A stock split event study using sector-indices vs. CDAX and some extensions of the standard market model
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Seminar paper from the year 2009 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1,3, Humboldt-University of Berlin (Institut für Bank und Börsenwesen), course: Seminar of Banking and Financial Markets, language: English, abstract: There are many theories in literature which try to examine possible reasons for a stock split. While a stock split seems to be just a cosmetic corporate event, it is often claimed that the motivation to carry out a stock split is to signal future profitability or to bring the share price to a preferred trading-range. Add...
Seminar paper from the year 2009 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1,3, Humboldt-University of Berlin (Institut für Bank und Börsenwesen), course: Seminar of Banking and Financial Markets, language: English, abstract: There are many theories in literature which try to examine possible reasons for a stock split. While a stock split seems to be just a cosmetic corporate event, it is often claimed that the motivation to carry out a stock split is to signal future profitability or to bring the share price to a preferred trading-range. Additionally there are many papers published, where the impact of a stock split on liquidity and institutional ownership is examined. Some results of these studies are briefly discussed in the Literature Review.Most researchers calculate their abnormal returns with the market model by using the most common index in their economy. In this paper, I check whether sector-indices fit the data better than the CDAX does. In some cases, the sector-indices describe the stock returns better.Another topic of event studies that researchers of the finance area often deal with is whether the assumptions of the market model established by Fama, Fisher, Jensen and Roll (1969) do hold for daily stock returns. I will discuss some of the weaknesses when applied to financial time series and I present two models which can improve the efficiency of the model.
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