Stylised facts of financial time series and hidden Markov models in continuous time

Peter Nystrup, Henrik Madsen, Erik Lindström

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Abstract

Hidden Markov models are often applied in quantitative finance to capture the stylised facts of financial returns. They are usually discrete-time models and the number of states rarely exceeds two because of the quadratic increase in the number of parameters with the number of states. This paper presents an extension to continuous time where it is possible to increase the number of states with a linear rather than quadratic growth in the number of parameters. The possibility of increasing the number of states leads to a better fit to both the distributional and temporal properties of daily returns.
Original languageEnglish
JournalQuantitative Finance
Volume15
Issue number9
Pages (from-to)1531-1541
ISSN1469-7688
DOIs
Publication statusPublished - 2015

Keywords

  • Hidden Markov models
  • Continuous time
  • Daily returns
  • Leptokurtosis
  • Volatility clustering
  • Long memory

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