• Medientyp: E-Artikel
  • Titel: Market frictions and the geographical location of global stock exchanges. Evidence from the S&P Global Index
  • Beteiligte: Gregoriou, Andros; Hudson, Robert
  • Erschienen: Emerald, 2020
  • Erschienen in: Journal of Economic Studies, 48 (2020) 2, Seite 354-366
  • Sprache: Englisch
  • DOI: 10.1108/jes-03-2020-0091
  • ISSN: 0144-3585
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: PurposeWe examine the impact of market frictions in the form of trading costs on investor average holding periods for stocks in the S&P global 1200 index to examine constraints on international portfolio diversification.Design/methodology/approachWe determine whether it is appropriate to pool stocks listed in the USA, Canada, Latin America, Europe, Japan, Asia and Australia into investigations using the same empirical specification. This is very important because the pooled effects may not provide consistent estimates of the average.FindingsWe report overwhelming econometric evidence that it is not valid to pool stocks in all the underlying regional equity indices for our investigation, indicating that the effect of frictions varies between markets.Research limitations/implicationsWhen we pool the stocks within markets, we discover that for companies listed in the USA, Europe, Canada and Australia, market frictions do not significantly influence holding periods and hence are not a barrier to portfolio rebalancing. However, companies listed in Latin America and Asia face market frictions, which are significant in terms of increasing holding periods.Practical implicationsWe ascertain that taking into account the properties of stock markets in different geographical locations is vital for understanding the limits on achieving international portfolio diversification.Originality/valueUnlike prior research, we overcome the problems caused by contemporaneous correlation, endogeneity and joint determination of investor average holding periods and trading costs by employing the Generalized Method of Moments (GMM) system panel estimator. This makes our empirical estimates robust and more reliable than the previous empirical research in this area.