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A1334
Title: Wavelet analysis applied to directors dealings Authors:  Michaela Kiermeier - University of Applied Sciences Darmstadt (Germany) [presenting]
Abstract: The validity of efficient market hypotheses have been tested in a multitude of econometric settings. We investigate if insiders have superior information with which the market can be outperformed in a statistically significant way. For this purpose, we analyze data on insider trades from various European countries that have not been analyzed before and estimate returns on performances by insiders or outsiders who could use information on insiders trade activities. A common problem with this approach however is that expected returns have to be modelled using factor models like CAPM or APT. We use wavelet analysis to distinguish between expected returns and noise. A second application for wavelet analysis is concerned with the time period insider information might be able to generate outperformance. We therefore filter the return data and analyze the performance scale-by-scale.