Lecture 6 - Empirical Findings [Compatibility Mode]

Lecture 6 - Empirical Findings [Compatibility Mode] -...

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Unformatted text preview: 14/04/2009 Empirical findings Lecture 6 Empirical findings Market Market Efficiency Hypothesis – Weak form – Semi-strong form Semi– Strong form Research Research findings By Quach Manh Hao – More applicable to developed financial markets – Implying the role of security analysis in developing markets. The The lecture today presents the empirical findings as evidence of anomalies to the MEH and the risk models studied in the previous lectures. Filter rule In In the absence of no new information, a stock price trades within certain, established bounds. In In other words, we should expect no “special movement” in the stock price. – On new news, if stock rises above the established ceiling, buy it – On new news, if stock falls below the established floor, sell it. This This works because the stock is in process of establishing new a trading range. This This filter rule is used today by many investment professionals. In consideration: what factors? Remember: Remember: if the Weak form version of the EMH is correct, one should not be able to earn excess return on the basis of known, observable information on a firm But, But, there are a number of such factors that have received a great deal of attention over the years. These These are the empirical findings and they may be changed from time to time depending on data mining. But But they do serve as a practical guide to the market! For For academic purpose, you can also think of them as the tests of the hypotheses that we have studied. Firm characteristics The The CAPM says that only market risk was relevant in explaining the cross-section of crossexpected returns Evidence Evidence began to emerge that other, firmfirmspecific information seemed to be able to enhance the explanation. This This means the firm specific information is indeed important to explain the stock return/price. The size effect Banz Banz (1981) was the first to identify an apparent anomalous relationship between firm size and return Excess Excess returns between 1936 and 1977 on US stock market could be earned by investing in small stocks An An additional 19.8% per year! Banz Banz found that small cap betas were lower on average than large cap betas Implying Implying that higher return had been achieved by incurring lower (CAPM) risk This This study calls into question both the EMH and the CAPM 1 14/04/2009 The size effect explanations CAPM CAPM Betas biased downwards for small stocks because of infrequent trading (Roll (1981) Journal of Finance) i.e. small stocks seem less liquid. Perhaps Perhaps CAPM is an inappropriate model, do the results hold for APT risk-adjustment? riskIn In their research, Chen, Chan and Hsieh (1985) found that APT could explain most of the difference between large and small stocks In In the CCH results, size seemed to be proxying for additional default risk not captured by CAPM i.e. not explained by the market. Liquidity Liquidity and transactions costs, not considered explicitly by the CAPM, may also play a part in the higher return of small stocks A practical guide Complicated Complicated portfolio formation process often used to disentangle the effects You You should try this for forming your own portfolio: – Identify high and low PE stocks. Assign ranking e.g. 1 to 3. – Identify size (market capitalization). Assign second ranking based upon size e.g. from 1 to 3. Form Form portfolios based upon PE and size: Case Case 1: Sort stocks by PE and form portfolios based upon PE – see what you get? – Expected: Low PE outperforms. Market to Book Effect Fama Fama and French, and Chan, Hamao and Lakonishok found that high book to market value firms outperform low book to market value firms: High High book to market value firms = Value firms Low Low book to market value firms = Growth firms Using Using US stock return data, the premium (i.e. the excess return) found to be around 7.8% per year. PE Effect Basu Basu (1977) found relationship between expected returns and PE ratio High High PE stocks subsequently underperform low PE stocks Or Or “Value outperforms Growth” Value Value stocks: low PE, low PB and high dividend. Growth Growth stocks: high PE, high PB and low dividend. Investors Investors get overexcited about growth prospects and then subsequently revise down expectations Other Other researchers found that once one controls for “Size” the effect disappears In In short, “value stocks” are better but the “size effect” is important. A practical guide Case Case 2: Sort stocks by Size and form portfolios based upon PE – see what you get? – Expected: Small stock outperforms Case Case 3: Sort by PE and then by Size. Compare large low PE portfolio returns with large high PE portfolio returns. – Expected: The findings are mixed but we would expect a smallsmall-low PE to outperform. But largeBut if large-low PE portfolio outperforms large-high largePE portfolio then possibly due to PE effect i.e. you might find it useful to focus on PE analysis. Firm characteristics and fund management Another Another consequence of anomalies is “Style investing” Fund Fund manager picks a style: – Growth – Value – Recovery: stocks that have experienced a downward movement. The notion is simple that “things that have gone down must go up”. Then Then manages the portfolio according to this style 2 14/04/2009 Seasonality Seasonal Seasonal patterns in stock market returns have been identified by empirical research. Patterns