Capital market anomaly

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Capital market anomalies , also known as price anomalies , denote a situation in which the observations on the capital market do not agree with previous capital market theories. The standard model is the CAPM . However, there are also alternative asset pricing models, such as the Fama-French three-factor model . Since an anomaly can only ever be explicated in relation to a specific risk model, economists therefore also prefer the neutral term of the return predictor. There is no need to define a benchmark model.

From the end of the 1970s, studies were undertaken to prove and record the deviations from existing models. The four main explanations for the existence of return predictors or anomalies are: (1) mispricing, (2) unmeasured risk , (3) limits of arbitrage, and (4) sample bias . There is no consensus within research on the correct explanation of return predictors. However, the explanatory approaches of sample bias, incorrect assessments and risk-based theories are particularly represented by prominent authors.

The predicted returns often decrease after their publication, or disappear completely, suggesting arbitrage by market participants. Furthermore, the studies generally do not consider transaction costs. This means that anomalies can often not be exploited profitably if transaction costs are taken into account. However, there are also strategies that successfully exploit specific return predictors while taking transaction costs into account. This enables long-term returns above the market return (beta). These include the value strategy or, more generally, factor investing or smart beta investing.

The existence of anomalies does not per se refute the market efficiency hypothesis . For this it would have to be shown that the anomaly exists beyond the asset pricing model to be specified beforehand. Behind this is the composite hypothesis problem .

Types of capital market anomalies

Calendar anomalies

Calendar anomalies, also known as seasonality, deal with the fact that on certain calendar days or even entire months, securities achieve significantly higher returns. One speaks in particular of the January effect, weekend or Monday effect, holiday effect and company neglect effect. However, these anomalies provide opportunities for arbitrage deals.

January effect

This effect often occurs in the first weeks of January of a new year and describes the course of the stock markets . During this time, above-average returns are achieved, as many investors have decided to sell their securities, stocks or the like before the end of the previous year in order to avoid tax losses. Many of them then decide to reinvest their capital in the new year , as they are assuming that share prices will rise . Other factors that can also favor higher investments in the new year are the hedging of the performance of fund managers or the shifting of portfolios into larger companies. This phenomenon was determined by measuring the returns in the first days of January and on the remaining days of the year. Then the averages of the calendar weeks were formed and compared with one another. However, the January Effect disappeared shortly after it was released, suggesting arbitrage by market participants.

Weekend effect

Empirical , statistical elaborations over a decade-long period show that, especially during the week on Mondays, the returns differ from other days of the week. They are mostly negative, while they are generally positive on average for the rest of the week. One reason for this can be that negative reports are usually published by companies after the stock market closes on Fridays and on weekends, so that shareholders or potential interested parties have time to prepare for the news and think about their next actions. This is supposed to achieve a supposedly better, not too bad course , but this only happens to a limited extent in practice. As soon as the stock exchanges open on the following Monday, the traders and thus the stock exchange prices react negatively to the reports. The reactions are usually weaker, compared to an announcement on a normal trading day , where an immediate sale would have been possible.

Holiday Effect

Trading days that are either before or after public holidays also have significantly higher returns than conventional days. One possible reason for this would be that short sellers in particular want to get rid of their risky papers or close them before the holidays so as not to be exposed to market risk . Short sellers are market participants who bet on falling prices by short selling securities so that they can later buy these positions again cheaply. This is how they generate their profits. However, if there is a longer break in trading on certain markets , there is no chance of reacting quickly to emerging risks . Therefore, such actions usually have to be completed beforehand.

KPI anomalies

Key figure anomalies concentrate and relate particularly to the refutation of the theories of CAPM , which becomes evident when observing the individual capital markets . Furthermore, these anomalies focus on company size and the value effect.

Value effect

This effect puts value investing in the foreground and shows it to be a particularly outstanding investment strategy . Several criteria such as the price / earnings ratio , the price / sales ratio and also the dividend yield play a role here. The effect is justified by the assumption that investors clearly overestimate the course of growth companies and underestimate that of valuable companies . The price-earnings ratio (P / E) is particularly interesting. It has been proven that companies with a lower ratio achieve a significantly higher return than those with a very high P / E ratio. In practice, it is often the case that the high growth expectations cannot be met, which immediately leads to a collapse in prices. These factors are particularly interesting for companies with a very high market capitalization , as they are even more involved in the market than those with only a small market capitalization.

Size effect

Another empirical study by Fama and French has shown that small companies often generate higher returns than larger corporations or companies . However, this effect does not occur linearly with the size of a company , but mostly only for smaller companies. Therefore one can also speak of a “small firm” effect. After intensive discussions about this phenomenon , it was quickly recognized that there was no real streamlined relationship between the return on investment and the size of the company. Differences in the range of the return of plus or minus 35 percent were the result, up to results which showed that small companies achieved particularly small returns. Therefore, it can be assumed that investors should not rely on this anomaly.

