Change point dynamics for financial data: an indexed Markov chain approach

Guglielmo D’Amico (), Ada Lika and Filippo Petroni
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Guglielmo D’Amico: Università “G. D’Annunzio” di Chieti-Pescara
Ada Lika: Università degli studi di Cagliari
Filippo Petroni: Università degli studi di Cagliari

Annals of Finance, 2019, vol. 15, issue 2, No 5, 247-266

Abstract: Abstract This paper uses an Indexed Markov Chain to model high frequency price returns of quoted rms. Introducing an Index process permits consideration of endogenous market volatility, and two important stylized facts of financial time series can be taken into account: long memory and volatility clustering. This paper rst proposes a method to optimally determine the state space of the Index process, which is based on a change-point approach for Markov chains. Furthermore, we provide an explicit formula for the probability distribution function of the rst change of state of the Index process. Results are illustrated with an application to intra-day firm prices.

Keywords: Change point; Financial returns; Volatility; Intra-day prices (search for similar items in EconPapers)
JEL-codes: C02 G30 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10436-018-0337-0

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