Dynamic Autocorrelation and International Portfolio Allocation

Jyri Kinnunen, Minna Martikainen

Research output: Contribution to journalArticleScientificpeer-review


We explore the relevance of dynamic autocorrelation in modeling expected returns and allocating funds between developed and emerging stock markets. Using stock market data for the US and Latin America, we find that autocorrelation in monthly returns vary with conditional volatility, implying some investors implement feedback trading strategies. Dynamic autocorrelation models fit the data considerably better than a conditional version of the zero-beta CAPM, while differences between models with an autoregressive term are modest. Investors can improve their portfolio optimization between developed and emerging stock markets by considering time-varying autocorrelation. The most drastic difference in portfolio performance is not due to allowing autocorrelation to vary over time, but realizing that stock returns are autocorrelated, especially in emerging stock markets.
Original languageEnglish
Peer-reviewed scientific journalMultinational Finance Journal
Issue number1
Pages (from-to)21-48
Number of pages28
Publication statusPublished - 24.09.2018
MoE publication typeA1 Journal article - refereed


  • 512 Business and Management
  • autocorrelation
  • volatility
  • portfolio
  • international
  • emerging markets


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