Distress effect

Companies are rated internationally based on a rating and their possible probability of insolvency is assessed. The rating agencies Standard & Poor's and Moody's are well known. The ratings are recognized, but are very often neglected in company evaluations and sometimes not or insufficiently considered. In recent years it has been increasingly observed how these seemingly neglected assessments very often appeared in reality and companies went bankrupt . This effect is known as a distress anomaly. In addition, it was found that companies with a bad rating are mostly overvalued and generate lower returns.

Efficiency anomalies

These types of anomalies are particularly caused by the propensity of investors . Incorrect or no assessment of current information, questionable valuation of companies and the resulting incorrect price estimates lead to price distortions in the markets . Representatives of this anomaly are on the one hand the intraday effect and on the other hand the winner-loser effect.

Intraday effect

As a starting point for these studies, it was determined that current stock prices reflect all possible information regarding the company or political situation. The study examined how newly emerging, previously unknown information influences the level of returns on a trading day. Significant fluctuations in the facts of whether the news was published before or after upcoming transactions were the result. This phenomenon is called the intraday effect. How big these differences are depends clearly on the type of information. If the set goals cannot be achieved, there is a chance of a takeover, a major contract was awarded or there were scandals within the group . Depending on the case, there are different price reactions and thus rising or falling returns.

Winner-loser effect

With the assumption that market participants often hide or misinterpret relevant background information, further studies followed with remarkable results. It was also recognized that companies with the lowest returns in a 3-year trend were up to 30 percent above the general market return in the following five years. In contrast, it became clear that companies that had the highest returns in the first three years were up to ten percent below the market level in the next few years. This is why many investors focus on companies, so-called losers, which have tended to be undervalued in recent years despite good profits. Winners, i.e. companies whose profit situation has been overrated, lose the interest of potential investors. They assume that the expected price corrections will lower the price of the security and thus dwindle investor profits.

Momentum effect

In contrast to the winner-loser effect, when looking at the momentum effect, the focus is on short-term trends. Forecasts for the future are developed on the basis of the respective course of the last year (short to medium-term performance) . The focus is on the possible development of the shares in the next 3–12 months. It was observed that, above all, stocks that have distinguished themselves with high returns in the last six months behave similarly in the following months and also continue to achieve higher returns.

Other anomalies

The human psyche also plays a role in financial transactions. Influences from nature and the social environment can change or burden human perception and lead to incorrect assessments. The assumption that z. B. Climate changes or moon phases have an influence on share prices, however, has not yet been proven.

