On multifractality and predictability of financial time series
Author: | Mgr. Michael Heller |
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Year: | 2021 - summer |
Leaders: | prof. PhDr. Ladislav Krištoufek Ph.D. |
Consultants: | |
Work type: | Finance, Financial Markets and Banking Masters |
Language: | English |
Pages: | 141 |
Awards and prizes: | |
Link: | https://dspace.cuni.cz/handle/20.500.11956/150423 |
Abstract: | The aim of this thesis is to examine an empirical relationship between multifractality of financial time series and its returns. We approach the multifractality of a given time series as a measure of its complexity. Multifractal financial time series exhibit repeating self-similar patterns. Multifractality could be a good predictor of stock returns or a factor which can be used in asset pricing. We expected that capturing the complexity of a given time series by a model, a positive or a negative risk premia for investing into “more multifractal assets” could be found. Daily prices of 31 stock indices and daily returns of 10-years US government bonds were downloaded. All the data were recorded between 2012 and 2021. After estimation the multifractal spectra, applying MF-DFA method, of all stock indices, we ordered all stock indices from the lowest to the most multifractal. Then, we constructed a “multifractal portfolio” holding a long position in the 7 most multifractal and holding a short position in the 7 least multifractal stock indices. Fama-MacBeth regression with market risk premia and multifractal variable as independent variables was applied. Multifractality in all examined financial time series was found. We also found a very low negative risk premia for holding “a multifractal portfolio”. These results suggest that “more multifractal assets” are connected with lower returns and with lower risks in average. According to our results, an investor seeking a lower risk and lower return in average should hold a long position in “more multifractal assets” and hold a short position in “less multifractal assets” with respect to the market. |