真实世界衡量下包含信用风险的Libor市场模型

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE Journal of Computational Finance Pub Date : 2019-12-02 DOI:10.21314/jcf.2020.399
S. Lopes, Carlos Vázquez Cendón
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引用次数: 0

摘要

我们提出了一种方法,在现实世界的概率度量下,为不同的信用评级生成利率的未来情景。更准确地说,我们解释了如何通过推广多维移位对数正态伦敦银行间同业拆借利率市场模型来考虑信用评级和风险矢量过程的市场价格规范,来对不同评级类别的现实世界远期利率进行模拟。拟议的方法允许负利率的存在,正如目前在市场上观察到的那样,并保证远期利率相对于信用评级的单调性。
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A Libor Market Model Including Credit Risk Under the Real-World Measure
We present a methodology to generate future scenarios of interest rates for different credit ratings under a real-world probability measure. More precisely, we explain how to perform simulations of the real-world forward rates for different rating classes by generalizing the multidimensional shifted lognormal London Interbank Offered Rate market model to account for credit ratings and a specification of the market prices of risk vector processes. The proposed methodology allows for the presence of negative interest rates, as currently observed in the markets, and guarantees the monotonicity of forward rates with respect to credit ratings.
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
8
期刊介绍: The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.
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