Stock market anomalies literature review

Stock market anomalies literature review

Author: 9mm On: 15.06.2017

An Empirical Study of Stock Market Anomalies

Current consensus seems to be that earnings and cash flow effects are subsumed by the book-to-market ratio and firm size Fama and French, In order to capture this return, momentum investors must keep a short position in these stocks after the delisting day, which is not likely.

Shumway and Shumway and Warther show that delisting returns reported in the CRSP database need to be evaluated carefully. The cost of frequent trading in the momentum portfolio, together with the disproportionately high costs of precisely the stocks on which the anomaly relies, eliminates any perceived arbitrage profits Lesmond, Schill and Zhou, THE LONG-HORIZON WINNER-LOSER EFFECT a. The January effect refers to the tendency for stock market returns to be higher in January than in any of the other months Rozeff and Kinney, The January effect is mainly located in the first 2 weeks of January.

Booth and KeimTable 1 NYSE-AMEX-NASDAQ stocks estimate the small firm Decile10 -large firm Decile1 January effect to be statistically significant at 9. Note that the estimates of the small-firm January effect are variable over time, with high returns forlower returns forhigher returns for and again lower returns for Nevertheless, all estimates of the January returns are statistically significant. The results of Hawawini and KeimNYSE-AMEX show that the January effect relative to the other months is appr.

At the end of the year, many investors seem to be exiting the financial markets with a preference for liquidity, probably to meet year-end cash flow obligations Griffiths and Winters, Moreover, the size of the money changes in December and January appear to be significantly related to the returns on the stock market at that time Chen and Fishe, Table 4.

Empirical studies have turned up a wide range of anomalies relating to seasonality in stock returns. Among these are the Monday effect Cross,the Holiday effect Ariel,turn-of-the-month effect Ariel, and some others. Other anomalies are based on such oddities as the lunar cycle, geomagnetic storms sunspotsweather sunshine, rain, cloud cover, temperatureSuper Bowl indicators.

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Banz was the first to document this phenomenon for U. Banz found that the coefficient on size has more explanatory power than the coefficient on the CAPM beta in describing the cross section of returns. The size effect has been reproduced for numerous sample periods and for most major securities markets around the world Hawawini and Keim, Booth and KeimTable 1 NYSE-AMEX-NASDAQ stocks estimate the small firm Decile10 -large firm Decile1 effect to be statistically significant at 0.

Horowitz, Loughran and SavinTable 1 NYSE-AMEX-NASDAQ stocks estimate 1. The size effect is only a January effect; no size effect exists in the average returns of other months of the year Hawawini and Keim,Figure 1 Table 5 NYSE-AMEX stocks ; Booth and Keim, Table 1 and 2 NYSE-AMEX-NASDAQ The size effect is exaggerated due to delisting bias in the CRSP database.

Correction for negative delisting returns eliminates the size effect in NASDAQ stocks Shumway and Warther, although not in NYSE-AMEX stocks Shumway, The size effect is exaggerated due to the bid-ask bounce and rebalancing effect in calculated short-run daily, monthly returns Conrad and Kaul, Using geometric returns for long-run returns reduces the size premium to 0. Some of these returns may be related to CRSP database errors, for example failures to adjust for reverse stock splits and stock conversions following bankruptcy reorganizations Bhardwaj and Brooks, footnote 8.

The size effect is unreliable. In the US the average size effect over all months has disappeared after Booth and Keim, Table 2; Horowitz, Loughran and Savin, Table 1 and Figure A and was never consistent to begin with Booth and Keim, Table 1. The disappearance of the size effect is mirrored in the decline of the January effect in small stocks. The size effect is driven by brief periods of extraordinary high returns, such as the period in the US Siegel, Figure or extraordinary low returns, get kinzcash fast as the period Brown, Kleidon and Marsh, The average size effect also disappeared in the UK after and in fact turned into a negative effect Dimson and Marsh, Table 2.

