Abstract
Time series generated by a complex hierarchical system exhibit various types of dynamics at different time scales. A financial time series is an example of such a multiscale structure with time scales ranging from minutes to several years. In this paper we decompose the volatility of financial indices into five intrinsic components and we show that it has a heterogeneous scale structure. The small-scale components have a stochastic nature and they are independent 99% of the time, becoming synchronized during financial crashes and enhancing the heavy tails of the volatility distribution. The deterministic behavior of the large-scale components is related to the nonstationarity of the financial markets evolution. Our decomposition of the financial volatility is a superstatistical model more complex than those usually limited to a superposition of two independent statistics at well-separated time scales.
Authors
Keywords
Computational Methods; superstatistics; econophysics; financial time series analysis; volatility; multiscale structure; nonstationarity of financial markets evolution
Paper coordinates
C. Vamoş, M. Crăciun, Intrinsic superstatistical components of financial time series, The European Physical Journal B 87 (2014): 301, pp. 9,
doi: 10.1140/epjb/e2014-50596-y
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About this paper
Journal
The European Physical Journal B
Publisher Name
Springer Berlin Heidelberg
Print ISSN
1434-6028
Online ISSN
1434-6036
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References
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