ASSET PRICING

Question 1

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

Why do consumers turn to fellow customers when choosing among products instead of relying on expert advice?

Answer 1

Because of:
1. The emergence of social media platforms;

2. The increase in creation, popularity & consumption of user-generated content.

Question 2

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What are the 2 Research Questions of this paper?

Answer 2

1. Do peer opinions include value-relevant news or do they merely constitute “random chatter” (i.e. the task should be left to professional analysts)?
2. Are some users attempting to intentionally spread false “information” and mislead fellow market participants?

Question 3

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What are the goals of this study?

Answer 3

1. To assess the performance of investors-turned-advisors

2. To test whether investors can turn to their peers for genuine, useful investment advice.

Question 4

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What is the main source of the data in this study, and how is it measured?

Answer 4

“Seeking Alpha (SA)” - one of the biggest investment-related social media websites in the US.

The data is measured in the frequency of negative words used in an article.

Question 5

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What are the two channels in SA for investors to voice their opinion?

Answer 5

1. Through opinion articles which are reviewed by a panel and are subject to editorial changes;
2. Through commentaries written in response to the opinion articles.

Question 6

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What are the key variables used to make a regression in this study?

Answer 6

X1 & X2:
1. NegSAi,t – an average fraction of NEGATIVE WORDS across all single-ticker ARTICLES published on SA about company i on day t

2. NegSA-Commenti,t – an average fraction of NEGATIVE WORDS across all SA COMMENTS posted in an article about company i on day t

Y:
3. ARet - abnormal returns - “the difference between RAW RETURNS minus RETURNS on a value-weighted portfolio OF FIRMS WITH SIMILAR SIZE, book-to-market ratio, and past returns”.

Question 7

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What is the main finding of this study?

Answer 7

“The fraction of negative words in SA articles and the fraction of negative words in SA comments both negatively predict stock returns over the ensuing three months”.

As per our dear Kostja:
If negative words in articles/comments are up by 1%,
the future abnormal returns are lower by 0.332%/0.194%.

Question 8

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What are the possible reasons (channels) behind the main finding of the study?

Answer 8

Possible reasons behind findings:

1. Predictability Channel: SA articles & commentaries contain pieces of value-relevant information which are not fully factored into the stock price as of the article publication date. As investors learn from the SA view, prices gradually adjust.
   - -If this reason is true:
   - —SA views indeed predict future stock market performance;
   - —Social media outlets are a useful source of value-relevant advice
2. Clout Channel: SA views reflect false information and cause investors to trade in the direction of the underlying articles and comments and move prices accordingly” (i.e. exploiting naïve investors)
   - -This reason is less likely to be true due to:
   - —SA followers’ insufficient capital to cause real & sufficient market movements.

Question 9

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What is an Earnings Surprise?

Answer 9

The difference between:
–the REPORTED earnings-per-share (EPS) AND;

–the average of financial ANALYSTS’ EPS FORECASTS issued within 30 days prior to the earnings announcement.

Question 10

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

How do the authors prove if the information in SA is value-relevant (Predictability Channel) or false (Clout Channel)?

Answer 10

They regress the number of negative words in articles/comments (the same X1 & X2 as before) on subsequent earnings surprises (new Y).

If they find that negative words predict earnings surprises: the information in SA is value-relevant and is not fully factored into the stock price as of the article publication date.

If they find that negative words do NOT predict earnings surprises: the information in SA is false as users cannot affect the company’s earnings (no relationship between X1, X2 & Y).

Question 11

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

Do the authors find that the SA articles & commentaries contain pieces of value-relevant or false information?

Answer 11

They find that:

“The fraction of negative words in SA articles & comments strongly predict earnings surprises,” which suggests that the opinions expressed in SA articles & comments.
indeed provide value-relevant information.

Question 12

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

Why should a SA user share their insights of value-relevant information publicly?

Answer 12

1. Popularity: (users want attention & recognition they receive from posting opinions that subsequently are
   confirmed by the stock market. Sometimes, SA articles

are referred to and discussed in Forbes, WSJ, etc. - many users strive to become online celebrities)

2. Monetary Compensation: (each SA contributor earns $10 per 1,000-page views & potentially more depending on the article quality)
   - -is TESTED on this paper
3. Immediate Feedback: (users correct bad
   articles, which, on the assumption that the crowd is educated, increases the informativeness of social media)
   –is TESTED on this paper
4. Convergence to Fundamental Value: (if SA users have some price impact they can expect the direction of market prices to go to what authors perceive to be the
   fair fundamental value)

Question 13

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

The authors test whether Monetary Compensation and Immediate Feedback drives users to post more value-relevant information on the paper. What do they conclude?

