Abstract
This paper aims to investigate whether including agricultural commodities can improve the portfolio performance by comparing the risk and return of multi-asset portfolio with and without an agricultural commodity price. To achieve our goal, we propose fitting a C-Vine copula based AR-GARCH model to interval data which allows us to capture uncertain characteristics that cannot be sometimes fully described with single data series. By using a convex combination method, we can obtain expected marginal distribution and joint density function, respectively. We then evaluate the portfolios’ risk and return using the expected shortfall concept. The results present that the average risk and return of non-agricultural portfolio outperforms agricultural portfolios. However, considering the one step ahead forecasting efficient frontier, the portfolio with soybean futures becomes superior to other portfolios.
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Acknowledgement
The authors would like to thank Mr. Woraphon Yamaka for a rolling window suggestions. Last but not least, we would like to thank all the referees for giving comments on the manuscript.
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Khiewngamdee, C., Song, Q., Chanaim, S. (2018). The Role of Agricultural Commodity Prices in a Portfolio. In: Huynh, VN., Inuiguchi, M., Tran, D., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2018. Lecture Notes in Computer Science(), vol 10758. Springer, Cham. https://doi.org/10.1007/978-3-319-75429-1_32
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