Luo Cuicui, Wu Desheng
Stockholm Business School, Stockholm University, Stockholm, Sweden.
University of Chinese Academy of Sciences, No.80, Zhongguancun East Road Haidian District, Beijing, 100190, China.
Environ Res. 2016 Aug;149:297-301. doi: 10.1016/j.envres.2016.02.007. Epub 2016 Feb 24.
Climate change has been one of the biggest and most controversial environmental issues of our times. It affects the global economy, environment and human health. Many researchers find that carbon dioxide (CO2) has contributed the most to climate change between 1750 and 2005. In this study, the orthogonal GARCH (OGARCH) model is applied to examine the time-varying correlations in European CO2 allowance, crude oil and stock markets in US, Europe and China during the Protocol's first commitment period. The results show that the correlations between EUA carbon spot price and the equity markets are higher and more volatile in US and Europe than in China. Then the optimal portfolios consisting these five time series are selected by Mean-Variance and Mean-CVAR models. It shows that the optimal portfolio selected by MV-OGARCH model has the best performance.
气候变化一直是我们这个时代最大且最具争议性的环境问题之一。它影响着全球经济、环境和人类健康。许多研究人员发现，在1750年至2005年期间，二氧化碳（CO₂）对气候变化的影响最大。在本研究中，采用正交广义自回归条件异方差（OGARCH）模型来检验《京都议定书》第一个承诺期内欧洲二氧化碳配额市场、原油市场以及美国、欧洲和中国股票市场之间的时变相关性。结果表明，美国和欧洲的欧盟排放配额（EUA）碳现货价格与股票市场之间的相关性高于中国，且波动性更大。然后通过均值 - 方差模型和均值 - 条件风险价值（Mean - CVAR）模型选择由这五个时间序列组成的最优投资组合。结果表明，由均值 - 方差 - 正交广义自回归条件异方差（MV - OGARCH）模型选择的最优投资组合表现最佳。