The size effect is actually a small or low price effect; other indicators of size such as book value, sales, number of employees, etc.

stock market anomalies literature review

There is no trading opportunity in such observed data. Including appropriate transaction costs for the relevant stocks eliminates any profits from frequent trading strategies based on the forex kft budapest daily or monthly return studies for example Stoll and Asx stocks to buy august 2016, ; Schultz, ; Bhardwaj and Brooks, ; Al-Rajoub and Hassan, Long horizon buy-hold returns suffer less from trading costs Stoll and Whaley, ; Schultz,but one needs to be stock market anomalies literature review careful in calculating the appropriate holding period returns avoiding the portfolio rebalancing problem and other problems of aggregating monthly returns for example, Conrad and Kaul, ; Roll, ; Blume and Stambaugh, No value effect exists in the average returns of the other months of the year Hawawini and Keim,New ipo coming dhaka stock exchange 1 Table 5 NYSE-AMEX stocks The BM effect is exaggerated due to delisting bias and rebalancing effects.

The value effect is irrelevant with respect to the efficient market hypothesis. Including appropriate transaction costs for the relevant stocks eliminates any profits from value trading strategies based on an annual buy-hold return study for example Agarwal and Wang, The abnormal return for is THE MOMENTUM EFFECT Jegadeesh and Titman found that recent past winners stocks with high returns in the past 12 months outperform recent past losers.

Whereas Schwert finds the momentum effect relatively robust across subsamples inKothari, Shanken and Sloan find the momentum effect unreliable with in the post period winners earning negative abnormal returns stock market anomalies literature review losers earning positive abnormal returns.

stock market anomalies literature review

The momentum effect in itself is not an anomaly. In a cross-section of stocks where average, expected returns how to make money during unemployment dispersed - presumably due to differences in risk premiums - high returns and low returns tend to persist.

Momentum is found to be strong and highly significant, but this is fundamental Conrad and Kaul, ; Lo and MacKinlay, One needs to separate any anomalous momentum effect unwarranted time series predictability from the fundamental momentum effect cross-section dispersion effect and time-varying risk premiumswhich may be very difficult. Bulkley and Nawosah report that simply correcting fundamental stock screener india individual stock's sample average returns eliminates the momentum effect.

This in contrast to Jegadeesh and Titman who find that demeaning how much money did the internship make in their sample does not eliminate momentum.

Their residual momentum effect appears to be related to some special feature of NASDAQ stocks. Momentum profitability is large and significant among firms with low credit easy tips for forex trading ltd, but nonexistent among high-grade firms.

Momentum is attributable to continuation among low-grade loser firms that experience negative returns following rating downgrades. Loser stocks exhibit lower analyst following, negative analyst forecast revisions and negative earnings surprises following the portfolio formation date Avramov, Chordia, Jostova and Philipov, Shumway shows that the delisting effect is small, but using buy-hold returns instead of eliminates the winner-loser effect in a replication of the De Bondt and Thaler results NYSE, Including data from the U.

Although still open to debate, a number of studies have found that the winner-loser contrarian effect disappears with a correction for normal returns boston scientific stock options on the Fama-French 3-factor model for example, Fama and French,; Clements, Drew, Reedman and Veeraraghavan, The FF 3-factor model has been criticized for its lack of theoretical foundation in risk models.

Others have also shown a strong relationship between the big-small and high-low factor portfolios and the business cycle, but so far fail to provide strong arguments for the type of risk that this would represent. The usual explanations suggested for the stock market January effect are tax-loss selling selling loser stocks in December to realize tax-offsetting capital losses in the current year and institutional window-dressing selling assets in December not to be included in year-end public disclosures.

The empirical evidence is mixed.

The January effect also exists in countries without capital gains tax e. Japan beforeCanada before The UK and Australia have January effects, even though their tax years begin on April 1 and July 1. Large and small stocks that have risen during the previous year also show January effects.

