Dynamic cross-autocorrelation in stock returns

Jyri Kinnunen

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

I investigate whether the cross-autocorrelation pattern of US small- and large-firm returns changes with the variance of returns using an exponential vector autoregressive model with volatility. The model allows the testing of dynamic cross-autocorrelation effects, while controlling for own time-varying autoregressive coefficients. Using daily and weekly data from 1965 to 2015, a constant cross-autocorrelation pattern is rejected. Returns on a large-firm portfolio are found to lead returns on a small-firm portfolio. The lead-lag relation changes over time with the variance of the large-firm returns. Traditional vector autoregressions with constant cross-autoregressive coefficients appear to be overly restrictive when testing lead-lag relations in stock markets.
Original languageEnglish
Peer-reviewed scientific journalJournal of Empirical Finance
Volume40
Issue numberJanuary
Pages (from-to)162-173
Number of pages12
ISSN0927-5398
DOIs
Publication statusPublished - 09.2016
MoE publication typeA1 Journal article - refereed

Keywords

  • 512 Business and Management
  • Autocorrelation
  • Cross-autocorrelation;
  • Volatility
  • Vector autoregressive model
  • Exponential autoregressive model

Fingerprint Dive into the research topics of 'Dynamic cross-autocorrelation in stock returns'. Together they form a unique fingerprint.

  • Cite this