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Investor Sentiment Aligned: A Powerful Predictor of Stock Returns

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Investor Sentiment Aligned: A Powerful Predictor of Stock Returns. Dashan Huang Fuwei Jiang Jun Tu Guofu Zhou Singapore Management University (Huang, Jiang, Tu) Washington University in St. Louis (Zhou). For the Q-Group Presentation on April 7th, 2017 at Charleston, SC. - PowerPoint PPT Presentation
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Investor Sentiment Aligned: A Powerful Predictor of Stock Returns For the Q-Group Presentation on April 7th, 2017 at Charleston, SC. Dashan Huang Fuwei Jiang Jun Tu Guofu Zhou Singapore Management University (Huang, Jiang, Tu) Washington University in St. Louis (Zhou)
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Page 1: Investor Sentiment Aligned:  A Powerful Predictor of Stock Returns

Investor Sentiment Aligned: A Powerful Predictor of Stock Returns

For the Q-Group Presentation

on April 7th, 2017 at Charleston, SC.

Dashan Huang Fuwei Jiang Jun Tu Guofu Zhou

Singapore Management University (Huang, Jiang, Tu)

Washington University in St. Louis (Zhou)

Page 2: Investor Sentiment Aligned:  A Powerful Predictor of Stock Returns

Sentiment and Stock Returns

Sentiment: People feel excessively optimistic or pessimistic

about a situation not justified by the facts at hand Long history in finance: Keynes (1936)

Theoretically, sentiment can drive asset prices away from their fundamental values due to limits of arbitrage

e.g., short-sell constraint, margin constraint, noise trader risk

Empirically, sentiment strongly predicts stocks that are speculative, hard to arbitrage, or in the short legs of long-short strategies e.g., Baker and Wurgler (2006, 2007), Baker, Wurgler, and Yuan (2012,

JFE), Stambaugh, Yu, and Yuan (2012, JFE)

Page 3: Investor Sentiment Aligned:  A Powerful Predictor of Stock Returns

Why Sentiment Matter?: Some Macro Points

Money is scarce in recessions/downturns: In bad times, investors expect much higher

return to put money into stocks. Shocks in supply/liquidity:

Loss of returns on the market Loss of jobs

Risk appetite change: Investors are unwilling to take risks in good times

Borrowing constraints: ever more stringent

Page 4: Investor Sentiment Aligned:  A Powerful Predictor of Stock Returns

Measurement of Sentiment Sentiment is not directly observable Baker and Wurgler (2006, JF) construct a sentiment index as

the first principal component (PC1) of the 6 sentiment proxies: Closed-end fund discount rate, CEFD Share turnover, TURN Number of IPOs, NIPO First-day returns of IPOs, RIPO Dividend premium, PDND Equity share in new issues, S

explains well the cross-sectional stock returns influential: > 1111 google citations

Bottom Line: the BW index cannot explain the time variation of the aggregate stock market return.

Page 5: Investor Sentiment Aligned:  A Powerful Predictor of Stock Returns

What Do We Do? This paper seeks to answer

Does sentiment forecast the aggregate stock market if it is aligned in the right way?

What is the economic channel/driving force? We find

sentiment strongly forecasts the aggregate stock market; it outperforms greatly marcoeconomic predictors, at least in the

month-by-month horizon; The value of predictability is of economic/practical significance; The forecasting power of sentiment comes from the investor's

underreaction to cash flow information Theoretical basis:

Econometrically, a method eliminating a common noise of the proxies Economically, market trends and sentiment are related (e.g., De Long

et al. (1990, JPE), and Zhou and Zhu (2014, working paper)

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Conclusions and Future Works This paper finds

sentiment strongly forecasts the aggregate stock market if it is aligned properly;

it outperforms greatly marcoeconomic predictors, at least in the month-by-month horizon;

The value of predictability is of economic/practical significance; The forecasting power of sentiment comes from the investor's

underreaction to cash flow information Future Research:

More sentiment proxies: Consumer sentiment VIX Returns on Art and Other Collectibles

Combined with technical analysis: More theory in addition to Zhou and Zhu (2014), and more empirical work

along lines of Neely, et al (2014) and Han and Zhou (2013).


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