Answer 13

1. Monetary Compensation Findings
   - -“The number of page views AND the number of times an article is read-to-end are increasing with the author’s historical level of consistency.“
   - -SA followers can “differentiate between authors that offer historically good VS bad advice;
   - -SA followers give more “popularity” to the good than the bad advice given.
2. Immediate Feedback:
   - -The authors test “to what degree SA commentaries are of a different tone than the underlying SA article”
   - -They find that “followers disagree with authors more when the authors’ articles have been inconsistent.”
   - -They find that if “the authors’ articles are inconsistent, it is the tone of COMMENTS that more reliably predicts subsequent stock market performance.”

Question 14

“Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media” (Chen, H., De, P., Hu, Y. J., Huang, B., (2014))

What are the key takeaways from the article?

Answer 14

• -Peer-based advice is Useful & Value-Relevant
• -Social media outlets enable direct & immediate interaction among users which, combined with intelligence of a “crowd,” are one of the primary reasons social media platforms are able to produce value-relevant content.

Question 15

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

Why should we have tougher criteria today for discovering a factor that supposedly explains expected returns?

Answer 15

Context:
There have been hundreds of papers trying to explain the cross-section (factors) of expected returns since one of the first CAPM tests forty years ago. Given this extensive data mining, the usual t-statistics cut-off is insufficient for establishing significance. Moreover, most of the sample factors have been proposed over the last ten years.

Why should we have tougher criteria?

–The rate of discovering a true factor has likely decreased.

–There is a limited amount of data

–The cost of data mining (examining databases to gain new information) has dramatically decreased (aka it is easy to get data)

Question 16

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

What are Type I & Type II Errors in Statistics?

Answer 16

Type I and Type II errors
• Type I error:

• -a false positive;
• -the error of rejecting a null hypothesis when it is actually true;
• -plainly speaking, we are observing a difference when in truth there is none.

• Type II error:
- a false negative;
–the error of not rejecting a null hypothesis when the alternative hypothesis is true.
–plainly speaking, it occurs when we are failing to
observe a difference when in truth there is one.

Question 17

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

What is Multiple Testing in Statistics?

Answer 17

Multiple Testing:
–the potential increase in Type I error that occurs

when statistical tests are used repeatedly.

What does that mean?

Suppose we consider the efficacy of a drug in terms of the reduction of any one of a number of disease symptoms. As more (=multiple) symptoms are considered on the same sample, it becomes increasingly likely that the drug will appear to be an improvement (=more false positives) over existing drugs in terms of at least one symptom.

Question 18

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

What is a Bonferroni Correction?

Answer 18

Bonferroni Correction:

Shows how much the size of the allowable error (usually 0.05/0.10) should be reduced to reject null hypothesis (depending on the number of tests done).

Question 19

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

What do the researchers do in their experiment?

Answer 19

• They use Multiple Testing Framework for the 316 supposedly “discovered” factors to determine whether they are still applicable if put under a more “strict” cut-off.
• They use Bonferroni, Holm & BHY corrections to determine what the “cut-off” for rejecting null hypothesis should have been for the factors.
• They compute adjusted t-statistics using the three adjustments and plot the sample factors against the new significance levels.

Question 20

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

What are the results of their experiment?

Answer 20

“A much higher t-statistic threshold is needed when multiple testing is taken into account.”

“A newly discovered factor today should have a t-statistic that exceeds 3.0 (a p-value of 0.27%). (a usual t-statistic of 2.0 has a p-value of 5%)”

Of the 296 published significant factors, over 100 would be considered false discoveries under Holm, BHY & Bonferroni (Bonferroni claimed the highest - 158 factors as false discoveries!)

Question 21

“…and the Cross-Section of Expected Returns”
(Harvey, C. R., Liu, Y., Zhu, H. (2016))

Which of the factors survive all three adjustments and new “cut-offs”?

