In this paper we compare counterfactual corporate bond issuing dates to actual issuing dates in order to test the ability of firms to time the credit market. The 50 most active bond issuing financial firms and the 50 most active industrial firms are studied using one week, one month, and one quarter windows. The ability to time firm-specific CDS prices is studied from January 2002 - October 2009. The ability to time the risk-free rate (10 year US government bond) is studied from January 1988 - October 2009. We find that: firms do not successfully time the risk-free rate or the credit spreads. There is no evidence of CDS timing ability over one week or one month, but there is some borderline evidence at one quarter. For a typical bond issue, the firm loses about 1% of the face value of the bond relative to a 1 month window, due to their inability to time the market. If the firms could improve their market timing, they could save many hundreds of millions of dollars. Since there is a degree of statistical predictability in the data, we find it surprising that these firms are not able to do a better job of timing the credit market.

This paper consists of two parts. In the first part, through the calculation of “binomial correlation measure”, we suggest that from the perspective of default correlation it would be better to use structural approach rather than reduced form approach for pricing derivatives with two counterparties and its CVA calculation unless default intensities follow jump-diffusion process in latter one. In the second part, we derive the pricing model for CDS with counterparty risk and its CVA calculation by Black-Cox first passage time model in structural approach. Different from most of the previous paper our recovery is based on the CDS with counterparty risk, so the pricing model is a boundary-value problem of fully-nonlinear PDE. To solve it, we introduce an approximation problem by penalty model in reduced form approach by assuming an incentive function. Also finite element method and iteration approach are used. The numerical results show the convergence of approximation problem, iteration problem and finite element method, a comparison between CVA with different recovery rules and also the impact of wrong-way risk and right-way risk on CVA.

作为一种特殊的大宗商品，黄金具有商品、货币和避险的多重属性。在07年开始的金融危机中，黄金表现出了较强的货币和避险属性，而过去的研究很少有涉及到其避险属性。本文就当前货币体系下的黄金定价问题，综合考虑了黄金的大宗商品、货币和避险属性，将黄金价值分解为：商品基准价值、基于汇率的“隐性货币价值”、主权国家信用违约的风险溢价，并分别以大宗商品CRB指数、美元指数USDX和美国国债CDS利差等资产价格作为代理变量对其进行定价研究。基于向量自回归（VAR）模型的研究表明：美元指数USDX负向驱动黄金价格，大宗商品指数CRB、美国国债指数CDS正向驱动黄金价格；其中大宗商品指数CRB滞后一阶、美元指数USDX滞后一阶、美国国债CDS利差滞后二阶价格信息对黄金价格的影响最显著。研究还表明：黄金价格波动率存在聚类性、长记忆性，但不存在非对称性。

作为一种特殊的大宗商品，黄金具有商品、货币和避险的多重属性，在此次金融危机中，黄金表 现出了较强的货币和避险属性。就当前货币体系下的黄金定价问题：本文提出了一个基于各大类资产时间 序列定价（大类资产定价）的新思路，模型综合考虑了黄金的商品、货币和避险属性，将黄金价值分解为： 商品基准价值、基于汇率（货币篮子）的“隐性货币价值”和主权国家信用违约的风险溢价，并分别以大宗 商品CRB指数、美元指数USDX和美国国债CDS利差等资产价格作为代理变量对其进行定价研究。向量自 回归（VAR）模型研究表明：美元指数USDX负向驱动黄金价格，大宗商品指数CRB、美国国债指数CDS 正向驱动黄金价格；其中大宗商品指数CRB滞后一阶、美元指数USDX滞后一阶、美国国债CDS利差滞后 二阶价格信息对黄金价格的影响最显著。研究还表明：黄金价格波动率存在聚类性、长记忆性，但不存在 非对称性。