Presentation is loading. Please wait.

Presentation is loading. Please wait.

Te Kunenga ki Pūrehuroa Creating leaders Transforming business Investor Sentiment Risk Factor and Asset Pricing Anomalies Chienwei Ho Massey University.

Similar presentations


Presentation on theme: "Te Kunenga ki Pūrehuroa Creating leaders Transforming business Investor Sentiment Risk Factor and Asset Pricing Anomalies Chienwei Ho Massey University."— Presentation transcript:

1 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Investor Sentiment Risk Factor and Asset Pricing Anomalies Chienwei Ho Massey University Chi-Hsiou Hung Durham University

2 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Motivations Standard CAPM (Sharpe, 1964; Lintner, 1965)‏ – Expected return is associated with market risk – Unable to explain pricing anomalies Size effect (Banz, 1981)‏ Value effect (Chan, Hamao, and Lakonishok, 1991)‏ Momentum effect (Jegadeesh and Titman, 1993)‏ Investor sentiment affects stock returns (Black, 1986; De Long, Shleifer, Summers and Waldmann, 1990; Baker and Wurgler, 2006; Yu and Yuan, 2011). Investor sentiment as a risk factor. Conditional/Dynamic models outperform unconditional/static models (Harvey, 1989; Gibbons and Ferson, 1985; Ferson, Kandel, and Stambaugh, 1987)‏. 2

3 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Research Questions Is investor sentiment a risk factor? (i.e., Is investor sentiment priced?) Does investor sentiment, as a risk factor, help to explain pricing anomalies: size, value, liquidity, and momentum effects? Asset pricing models: CAPM, FF, FFP, FFW, FFPW Time-varying: default spread, (Size+B/M) 3

4 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Contributions Constructing a sentiment risk factor, SMN (sensitive minus non-sensitive). Showing SMN is a priced factor. Stocks with certain firm characteristics react differently to investor sentiment. SMN alone can explain the size premium. Sentiment-augmented asset pricing models can capture the pricing anomalies: size, value, momentum effects. 4

5 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Literature Sentiment and stock returns A negative relationship b/t the consumer confidence level in one month and returns in the following month (Fisher and Statman, 2002). High levels of sentiment result in lower returns over the next 2 to 3 years (Brown and Cliff, 2005). Changes in consumer sentiment are positively related to excess stock market returns (Charoenrook, 2005). Investor sentiment has larger effects on stocks whose valuations are highly subjective and difficult to arbitrage (Baker and Wurgler, 2006). 5

6 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Literature (Cont’d) Sentiment and firm characteristics Closed-end fund discount and net mutual fund redemptions predict the size premium (Neal and Wheatley, 1998). Individual investors who are more prone to sentiment than institutional investors tend to have disproportionally large holdings on small stocks (Lee, Shleifer, and Thaler, 1991; Nagel (2005). Difficult-to-arbitrage and hard-to-value stocks (small, young, non- dividend-paying, etc.) are more responsive to investor sentiment (Baker and Wurgler, 2006; Lee, Shleifer, and Thaler; Lemmon and Portniaguina, 2006) 6

7 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Construction of Sentiment Factor – SMN Using 25-month rolling windows to obtain sentiment beta for each stock,, (Brown and Cliff, 2005 find high sentiment results in lower market returns over the next 2 to 3 years). In each month, break stocks into 5 groups based on the absolute value of. Monthly SMN = Sensitive Return – Non-sensitive Return 7

8 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Conditional Sentiment-augmented Models Conditioning variables Macro variables: default spread Firm-specific characteristics: B/M and size 8

9 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Empirical Framework Indicator of explanatory power of model: adj-R2 (lower ==> better)‏ 9 Ho: Ct = 0 ? adjusted return (second-pass regression)‏ conditional asset pricing model (first-pass regression)‏ pricing anomalies

10 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Asset Pricing Models 10 traditional risk factors

