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Animal Spirits

Are investors and traders cats, rationally and independently sniffing out returns? Or are they cows, flowing with a herd that must know something? These blog entries relate to behavioral finance, the study of the animal spirits of investing and trading.

Remedies for Publication Bias, Poor Research Design and p-Hacking?

How can the financial markets research community shed biases that exaggerate predictability and associated expected performance of investment strategies? In his January 2017 paper entitled “The Scientific Outlook in Financial Economics”, Campbell Harvey assesses the conventional approach to empirical research in financial economics, sharing insights from other fields. He focuses on the meaning of p-value, its limitations and various approaches to p-hacking (manipulating models/data to increase statistical significance, as in data snooping). He then outlines and advocates a Bayesian alternative approach to research. Based on research metadata and examples, he concludes that: Keep Reading

Mood Beta as Stock Return Predictor

Do individual stocks react differently and persistently to aggregate investor mood changes? In their December 2016 paper entitled “Mood Beta and Seasonalities in Stock Returns”, David Hirshleifer, Danling Jiang and Yuting Meng investigate whether some stocks have higher sensitivities to investor mood changes (higher mood betas) than others, thereby inducing calendar effects in the cross-section of returns. They specify mood based on three calendar-based U.S. stock market return anomalies:

  1. January (highest average excess return of all months) represents good mood, while October (lowest average excess return of all months) represents bad mood.
  2. Friday (highest average excess return of all days) represents good mood, while Monday (lowest average excess return of all days) represents bad mood.
  3. The two days before holidays (abnormally high average excess return) represent good mood, while the two days after holidays (abnormally low average excess return) represent bad mood.

They structure their investigation via a factor model of stock returns, with mood as a factor. They measure a stock’s mood beta by regressing its returns during high and low mood intervals versus contemporaneous equal-weighted market returns over a rolling historical window. Each year, they regress a stock’s monthly January and October returns versus monthly equal-weighted market returns for those months over the last 10 years. Each week, they regress a stock’s daily Friday and Monday returns versus contemporaneous equal-weighted market returns for those days over the last ten weeks. Each holiday, they regress a stocks pre-holiday and post-holiday daily returns versus versus equal-weighted market returns for those days over the last year (including the same holiday the previous year. They then use the stock’s mood betas to predict its returns during subsequent times of good and bad mood. Using daily and monthly stock returns for a broad sample of U.S. common stocks during January 1963 through December 2015, they find that: Keep Reading

How Investors Really Treat Dividends

Do investors treat stock dividends as part of total returns, or do they view them as a separate income stream? In their December 2016 paper entitled “The Dividend Disconnect”, Samuel Hartzmark and David Solomon investigate whether trading and pricing of stocks exhibit a “free dividend” fallacy (disregard for the fact that dividends directly debit stock price as paid). Specifically, they test whether investors: (1) consider both dividends and capital gains when evaluating stock performance; (2) view dividend stocks differently based on market conditions/competing sources of return; and, (3) reinvest dividends and capital gains differently. Using daily individual trader data during January 1991 through November 1996, quarterly institutional and mutual fund holdings data (SEC filings) during 1980 through 2015 and contemporaneous daily stock and stock index prices, return and dividend data, they find that: Keep Reading

Hedge Fund Manager Personal Risk Taking vs. Investment Performance

Do hedge fund managers who seek excitement as indicated by choice of cars invest differently from those who do not? In their December 2016 paper entitled “Sensation Seeking, Sports Cars, and Hedge Funds”, Yan Lu, Sugata Ray and Melvyn Teo investigate the relationship between hedge fund manager personal car selection (body style, maximum horsepower, maximum torque, passenger volume and safety ratings) and fund performance. After identifying a large set of hedge fund managers, they match managers to cars and car characteristics via VIN Place, Autocheck, cars.com, cars-data and the Insurance Institute for Highway Safety, categorizing cars as sports cars, minivans or other based on body style. They then relate hedge fund manager car data as available to subsequent performance and characteristics of associated hedge funds. Using car data and monthly net-of-fee returns, assets under management and other fund characteristics for 1,774 vehicles (including 163 sports cars and 101 minivans) purchased by 1,144 hedge fund managers during January 1994 through December 2015, they find that: Keep Reading

Exploiting Manufactured Earnings Surprises

Is there a way to tell which corporate executives are manipulating earnings? In their November 2016 paper entitled “Expectations Management and Stock Returns”, Jinhwan Kim and Eric So examine the relationship between firm incentives to manage earnings and stock returns around earnings announcements. They define an expectations management incentives (EMI) indicator that combines three groups of incentives:

  1. Attention – the extent of external scrutiny of reported earnings, consisting of analyst coverage and institutional ownership.
  2. Resources – the capacity to manage expectations, consisting of cash reserves and shareholder equity.
  3. Pressure – unsustainable growth expectations, measured by trailing sales growth.

