Objective research to aid investing decisions

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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.

Beware the Favorite Investments of Stock Market Gurus?

Do the favorite equity investments of stock market newsletter gurus reliably outperform the market? One way to answer this question is a test of the performance of the favorite investments identified in the historical reports at NewsletterAdvisors.com published from 11/1/05 to 11/1/07. In each of these seven reports, a group of “top investment gurus reveal their favorite investment ideas.” NewsletterAdvisors.com is published by Business Financial Publishing, “a diversified publisher of investment news, research, and analysis for individual investors through paid subscription newsletters, free e-letters, and regular special reports.” Using historical price data from Yahoo!Finance for the sample of 70 favorite investments in in the seven reports and contemporaneous S&P Depository Receipts (SPY) performance data for benchmarking, we find that: Keep Reading

The Timing Performance of Expert Futures Traders

Do Commodity Trading Advisors (CTAs), generally associated with the “managed futures” hedge fund style, successfully time their chosen markets? These traders take long or short positions in investment vehicles with low transaction cost (such as futures contracts) to exploit trends in commodity prices, exchanges rates, interest rates and equity prices. In the February 2008 version of their paper entitled “Market Timing of CTAs: An Examination of Systematic CTAs vs. Discretionary CTAs”, Hossein Kazemi and Ying Li investigate the return and volatility timing ability of CTAs and examine whether there is a difference in market timing abilities between systematic and discretionary traders. To this end, they develop a set of risk factors based on returns from the most heavily traded futures contracts. Using monthly, net-of-fees return data for 1994-2004 (encompassing 278 live and 622 defunct CTA funds), they conclude that: Keep Reading

Do Stock Recommendations on Blogs Have Value and Move the Market?

What is the nature and value of stock recommendations made by bloggers? Do investors/traders act on them? In his recent paper entitled “The Impact of Blog Recommendations on Security Prices and Trading Volumes”, Veljko Fotak measures the performance and influence of blogger stock recommendations based on a sample of 340 buy and 160 sell recommendations from 122 distinct bloggers (with posted biographies) via Seeking Alpha during 2006. Using this sample, along with daily price and volume data for the recommended stocks, he concludes that: Keep Reading

Filtering the Luck Out of Mutual Fund Performance Data

What proportion of mutual funds truly, after accounting for luck, generate positive alpha? Is there a reliable way to find such funds? In the March 2008 version of their paper entitled “False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas”, Laurent Barras, Olivier Scaillet and Russ Wermers apply a new technique to measure the role of luck across a large sample of mutual funds. Using monthly returns for 2,076 U.S. actively managed domestic equity mutual funds (1,304 growth, 388 aggressive growth and 384 growth and income) existing for at least 60 months during 1975-2006, they conclude that: Keep Reading

The Wall Street Journal’s SmartMoney Fund Screen

Does the Wall Street Journal’s SmartMoney Fund Screen help its readers beat the market? In the February 2008 version of their paper entitled “Do Mutual Fund Media Recommendations Hold Value? An Empirical Analysis of the Wall Street Journal’s SmartMoney Fund Screen”, George Comer, Norris Larrymore and Javier Rodriguez employ two methods to test the performance of mutual funds listed at the ends of the Wall Street Journal’s SmartMoney Fund Screen columns during the year before and the year after publication. These weekly columns flag top performing mutual funds based on criteria such as fund objective, historical returns and expense ratios. The authors collect and assign the funds in these lists to one of five fund categories: domestic equity, international equity, sector, hybrid (asset allocation and balanced funds) and fixed income. Using daily returns for 399 mutual funds (263 unique) listed during 2005, they conclude that: Keep Reading

Comprehensive Overview of Research on Equity Analyst Forecasting

What is the state of research on the forecasting methods and outputs of equity analysts? In their 2008 paper entitled “The Financial Analyst Forecasting Literature: A Taxonomy with Suggestions for Further Research”, Sundaresh Ramnath, Steve Rock and Philip Shane catalog and organize past research on the forecasting of equity analysts with focus on the period since 1992. Using results from approximately 250 post-1992 papers related to equity analysts from eleven major research journals, they summarize findings related to the following questions: Keep Reading

Reliable Outperformance Among Bond Fund Managers?

Does past performance predict future results for bond funds? In their April 2007 paper entitled “‘Hot Hands’ in Bond Funds”, Joop Huij and Jeroen Derwall measure persistence in the relative performance of bond mutual funds. Using return data for 3,549 bond funds spanning 1990-2003, they find that: Keep Reading

Analyst Ratings: Levels or Changes?

In considering the stock ratings of expert analysts, should investors focus more on the level of the ratings or changes in ratings? In their December 2007 paper entitled “Ratings Changes, Ratings Levels, and the Predictive Value of Analysts’ Recommendations”, Brad Barber, Reuven Lehavy and Brett Trueman investigate the potential value to investors of both levels of (strong buy, buy, hold, sell, strong sell) and changes in analyst stock ratings. Using real-time analyst stock ratings from two databases spanning 1986-2006 (more than 1,000,000 ratings) and contemporaneous daily stock returns, they conclude that: Keep Reading

Mutual Fund Investors Underperform Their Underperforming Funds?

Mutual fund investors have two ways to beat the market: (1) pick the right funds, and (2) time their purchases and sales. How effectively does the average fund investor execute the latter goal? In their December 2007 paper entitled “Investor Timing and Fund Distribution Channels”, Mercer Bullard, Geoff Friesen and Travis Sapp examine the investment timing performance of equity mutual fund investors and the relationship of this performance to the fund distribution channel. Using data on returns and funds flows for 6,164 U.S. equity mutual funds during 1991-2004, they conclude that: Keep Reading

Invest Like the Ivy League?

Just why do those Ivy League endowments do so well? In their October 2007 paper entitled “Secrets of the Academy: The Drivers of University Endowment Success”, Josh Lerner, Antoinette Schoar and Jialan Wang investigate the performance of university endowments overall during the past decade and the factors contributing to outperformance of the most successful ones. Using voluntarily provided holdings and return data for over 1,300 university endowments mostly over the period 1992-2005, they conclude that: Keep Reading

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