基于第一HJ距离的线性因子模型设定检验

模型设定检验是金融建模的重要环节,是减少模型风险的关键步骤.本文基于Hansen和Jagannathan1]提出的第一HJ距离模型误设测度,以台湾市场丰富的股票和指数期权数据为基础,对8种常见的线性因子模型(包括基于金融资产价格的线性因子模型)进行模型误设检验,并探究模型设定对参数检验的影响.研究发现:在5%的显著性水平下,所有无条件信息模型均存在模型误设问题,仅FF3、LM、VanM、SkewM的条件信息模型成为可接受的正确模型;同时,是否考虑模型可能误设会影响SDF参数的检验,考虑模型可能误设能更有效地侦测因子的定价能力,而不考虑模型可能误设会高估模型SDF参数的t值绝对值,致使部分因子可能存在"伪"定价现象.

Linear factor models' model specification test based on the first HJ distance

Model Specification Test is a key step in financial modeling to reduce the model risk.Based on the first HJ distance proposed by Hansen and Jagannthan(1997), Taiwan market data are used to test the model specifications of eight linear factor models (including models based on financial asset prices), and the impacts of model specification assumptions on parameter tests are discussed.The paper finds that, under the 5% significance level, there exists model misspecification problems for all unconditional models and only the conditional versions of FF3, LM, VanM and SkewM are acceptable right models.Meanwhile, taking potential model misspecification into account may detect the factors' pricing ability more efficiently.Assuming a model is rightly specified overestimates the t absolute values of SDF parameters, resulting in a"pseudo-pricing" for some parts of the factors.