On the other hand, the turn of the year effect in the US seems to have started after introduction of personal taxes in Schultz, ; Jones, Lee and Apenbrink, Following the Tax Reform Act change in fiscal year-end for mutual funds to end-October, empirical evidence suggests a November effect Bhabra, Dhillon and Ramirez, Window-dressing would suggest that the January effect is strongest for firms with institutional shareholders, but the evidence suggests larger January effects for firms with individual shareholders Sias and Starks, Overall problem with these explanations is that there is no substantial negative December effect that reflects downward selling pressure on prices.

On the other hand, December trading volumes for loser stocks are high and for winner stocks low Dyl,more transactions seem to occur at the lower bid price than the higher ask price Keim,more individual investor odd-lot sales than purchases Dyl and Maberly, The January effect is not an isolated stock market phenomenon.

A January effect has also been found in returns and yields of US low rated corporate bonds see Chang and Pinegar, ; Chang and Huang, ; Fama and French, ; Barnhill, Joutz, and Maxwell, and municipal bond returns see Kihn, Evidence for the government bond and bill market is not so clear.

Interest rates on commercial paper that matures across the year-end show a significant higher premium low price in the run-up to year end, relative to Treasury bills Musto, ; Griffiths and Winters, OTHER SEASONAL EFFECTS, CALENDAR ANOMALIES, THE WEATHER, AND OTHER ODDITIES Empirical studies have turned up a wide range of anomalies relating to seasonality in stock returns.

FamaKeim have pointed out that calendar anomalies are anomalies in the sense that asset-pricing models do not predict them, but at the same time most anomalies are irrelevant due to the fact that the abnormal returns observed fall within the limits of relevant bid-ask spreads and therefore do not generate opportunities for arbitrage profits.

Why at certain times prices appear to have higher probabilities of being closer to bid or ask prices is subject of further study. Jacobsen and Marquering point out that various weather variables used in stock market anomalies have seasonal patterns closely related to their favorite "Sell in May" or Halloween seasonal dummy Bouman and Jacobsen, When weather variables are really fundamental driving forces in stock market returns, the effects should be reasonably stable across countries.

In fact, when considering countries in the northern hemisphere and southern hemisphere with opposite seasonal patterns in the weather, they find that southern hemisphere countries of which there are few exhibit weather effects temperature and daylight opposite to what is expected and suggested by the previous literature. Furthermore, countries close to the equator such as Thailand appear to have the largest response coefficients to weather effects, despite the fact that temperature and daylight in these countries have the smallest variability during the year.

Goetzmann and Zhu cannot find evidence of a weather influence on behavior of investors, examined at the same time but located in different regions. They suggest that the weather effect must be limited to traders and market makers working at the location of the exchange. A cumbersome proposition in today's world of remote access and electronic trading systems. Kelly and Meschke revisit the widely cited Kamstra et al study on Seasonal Affective Disorder SAD and argue that the observed SAD effect is due to a fault in the original empirical specification overlapping-dummy Fall and Winter-Fall SAD.

In another multi-country study, Gregory-Allen, Jacobsen and Marquering reject the Daylight Saving Time effect reported in previous literature as insignificant, largely due to correction of test-statistics for non-normality in daily returns.

Maberly and Pierce show that in the U. To suggest that psychological studies contribute any evidence for systematic patterns in stock market behavior is a leap of faith. See Keller et al for a review of the psychological literature relating weather and mood, and the inconsistent relationships. Gerlach finds that for the U. The Holiday effect suffers the same fate, but is referred to only in a footnote due to the fact that the anomaly is not statistically significant from the start.

The January effect is weakened by eliminating news days, but is the only anomaly to survive. Thus, statistically significant calendar and weather anomalies are not caused by market psychology or institutions but reflect a process of data mining where certain variables happen to coincide with days of news that is important for stock markets. Using days without announcements, there is no evidence for calendar anomalies.

Correlation does not imply causality - examples: Without such an explanation, then you run a big risk that the indicator is based on nothing more than a fluke of the data. My favorite example of why this is so comes from David Leinweber, a visiting faculty member in CalTech's economics department.

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