Calendar studies, Financial Management

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Calendar Studies

These attempted to predict rates of return during a calendar year and examine if there is any particular observable pattern in the rates of return on the stocks that would allow investors to predict returns on stocks in advance. They also test for the presence of any irregularities. Besides "January Anomaly", they also consider a variety of other daily and weekly regularities.

The January Anomaly: This was proposed as a unique trading rule to make use of tax selling. Most investors are observed to adopt tax selling at the end of the year to establish losses on stocks that have declined and re-acquire the same shares in the next year or buy other stocks that are attractive. This tendency of the investors leads to a downward pressure on the stock prices during the end of the year (November and December) and positive pressure during the beginning (January) of the next year. This is termed January Anomaly. The advocates of the efficient markets believe that this kind of seasonal pattern does not last for a longer period as it is likely to be eliminated by arbitrageurs' action of buying in December and selling in January of the next year.

Several studies conducted by different people at different points of time supported this January Anomaly. December trading volume was found to be abnormally high for the stocks that have declined during the previous year and the volume was low for stocks that have experienced large gains.

Another observation confirmed that the price patterns on the last day of December and the first four days of January support the anomaly. The presence of transaction costs does not deter the arbitrageurs from engaging in the January tax selling anomaly.

One of the studies indicated the existence of a negative relationship between size and abnormal returns. More than 50% of the January effect would be concentrated in the first week of trading, particularly on the first day of the year. In addition, a non-linear relationship is found to exist between dividend yields and stock returns in January. A strong seasonal pattern was also observed because the dividend yield-stock return relationship existed only during January. The year end effect was also observed for small firms particularly during the last day of the year with above normal trading activity continuing in January.

All the studies reveal that the January Anomaly is intriguing because it is pervasive. The seasonal impact also influences the dividend yield effect and trading volume, and a tax-loss explanation of this anomaly has received a mixed support.

 


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