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Volume 21, Number 1 / March 2017 , Pages 1-48
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Asymmetric Fund Performance Characteristics A Comparison of European and US Large-Cap Funds
Multinational Finance Journal, 2017, vol. 21, no. 1, pp. 1-20
Kenneth Högholm
, Hanken School of Economics, Finland
Johan Knif
, Hanken School of Economics, Finland
Corresponding Author
Email: johan.knif@hanken.fi
Gregory Koutmos
, Fairfield University, USA
Seppo Pynnönen
, University of Vaasa, Finland
Abstract:
The paper focuses on asymmetric fund performance by comparing performance characteristics of European and US large-cap mutual equity funds. The quantile approach applied enables the monitoring of fund performance across different conditional outcome scenarios. For the sample of 31 European and 35 US large-cap mutual equity funds the performance is found to be sensitive to the empirical estimation approach applied. Furthermore, the performance alphas exhibit asymmetry across the conditional return distribution. This asymmetric performance behavior might be utilized for the construction of a portfolio of funds with suitable hedge characteristics. A large part of the US individual funds significantly underperforms the benchmark, especially in the lower tail of the conditional distribution. A few of the European funds, on the other hand, exhibit significant and positive performance alphas in the lower tail of the conditional return distribution.
Keywords : asymmetric fund performance; european equity funds; US equity funds
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Dynamic Autocorrelation and International Portfolio Allocation
Multinational Finance Journal, 2017, vol. 21, no. 1, pp. 21-48
Jyri Kinnunen
, Hanken School of Economics, Finland
Corresponding Author
Email: jyri.kinnunen@hanken.fi
Minna Martikainen
, Hanken School of Economics, Finland
Abstract:
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.
Keywords : autocorrelation; volatility; portfolio; international; emerging markets
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