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Convertible Bond Pricing with Stochastic Volatility

机译:具有随机波动率的可转换债券定价

摘要

The aim of this paper is to compare the performance of different pricing models in valuing bonds with callable and convertible features. Additionally, we wish to provide a theoretical foundation and derivations of the models as we move through the paper. Much of the foundations for our approach to convertible bonds pricing,including optimal conditions for call and conversion, can be attributed to Ingersoll (1976) and Brennan and Schwartz (1977). These fundamental pricing conditions can then be built upon to arrive at more elaborate and numerically sophisticated models with the objective of more accurately pricing derivative securities. The Black-Scholes (BS) model is the most commonly used model in valuing short term derivative instruments, such as equity derivatives, for example. As for longer term securities, such as convertible bonds, movements in volatility and interest rates are likely to have a compounding effect. Consequently, we conjecture that that allowing for stochastic volatility and stochastic interest rates within the pricing of these longer term instruments is preferable. Additionally, given the much larger size of the fixed income derivatives markets when compared to other derivatives, it seems that the answer as to which pricing model is preferable carries significance.As to the findings with regard to equity derivatives, Bakshi, Cao, and Chen (1997) conclude that "taking stochastic volatility into account is of the first order importance in improving on the BS formula", but "going from the SV to the SVSI does not necessarily improve the fit much further." Firstly we shall look at pricing equity derivatives and convertible bonds using a more basic BS framework, then comparing this to the more complex SV and SVSI models later on in the paper. As for numerical pricing procedures, we concentrate on the use of the ADI finite difference method in order to estimate derivative values. Given the multiple variables that we wish to model, including firm value, volatility, and interest rates, we want apricing procedure that is both accurate and computationally efficient. Whilst the ADI method is ideal for this situation, monte-carlo simulation is also an attractive approach to pricing convertible bonds. Indeed, in the case where the value of the option is path dependant, monte-carlo simulation is the ideal choice. To see examples of finite difference techniques used in the context of convertible bonds pricing, see Andersen and Buffum (2002). Alternatively, for a look into monte-carlo simulation, see Lvov, Yigitbasioglu, and Bachir (2004).
机译:本文旨在比较具有可赎回和可转换特征的债券定价中不同定价模型的表现。此外,我们希望在本文中提供模型的理论基础和推导。我们可转换债券定价方法的许多基础,包括看涨期权和转换的最佳条件,都可以归因于Ingersoll(1976)和Brennan and Schwartz(1977)。然后,可以基于这些基本定价条件,以得出更精细和数值复杂的模型,以更精确地对衍生证券进行定价。 Black-Scholes(BS)模型是评估短期衍生工具(例如股票衍生工具)时最常用的模型。至于可转换债券等长期证券,波动率和利率的变动可能会产生复合效应。因此,我们推测,在这些长期工具的定价范围内考虑随机波动和随机利率是可取的。此外,鉴于固定收益衍生产品市场规模要比其他衍生产品大得多,因此似乎认为哪种定价模型更可取具有重要意义。至于股票衍生产品Bakshi,Cao和Chen的发现(1997年)得出的结论是:“考虑随机波动性对于改善BS公式具有首要的重要性”,但“从SV转向SVSI并不一定能进一步提高拟合度”。首先,我们将使用更基本的BS框架研究股票衍生工具和可转换债券的定价,然后将其与更复杂的SV和SVSI模型进行比较。对于数字定价程序,我们专注于使用ADI有限差分法来估计衍生价值。考虑到我们希望建模的多个变量,包括公司价值,波动性和利率,我们希望定价过程既准确又计算有效。虽然ADI方法非常适合这种情况,但蒙特卡罗模拟还是一种可转换债券定价的有吸引力的方法。实际上,在期权价值取决于路径的情况下,蒙特卡洛模拟是理想的选择。要查看可转换债券定价中使用的有限差分技术的示例,请参阅Andersen和Buffum(2002)。另外,有关蒙特卡洛模拟的信息,请参见Lvov,Yigitbasioglu和Bachir(2004)。

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    Garisch Simon Edwin;

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  • 年度 2009
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