11 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Time-Varying Beta 11

12 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Beta Specifications 12 Unconditional Model Conditional Model Specification A: function of (SIZE + B/M) Specification B: function of def Specification C: function of (SIZE + B/M)def

13 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Two-Pass Framework (using CAPM as an Example)‏ 13 Risk Factors ( for CAPM here )‏ Anomalies Adjusted Return

14 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Investor Sentiment Indices Baker and Wurgler, 2006 ( ∆BW )‏ ∆BW: A composite sentiment index based on the first principal component of six raw sentiment proxies: NYSE turnover, closed-end fund discount, the number of IPOs, the first-day return on IPOs, the equity share in new issues and the dividend premium. ∆BWWort: a cleaner sentiment measure that removes business cycle variations from ∆BW. Investors’ Intelligence Index (II)‏ Opinions of 150 newsletters: bullish, bearish, neutral. Proportion of bullish advices. Directly reflects (professional) investors’ opinions on stock markets. 14

15 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Trading Data and Variables for Anomalies 8,526 NYSE/AMEX/NASDAQ common stocks ( ) from CRSP/COMPUSTAT meeting the specified criteria: The returns in the current month, t, and over the past 60 months must be available. Stock prices and shares outstanding have to be available in order to calculate firm size, and trading volume in month t – 2 must be available to calculate the turnover. Sufficient data has to be available from the COMPUSTAT dataset to calculate the book-to-market ratio as of December of the previous year. Only stocks with positive book-to-market ratios are included in our sample. Book-to-market ratio values greater than the fractile or less than the fractile are set equal to the and fractile values, respectively. 15

16 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 1: Summary Statistics and Cross-Sectional Regressions (8,526 firms: )‏ 16 (size effect) (value effect) (momentum effect)

17 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Figure 1: Stock Returns by Firm Characteristics and Sentiment Beta

18 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Is the Investor Sentiment Factor (SMN) Priced? 18 Ho: = 0

19 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 2: Cross-Sectional Regressions of Excess Returns on SMN Beta 19 * indicates significant at the level of 5%; ** indicates significant at the level of 1%.

20 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 3: Fama-MacBeth Regression Estimate for Unconditional Models 20

21 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 4: Fama-MacBeth Regression Estimate with SMN (conditional models) 21

22 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 5: Fama-MacBeth Regression Estimate with CAPM + SMN (conditional) 22

23 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 6: Fama-MacBeth Regression Estimate with FF + SMN (conditional) 23

24 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 7: Fama-MacBeth Regression Estimate with FF + PS + SMN (conditional) 24

25 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 8: Fama-MacBeth Regression Estimate with FF + momentum + SMN (conditional) 25

26 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Table 9: Fama-MacBeth Regression Estimate with FF + PS + momentum + SMN (conditional) 26

27 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Summary of Findings Stocks with certain firm characteristics are more vulnerable to investor sentiment. Returns on small firms are more sensitive to changes in investor sentiment than large firms. Value stocks (high B/M) have larger sentiment beta than growth stocks. A positive relationship between turnover and sentiment beta. Past winners tend to be more responsive to changes in investor sentiment than past losers. Stocks with higher sentiment beta earn higher returns. 27

28 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Summary of Findings Investor sentiment helps to explain the cross-section of stock returns and pricing anomalies. SMN is a risk factor, i.e., investor sentiment factor is priced. SMN can always explain the size effect without requiring conditional pricing model. Conditional versions of the sentiment-augmented FF-based models often capture the size and value effects. Momentum effect sharply reduces when the factor loadings are conditional on the default spread in the sentiment-augmented models that contain the momentum factor. Hence, investor sentiment is also associated with the momentum profits. 28

29 Te Kunenga ki Pūrehuroa Creating leaders Transforming business Q & A 29


Download ppt "Te Kunenga ki Pūrehuroa Creating leaders Transforming business Investor Sentiment Risk Factor and Asset Pricing Anomalies Chienwei Ho Massey University."

Similar presentations


Ads by Google