Answer 21

1. Book-to-Market ratio
2. Momentum factor
3. Durable Consumption Goods (goods that do not quickly wear out; goods that yield utility over time)
4. Short-Run Volatility
5. Market Beta

…are considered good factors when measuring expected returns.

Question 22

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

What are the two pillars of asset pricing?

Answer 22

When we try to determine whether the price of an asset is correct, there are two possible sides on how to look at it:

1. Efficient Market Hypothesis
2. The existing models of Asset Pricing
   *
   The models of Asset Pricing are usually derived assuming Market Efficiency; AND you can prove Market Efficiency by using a model of Asset Pricing (a chain that should work both ways).

Question 23

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

What is the Efficient Market Hypothesis?

Answer 23

EMH claims that asset prices reflect ALL available information (past and present, public and private).

Question 24

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

What are the 3 possible forms of Market Efficiency?

Answer 24

3 forms of Market Efficiency:
1.Weak Market Efficiency:

• -prices reflect only past information
• -prices reflect only publicly available past information

2. Semi-Strong:
   - -prices reflect past AND present information
   - -prices reflect only publicly-available information
3. Strong:
   - -prices reflect past AND present information
   - -prices reflect public AND private information

Question 25

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

What is the Joint Hypothesis problem?

Answer 25

Introduction:

When you want to test for Market Efficiency, you have a goal of “determining whether the expected return of a certain asset (which is derived from a certain asset pricing model) is equal to the actual return of the asset.”

Joint Hypothesis problem:

If the expected return is not equal to the actual return (aka Market Efficiency rejected), it can mean that either:

1. The Market is indeed Inefficient OR;
2. The chosen Asset Pricing Model is bad.

Question 26

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

What are the ways how to test Market Efficiency?

Answer 26

1. With Event Studies;
2. With Predictive Regressions;
3. With Time-Varying Expected Stock Returns;
4. With Bubbles

Question 27

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

How to test Market Efficiency with Event Studies?

Answer 27

Fama has tested Market Efficiency by looking at an adjustment of stock prices to a specific company announcement (=an event, in this case, stock splits).

What is a stock split?

A stock split is an action in which a company divides its existing shares into multiple shares to boost the liquidity of the shares.

• The number of shares increases by a specific multiple (the most common split ratios are 2-for-1 or 3-for-1, which means that the stockholder will have two or three shares for every share held earlier), BUT;
• The price per share after the 3-for-1 stock split will be reduced by dividing the price by 3 (so, the real market value of the company does not change - no. of stocks multiply, but stock prices divide).

Continuing on Fama:

• In efficient markets, stock prices should adjust accurately to new (present) information.
• In his study about an announcement of a stock split, Fama finds that all stock split-related information is incorporated into prices months before the split, confirming market efficiency in short term periods.
• However, he says that in long term, expected returns are larger than the price of the effect of a studied event, thus, JHP becomes relevant again.

Question 28

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

How to test Market Efficiency with Predictive Regressions?

Answer 28

Irving Fisher’s Market Efficiency Hypothesis claims: interest rates should contain expected real return plus the best possible forecast of the inflation rate.

And Fama finds out:

1) Bond and Real Estate prices incorporate the best possible forecast of inflation (nominal interest rate=real return+forecast of inflation).
Therefore, for bonds & real estate:
–we accept market efficiency proposition that bond and real estate prices incorporate the best possible forecasts of inflation;
–we accept a model of market equilibrium in which expected real returns vary independently of expected inflation.

2)Stock prices do NOT incorporate the best possible forecast of inflation (findings are the pure opposite - when expected stock returns are higher, expected inflation is low: nominal return»>real return+forecast of inflation)
A question appears - why did this equation not work for stocks? Two answers appear (JHP):
–either is it due to poor inflation forecasts (market inefficiency) OR;
–we chose a bad model of stock market equilibrium/asset
pricing model)

Question 29

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

Can a Market be Efficient with Time-Varying
Expected Stock Returns?

Answer 29

Earlier: Efficient Market assumed expected stock returns to be constant over time.

Now: Both Risk & My Willingness to bear risk are not assumed to be constant over time. But can a Market be Efficient with Time-Varying Expected Stock Returns?

Fama thinks: YES

• -predictable (!!!) volatility in expected returns on stocks is rational (aka it is rational and predictable to change risk-willingness over lifetime);
• -therefore, even a market with variation in risk or people’s willingness to bear risk is an efficient market.

