摘要
本文构建了基于条件信息的因子定价模型,并运用基于GMM(generalized method ofmoments)估计的实证框架对此模型进行实证研究.实证结果显示:1.条件定价模型确实在定价中确实加工了条件信息;2.预测性越强的条件信息变量对定价越起到决定性作用;3.各国代表性投资者对条件信息的理解存在差异,但整体来说跨期对冲原理和动态策略原理两种条件信息使用方法在定价中的重要性持平;4.与其他西方发达国家相比,中国条件信息变量对债券回报率的预测能力和方向存在较大偏差,且经济体系受到全球经济衰退的影响较小.在定价模型中合理使用条件信息有助于更好地解释债券回报率中的风险溢价补偿关系,而对条件定价研究也是金融经济学中极具前途的一个发展方向.
This paper constructs a conditional factor pricing model and accommodates it in the framework of GMM and this yields rich testable hypothesis. The main conclusions can be summarized as below：Our conditional pricing models indeed consider the conditional information in pricing, and conditional information variables which have more predicting power will be more decisive in pricing. Globally speaking though representative investors from different countries will take different views on same conditional information, and their incentives to inter-temporal hedging and dynamic strategy are comparable. Furthermore, conditional information variables in China differ from those countries in their predictability power and direction, while the economy system in China seems to receive less influence from global recessions. In all, we claim conditional information are helpful with describing the risk-premium trade-off in bond returns, and it makes conditional asset pricing a promising endeavor in future researches of financial economics.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2016年第11期2820-2828,共9页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(71471142)~~
关键词
条件信息
因子定价模型
GMM估计
conditional information
factor pricing model
GMM estimation
