DocumentCode
620471
Title
Pricing credit spread option with Kalman filter and Monte Carlo simulation
Author
Du Sinan ; Zhou Rongxi ; Wang Xianliang ; Wang Yongchao
Author_Institution
Sch. of Econ. & Manage., Beijing Univ. of Chem. Technol., Beijing, China
fYear
2013
fDate
25-27 May 2013
Firstpage
4263
Lastpage
4266
Abstract
This paper presents a method of pricing credit spread option on the basis of multiple factors affine term structure model of interest rates with Kalman filter and Monte Carlo simulation. In this way, the term structures of the Aaa corporate bonds and the Treasury debts with the same maturity in interbank market of China are obtained. Then the credit spreads of corporate bonds are obtained. So European credit spread put option can be priced according to the definition of pricing option. The correlations of option price and strike spread, option expiration are considered. The results show that the return of the credit spread put option increases when the strike spread decreases. The market prices of corporate bonds have a negative correlation with the market spreads. Due to different option expirations, the prices of corporate bonds will be distinct, and so will be the credit spread option prices.
Keywords
Kalman filters; Monte Carlo methods; banking; economic indicators; marketing; pricing; Aaa corporate bonds; European credit spread put option; Kalman filter; Monte Carlo simulation; interbank market; interest rates; market spreads; multiple factors affine term structure model; negative correlation; option expiration; pricing credit spread option; strike spread; treasury debts; Correlation; Economic indicators; Educational institutions; Kalman filters; Modeling; Monte Carlo methods; Pricing; Affine Term Structure Model; Credit Spread Option; Kalman Filter; Monte Carlo Simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location
Guiyang
Print_ISBN
978-1-4673-5533-9
Type
conf
DOI
10.1109/CCDC.2013.6561700
Filename
6561700
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