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Dynamic Autocorrelation and International Portfolio Allocation

Jyri Kinnunen & Minna Martikainen

Multinational Finance Journal2017article
AJG 1ABDC B
Weight
0.34

What the paper says

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.

1 citation

Cite this paper

@article{jyri2017,
  title        = {{Dynamic Autocorrelation and International Portfolio Allocation}},
  author       = {Jyri Kinnunen & Minna Martikainen},
  journal      = {Multinational Finance Journal},
  year         = {2017},
}

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Evidence weight

0.34

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.00 × 0.4 = 0.00
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.