Introduction. Wall Street Journal, Europe Edition, May 25, 2011, 11:32 A.M.

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1 SENTIMENT

2 Introduction LONDON (Dow Jones)--The premium investors demand to hold Spanish debt over benchmark German debt, and the cost of insuring Spanish debt against default, fell Wednesday, but traders cautioned against seeing the moves as evidence of a positive turn in investor sentiment. Wall Street Journal, Europe Edition, May 25, 2011, 11:32 A.M. ET All this talk of restructuring on Greece is really hitting sentiment now, the ECB seem to have disappeared from the market and the whole periphery is getting hit a trader said Reuters, Apr 14, :49am EDT,

3 Introduction If you get a series of opposition victories it may at the margin increase Spain's vulnerability to a negative change in market sentiment Richard McGuire, rate strategist at Rabobank said. REUTERS, 05/20/11, The details of the Irish package were so far unsuccessful in soothing market sentiment, said Kornelius Purps, a fixed- income strategist at UniCredit SpA in Munich. Dobson, Bloomberg, Nov 29, :53 PM GMT+0200,

4 Introduction Many authors argue that a lot of the anomalies observed in financial markets are due to investor sentiment Barberis, Shleifer, and Vishny (1998) present and solve a one-asset oneinvestor model where the investor s beliefs reflect consensus forecasts (the investor also believes that earnings are either mean-reverting or trending) and where the solution generates both underreaction and overreaction for a wide range of parameter values Daniel, Hirshleifer and Subrahmanyam (1998) assume that investors are overconfident and (in the case where self-attribution bias is also present) the subsequent arrival of information that either confirms or disconfirms investor private information will lead to asymmetric reaction. That is, in the short-term the overconfidence increases following the arrival of confirming news and that leads to further overreaction and return momentum; in the long run, as investors realize their errors, a return reversal is observed. Furthermore, since on average investors hold long positions an increase in market prices will result in higher overconfidence and greater return momentum.

5 Introduction As Zhang (2008) points out, however, the term sentiment is used in different ways among economists, professionals, academics, etc. As a result the concept of investor sentiment is considered to general. This is reflected in the many different ways in which we measure sentiment Measures of sentiment may be classified in two broad categories indirect indexes that are based on market data direct indexes that are based on market surveys and survey data

6 Introduction Major proxies for sentiment that have been used in empirical studies are: closed-end fund discount consumer confidence indexes market liquidity investor intelligence surveys option implied volatility odd-lot sales to purchases mutual fund flows dividend premium IPO first-day returns IPO volume etc (see Brown, Goetzmann, Hirkai, Shiraishi, & Watanabe (2002), Baker & Stein (2004), Neal & Wheatley (1998), Simon & Wiggins (2001), Fisher & Statman (2003), among others).

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8 Empirical Studies Recent academic literature has seen a rise of studies investigating the effect of individual investor sentiment on stock returns. Several papers document a strong link between the two variables both in the time-series and cross-sectionally. These papers estimate predictive regressions of the form R (t+1) = α + β sentiment(t) + η(t) where R(t+1) is the return of the aggregate stock market or a (zero-cost) portfolio at time (t+1) and Sentiment(t) is a proxy for (lagged) investor sentiment. A common finding for the US stock market is a statistically and economically significant negative coefficient estimate for β. Schmeling (2009)

9 Empirical Studies Fisher and Statman (2000): Investors are not all alike, and neither are their sentiments. We show that the sentiment of Wall Street strategists is unrelated to the sentiment of individual investors or that of newsletter writers, although the sentiment of the last two groups is closely related. Sentiment can be useful for tactical asset allocation. We found a negative relationship between the sentiment of each of these three groups and future stock returns, and the relationship is statistically significant for Wall Street strategists and individual investors.

10 Empirical Studies Fisher and Statman (2000): Alan Greenspan, chair of the U.S. Federal Reserve Board, warned against irrational exuberance in December In 1999, he warned against Internet mania. Greenspan told the Senate Budget Committee on January 28, 1999, that the impulse that drives Internet investors is the not-quite-rational impulse that drives lottery ticket buyers. One day earlier, Arthur Levitt, chair of the U.S. Securities and Exchange Commission, warned day traders that they should trade only with funds they can afford to lose (Wessel 1999).

