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The Impact of Mergers and Acquisition Activity on the Time Series Variation in the Stock Size Premium
Kaplan, Robert ; Novák, Jiří (advisor) ; Geršl, Adam (referee)
This work studies whether intertemporal variation in future takeover activity explains intertemporal changes in stock size premium. Taking into account that takeover activity involves 2-9% of firms every year and building upon existing research stating that small firms are more likely takeover targets, receive 40% higher takeover premium than large firms, we argue that small firms benefit from high takeover activity more than large firms and size premium should be more pronounced in the time of high takeover activity. We study takeover activity as well as stock size premium on aggregate level and test whether size premium can be explained by the expected takeover activity, i.e. its change compared to past. We find that change in takeover activity in the next six months versus last six months is positively correlated with size premium. Additionally, we construct a simple predictive model for estimating future takeover activity. The relation between size premium and change in takeover activity remains significant when we use forecasted values given by the predictive model instead of true future values in the model.
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The fractal dimension and forecasting of financial time series
Kaplan, Robert ; Krištoufek, Ladislav (advisor) ; Džmuráňová, Hana (referee)
In this thesis, we strive to build on the fractal market hypothesis and to develop two methods which aim to reveal whether the fractal dimension, as a property of the short memory, can be applied for forecasting of financial time series. In the first one, we use ten world market indices and repeatedly estimate the fractal dimension by boxcount, Hall-Wood, and Genton estimators on fixed number of returns and make one step ahead forecasts by AR(1) and ARMA(1,1) models; then, we look whether forecast errors from realized returns are lower when the fractal dimension is estimated lower. The second method incorporates only the fractal dimension and studies, if the sign of return persists in next period more likely with lower fractal dimension. The results indicate that the short memory is truly present in the markets and the fractal dimension may be potentially useful for prediction and increased profit for investors. However, the significance of our results is not strong. We recommend more sophisticated methods and models for further research.
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