Cointegration in high frequency data

Simon Clinet, Yoann Potiron

研究成果: Article査読

抄録

In this paper, we consider a framework adapting the notion of cointegration when two asset prices are generated by a driftless Itosemimartingale featuring jumps with infinite activity, observed regularly and synchronously at high frequency.We develop a regression based estimation of the cointegrated relations method and show the related consistency and central limit theory when there is cointegration within that framework. We also provide a Dickey-Fuller type residual based test for the null of no cointegration against the alternative of cointegration, along with its limit theory. Under no cointegration, the asymptotic limit is the same as that of the original Dickey-Fuller residual based test, so that critical values can be easily tabulated in the same way. Finite sample indicates adequate size and good power properties in a variety of realistic configurations, outperforming original Dickey-Fuller and Phillips-Perron type residual based tests, whose sizes are distorted by non ergodic time-varying variance and power is altered by price jumps. Two empirical examples consolidate the Monte-Carlo evidence that the adapted tests can be rejected while the original tests are not, and vice versa.

本文言語English
ページ(範囲)1263-1327
ページ数65
ジャーナルElectronic Journal of Statistics
15
1
DOI
出版ステータスPublished - 2021

ASJC Scopus subject areas

  • 統計学および確率
  • 統計学、確率および不確実性

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