11 Empirical Studies For the sentiment of the large investors, we used data from Merrill Lynch, which has compiled the sentiment of Wall Street sell-side strategists since September Merrill Lynch defines the sentiment of Wall Street strategists as the mean allocation to stocks in their recommended portfolios. Merrill Lynch compiles the sentiment of strategists monthly, and responses are received close to the end of each month. Data on medium-sized investors came from Chartcraft, an investment services company that publishes Investors Intelligence, a survey of the sentiment of more than 130 investment newsletter writers. Investors Intelligence classifies newsletter writers into three categories bullish, bearish, or waiting for a correction and it promotes the sentiment data as a contrary indicator; investors are advised to sell when the proportion of bulls among newsletter writers is high.

12 Empirical Studies Fisher and Statman (2000): Our data on the sentiment of small investors came from the American Association of Individual Investors (AAII), which has conducted a sentiment survey among its members since July The AAII asks respondents to classify themselves as bullish, bearish, or neutral. We used the percentage of bullish investors in the last week of each month as a measure of the sentiment of individual investors that would correspond to the measure of sentiment of newsletter writers and Wall Street strategists.

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16 Empirical Studies Fisher and Statman (2003), use the consumer confidence measures of the University of Michigan and the Conference Board as proxies of sentiment They find that consumer confidence has some predictive ability on stock returns; a negative relationship is found between the level of consumer confidence and subsequent Nasdaq and small cap stock returns.

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20 Empirical Studies Schmeling (2009) also examines consumer confidence as a proxy for individual investor sentiment for 18 industrialized countries He finds that sentiment negatively forecasts aggregate stock market returns, on average, across countries When sentiment is high, future returns tend to be low; when sentiment is low future stock returns tend to be high This holds mainly for growth stocks and small stocks

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26 Empirical Studies Brown & Cliff (2004) investigate investor sentiment and its relation to near-term stock market returns. They find that many commonly cited indirect measures of sentiment are related to direct measures (surveys) of investor sentiment. However, past market returns are also an important determinant of sentiment. Although sentiment levels and changes are strongly correlated with contemporaneous market returns, their tests show that sentiment has little predictive power for near-term future stock returns. Their evidence does not support the conventional wisdom that sentiment primarily affects individual investors and small stocks.

27 Empirical Studies The ratio of the number of advancing issues to declining issues (ADV/DEC). At the monthly level, the percent change in margin borrowing (DMARGIN) as reported by the Federal Reserve. This measure is frequently cited as a bullish indicator since it represents investors using borrowed money to invest. On a monthly basis, the percent change in short interest (DSHORTIR) is viewed as a bearish indicator. In the weekly sample, the ratio of short sales to total sales (SHORTSLS). The ratio of CBOE equity put to call (PUT/CALL) trading volume is widely viewed as a bearish indicator. The Commodities Futures Trading Commission (CFTC) reports the change in the net position in SPX futures by trader type. They use these data on non-commercial traders (FUTp) as a proxy for institutional sentiment and activity by small traders (FUTa) as a proxy for individual sentiment.

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31 Empirical Studies Simon and Wiggins (2001) study the S&P500 futures contract and proxy sentiment with the volatility index, the put-call ratio, and the trading index; their findings indicate that these proxies are contrarian indicators. They argue that this is consistent with the view that periods of extreme fear in the stock market have provided excellent buying opportunities. Kurov (2008) estimates the sentiment index as the ratio of the percentage of bullish investors to the sum of the percentages of bullish and bearish investors and suggests that positive feedback trading in index futures markets appears to be more active in periods of high investor sentiment; a finding consistent with the view that feedback trading is driven by the expectations of noise traders. Other findings indicate that sentiment-driven trading in derivative markets increases market liquidity.

32 Empirical Studies Neal and Wheatley (1998) use the level of discounts on closed-end funds, the ratio of odd-lot sales to purchases, and net mutual fund redemptions as proxies of investor sentiment and find that fund discounts and net redemptions predict the return difference between small and large firm returns, while the odd-lot ratio has no predictive ability on either small or large firm returns. Wang et al. (2006) test whether sentiment is useful for volatility forecasting purposes. Their findings indicate that most of the sentiment measures employed (putcall trading volume ratio, OEX put-call open interest ratio, the ARMS index, and two survey indexes) are affected by returns and volatility rather than vice versa, and that all sentiment variables have extremely limited forecasting power once returns are included as a forecasting variable.

