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Investor Sentiment and Stock Return Anomalies 股票市场和投资者心态实验

Investor sentiment refers to the propensity of individuals to trade on “noise” and emotions rather than fundamentals. As a contrarian stock market indicator, investor sentiment affects stock prices. Indicators that measure investor sentiment includes: Investor Intelligence Sentiment Index, American Association of Individual Investors (AAII) Sentiment Indicator, Nova/Ursa Ratio, the Short Interest/Total Market Float, and the Put/Call Ratio. CNNMoney also introduces the “Seven Fear & Greed Indicators” tracking how emotion is driving the stock market on a daily basis:

  1. Stock price strength
  2. Junk bond demand
  3. Market momentum
  4. Safe haven demand
  5. Market volatility
  6. Stock price breadth
  7. Put and call options

Studies of the relationship between investor sentiment and aggregate stock returns emerged in the 1980s, with the focus on:

  • The tendency of aggregate returns to mean revert
  • The volatility in stock index returns that could not be justified by volatility in fundamentals
  • The predictability of aggregate returns using valuation such like the ratio of dividends to stock market value

Two decades later, researchers include Rober F. Stambaugh (Wharton), Malcolm Baker & Jeffrey Wurgler (Stern) furthered the subject with more advanced and reasonable approaches.

In Stambaugh’s experiment, namely, he identified stock return anomalies associated with the price changes after adjusting for the Fama-French three-factor exposures:

  • Firms with growth in assets like plant equipment, fleets of vehicles, property and inventories
  • Firms in financial distress
  • Firms with net stocks issues
  • Firms with composite equity issues
  • Firms with high accruals
  • Firms that show share-price momentum
  • Firms with gross profitability premium
  • Firms that distinguished by their return on assets, ratio of investments to assets, net operating assets

For each anomaly, value-weighted portfolio returns are calculated. Stambaugh’s selected the 10% of stocks that performed best and the 10% that performed worst. For each, Stambaugh examined a long/short investment strategy that purchased the best-performing stocks and shorted the worst-performing ones. The results were then studied in relation to the overall market sentiment at the time.

Similarly, Baker & Wurgler’s adopted six measures in their approach:

  1. Trading volume as measured by NYSE turnover
  2. Dividend premium (the difference between the average market-to-book ratio of dividend payers and non-payers)
  3. Closed-end fund discount
  4. Number of IPOs
  5. First-day returns on IPOs
  6. Equity share in new issues

Along with some earlier tests, it is interesting to note that:

  1. Investor sentiment partly explains equity market anomalies in cross-sectional stock returns.
  2. Investor sentiment plays a significant role in market volatility, and it generates return predictability of a form consistent with corrections of overreaction.
  3. The global component of total sentiment is a contrarian predictor of country-level market returns.
  4. High investor sentiment predicted low future returns, and vice versa, for both value- and equal- weighted market returns and for non-U.S. markets.
  5. The economic significance of the effect was nontrivial.
  6. Broad waves of sentiment has greater effects on hard-to-arbitrage (i.e. with greater costs or risks) and hard-to value stocks (e.g. growth and distressed stocks), which tend to exhibit high sentiment beta. Furthermore, the effect is much smaller on low volatility or large stocks, as they are relatively easy to arbitrage and value.
  7. Investor sentiment was contagious, which means that, U.S. sentiment impacted returns for countries linked with the U.S. by significant capital flows.
  8. Comparing private markets with public markets, investor sentiment leads to prolonged periods of mispricing in private markets, while price revelation occurs more rapidly in public stock markets where the ability of informed investors to short-sell exists.
  9. Firms that hold extremely good news following low sentiment periods earns significantly higher excess returns than those following optimistic sentiment periods.
  10. In U.S. equity long/short strategies, investor sentiment affects equity anomalies differently in the shorting strategy and in the long strategy.
  11. An environment of high investor sentiment, where there are many overpriced stocks, tends to be more prevalent than that of low sentiment, i.e., profits are significantly greater in the shorting strategy following a period of high sentiment.
  12. The impediments to short-selling limit the potential that overpricing can be exploited. It is harder to sell stocks short to bet on a price drop than it is to buy stocks to bet on a gain, thus stocks could be more likely to be overpriced when sentiment is high. The long-shrot spreads are much more profitable following high investor sentiment, because short sales become very profitable due to overpricing from high sentiment.

In brief, if the disparity could be identified in the stocks with anomalous pricing behavior, it would help greatly in reducing forecasting errors; in addition, the discoveries also indicate a better way of allocating research resources for the investment management firms with equity long/short strategies.

References:

  • Malcolm Baker and Jeffrey Wurgler (2007)
  • Joshua Livnat & Christine Petrovits (2008)
  • David C. Ling, Andy Naranjo, and Benjamin Scheick (2010)
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