Measuring multiscaling in financial time-series

Riccardo Junior Buonocore, Tomaso Aste and Tiziana Di Matteo

Papers from arXiv.org

Abstract: We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analysing the multi/uni-scaling behaviour of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range [2,5]. We discuss the right aggregation horizon to mitigate this bias.

Date: 2015-09, Revised 2015-09
New Economics Papers: this item is included in nep-ecm and nep-ets
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