33 Empirical Studies Tetlock (2007) uses the daily content from a popular Wall Street Journal column to quantify sentiment and finds evidence consistent with noise and liquidity traders; more specifically the results indicate that high media pessimism predicts downward pressure on market prices followed by a reversion to fundamentals, and unusually high or low pessimism predicts high market trading volume. Kumar and Lee (2006) use retail investor transactions and show that systematic retail trading explains return comovements for small-cap stocks, value stocks, lower institutional ownership stocks, and lower-priced stocks, particularly if these stocks are costly to arbitrage. The authors argue that their findings support a role for investor sentiment in the formation of returns.

34 Empirical Studies Cornelli et al. (2006) examine whether the post- Initial Public Offering (IPO) prices are driven by the irrational behaviour of small retailinvestors and find that overoptimism for specific stocks causes aftermarket prices to be 40.5% higher, on average, than they would have been in the absence of overoptimistic investors, with the temporary price increases partially reversed over the first year. Overall their findings indicate the existence of both sentiment and sophisticated investors, with the latter taking advantage of the actions of the sentiment investors.

35 Empirical Studies Edmans, Garcia, Norli (2007) investigate the stock market reaction to sudden changes in investor mood, using a cross-section of 39 countries Motivated by psychological evidence of a strong link between soccer outcomes and mood, they use international soccer results as their primary mood variable. They find a significant market decline after soccer losses. For example, a loss in the World Cup elimination stage leads to a next-day abnormal stock return of 49 basis points. Also, elimination from a major international soccer tournament is associated with a next-day return on the national stock market index that is 38 basis points lower than average. This loss effect is stronger in small stocks and in more important games, and is robust to methodological changes. They also document a loss effect after international cricket, rugby, and basketball games.

36 Empirical Studies Mood and behavior? Motivation according to Edmans, et al (2007): Wann et al. (1994) document that fans often experience a strong positive reaction when their team performs well and a corresponding negative reaction when the team performs poorly. More importantly, such reactions extend to increased or decreased selfesteem andto positive or negative feelings about life in general. Hirt et al. (1992) find that Indiana University college students estimate their own performance to be significantly better after watching a win by their college basketball team than after watching a loss. Schwarz et al. (1987) document that the outcome of two games played by Germany in the 1982 World Cup significantly changed subjects assessments of their own well-being and their views on national issues.

37 Empirical Studies Schweitzer et al. (1992) shows that assessments of both the probability of a 1990 war in Iraq and its potential casualties were significantly lower among students rooting for the winning team of a televised American football game than among fans of the losing team. Changes in mood also affect economic behavior. Arkes, Herren, and Isen (1988) find that sales of Ohio State lottery tickets increase in the days after a victory by the Ohio State University football team. Given the evidence that sports results affect subjects optimism or pessimism about not just their own abilities, but life in general, we hypothesize that they impact investors views on future stock prices Edmans, et al (2007), Data: International soccer results from January 1973 through December 2004 from the websitewww.rdasilva.demon.co.uk. The data include games from the World Cup and the main continental cups (European Championship, Copa America, and Asian Cup).

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43 Empirical Studies Palomino, Renneboog, Luc, & Zhang, (2008) argue that soccer clubs listed on the London Stock Exchange provide a unique way of testing stock price reactions to different types of news. For each firm, two pieces of information are released on a weekly basis: experts expectations (betting odds), and the game outcomes themselves. The stock market reacts strongly to news about game results, generating significant abnormal returns and trading volumes. They find evidence that the abnormal returns for the winning teams do not reflect rational expectations but are high due to overreactions induced by investor sentiment. This is not the case for losing teams. There is no market reaction to the release of new betting information although these betting odds are excellent predictors of the game outcomes. They also find that betting information predicts a stock price overreaction to game results which is influenced by investors mood (especially when the teams are strongly expected to win).

