非参数利率上限定价:对“无跨越随机波动”的启示

Tao Wu
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引用次数: 1

摘要

资产价格取决于两个要素:状态变量的动态和定价内核。传统的期限结构模型在因素动力学上有所不同。然而,它们中的大多数都包含对数线性定价内核。本文运用非参数方法实证研究了因子动力学和定价核在利率衍生品定价中的作用。我们发现,利率上限价格对因子动态的规范非常敏感,特别是当它们接近到期时。此外,非线性对数定价核改进了长期上限的定价,尽管仍然存在显著的定价误差。最近的研究证明,模型与伦敦银行同业拆借利率和掉期利率相符,但不能很好地为衍生品定价,从而导致了所谓的“无跨度随机波动之谜”。似乎需要额外的波动因素来解释上限价格。然而,利率上限与基础LIBOR和掉期利率之间的相对错误定价也可能是由于所使用的参数模型规格不当。本文从非参数的角度提供了无跨度随机波动的证据。
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Nonparametric Interest Rate Cap Pricing: Implications for the 'Unspanned Stochastic Volatility'
Asset prices depend on two elements: the dynamics of the state variables and the pricing kernel. Traditional term structure models differ in factor dynamics. However, most of them imply a log-linear pricing kernel. We investigate empirically the role of factor dynamics and pricing kernel in pricing interest rate derivatives using a nonparametric approach. We find that interest rate cap prices are very sensitive to the specification of factor dynamics, especially when they are close to expiration. In addition, nonlinear log-pricing kernels improve the pricing of long-maturity caps, although significant pricing errors remain. Recent research document models that fit LIBOR and swap rates but do not price derivatives well, leading to the so called "unspanned stochastic volatility puzzle". Additional volatility factors seem to be needed to explain cap prices. However, the relative mispricing between interest rate caps and underlying LIBOR and swap rates could also potentially be due to mis-specifications of the parametric models used. Our paper provides evidence for unspanned stochastic volatility from a nonparametric perspective.
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