Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions

Siem Jan Koopman, Rutger Lit and Andre Lucas
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Rutger Lit: VU University Amsterdam, the Netherlands

Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We investigate the intraday dependence pattern between tick data of stock price changes using a new time-varying model for discrete copulas. We let parameters of both the marginal models and the copula vary over time using an observation driven autoregressive updating scheme based on the score of the conditional probability mass function with respect to the time-varying parameters. We apply the model to high-frequency stock price changes expressed as discrete tick-size multiples for four liquid U.S. financial stocks. Our modeling framework is based on Skellam densities for the marginals and a range of different copula functions. We find evidence of intraday time-variation in the dependence structure. After the opening and before the close of the stock market, dependence levels are lower. We attribute this finding to more idiosyncratic trading at these times. The introduction of score driven dynamics in the dependence structure significantly increases the likelihood values of the time-varying copula model. By contrast, a fixed daily seasonal dependence pattern clearly fits the data less well.

Keywords: time-varying copulas; dynamic discrete data; score driven models; Skellam distribution; dynamic dependence (search for similar items in EconPapers)
JEL-codes: C32 G11 (search for similar items in EconPapers)
Date: 2015-03-19
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-mst
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20150037

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