Behavioral Finance 1-1. Chapter 4 Challenges to Market Efficiency

Transcription

1 Behavioral Finance 1-1 Chapter 4 Challenges to Market Efficiency 1

2 Introduction 1-2 Early tests of market efficiency were largely positive However, more recent empirical evidence has uncovered a series of anomalies. Efficiency tests are by their very nature joint hypothesis tests Market efficiency and a particular risk-adjustment technique together constitute the maintained hypothesis 2

3 Introduction (cont.) 1-3 Because there are significant limits to arbitrage, not all mispricing need disappear quickly. Arbitrage involves the simultaneous purchase and sale (or short-sale) of securities so as to lock in a risk-free profit 3

4 Introduction (cont.) 1-4 These limits stem from 1) noise-trader risk: the possibility that mispricing worsens in the short-run 2) fundamental risk: it exists when the substitute security is an imperfect substitute 3) implementation costs: trading costs and the potential non-availability of the security that must be short-sold 4

5 Some Key Anomalies Lagged reactions to earnings announcements 2. The small-firm effects 3. Value vs. growth 4. Momentum and reversal 5

6 Lagged reactions to earnings announcements 1-6 Event study methodology Look at a large number of similar events for a comprehensive sample of firms; work in terms of event-time rather than calendar-time Calculate excess returns on days leading up to the event, on the day of the event, and on days after the event Average these excess returns over all events in the sample Accumulate these average excess returns to arrive at cumulative average returns (CARs) 6

7 Lagged reactions to earnings announcements Event study methodology (cont.) For each event, calculate standardized unexpected earnings (SUE) SSSSSS = EEEEEE EE(EEEEEE) SSSSSS where EPS and E(EPS) are actual and forecasted earnings per share, respectively, and SEE: S.E. of the estimate Based on these SUE values, each announcement was put into one of the SUE categories CAR paths were calculated over the relevant quarter for each of the SUE categories 1-7 7

8 Lagged reactions to earnings announcements 1-8 Event study methodology (cont.): Results On the day of the announcement the market reacts positively to positive surprises and negatively to negative surprises Most notable is the tendency for there to be a continued drift in prices, especially after unexpected very good or unexpected very bad earnings announcements This is inconsistent w/ market efficiency since it appeared that the drift was sufficiently large 8

9 Small-firm effect 1-9 Small-firm effect Tendency for firms w/ low levels of market capitalization to earn excess returns after accounting for risk Using U.S. data, a portfolio(long the smallest firms and short the largest firm) was able to earn 1.54% per month during In addition, much of the effect was concentrated in January, January effect 9

10 Small-firm effect 1-10 Explanations The tax-loss selling-pressure hypothesis: some investors sold securities at the end of each calendar year to establish short-term capital losses for income tax purposes the size of a stock s rebound in Jan. & poor performance in the prior year However, patterns in the data will often be found merely because of randomness The stability of the effect has been questioned The effect has declined dramatically in the last 20 years or so publishes research has revealed to arbitrageurs profitable opportunities 10

11 Value vs. Growth 1-11 Value vs. Growth Value stocks: stocks w/ prices that are low relative to such accounting magnitudes as earnings, CFs, and book value Growth stocks: stocks w/ prices that are high relative to such accounting magnitudes P/E ratios study (Basu, 1977) Sampling an average of 500 stocks per year over , he grouped them into quintiles on the basis of P/E ratios 11

12 Value vs. Growth 1-12 P/E ratios study (Basu, 1977), cont. High P/E firms had lower returns than did low P/E firms Market risk did not explain this regularity, however. Low P/E portfolios were actually less risky than were high P/E portfolios Book-to-market price (B/P) ratio study Firms w/ high B/P have tended to outperform firms w/ low B/P Is there consistency over different markets and time periods? 12

13 Value vs. Growth portfolios: International evidence

14 Momentum and Reversal 1-14 Weak form efficiency Returns should not be predictable by conditioning merely on lagged returns This does not always hold in practice The sign of the correlation is horizon-dependent Momentum and reversal Momentum exists when returns are positively correlated w/ past returns While reversal exists when returns are negatively correlated w/ past returns 14

15 Momentum and Reversal 1-15 Momentum and reversal, cont. For short-term (one-month) intervals, there is reliable reversal primarily a technical issue For medium-term intervals (about 3-12 months), there is well-documented momentum For long-term intervals (about 3-5 years) reversal is typical Reversal for LT intervals (De Bondt and Thaler, 1985): winner-loser effect Forming portfolios of the top/bottom 50 stocks in terms of performance net of the market over the previous three years then track them going forward 15

16 Momentum and Reversal 1-16 Reversal for LT intervals, cont. There are substantial differences: past lowers substantially outperform past winners 1) Much of the difference is generated by the strong performance of lowers rather than the weak performance of winners 2) Much of the return boost/drop occurs in the month of January 3) The difference is significant in a statistical sense, but the p-values are not convincingly high 16

17 Reversal evidence 1-17 Source: Figure 3 from De Bondt, W. F. M., and R. Thaler, 1985, Does the stock market overreact? Journal of Finance 40, Wiley Publishing, Inc. this material is used by permission of John Wiley & Sons, Inc. 17

18 Momentum and Reversal 1-18 Momentum for MT intervals A long-short zero-cost portfolio formed on the basis of returns over the previous six months earned an average excess return of 0.95% per month over the next six months Momentum exists not just at the level of the firm, but also at the level of the industry There is a relationship b/w post-earnings announcement drift and momentum 18

19 Momentum evidence

20 Key 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! 20

21 Key trading rules that have shown to be effective ii Value vs. growth portfolios (usually value firm has a high book/market and a growth firm here is one with an absence of value): Go for value! Predictable serial correlation: Medium-term momentum! Long-term winners vs. losers: Reversals: losers become winners! 21