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Behavioral Finance

Chapter 13 Behavioral Explanations

for Anomalies

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Introduction

Four key anomalies reviewed – 1) The small firm effect 2) lagged reactions to

earnings announcements 3) value vs. growth 4) momentum and reversal

In this chapter we discuss possible explanations for the last three anomalies – The small-firm effect is not usually attributed to

behavioral factors. – Yet, it is included in the group of key anomalies b/c

it plays a central role in the Fama-French three-factor model 2

1- 3 Review of trading rules that have shown to be effective i.

Small cap portfolios vs. large cap portfolios? – Small cap wins out!

Portfolios formed based on P/Es: – Low P/Es do better!

Earnings announcements momentum: – Reaction to extreme announcements is slow!

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Value vs. growth portfolios (usually value firm has a high book-to-market and a growth firm has a low book-to-market): – Go for value!

Predictable serial correlation: – Medium-term momentum!

Long-term winners vs. losers: – Reversals: losers become winners!

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Review of trading rules that have shown to be effective ii.

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Behavioral finance and anomalies Some of the previously described anomalies

can be potentially explained using insights of behavioral finance. This is not without controversy, especially from

strict adherents to EMH. These researchers say that most anomalies are: – Attributable to improper risk-adjustments – Or, because of transaction costs, cannot be

capitalized on

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1- 6 What explains these anomalies? Risk?

Risk? For example, perhaps stocks with certain characteristics are riskier, and beta doesn’t reflect this additional risk. Fama-French 3-factor model:

– Risk factors are: • Market • Value vs. growth • Small cap vs. large cap

Momentum is main anomaly not explained (they acknowledge).

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1- 7 What is behind lagged reactions to earnings announcements?

Extreme earnings announcements, whether very positive or very negative, are only incompletely reflected in prices. – It leads to a period of delayed reaction – Both analysts and investors anchor on recent

earnings underreact to new information Concurrent w/ underreaction in the short term

may be overreaction in the long term. – The P/E ratios (a measure of expected earnings

growth) were quite dispersed in the U.S. at the end of 1999: 10th percentile 7.4 vs. 90th percentile 53.9

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1- 8 What is behind lagged reactions to earnings announcements? cont.

Concurrent w/ underreaction in the short term may be overreaction in the long term. – Same disparity existed at the same time among

analysts, w/ their forecasts of five-year earnings growth rates

– 10th percentile 8.9% vs. 90th percentile 40% – Yet, the evidence is that few firms grow rapidly for

long periods and mean reversion is the order of the day

– Analysts’ forecasts also tend to be too optimistic

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What is behind value advantage? It has been suggested that there are four main

reasons why retail and institutional investors have favored growth stocks over value stocks: 1. They are committing judgment errors in extrapolating

past growth rates too far into the future, and are thus surprised when value stocks shine and growth stocks disappoint. This is so-called “expectational error hypothesis”

2. Because of representativeness, investors may assume that good companies are good investments

These first two reasons are mistakes of judgment : likely individual investors are more subject to committing them than institutional investors.

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What is behind value advantage? cont. Next two reasons are due to agency

considerations (rational reasons to shy away from value): – 3. Because sponsors view companies with steady earnings

and buoyant growth as prudent investments, so as to appear to be following their fiduciary obligation to act prudently, institutional investors may shy away from hard-to-defend, out-of-favor value stocks

– 4. Also because of career concerns, institutional investors, who are evaluated over short horizons, may be nervous about tilting too far in any direction thus incurring tracking error. A value strategy would require such a tilt and may take some time to pay off, so it is in this sense risky.

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1- 11 Explaining long-run value outperformance (point 1)

Expectational error hypothesis (extrapolation hypothesis) – Investors tend to extrapolate past growth rates too far into

the future – When earnings realized and financial results are made

public, investors are faced w/ surprises. – For value stocks, which have low implicit future growth

rates, earnings realizations are systematically above expectations (investors exhibit pessimism) and result in positive stock returns.

– For growth stocks, the opposite happens, and earnings realizations tend to lead to negative return surprises (investors suffer from optimism).

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1- 12 Explaining long-run value outperformance (point 2)

Take a growth stock with a high P/E or P/B. – Such stocks have a period of anticipated higher-than-

normal growth. What if market overestimates length of

supernormal growth period? – When it becomes clear that mean reversion is

occurring, growth stocks deteriorate. Similar story (in reverse) can be told for value

stocks.