Patterns of this kind are the most obvious challenge to the weak form version of the EMH. The The ‘January Effect’ is probably the most famous of these anomalies UK Evidence The January Effect “Sell in May and go away” Informally Informally recognised by participants that January was typically a good month for equities Researchers Researchers confirmed this in 1970s and 1980s The The January effect seemed to be prevalent across: – different markets – and for both bonds and equities Empirical evidence Gultekin Gultekin (1983) find evidence of January effect in 17 different stock markets Further Further tests showed that the January Effect was concentrated in first few days of January In In the UK Clare et al (1994) find evidence et (1994) for an “April effect” too (see previous slide) But But surely seasonal patterns like those documented in many papers would be traded away in an efficient market ? January and the size effect “It’s the size effect in disguise” A number of researchers have found that it is small number firms in particular that display the January effect. It It means that the January effect is “no problem” with large stocks. The The implication is simple: if you are holding small stocks, when would be the best time to sell them? The The answer is “January” I write the January in brackets to implicitly mean write that it should be considered better as a name. January and tax effects “It’s something to do with tax” In In US and in many countries the tax year ends in December In In order to minimise their tax bill, investors realise losses on losing investments, i.e. selling poorly performing stocks in December. ‘Losers’ ‘Losers’ with depressed prices in December are then snapped up in January leading to an increase in their price Known Known as the “tax loss selling hypothesis” 3 14/04/2009 January and tax effects cont If If tax loss selling is the cause then we might expect to find other features in returns: We We can observe lower than average returns in December – particularly end of December. This explains the downward movement of the market at the end of December. We We can expect high proportion of small ‘loser’ stocks at the end of the year. The The seasonal pattern is changed where the tax regime is different: – no capital gains tax – different fiscal year end January and tax effects cont In In the UK there is an April effect (see Clare et al et (1994) (1994) It It is because the UK’s tax year ends on April 5th But But why does the UK (Australia, Japan) have a January effect then? Also, Also, in US there is a January effect evident before the introduction of income tax So So taxation may only be a partial explanation, at best. There There must be something else to explain this effect … but we haven’t found! Other seasonalities Returns Returns are higher on Fridays than on Mondays Similar Similar effect over bank holidays? Possible Possible explanations: Bad Bad company news released over the weekend? Portfolio Portfolio rebalancing? The “turn-of-theThe “turn-of-the-month” effect (Ariel 198X): see the new finding at http://www.cxoadvisory.com/blog/external/blog7http://www.cxoadvisory.com/blog/external/blog720-06/ 20- January and tax effects cont What What should we do then? Buy Buy security that reaches its annual low in last week of December Hold Hold until end of January Researchers Researchers have found that this strategy produced significant excess returns January and window dressing In In some markets (US) there will be the added benefit of a lower tax bill - explaining why losers are sold at end of the year Once Once the portfolio is dressed and bonuses have been banked the fund managers can buy the cheap looking losers in early January Explaining Explaining why losers become winners. Please note, this is also why the notion “things have gone down must go up” to be true. The overreaction hypothesis Debondt Debondt and Thaler (1985) find evidence to suggest that losing stocks over a 3-5 year period 3subsequently turn out to be winners in the next 3-5 3year period Also Also find that the response is asymmetric and prominent in January The The reason: investors overreact to bad news and underreact to good news – a psychological explanation Clare Clare and Thomas (1994) find similar effect in the UK, but attribute it to a manifestation of the firmfirmsize effect (yet again) 4 14/04/2009 Conclusions This This lecture does not give you any theory but the empirical findings This This is a good practical guide to your investment decisions. The The findings may be different due to data mining, and many other factors. You You can apply but don’t blame me for your losses!!! Big lessons Filter Filter rule: there are always bounds for a stock price. Sell when it tends to go down and buy when it goes up. Size Size effect: Small outperforms big. Value Value outperforms growth. Specifically: – Low PE > High PE – Low MB > High MB – High Div > Low Div “January” “January” effect: buy in December and sell in January or “Buy late sell early”. The The seasonal effect is found with: Weekends, Turn of the Month .etc You You may expect the tax year end is an important turn”. Don’t Don’t tell others this whole story as you may make a fortune. Thank you! Unfortunately, Unfortunately, all of us know and it’s publicly available. But But hope is still alive…market is not efficient. 5 ...
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This note was uploaded on 01/16/2012 for the course ECON 101 taught by Professor Tom during the Spring '11 term at FH Joanneum.

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