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Risks 2015, 3(2), 219-233; doi:10.3390/risks3020219

Multiscale Analysis of the Predictability of Stock Returns

Cracow University of Economics, Rakowicka 27, 31-510 Kraków, Poland
Academic Editors: Mogens Steffensen and Gurdip Bakshi
Received: 16 April 2015 / Accepted: 1 June 2015 / Published: 8 June 2015
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Abstract

Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were varying degrees to which these tools complied with the formal definitions of efficiency and predictability. In our earlier work, we analysed the predictability of stock returns at two time scales using the entropy rate, which can be directly linked to the mathematical definition of predictability. Nonetheless, none of the above-mentioned studies allow any general understanding of how the financial markets work, beyond disproving the Efficient-Market Hypothesis. In our previous study, we proposed the Maximum Entropy Production Principle, which uses the entropy rate to create a general principle underlying the price formation processes. Both of these studies show that the predictability of price changes is higher at the transaction level intraday scale than the scale of daily returns, but ignore all scales in between. In this study we extend these ideas using the multiscale entropy analysis framework to enhance our understanding of the predictability of price formation processes at various time scales. View Full-Text
Keywords: predictability; market efficiency; information theory predictability; market efficiency; information theory
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Fiedor, P. Multiscale Analysis of the Predictability of Stock Returns. Risks 2015, 3, 219-233.

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