Econometric Asset Pricing Modelling
提出一种基于无套利假设的计量经济学资产定价方法，通过随机贴现因子和风险中性因子动力学，构建三种建模策略，并应用于证券市场模型和利率期限结构模型，实现灵活的历史动态与可处理的定价公式。
The purpose of this paper is to propose a general econometric approach to no-arbitrage asset pricing modelling based on three main ingredients: (i) the historical discrete-time dynamics of the factor representing the information, (ii) the stochastic discount factor (SDF), and (iii) the discrete-time risk-neutral (RN) factor dynamics. Retaining an exponential-affine specification of the SDF, its modelling is equivalent to the specification of the risk-sensitivity vector and of the short rate, if the latter is neither exogenous nor a known function of the factor. In this general framework, we distinguish three modelling strategies: the direct modelling, the RN constrained direct modelling, and the back modelling. In all the approaches, we study the internal consistency conditions (ICCs), implied by the absence of arbitrage opportunity assumption, and the identification problem. The general modelling strategies are applied to two important domains: security market models and term structure of interest rates models. In these contexts, we stress the usefulness (and we suggest the use) of the RN constrained direct modelling and of the back modelling approaches, both allowing us to conciliate a flexible (non-Car) historical dynamics and a Car (compound autoregressive) RN dynamics leading to explicit or quasi-explicit pricing formulas for various derivative products. Moreover, we highlight the possibility to specify asset pricing models able to accommodate non-Car historical and non-Car RN factor dynamics with tractable pricing formulas. This result is based on the notion of (RN) extended Car process that we introduce in the paper, and which allows us to deal with sophisticated models such as Gaussian and inverse Gaussian GARCH-type models with regime-switching, or Wishart quadratic term structure models.