Multivariate time-varying parameter modelling for stock markets


NESLİHANOĞLU S., Bekiros S., McColl J., Lee D.

Empirical Economics, cilt.61, sa.2, ss.947-972, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 61 Sayı: 2
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1007/s00181-020-01896-2
  • Dergi Adı: Empirical Economics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, IBZ Online, International Bibliography of Social Sciences, ABI/INFORM, Business Source Elite, Business Source Premier, EconLit, Geobase, Public Affairs Index
  • Sayfa Sayıları: ss.947-972
  • Anahtar Kelimeler: CAPM, Multivariate model, State space model, Stock market returns, Systematic covariance (beta) risk, Time-varying beta, RISK, EQUILIBRIUM, PORTFOLIOS, BETA
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.This paper evaluates the appropriateness of a Linear Market Model (LMM) which allows for systematic covariance (beta) risk. The performance of LMM will be compared against two extensions, a comparison having yet to be undertaken in the literature. The first extension is the Time-varying Linear Market Model (Tv-LMM) which allows for time-varying systematic covariance risk in the form of a mean reverting state space model via the Kalman filter. The second extension is the multivariate Time-varying Linear Market Model (MTv-LMM) which allows for the time-varying systematic covariance risk of country stock market correlation structure via the multivariate KFMR. The comparison between LMM, Tv-LMM and MTv-LMM, is implemented utilising weekly data collected from several developed and emerging markets for the periods; before and after financial crisis in October 2008, and forecasting 2 years forwards. The empirical findings of that process overwhelmingly support the use of the Multivariate Time-varying Linear Market Model (MTv-LMM) when modelling and forecasting stock market returns, especially for developed stock markets.