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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.

Critically Delegating, or Fearfully Abrogating?

Do individuals tend to think critically about financial advisor recommendations, or blindly follow them? In the March 2009 article entitled “Expert Financial Advice Neurobiologically ‘Offloads’ Financial Decision-Making under Risk”, Jan Engelmann, Monica Capra, Charles Noussair and Gregory Berns investigate the neurobiological basis of the influence of expert advice on financial decisions via functional Magnetic Resonance Imaging monitoring of individuals choosing between a certain payment and a lottery, with and without expert advice. Using test results for 24 individuals (mostly female and mostly undergraduate students), they conclude that: Keep Reading

Mutual Fund Stock Selection vs. Market Timing

Can investors assess the performance of an active fund manager without access to the fund’s detailed trading records (especially trades not evident from quarterly holdings reports)? In the February 2009 update of his paper entitled “Active Alpha and Active Beta – Detecting the Unobserved Actions of Portfolio Managers”, Anders Ekholm presents a new methodology for indirectly measuring the effects of a fund manager’s trading that relies exclusively on portfolio returns. His approach decomposes fund tracking error into two aspects of active management: stock selection (idiosyncratic risk, or active alpha) and general market timing (systemic risk, or active beta). Applying this methodology to daily returns for a sample of actively managed U.S. equity mutual funds over the period 12/31/99-3/31/08, he finds that: Keep Reading

Morningstar Ratings and Future Returns

Does the Morningstar mutual fund rating system work? If so, how? In their March 2009 paper entitled “Selectivity, Market Timing and the Morningstar Star-Rating System”, Antonios Antypas, Guglielmo Caporale, Nikolaos Kourogenis and Nikitas Pittis investigate whether Morningstar mutual fund ratings enable investors to select funds that are likely to outperform in the future. Using data for 1,511 rated equity mutual funds since January 1998, they conclude that: Keep Reading

Converging Guru Accuracies

Do stock market gurus tend to anchor on bullish or bearish outlooks, regardless of market trends? If so, the distribution of their stock market forecasting accuracies should diverge when the market persists in one mode over a long period and converge when the market changes modes. The results at Guru Grades offer a limited way to test these hypotheses. Forecasts from the 2003-2007 bullish period still dominate the samples. If the gurus are mostly anchored on their outlooks, the 2008-2009 bearish period should be compressing the previously spreading distribution of accuracies by raising the grades of stuck bears and lowering the grades of stuck bulls. Based on trends in the Guru Grades accuracy rates over the past five bearish months, we find that: Keep Reading

The Advised, the Non-advised and Frequent Traders

How do financial advisors affect the investing practices of individual investors? Does their advice decisively improve client performance, or are other factors more explanatory? In their February 2009 paper entitled “The Influence of Financial Advisors on Household Portfolios: A Study on Private Investors Switching to Financial Advice”, Ralf Gerhardt and Andreas Hackethal compare the portfolios and transactions of advised and non-advised German investors to determine the effects of advice. They further decompose the sample of investors to explore whether differences between advised and non-advised arise from the advice per se or from investor socio-demographics or trading frequency. Using portfolio compositions and transactions for over 65,000 German investors during February 2006 through July 2007, including 597 who initiated a relationship with a financial advisor during that period, they conclude that: Keep Reading

Usefulness of Non-U.S. Analyst Stock Recommendations and Earnings Forecasts

Are stock recommendations and earnings forecasts from analysts in markets outside the U.S. useful to investors? In their February 2009 paper entitled “International Evidence on Analyst Stock Recommendations, Valuations, and Returns”, Ran Barniv, Ole-Kristian Hope, Mark Myring and Wayne Thomas examine the usefulness of non-U.S. analyst outputs by testing relationships between: (1) valuation estimates and stock recommendations; (2) valuation estimates and future excess returns; and, (3) stock recommendations and future stock returns. They segment results according to level of investor legal protection within the analyst’s country, as indicated by assessments of rule of law, judicial system efficiency and corruption. Using earnings forecasts, stock recommendations and monthly stock return data for 30 countries over the period January 1993 to May 2007, they conclude that: Keep Reading

The Advised Versus the Self-directed

Do individuals who use investment advisors achieve higher returns than those who do not? Two closely related papers entitled “Investment Advice and Individual Investor Portfolio Performance” of January 2009 by Marc Kramer and “The Impact of Financial Advisors on Individual Investor Portfolio Performance” of March 2012 by Marc Kramer and Robert Lensink address this question. Using monthly portfolio returns for thousands of advised and self-directed individual Dutch investors during April 2003 through August 2007 (52 months), they conclude that: Keep Reading

S&P 500 Quarterly Aggregate Earnings Estimate Evolutions

Several readers have inquired or commented about the accuracy of  Standard and Poor’s quarterly S&P 500 earnings estimates. How accurate have they been? Since late 2005, we have tracked the evolving bottoms-up S&P 500 year-over-year quarterly operating earnings growth estimates for 2006-2009 at roughly biweekly intervals. During the early part of this period, we recorded the average of the publicly available Standard and Poor’s and Reuters earnings estimates (generally similar). During the latter part, we recorded only the Standard and Poor’s estimates. Using evolving earnings forecasts for 2006-2009, we find that: Keep Reading

New Funds Outperform?

Do new mutual funds bring fresh alpha to the marketplace, outperforming until the market catches up and extinguishes it? In their August 2008 paper entitled “Performance and Characteristics of Mutual Fund Starts”, Aymen Karoui and Iwan Meier examine the performance and portfolio characteristics of U.S. equity mutual funds launched during 1991-2005. Using monthly return, quarterly holdings and fund characteristics/fee data for 1,374 U.S. domestic equity mutual funds and 828 fund starts over this period, they conclude that: Keep Reading

Hedge Fund Outperformance: Skill or Liquidity Risk?

Can outperforming hedge funds readily convert assets into cash for fund investors? In their October 2008 paper entitled “Hedge Fund Alphas: Do They Reflect Managerial Skills or Mere Compensation for Liquidity Risk Bearing?”, Rajna Gibson and Songtao Wang study the effect of market-wide liquidity risk (the time and costs of transforming a given position into cash and vice versa) on the performance of various hedge fund portfolio strategies. The strategies they consider are: Convertible Arbitrage, Dedicated Short Bias, Emerging Markets, Equity Market Neutral, Event-Driven, Fixed Income Arbitrage, Global Macro, Long/Short Equity Hedge, Managed Futures and Multi-Strategy. Using performance data for a broad sample of live (2,743) and defunct (1,955) hedge funds during 1994-2006 and contemporaneous measures of market-wide (U.S. equities) liquidity, they conclude that: Keep Reading

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