Extreme price moves: an INGARCH approach to model coexceedances in commodity markets
研究提出整数型广义自回归条件异方差模型，识别农产品共同极端价格变动的传导渠道，发现新兴市场需求、原油、汇率、股市和信用利差能解释极端联合收益，心理因素和周一效应也有影响，但天气异常无解释力。
Abstract This study presents a set of integer-valued generalised autoregressive conditional heteroskedastic models to identify possible transmission channels of joint extreme price moves (coexceedances) across a group of agricultural commodities. These models are very useful to identify factors affecting joint tail events and they are superior in terms of goodness of fit to models without autoregressive components. Emerging market demand, crude oil, exchange rate, stock market conditions and credit spread explain extreme joint returns. Psychological factors and the Monday effect play a role in affecting extreme events, while weather anomalies (El Niño and La Niña episodes) do not have explanatory power.