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Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations

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  • Martin Rypdal
  • Espen Sirnes
  • Ola L{\o}vsletten
  • Kristoffer Rypdal

Abstract

Maximum likelihood estimation applied to high-frequency data allows us to quantify intermittency in the fluctu- ations of asset prices. From time records as short as one month these methods permit extraction of a meaningful intermittency parameter {\lambda} characterising the degree of volatility clustering of asset prices. We can therefore study the time evolution of volatility clustering and test the statistical significance of this variability. By analysing data from the Oslo Stock Exchange, and comparing the results with the investment grade spread, we find that the estimates of {\lambda} are lower at times of high market uncertainty.

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File URL: http://arxiv.org/pdf/1202.4877
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Paper provided by arXiv.org in its series Papers with number 1202.4877.

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Date of creation: Feb 2012
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Handle: RePEc:arx:papers:1202.4877

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  8. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
  9. Czarnecki, Łukasz & Grech, Dariusz & Pamuła, Grzegorz, 2008. "Comparison study of global and local approaches describing critical phenomena on the Polish stock exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6801-6811.
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  11. Sun, Xia & Chen, Huiping & Yuan, Yongzhuang & Wu, Ziqin, 2001. "Predictability of multifractal analysis of Hang Seng stock index in Hong Kong," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 473-482.
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