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50 Empirical Studies Chung, Hung, YehWe (2012, Journal of Empirical Finance) examine the asymmetry in the predictive power of investor sentiment in the crosssection of stock returns across economic expansion and recession states. They test the implication of behavioral theories and evidence that the return predictability of sentiment should be most pronounced in an expansion state when investors' optimism increases. They segregate economic states according to the NBER business cycles and further implement a multivariate Markov switching model to capture the unobservable dynamics of the changes in the economic regime. The evidence suggests that only in the expansion state does sentiment perform both in-sample and out-of-sample predictive power for the returns of portfolio formed on size, book-tomarket equity ratio, dividend yield, earnings-to-price ratio, age, return volatility, asset tangibility, growth opportunities, and 11 widely documented anomalies. In a recession state, however, the predictive power of sentiment is generally insignificant.

51 Empirical Studies Baker and Wurgler (2006) argue that any single proxy for sentiment will be imperfect and noisy; Thus a practical approach could be to average various proxies and use the common component as a measure of sentiment. They form a composite index of sentiment that is based on the common variation in six underlying proxies for sentiment such as: the closed-end fund discount, NYSE share turnover, the number and average first-day returns on IPOs, the equity share in new issues, and the dividend premium. More specifically, they form a sentiment levels index and a sentiment changes index as follows: the levels index is simply the first principal component of the six (standardized) sentiment proxies and the changes index is the first principal component of the changes in the six (standardized) sentiment proxies.

52 Empirical Studies Their empirical results suggest that when investor sentiment is low, subsequent returns are relatively high on small stocks, very young stocks, high volatility stocks, unprofitable stocks, nondividend- paying stocks, extreme-growth stocks and distressed stocks, suggesting that these categories were relatively underpriced ex ante. When sentiment is high, on the other hand, the patterns largely reverse, suggesting that the same categories were relatively overpriced ex ante. Baker and Wurgler (2007) also show that stocks that are difficult to arbitrage or to value are most affected by their sentiment index.

53 Empirical Studies Baker et al. (2009) construct similar investor sentiment indexes for six major markets and decompose them into one global and six local indexes and find that both indexes are contrarian predictors of the time series of returns; when sentiment is high, future returns are low on various categories of difficult to arbitrage and difficult to value stocks. Yu and Yuan (2011) use the investor sentiment index proposed by Baker and Wurgler (2006) in order to identify high- and low-sentiment periods and then analyse the mean-variance trade-off within both regimes. The authors point out that there is a significant role for investor sentiment in the meanvariance relation. More specifically they find that the stock market s expected excess return is positively related (unrelated) to the market s conditional variance in lowsentiment periods (high-sentiment periods).

54 Empirical Studies Ho and Hung (2009) use survey sentiment measures and a composite index as proxies for investor sentiment and investigate whether incorporating sentiment as conditioning information in asset-pricing models helps explain the impact of various phenomena (size, value, liquidity, momentum) on risk-adjusted returns of individual stocks. They find that the conditional models often capture the value, liquidity and momentum effects.

55 Empirical Studies Chung, Hung, YehWe (2012, Journal of Empirical Finance) examine the asymmetry in the predictive power of investor sentiment in the crosssection of stock returns across economic expansion and recession states. They test the implication of behavioral theories and evidence that the return predictability of sentiment should be most pronounced in an expansion state when investors' optimism increases. They segregate economic states according to the NBER business cycles and further implement a multivariate Markov switching model to capture the unobservable dynamics of the changes in the economic regime. The evidence suggests that only in the expansion state does sentiment perform both in-sample and out-of-sample predictive power for the returns of portfolio formed on size, book-tomarket equity ratio, dividend yield, earnings-to-price ratio, age, return volatility, asset tangibility, growth opportunities, and 11 widely documented anomalies. In a recession state, however, the predictive power of sentiment is generally insignificant.

56 Empirical Studies Chung, Hung, YehWe (2012) also employ the monthly orthogonalized sentiment index of Baker and Wurgler (2006) as a proxy for investor sentiment to predict monthly returns They consider a wide range of firm characteristics including size, book-tomarket ratio, dividend yield, earnings-to-price ratio, age, return volatility, R&D expense-to-assets ratio, fixed assets, sales growth, and external finance-to-assets. Their hypothesis is based on the arguments that prior studies have shown that overpricing occurs in good times and underpricing appears in bad times. For example, Daniel et al. (1998) show that a string of good (bad) news related to the economy or firms leads to overpricing (underpricing). Gervais and Odean (2001) argue that agents attribute success heavily to superior ability rather than luck. Since most investors are long in stocks, in times when the market gains, the aggregate overconfidence becomes higher, leading to more aggressive trading.

