Modelling risk in agricultural finance: Application to the poultry industry in Taiwan

  • Authors:
  • Biing-Wen Huang;Meng-Gu Chen;Chia-Lin Chang;Michael McAleer

  • Affiliations:
  • Department of Applied Economics, National Chung Hsing University, 250 Kuo Kuang Road, Taichung 402, Taiwan;Department of Applied Economics, National Chung Hsing University, 250 Kuo Kuang Road, Taichung 402, Taiwan;Department of Applied Economics, National Chung Hsing University, 250 Kuo Kuang Road, Taichung 402, Taiwan;School of Economics and Commerce, University of Western Australia, Australia and Faculty of Economics, Yokohama National University, Japan

  • Venue:
  • Mathematics and Computers in Simulation
  • Year:
  • 2009

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Abstract

The volatility in agricultural prices, such as for broiler and color broiler chickens in Taiwan, is similar in various aspects to financial volatility as it relates to the risk and returns associated with agricultural production. However, as the characteristics of agricultural markets may be different from financial markets, the results arising from empirical risk analysis need to be investigated. The broiler and color broiler industries are the second and third largest livestock industries in Taiwan. When Taiwan applied to join the World Trade Organization (WTO) in the 1990s, these two industries faced the threat of deregulation of chicken meat imports. However, developments in these two industries have not been the same under deregulation, with the level of competition in the broiler and color broiler industries being markedly different. The purpose of the paper is to model the prices, growth rates and their respective volatilities in weekly broiler and color broiler chicken prices in Taiwan from January 1995 to June 2007. The empirical results show that the time series of broiler and color broiler prices, their logarithms and their growth rates are stationary, and that the estimated symmetric and asymmetric conditional volatility models all fit the data extremely well. The empirical second moment and log-moment conditions also support the statistical adequacy of the estimated volatility models. The empirical results have significant implications for risk management and policy considerations in the agricultural production industry in Taiwan.