Wisdom of Crowds (Chen)

Question 1

What investigates this paper “Wisdom of Crowds: the value of stock opinions transmitted through social media”?

Answer 1

It investigated the extent to which investor opinions transmitted through social media predict future stock returns and earning surprises.

Question 2

What financial analysis professionals are worried of?

Answer 2

That the institution of financial analysis risks becoming de-professionalized. With the use of new tools and info in terms of DIY in financial analysis.

Question 3

What impact social media has on consumers and expert advice?

Answer 3

The creation and consumption of user-generated content has resulted in:
consumers turning to fellow customers when choosing among products instead of relying on expert advice.

Question 4

How much of US investors rely on peer opinions?

Answer 4

25% rely on peer opinions transmitted via social media.

Question 5

What is “Earnings surprise” that authors introduce here?

Answer 5

Earnings surpise is the difference between reported EPS and the average of financial analysts EPS forecasts updated within 30 days prior to earnings announcement.

Question 6

What is the 1 RQ on peer opinions?

Answer 6

Do peer opinions actually impart value-relevant news? Or do they merely constitute “random chatter”?

Question 7

What is 2 RQ on user spread false “information”?

Answer 7

Are some users attempting to intentionally spread false “information” and mislead fellow market participants?

Question 8

What is the goal of this study reagrding performance of advisors and peer advice?

Answer 8

The goal of this study is to assess the performance of investors-turned-advisors and to test whether investors can turn to their peers for genuine, useful investment advice.

Question 9

How do negative words in SA articles and commentaries predict returns?

Answer 9

Negative words in both negatively predict stock returns over the ensuing three months.

Question 10

How are future abnormal returns impacted by negative words in SA articles/comments?

Answer 10

Future abnormal returns are 0.332%/0.194% lower when the fraction of negative words in the SA articles/comments is 1% higher.

Question 11

Do SA articles and comments predict returns over different horizons?

Answer 11

Yes, the coefficient estimates are reliably different from zero and tend to increase with the length of the holding period.

Question 12

When predictability from SA comments is particularly evident?

Answer 12

When the number of comments over which the fraction of negative words is computed is relatively high.

Question 13

What is interpretation of “Predictability channel”?

Answer 13

SA articles and comments contain value-relevant information, not yet factored in the price of stock. As investors learn of it through SA, the prices gradually adjust.

Question 14

What is the implication of Predictability Channel if it is true?

Answer 14

SA views indeed predict future stock market performance; social media outlets are a useful source of value-relevant advice.

Question 15

What is the interpretation of “Clout channel”?

Answer 15

SA views reflect false or spurious info, yet still cause investors to trade in direction of articles, and move prices accordingly. (Exploiting naive investors)

Question 16

How likely is it to have “Clout channel” implications?

Answer 16

Less likely due to lacks of return reversal (market correction); SA followers insufficient capital to cause documented market movements.

Question 17

How negative words predict earning surprises?

Answer 17

Fraction of negatove words strongly predict subsequent scaled earnings surprises.

Question 18

What does earnings-surprises predictability suggest about opinions?

Answer 18

The opinions expressed in SA articles and comments indeed provide value-relevant information (beyond that provided by financial analysts).

Question 19

What are 4 incentives of truly informed users to share their insights?

Answer 19

1. Attention and recognition: even Forbes, Morningstar refer to the users; many users strive to become online celebrities.
2. Monetary compensation: earns 10$ per 1000-page views and potentially more depending of article quality
3. Immediate and public feedback: users can correct bad articles, on assumption that crowd is educated, increases the informativeness of social media.
4. Convergence to fundamental value: users have some price impact they can expedite the convergence of market prices to what authors perceive to be their fair fundamental value.

Question 20

Do folowers disgree more when author is inconcistent?

Answer 20

Yes, for inconsistent authors, the comments has more disagreement, hence, wisdom of crowds.

Question 21

What do the findings in the study point to?

Answer 21

It points to usefulness and value relevance of peer-based advice in their investment domain.

Question 22

What is the primary reason that social media platforms are able to produce value-relevant content?

Answer 22

They enable direct and immediate interaction among users, these interactions combined with the seeming intelligence of the “crowd”.