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DHS model: Explaining reversal

DHS model is based on overconfident investors overestimating precision of their own private signals. This leads to negative serial correlation in

price movements (i.e., reversal).

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DHS model details Begin in equilibrium at t=0. At t=1 private noisy information appears (one can

assume informed investors undertake some analysis generating private signals). At t=2 true value of security is revealed. Formally, the private information at t=1 is: s1 = θ + ε where θ is a mean-zero random variable w/ variance σ2

θ that represents the change in the true value of the security. It is observed imperfectly b/c of a mean-zero noise term w/ variance σ2

ε

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DHS model: Price response

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Price should go to:

Price does go to:

Since σ2ε > σ2

C , prices are more influenced by the signal than is rational!

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DHS example

Suppose that θ = 2; σ2θ = σ2

ε = 1; and σ2C =

0.5. Two cases: ε=2.5 (case 1) and ε=1.5 (case 2). Solid lines in graph show price paths assuming

that overconfident traders drive prices. Broken lines shows price paths assuming no

overconfidence.

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Price path graphs

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DHS example (cont.)

Case 1. – Even rational price goes to $2.25 (a little above

equilibrium value). – Because logical to believe that half of signal

(s1/2=(2+2.5)/2=2.25) is true information. – Overconfident investors believe that an even

greater proportion of s1 is information and push up prices even higher, to $3.

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DHS example cont. ii. Case 2.

– Rational price goes to $1.75 (a little below its equilibrium value).

– When half of the signal is true information and half error, as will be true on average, rational price will immediately go to equilibrium.

– Overreaction again occurs for the overconfident investors under case 2.

– They push prices up to $2.33. – Overconfident investors will on average overreact,

necessitating reversal.

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1- 20 BSV model: Explaining momentum/reversal

Recall sun and clouds example: – At first people were too anchored. – Then they were too influenced by new evidence.

What about earnings? – Anchoring and conservative adjustment dictates

that investors are slow to change views on earnings. – First surprise tends to be followed by a few more.

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Explaining momentum/reversal cont.

Eventually recency and base rate underweighting take over and past performance is extrapolated into future.

Overreaction: current high-growth/low-growth period is viewed as longer than is logical.

When it becomes clear that mean reversion is occurring, losers perform well and winners deteriorate.

Note that losers are often value stocks and winners are often growth stocks.

Markets overreact slowly!!!

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BSV model formalizes this story

Earnings follow a random walk: – Changes in earnings are +y or –y with equal

probability But investors, being coarsely calibrated,

believe that stocks switch between two regimes.

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1- 23 BSV model formalizes this story (cont.)

Regime 1. Earnings mean-revert: : – Given a positive/negative earnings change, there

is a low probability of another positive/negative earnings change in the next period

Regime 2. Earnings are persistent: : – Given a positive/negative earnings change, there

is a high probability of another positive/negative earnings change in next period

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1- 24 BSV model formalizes this story (cont. ii.)

At all points in time individuals must guess whether world is in regime 1 or 2. Estimated probabilities will rise and fall as

events unfold: – Sequence of alternating changes (e.g., +y, –y, +y, –y)

will lead people to believe that regime 1 is in effect – While sequence of like earnings changes (e.g., +y, +y,

+y, +y; or -y, –y, -y, –y)) will lead people to believe that regime 2 is in effect

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1- 25 BSV model formalizes this story (cont. iii.)

If earnings changes are the same at both t and t+1, the perceived probability that regime 1 is in place will fall after continuation it is less likely than before that we are in regime 1 If earnings changes are different at both t

and t+1, the perceived probability that regime 1 is in place will rise after reversal it is more likely than before that we are in regime 1

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Explaining momentum and reversal

Investor beliefs about regime will dictate prices: – When investors think regime 1 they underreact to

earnings changes – When investors think regime 2 they overreact to

earnings changes So this model can explain both underreaction

and overreaction. And momentum and reversal empirical

regularities can be simulated…

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1- 27 Simulated returns from earnings and returns sorts based on BSV

model

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Reprinted from the Journal of Financial Economics, Vol 49, Issue 3, Barberis, N., A. Shleifer and R. Vishny, "A model of investor sentiment," pp. 307-44, © September

1998. With permission from Elsevier.

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Simulation based on BSV model

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Source: Barberis, N., A. Shleifer, and R. Vishny, 1998, "A model of investor sentiment,“ Journal of Financial Economics 49, 307-44.

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Exercise

Momentum is the anomaly that gives those subscribing to efficient markets the most trouble. Explain.

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