【摘要】 实体经济是国民经济的基础和命脉，实体经济活动的预测对政策制定、企业发展以及投资行为都具有十分重要的现实意义。基于GJR-GARCH模型，采用我国上证50ETF期权价格数据，结合滤波历史模拟方法估计经验定价核，从中提取出代表性投资者的隐含风险厌恶。进一步地，选取全国居民消费价格总指数、社会固定资产投资总额、社会消费品零售总额和制造业PMI指数四个指标作为我国实体经济活动代理变量，通过建立灵活的混合数据抽样预测回归模型，考察代表性投资者的隐含风险厌恶是否能够预测我国实体经济活动。实证结果表明，隐含风险厌恶包含了市场前瞻性信息，对于我国实体经济活动具有一定的预测作用；隐含风险厌恶对于社会固定资产投资总额、社会消费品零售总额和制造业PMI指数具有较好的预测能力。更多还原

【Abstract】 The real economy is the foundation and lifeline of the national economy, and the prediction of real economic activity is of great importance to policy makers, firms and investors. This paper adopts the GJR-GARCH model combined with the filtered history simulation method to estimate the empirical pricing kernel and to extract the representative investor’s implied relative risk aversion by using the China’s SSE 50 ETF option price data. Further, using national consumer price index, total social fixed asset investment, total retail sales of social consumer goods and manufacturing PMI index as the proxies of China’s real economic activity, we propose the flexible mixed-data sampling predictive regression model to investigate whether the representative investor’s implied risk aversion predicts the growth of China’s real economic activity. The empirical results show that implied risk aversion contains forward-looking information, which predicts China’s real economic activity. Specifically, the implied risk aversion predicts total social fixed asset investment, total retail sales of social consumer goods and manufacturing PMI index.更多还原