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59 Empirical Studies Białkowski, Etebari, & Wisniewski, (2012) (Fast profits: Investor sentiment and stock returns during Ramadan; Journal of Banking & Finance) investigate stock returns during Ramadan (observed by more than 1.5 billion Muslims) for 14 predominantly Muslim countries over the years The results show that stock returns during Ramadan are significantly higher and less volatile than during the rest of the year. No discernible declines in market liquidity are recorded. They find these results consistent with a notion that Ramadan positively affects investor psychology, as it promotes feelings of solidarity and social identity among Muslims world-wide, leading to optimistic beliefs that extend to investment decisions.

60 Empirical Studies Białkowski, Etebari, & Wisniewski, (2012) motivation: Loewenstein et al. (2001) riskas-feelings theory posits that people s feelings and emotions often influence their decisions, especially when such decisions involve risk and uncertainty. According to this theory both emotional reactions and cognitive evaluations guide reasoning, but when they diverge, emotional reactions often dominate behavior and influence the eventual decision (Simon, 1967; Loewenstein et al., 2001). In line with the findings that people in good moods tend to be more optimistic in their judgments than those in bad moods (Wright and Bower, 1992), these studies demonstrate that market prices can be influenced by changes in investors emotional state even when the underlying events are economically neutral from a direct cost-benefit perspective.

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67 Empirical Studies Edelen, Marcus, Tehranian (2010) measure the relative sentiment of retail versus institutional investors by comparing their respective portfolio allocations to equity versus cash and fixed-income securities. Relative sentiment is uncorrelated with indicators of absolute investor sentiment and appears to have considerable value as a (contrarian) market timing tool at a quarterly frequency: High levels of relative retail sentiment are associated with significantly lower future excess equity returns, and the change in relative sentiment is strongly positively related to concurrent market returns. These results suggest that fluctuations in retail sentiment are a primary driver of equity valuations for reasons unrelated to fundamentals. Rather than employing proxies, this paper focuses on the essential meaning of sentiment: a time-varying propensity to invest in risky assets unrelated to fundamentals. Thus, they assess sentiment directly using observed allocations to (i.e., portfolio proportions held in) risky assets.

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74 Empirical Studies Using US stock portfolios that are formed on book-to-market equity (B/M), long term reversals, momentum, and size, a long sample period ( ), and the comprehensive sentiment index of Baker and Wurgler (2006) this article shows that contemporaneous returns of extreme portfolios are significantly related to monthly sentiment changes and tend to be higher during periods of negative sentiment. Stock returns, however, seem to Granger-cause sentiment changes and are more important in predicting sentiment changes than vice versa. In addition, conditional return volatility is significantly affected by lagged volatility rather than sentiment changes.

75 Empirical Studies Spyrou (2012) employs portfolios compiled from all NYSE, AMEX and NASDAQ stocks which are formed on the four most commonly reported inconsistencies of traditional finance theory: B/M, Momentum, Long Term (LT) Reversals and Market Capitalization. The High- Minus-Low (HML) and Small-Minus-Big (SMB) factors are also employed. Employs Baker and Wurgler s (2006) comprehensive sentiment index as a proxy for investor sentiment, which is based on the common variation in six underlying proxies for sentiment. Previous studies employ a number of different proxies for investor sentiment such as survey data on consumer/investor sentiment, derivative market data such as the volatility index and the put-call ratio, discounts and flows of closedend/ mutual funds, etc.

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78 The results from Table 5 suggest that we cannot reject the hypothesis that Sentiment Index Changes does not Granger Cause Portfolio Returns based on the p-values, for all 12 portfolios. On the other hand, the hypothesis that Portfolio Returns does not Granger Cause Sentiment Index Changes is rejected for a number of portfolios at various levels of significance.