Behavioralists think: NO
–volatility in expected returns on stocks is due to investor irrationality (irrational price swings, herd behavior, etc.)

Question 30

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

Can Bubbles be a part of an Efficient Market?

Answer 30

A bubble is defined as: “an irrational strong price increase that implies a predictable strong decline.”

Fama thinks: (maybe) YES

• -he denounces the “predictable strong decline” part of the definition with the argument that “there is no academic evidence that price declines are EVER predictable”.
• -he also denounces the “irrational price increase” part of the definition, saying that no, large swings (price increases, in this case) in prices are not irrational, but are rational responses to large swings in REAL economic activity. And, as per EMH definition (asset prices reflect ALL available information), if there are large price swings/trends in the real economy, efficient stock markets will reflect this available information and it will portray into stock prices.
• -why (maybe) YES? Fama is cautionary against the use of the “bubble” word at all without more careful definition and empirical validation.

Behaviorists think: NO
–“irrational price increase” is a part of human psychological behavior which constitutes that a market with bubbles cannot be efficient.

Question 31

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

What are the types of Asset Pricing Models?

Answer 31

1. Standard Equilibrium models:
   - -work from theoretical assumptions

–e.g. CAPM

2. Empirical models:
   - -work backwards from observed patterns in average returns and try to explain them by proposing factors
   - -e.g. Fama-French 3 or 4-factor model, APT

Question 32

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

Does Fama think that CAPM is a good Asset Pricing model?

Answer 32

Fama thinks: NO
–although the model was needed to lay the foundations of asset pricing theory;

–it has been proven that only β (the only unique variable in the model) is not sufficient to explain expected returns

Question 33

“Two Pillars of Asset Pricing” - (Fama, E. F. (2014))

Does Fama think that the 3-factor model is a good Asset Pricing model?

Answer 33

Fama thinks: YES and NO
–3-factor model adjusts well on the anomalies for:

• —size*;
• —sales growth;
• —various price ratios
• -*(however, here is long-standing controversy about the effect of the size on average returns)
• -BUT the model doesn’t absorb other anomalies.
• -Fama claims that momentum should be added as an explanatory factor (which it later is, in 4-factor model)

Question 34

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

What problem is the paper trying to solve?

Answer 34

Asset owners and portfolio managers want to incorporate ESG factors into their decisions, but there is no theoretical framework on how to do that.

Plus, there is not a common decision on how ESG impacts performance among academics and practitioners.

Thus, this paper tries to determine theoretically and test empirically if ESG improves or hurts performance.

Question 35

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

How did they divide the market participants?

Answer 35

Type-U (ESG-unaware) are unaware of ESG scores and simply seek to maximize return per unit of risk. Chooses tangency portfolio ignoring ESG information.

Type-A( ESG-aware) have the same goal, but they use assets’ ESG scores to update their views on risk/return. Chooses tangency portfolio using ESG information.

Type-M( ESG-motivated) are ready to sacrifice performance for high ESG, but still want maximum Sharpe ratio at each ESG level. Has a portfolio on ESG-efficient frontier.

Question 36

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

What proxies for E, S, G and ESG did they use?

Answer 36

As a measure of E (i.e., how green a company is), we compute each company’s carbon intensity (low carbon intensity = carbon emissions/sales)

As a measure of S, we use the sin stock indicator (non-sin stock = 1, sin stock = 0)

As a measure of G, we compute how (un)aggressive a company is in its accounting choices based on the accruals in the financial statement. Low accruals indicate that a firm is conservative in its accounting of profits.

As a measure of overall ESG, we use the aggregate ESG score produced by MSCI, a leading provider of ESG ratings.

Question 37

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

How do the proxies determine market returns?

Answer 37

E - correlates positively with investor demand and high valuations.

S - negatively predicts future profitability. However, the statistical significance is limited in these tests. This measure of S predicts profits negatively and high S is associated with stronger investor demand.

G - positively predicts future profitability. There is some increase in demand for these stocks, yet stocks with attractive G trade at relatively cheaper Tobin’s q.

Question 38

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

What happens when each type of investor prevails?

