From Proximity to Correlation: How Different Measures of Distance Shape U.S. Emerging Market Stock Market Co-Movements

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Abstract

This paper extends the gravity model to financial markets by examining how distance and bilateral linkages influence stock market correlations between the United States and selected emerging economies. To this end, the Poisson Pseudo Maximum Likelihood (PPML) estimator is used to account for heteroskedasticity and zero-value observations. Results show that greater economic distance weakens equity market correlations, while larger combined economic mass strengthens them, suggesting that bigger economies foster deeper financial linkages. Moreover, the results show that higher trade intensity between the U.S. and emerging markets results in negative correlations, which are explained by portfolio diversification motives—investors view these markets as substitutes, reallocating funds in opposite directions under varying conditions. The findings highlight how structural factors, distance measures, and trade intensity influence international equity market correlations, providing key insights for portfolio allocation and diversification strategies.

Original languageEnglish
Article number15
JournalEconomies
Volume14
Issue number1
DOIs
Publication statusPublished - Jan 2026

Keywords

  • Poisson Pseudo Maximum Likelihood
  • conditional correlation
  • distance
  • emerging markets

ASJC Scopus subject areas

  • Development
  • Economics, Econometrics and Finance (miscellaneous)

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