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85 Suggested References Baker, M., Wurgler, J. (2006) Investor Sentiment and the Cross-Section of Stock Returns, Journal of Finance, 61, Baker, M. Stein, J. (2004) Market liquidity as a sentiment indicator, Journal of Financial Markets, 7, Baker, M., Wurgler, J. (2007) Investor Sentiment in the Stock Market, Journal of Economic Perspectives, 21, Baker, M., Wurgler, J., Yuan, Y., (2009) Global, local, and contagious investor sentiment, Stern School of Business, Finance Working Papers, available at: Barberis, N., Shleifer, A., and Vishny. R. (1998) A model of investor sentiment, Journal of Financial Economics, 49, Brown, G., Cliff, M. (2004) Investor sentiment and the near-term stock market Journal of Empirical Finance, 11, Brown, S., Goetzmann, W., Hiraki, T., Shiraishi, N., Watanabe, M. (2005) Investor sentiment in Japanese and U.S. daily mutual fund flows, New York University working paper.

86 Suggested References Daniel, K., Hirshleifer, D., and Subrahmanyam, A. (1998) Investor psychology and investor security market under- and overreactions, Journal of Finance, 53, DeBondt, W., Thaler, R. (1985) Does the stock market overreact?, Journal of Finance, 40, Dennis, P., Mayhew, S. (2002) Risk-Neutral Skewness: Evidence from Stock Options,Journal of Financial and Quantitative Analysis, 37, Fama, E., French, K. (1992) The cross-section of expected stock returns, Journal of Finance, 47, Fama, E., French, K. (1995) Size and Book-to-Market Factors in Earnings and Returns, The Journal of Finance, 50, Fama, E., French, K. (1996) Multifactor Explanations of Asset Pricing Anomalies, The Journal of Finance, 51, Fisher, K., Statman, M. (2003) Consumer confidence and stock returns, The Journal of Portfolio Management, 30, Ho, C., Hung, C-H. (2009) Investor sentiment as conditioning information in asset pricing, Journal of Banking & Finance, 33, Hong, H., Stein, J. (1999) A unified theory of underreaction, momentum trading, and overreaction in asset markets, Journal of Finance, 54,

87 Suggested References Edmans, A., D Garcia, Ø Norli (2007) Sports sentiment and stock returns, The Journal of Finance, 62(4), Kumar, A., Lee, C. (2006) Retail Investor Sentiment and Return Comovements, The Journal of Finance, 61, Kurov, A. (2008) Investor Sentiment, Trading Behavior and Informational Efficiency in Index Futures Markets, The Financial Review, 43, Lakonishok, J., Shleifer, A., and Vishny, R.W. (1994) Contrarian Investment, extrapolation and risk, Journal of Finance, 49, Lee, W., Jiang, C., and Indro, D. (2002) Stock market volatility, excess returns, and the role of investor sentiment, Journal of Banking & Finance, 26, Lemmon, M., Portniaguina, E. (2006) Consumer Confidence and Asset Prices: Some Empirical Evidence, Review of Financial Studies, 19, Neal, R., Wheatley, S. (1998) Do Measures of Investor Sentiment Predict Returns? Journal of Financial and Quantitative Analysis, 33, Palomino, F.A.; Renneboog, Luc; Zhang, C. (2008) Information Salience, Investor Sentiment, and Stock Returns, CentER Discussion Paper; Vol Robert, N., Wheatley, S. (1998) Do Measures of Investor Sentiment Predict Returns?, Journal of Financial & Quantitative Analysis, 33,

88 Suggested References Schmeling, M. (2009) Investor sentiment and stock returns: Some international evidence, Journal of Empirical Finance, 16, Simon, D., Wiggins, R. (2001) S&P futures returns and contrary sentiment indicators, Journal of Futures Markets, 21, Tetlock, P. (2007) Giving Content to Investor Sentiment: The Role of Media in the Stock Market, The Journal of Finance, 62, Yu, J., Yuan, Y. (2010) Investor Sentiment and the Mean-Variance Relation, Journal of Financial Economics, Forthcoming Wang, Y-H., Keswani, A., and Taylor, S. (2006) The relationships between sentiment, returns and volatility, International Journal of Forecasting, 22, Watanabe, M., Brown, S., Goetzmann, W., Hiraki., T., and Shiraishi, N. (2002) "Investor Sentiment in Japanese and U.S. Daily Mutual Fund Flows, Yale School of Management Working Papers 274, Yale School of Management. Zhang, C. (2008) Defining, Modelling, and Measuring Investor Sentiment, University of California, Berkeley, Department of Economics, Thesis, available at