Individual evidence

  1. ↑ Philipp Eustermann: Behavioral Finance, Private Equity and Asset Price Bubble - Implications for Financial System Stability and Monetary Policy (=  series of publications by the Research Center for Banking Law and Bank Policy at the University of Bayreuth . Volume 12 ). Hamburg 2010, ISBN 978-3-8300-5312-5 , p. 92 .
  2. ^ Eugene F. Fama, Kenneth R. French: Common risk factors in the returns on stocks and bonds . In: Journal of Financial Economics . tape 33 , no. 1 , February 1993, p. 3-56 , doi : 10.1016 / 0304-405X (93) 90023-5 .
  3. ↑ a b c d R. David Mclean, Jeffrey Pontiff: Does Academic Research Destroy Stock Return Predictability ?: Does Academic Research Destroy Stock Return Predictability? In: The Journal of Finance . tape 71 , no. 1 , February 2016, p. 5-32 , doi : 10.1111 / jofi.12365 .
  4. ↑ EUGENE F. FAMA, KENNETH R. FRENCH: Multifactor Explanations of Asset Pricing Anomalies . In: The Journal of Finance . tape 51 , no. 1 , March 1996, ISSN  0022-1082 , pp. 55-84 , doi : 10.1111 / j.1540-6261.1996.tb05202.x .
  5. ↑ WERNER FM De Bondt, Richard Thaler: Does the Stock Market Overreact? In: The Journal of Finance . tape 40 , no. 3 , 1985, ISSN  1540-6261 , pp. 793-805 , doi : 10.1111 / j.1540-6261.1985.tb05004.x .
  6. ^ Campbell R. Harvey, Yan Liu, Heqing Zhu: ... and the Cross-Section of Expected Returns . In: Review of Financial Studies . tape 29 , no. 1 , January 2016, ISSN  0893-9454 , p. 5-68 , doi : 10.1093 / rfs / hhv059 .
  7. ^ Nicholas Barberis: Psychology-based Models of Asset Prices and Trading Volume . In: SSRN Electronic Journal . 2018, ISSN  1556-5068 , doi : 10.2139 / ssrn.3177616 .
  8. ^ John H Cochrane: Macro-Finance * . In: Review of Finance . tape 21 , no. 3 , May 1, 2017, ISSN  1572-3097 , p. 945-985 , doi : 10.1093 / rof / rfx010 .
  9. ↑ Heiko Jacobs, Sebastian Müller: Anomalies across the globe: Once public, no longer existent? In: Journal of Financial Economics . tape 135 , no. 1 , January 1, 2020, ISSN  0304-405X , p. 213–230 , doi : 10.1016 / j.jfineco.2019.06.004 .
  10. ^ A b Eugene F. Fama, Kenneth R. French: The Value Premium . ID 3525096. Social Science Research Network, Rochester, NY January 1, 2020, doi : 10.2139 / ssrn.3525096 .
  11. ^ Robert Novy-Marx, Mihail Velikov: A Taxonomy of Anomalies and their Trading Costs . National Bureau of Economic Research, Cambridge, MA December 2014, doi : 10.3386 / w20721 .
  12. ^ Eugene F. Fama, Kenneth R. French: A five-factor asset pricing model . In: Journal of Financial Economics . tape 116 , no. 1 , April 1, 2015, ISSN  0304-405X , p. 1–22 , doi : 10.1016 / j.jfineco.2014.10.010 .
  13. ^ Andrew Ang: Factor Investing . In: Asset Management . Oxford University Press, 2014, ISBN 978-0-19-995932-7 , pp. 442-488 , doi : 10.1093 / acprof: oso / 9780199959327.003.0014 .
  14. ↑ Factor investing - the basics. May 2, 2019, accessed on July 9, 2020 (German).
  15. ^ Eugene F. Fama: Efficient Capital Markets: A Review of Theory and Empirical Work . In: The Journal of Finance . tape 25 , no. 2 , May 1970, p. 383 , doi : 10.2307 / 2325486 , JSTOR : 2325486 .
  16. ^ Eugene F. Fama: Efficient Capital Markets: II . In: The Journal of Finance . tape 46 , no. 5 , 1991, ISSN  0022-1082 , pp. 1575-1617 , doi : 10.2307 / 2328565 , JSTOR : 2328565 .
  17. ↑ a b Rolf J. Daxhammer, Máté FASCar: behavioral finance . Konstanz / Munich 2012, p. 116 .
  18. ↑ G. William Schwert: Anomalies and Market Efficiency . Ed .: University of Rochester. Rochester 2003, p. 944 .
  19. ^ Burton G. Malkiel: The Efficient Market Hypothesis and Its Critics . In: Journal of Economic Perspectives . tape 17 , no. 1 , February 1, 2003, ISSN  0895-3309 , p. 59-82 , doi : 10.1257 / 089533003321164958 .
  20. ^ KR French: Stock Returns and the Weekend Effect . In: Journal of Financial Economies . tape 8 , 1980, p. 55-69 .
  21. ↑ JM Patell, MA Wolfson: Good News, Bad News, and the intraday timing of Corporate Disclosures . In: The Accounting Review . tape 57 , no. 3 , 1982, pp. 506 ff .
  22. ^ Robert A. Ariel: High Stock Returns before Holidays: Existence and evidence on Possible Causes . 1990, p. 1611 ff .
  23. ↑ a b Thomas Holtfort: Influence of seasonality on the momentum effect: An empirical study of the German stock market . Cologne 2009, p. 76 ff., 100 .
  24. ↑ J. Lakonishok, A. Shleifer, RW Vishy: Contrarian Investment, Extrapolation and Risk . In: Journal of Finance . tape 49 , 1994, pp. 1541-1578 .
  25. ↑ Ralf R. Sattler: Share forecast: Professional know-how on the asset situation . 1999, p. 158 .
  26. ↑ a b c Detlev Stock: On the relevance of the CAPM anomalies for the German stock market (=  European university publications . Volume 2772 ). Frankfurt am Main 2002, p. 19, 119, 138 .
  27. ↑ Dietmar Ernst, Werner Gleißner: Damodaran's country risk premium . In: WPg . tape 65 , no. 23 , 2012, p. 1252 .
  28. ↑ MJ Barcley, RH Litzenberger: Announcement Effects of New Equity Issues and the Use of Intra-Day Price data . In: Journal of Financial Economics . tape 21 , 1988, pp. 73 ff .
  29. ↑ Hersh Shefrin: Behavioral Corporate Finance - Decisions did Create Value . New York 2007.