Answer 38

When type-U investors prevail and ESG predicts high future profits, high ESG delivers high expected returns (high-ESG stocks are undervalued because type-U ignore useful ESG information)

When type-A prevail, prices of high-ESG stock are bid up, eliminating the premium

When type-M prevail, high-ESG stocks deliver low expected returns (type-M accept lower return for more ESG; high-ESG stocks are overpriced)

Question 39

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

How can ESG impact returns?

Answer 39

1. If ESG correlates with future fundamentals (profitability), then ESG can be used to pick ”better” stocks that will have higher return; this is a positive effect (return premium)
2. If ESG correlates with investor demand, then high-ESG stocks are sought by many investors, which pushes their valuation up and expected return down; this is a negative effect (return discount)

Question 40

“Responsible investing: The ESG-efficient frontier.” (Pedersen, H. Lasse, Shaun Fitzgibbons, and Lukasz Pomorski (2021))

What are the conclusions of the paper?

Answer 40

For E, S, and ESG they find mixed results on correlation with future fundamentals, and strong demand. They find high valuations and low or insignificant returns, in line with the theory.

For G they find both strong correlation with future fundamentals and also strong demand → theory is inconclusive. However, empirics reveal low valuations and high returns.

This means market does not fully incorporate information on G, and G offered “guiltless saintliness” → consider G in your portfolio

Question 41

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

What are the main findings of this paper? [How does the beta affect the CAPM predicted average returns?]

Answer 41

The average realized returns of low beta securities are higher and those of high beta securities lower than the CAPM predicts. In other words, the slope of the empirical security market line (SML) is less steep than implied by the CAPM.

Consequently, managers who use the CAPM for capital budgeting are willing to undertake low beta projects at prices that the market deems too high.

The stock market reaction to low beta investments is less favorable than to high beta investments.

Question 42

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

What data do the authors use in their research and why?

Answer 42

The authors study mergers and acquisitions as these are examples of large-scale investments, and their known announcement dates allow us to observe the stock market reaction.

Question 43

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

What is the determinant of how the stock market reacts to a potential acquisition announcement?

Answer 43

When bidder announces the potential acquisition, stock market reaction is found to be based on target’s asset beta – low beta targets cause smaller bidder’s CAR (realized return - expected return) and the opposite for high beta targets.

Question 44

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

What 3 aspects make the positive relation between the bidder’s CAR and target’s asset beta stronger?

Answer 44

1) Larger growth rate of the target’s expected operating free cash flows on a stand-alone basis.

2) Larger relative size of the bid vis-à-vis the bidder’s market capitalization.

3) Bidder relies more on the CAPM-based valuation of the target (relative to other valuation methods).

◦ Higher growth amplifies the difference between the value implied by the CAPM versus the empirical SML
◦ Misvaluing a target has a bigger effect if the target is large relative to the bidder
◦ Bidders overvalue low- and undervalue high-beta targets relative to the market’s assessment because they use the CAPM. Consequently, there is more over- or underpayment if bidders rely more on the CAPM

Question 45

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

How does the empirical SML slope affect the difference between CAPM based value and market value?

Answer 45

Difference between the CAPM-based value and the market value becomes smaller when the empirical SML becomes steeper.

Question 46

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

What are the main differences between private and public targets?

Answer 46

1) Seller’s outside option when negotiating with the bidder (The owners of a public target thus have a better outside option when bargaining with the bidder - can also sell to the market, not only the bidder. Relation between the target’s beta and the takeover price offered by the bidder is weaker for high beta public targets)

2) The ease with which observable prices can be used to complement a CAPM-based valuation (For a public target, the bidder may consider not only the CAPM-based value but also the target’s current market
capitalization, for private - comparable firms may play a role)

Question 47

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

How does company’s probability to receive a takeover bid depend on its beta?

Answer 47

A bid for a public firm is only made if the firm’s CAPM-implied equity value exceeds its current market capitalization. -> a public firm’s probability of receiving a takeover bid is decreasing with its beta because the CAPM-implied equity value is decreasing in beta

Question 48

Dessaint, Olivier, Jacques Oliver, Clemens A. Otto, and David Thesmar, 2021, CAPM-Based Company (Mis)valuations

How does bidder’s asset beta influence the method of payment in a takeover?

Answer 48

If bidders rely on the CAPM when assessing the value of their own equity, high beta bidders should be more likely than low beta bidders to propose stock as the method of payment (Bidders who believe their own stock to be overvalued by the market are more likely to propose payment in stock than in cash)