Specifically, monthly EMI is average percentile rank of analyst coverage, institutional ownership, shareholder equity per share, cash per share and sales growth, divided by the difference between the maximum and minimum percentiles of these characteristics, all as of 12 months ago. Using the specified data and associated returns for a broad sample of U.S. stocks encompassing about 420,000 quarterly earnings announcements during 1985 through 2015, they find that: Keep Reading

When Short Sellers Talk Trash

Do short sellers who publicly attack their targets affect stock prices? How do they choose their targets? In his October 2016 paper entitled “Activist Short-Selling”, Wuyang Zhao studies short sellers who publish adverse research on and/or publicly disparage the stocks they short. To assess unique effects of the negative publicity on targeted stock prices, he compares performances of targeted stocks on negative publicity days with those of the same stocks, and of industry peers with the closest or highest contemporaneous levels of short interest or increases in short interest, on short interest release days (five separate benchmarks). To identify characteristics of firms that attract activist short sellers, he examines 12 indicators of stock overvaluation and nine measures of uncertainty about firm prospects. Based on initial tests, he constructs aggregate metrics for overvaluation (averaging seven of the overvaluation indicators) and uncertainty (averaging six of the uncertainty measures) for subsequent tests. Using stock prices and firm characteristics related to 6,197 cases of activist short selling reported in Seeking Alpha or Activist Shorts Research during mid-February 2006 through December 2015, he finds that: Keep Reading

High Prices Mean Good Stocks?

Are stocks with high prices or low prices inherently better deals? In their October 2016 paper entitled “Nominal Stock Price Investing”, Ulrich Hammerich, Christian Fieberg and Thorsten Poddig examine the relationship between stock price and future stock performance in the German equity market. Specifically, they each month sort stocks by price and measure the difference in average total returns between the equally weighted tenth (decile) of stocks with the highest prices and the equally weighted decile with the lowest prices. Using monthly prices and total returns for a broad set of German stocks from the end of January 1990 through December 2013, they find that: Keep Reading

Stock Return Reversals Triggered by Earnings Announcements

Can traders exploit a tendency of some investors to over-anticipate good or bad news just before firm earnings announcements? In their 2016 paper entitled “Fear and Greed: a Returns-Based Trading Strategy around Earnings Announcements”, flagged by a subscriber, Ivo Jansen and Andrei Nikiforov investigate post-release reversal of extreme abnormal returns during the week before an earnings announcement. Specifically, they test a trading strategy that on earnings announcement day through the next day takes a long (short) position in stocks with extreme negative (positive) abnormal returns during the prior week. They define abnormal returns as the difference between a target stock’s return and the average return of the ranked tenth (decile) of stocks sorted on size (market capitalization) to which the stock belongs. To define extreme returns during the pre-announcement week, they consider returns outside thresholds of -5%/+5%, -10%/+10% and -15%/+15%. Using quarterly firm size, earnings announcement dates and associated daily stock prices for a broad sample of U.S. stocks priced at least $2 per share from the second half of 1971 through 2012, they find that: Keep Reading

Economic News Leaks to Some Traders?

Can small (unconnected) investors compete in trades on economic news? In the February 2016 draft of her paper entitled “Is Someone Front-Running You Around News Releases?”, Irene Aldridge examines U.S. stock price, volatility and trading activity around ISM Manufacturing Index and Construction Spending news releases (which occur while the stock market is open). Media violations of embargoes on pre-release distribution of such news, intended to promote widespread simultaneous scheduled release, could influence this activity. She uses average price response of Russell 3000 stocks as a market reaction metric. She considers news “direction” relative either to prior-month value (increase or decrease) or to consensus forecast (above or below). Using one-minute trading data for Russell 3000 Index stocks around monthly ISM Manufacturing Index and Construction Spending announcements during January 2013 through October 2015, she finds that: Keep Reading

Equity Factor Returns Across the Chinese Zodiac

Do the 12 yearly signs of the Chinese Zodiac cycle (Rabbit, Dragon, Snake, Horse, Goat, Monkey, Rooster, Dog, Pig, Rat, Ox, Tiger) relate individually to stock market behavior? In their January 2016 paper entitled “The Zodiac Calendar and Equity Factor Returns”, Janice Phoeng and Laurens Swinkels calculate four annual equity factor returns for each of the Zodiac signs: (1) market minus the risk-free rate; (2) small capitalization minus big capitalization; (3) value minus growth; and, (4) high momentum versus low momentum. They start each year on the first day of the Zodiac New Year and end at the last day of the same Zodiac year. Using daily U.S. equity factor returns from Kenneth French’s data library during early February 1927 through mid-February 2015, they find that: Keep Reading

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