A discrete-time model of high-frequency stock returns

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

A model of intraday financial time series is developed. The model is a dynamic factor model consisting of two equations. First, a rate of return of a 'stock' in a single day is assumed to be generated by several common factors plus some additive error ('intraday equation'). Secondly, the joint distribution of those common factors is assumed to depend on the hidden state of the day, which fluctuates according to a Markov chain ('day-by-day equation'). Together the equations compose a hidden Markov model. We investigate properties of the model. Among them is a central limit theorem for cumulative returns, which agrees with the well-known empirical phenomenon in the stock markets that the distributions of longer-horizon returns are closer to the normal. We propose a two-step procedure consisting of the method of principal components and the EM algorithm to estimate the model parameters as well as the unobservable states. In addition, we propose a procedure for predicting intraday returns. Finally, the model is fitted to empirical data, the Standard&Poors 500 Index 5 min return data, to see if the model is capable of describing intraday movements of the index.

Original languageEnglish
Pages (from-to)140-150
Number of pages11
JournalQuantitative Finance
Volume4
Issue number2
DOIs
Publication statusPublished - 2004 Apr
Externally publishedYes

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Discrete-time model
Stock returns
Common factors
Markov chain
Empirical data
Principal components
Dynamic factor model
Central limit theorem
Hidden Markov model
Joint distribution
EM algorithm
Financial time series
Rate of return
Stock market

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)

Cite this

A discrete-time model of high-frequency stock returns. / Hayashi, Takaki.

In: Quantitative Finance, Vol. 4, No. 2, 04.2004, p. 140-150.

Research output: Contribution to journalArticle

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