不完全会计信息下消费均衡框架下的信用风险定价

IF 1.6 3区 经济学 Q3 BUSINESS, FINANCE
Junchi Ma, Mobolaji Ogunsolu, Jinniao Qiu, Ayşe Deniz Sezer
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引用次数: 1

摘要

我们提出了一个基于消费的信用风险定价均衡框架,该框架基于Epstein-Zin (EZ)偏好,其中违约时间被建模为违约边界的首次到达时间,债券投资者对公司价值具有不完全/部分信息。不完全信息是由底层的观测状态变量和一个有噪声的确定值观测过程产生的。此外,消耗、波动和企业价值过程建模遵循仿射扩散过程。利用EZ均衡解作为定价内核,我们提供了一种等价的定价方法来计算金融衍生品的价格,作为在不完全信息下未来收益的贴现值。零息债券的价格用随机偏微分方程(SPDE)和确定性偏微分方程的解来表示;给出了这一表述和所涉及的SPDE的适定性的自包含证明。此外,对该SPDE进行了数值求解,从而对收益率差结构与模型参数之间的关系有了一些深入的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Credit risk pricing in a consumption-based equilibrium framework with incomplete accounting information

Credit risk pricing in a consumption-based equilibrium framework with incomplete accounting information

We present a consumption-based equilibrium framework for credit risk pricing based on the Epstein–Zin (EZ) preferences where the default time is modeled as the first hitting time of a default boundary and bond investors have imperfect/partial information about the firm value. The imperfect information is generated by the underlying observed state variables and a noisy observation process of the firm value. In addition, the consumption, the volatility, and the firm value process are modeled to follow affine diffusion processes. Using the EZ equilibrium solution as the pricing kernel, we provide an equivalent pricing measure to compute the prices of financial derivatives as discounted values of the future payoffs given the incomplete information. The price of a zero-coupon bond is represented in terms of the solutions of a stochastic partial differential equation (SPDE) and a deterministic PDE; the self-contained proofs are provided for both this representation and the well-posedness of the involved SPDE. Furthermore, this SPDE is numerically solved, which yields some insights into the relationship between the structure of the yield spreads and the model parameters.

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来源期刊
Mathematical Finance
Mathematical Finance 数学-数学跨学科应用
CiteScore
4.10
自引率
6.20%
发文量
27
审稿时长
>12 weeks
期刊介绍: Mathematical Finance seeks to publish original research articles focused on the development and application of novel mathematical and statistical methods for the analysis of financial problems. The journal welcomes contributions on new statistical methods for the analysis of financial problems. Empirical results will be appropriate to the extent that they illustrate a statistical technique, validate a model or provide insight into a financial problem. Papers whose main contribution rests on empirical results derived with standard approaches will not be considered.
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