195 randomly selected active and likely self-directed individual clients of a large European broker to an offer of free advice. This advice, unbiased in that it is free of monetary incentives for the broker, consists of personalized written and verbal guidance on mean-variance optimization of the client’s existing portfolio based on the client’s risk tolerance, wealth and investment horizon. The broker initiated the offer via email, with telephone follow-ups by an advisor to non-respondents. Using portfolio holder characteristics and daily portfolio holdings/price data from September 2005-May 2009 pre-offer, May 2009-October 2009 offer and post-offer measurement intervals (through March 2010), along with advised portfolio adjustments, they find that: Keep Reading

Does Accurate Forecasting Get Attention?

Do individual experts whose U.S. stock market forecasting records are good (bad) gain (lose) attention? The “pro” argument is that investors (and online intermediaries) eventually flock to good forecasters and ignore bad ones in search of a market timing edge. The “con” arguments are that loud noise (for example, marketing-related or entertainment-driven) swamps information, and/or investors do not or cannot measure forecaster accuracy, and/or investors are more interested in ideas than forecasts. As a simple test these arguments, we compare two data series: (1) the stock market forecasting accuracies of gurus in the Guru Grades summary table; and, (2) the attention paid to these same individuals as measured by the number of search results found by a Google query on (“[guru name]” “stock market”), with the “stock market” qualifier intended to filter out potential namesakes and connect each name to the forecasted variable. Using results from searches for 60 individually graded gurus on 7/20/11, we find that: Keep Reading

Survey of Research on Equity Analysts

There is a decades-long stream of academic research on equity analysts as sophisticated users of financial data, focusing on the usefulness of sell-side analyst earnings forecasts and stock recommendations. What is the gist of this stream? In his June 2011 paper entitled “Analysts’ Forecasts: What Do We Know After Decades of Work?”, Mark Bradshaw surveys research on equity analysts. Using results from dozens of studies spanning approximately four decades, he concludes that: Keep Reading

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

A Few Notes on The Most Important Thing

Howard Marks introduces his 2011 book, The Most Important Thing: Uncommon Sense for the Thoughtful Investor, by stating: “…I have built this book around the idea of the most important things–each is a brick in what I hope will be a solid wall, and none is dispensable. …I consider it my creed, and in the course of my investing career it has served like a religion. …You won’t find a how-to book here. There’s no surefire recipe for investment success. …Just a way to think that might help you make good decisions and, perhaps more important, avoid the pitfalls that ensnare so many. …the thing I most want to make clear is just how complex [investing] is.” Evolved from decades of investing experience, including that as co-founder and chairman of Oaktree Capital Management, some notable points from the book 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

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