基于双因子柳树的中国可转换债券定价研究

马长福, 许威, 袁先智

系统工程理论与实践 ›› 2019, Vol. 39 ›› Issue (12) : 3011-3023.

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系统工程理论与实践 ›› 2019, Vol. 39 ›› Issue (12) : 3011-3023. DOI: 10.12011/1000-6788-2019-1033-13
论文

基于双因子柳树的中国可转换债券定价研究

    马长福1, 许威1, 袁先智2,3,4,5
作者信息 +

Research on the valuation of Chinese convertible bonds based on two-factor willow tree

    MA Changfu1, XU Wei1, YUAN Xianzhi2,3,4,5
Author information +
文章历史 +

摘要

近年来,可转债已经成为我国上市公司再融资的重要方式,因此如何对其进行定价受到广泛关注.本文综合考虑了随机利率、股价、违约风险、赎回回售条款的触发条件,提出采用股价利率双因子柳树模型对我国市场上的可转债进行定价.较之现有的模型,柳树法模型的定价结果与可转债的市场价格匹配度更高.在估计标的股票的波动率参数时,本文既考虑了历史波动率也考虑了隐含波动率(通过可转债市场价格校准模型得到的波动率).实证结果表明采用隐含波动率时模型的精度有很大的提高.

Abstract

Convertible bond becomes an important way of refinancing for Chinese listed companies recently, and the pricing problem of convertible bond has attracted wide attention. In this paper, we propose a two-factor willow tree method to price Chinese convertible bonds with the consideration of stock price, interest rate, default rate and the trigger conditions of callable and putable clauses embedded in Chinese convertible bonds. By comparing with the existing models, our model matches the market prices better. In empirical research, we estimate the volatility of the stock price process with both historical volatility and implied volatility which is got by calibrating the valuation model with the market price of convertible bond. We find that the accuracy of the valuation model has been greatly improved.

关键词

可转债 / 随机利率 / 双因子模型 / 柳树法

Key words

convertible bond / stochastic interest rate / two-factor model / willow tree method

引用本文

导出引用
马长福 , 许威 , 袁先智. 基于双因子柳树的中国可转换债券定价研究. 系统工程理论与实践, 2019, 39(12): 3011-3023 https://doi.org/10.12011/1000-6788-2019-1033-13
MA Changfu , XU Wei , YUAN Xianzhi. Research on the valuation of Chinese convertible bonds based on two-factor willow tree. Systems Engineering - Theory & Practice, 2019, 39(12): 3011-3023 https://doi.org/10.12011/1000-6788-2019-1033-13
中图分类号: O29   

参考文献

[1] 冯建芬, 周轩宇, 段梦菲. 可转债期权条款设计与影响分析[J]. 管理评论, 2018, 30(8):58-68.Feng J F, Zhou X Y, Duan M F. Analysis of convertible bond option clause design and its effect[J]. Management Review, 2018, 30(8):58-68.
[2] 黄冰华, 冯芸. 可转换债券套利策略研究:中国市场的例子[J]. 管理评论, 2017, 29(11):3-16.Huang B H, Feng Y. Convertible bond arbitrage strategy:Case of Chinese market[J]. Management Review, 2017, 29(11):3-16.
[3] 袁显平, 柯大钢. 可转换债券融资相关事件的股价效应研究[J]. 管理评论, 2008, 20(4):17-24.Yuan X P, Ke D G. Research on stock price effect of convertible bond financing-related events[J]. Management Review, 2008, 20(4):17-24.
[4] Brennan M J, Schwartz E S. Convertible bonds:Valuation and optimal strategies for call and conversion[J]. The Journal of Finance, 1977, 32(5):1699-1715.
[5] Ayache E, Forsyth P A, Vetzal K R. The valuation of convertible bonds with credit risk[J]. Journal of Derivatives, 2003, 11(1):9-29.
[6] 尤左伟, 刘善存, 张强. 混合分数布朗运动下可转债定价模型研究[J]. 系统工程理论与实践, 2017, 37(4):843-854.You Z W, Liu S C, Zhang Q. Convertible bond pricing in a mixed fractional Brownian motion environment[J]. Systems Engineering-Theory & Practice, 2017, 37(4):843-854.
[7] 孙玉东, 师义民, 谭伟. 带跳混合分数布朗运动下利差期权定价[J]. 系统科学与数学, 2012, 32(11):1377-1385.Sun Y D, Shi Y M, Tan W. Pricing for outer performance option in mixed fractional Brownian motion with jump[J]. Journal of Systems Science & Mathematical Sciences, 2012, 32(11):1377-1385.
[8] 刘棠, 张盘铭. 期权定价问题的数值方法[J]. 系统科学与数学, 2004, 24(1):10-16.Liu T, Zhang P M. Numerical methods for option pricing problems[J]. Journal of Systems Science & Mathematical Sciences, 2004, 24(1):10-16.
[9] Ammann M, Kind A, Wilde C. Simulation-based pricing of convertible bonds[J]. Journal of Empirical Finance, 2008, 15(2):310-331.
[10] 马俊海, 杨非. 可转换债券蒙特卡罗模拟定价的控制变量改进方法[J]. 系统工程理论与实践, 2009, 29(6):77-85.Ma J H, Yang F. Improved control variable methods of Monte Carlo simulation for pricing convertible bonds[J]. Systems Engineering-Theory & Practice, 2009, 29(6):77-85.
[11] 张卫国,史庆盛,许文坤. 基于全最小二乘拟蒙特卡罗方法的可转债定价研究[J]. 管理科学, 2011, 24(1):82-89.Zhang W G, Shi Q S, Xu W K. Pricing model of convertible bonds in China by total least-squares Quasi-Monte Carlo method[J]. Journal of Management Science, 2011, 24(1):82-89.
[12] Fan C X, Luo X G, Wu Q B. Stochastic volatility vs. jump diffusions:Evidence from the Chinese convertible bond market[J]. International Review of Economics & Finance, 2017, 49:1-16.
[13] 李念夷, 陈懿冰. 基于违约风险的三叉树模型在可转债定价中的应用研究[J]. 管理评论, 2011, 23(12):26-31.Li N Y, Chen Y B. Trinomial tree with default risk and its application to pricing convertible bonds[J]. Management Review, 2011, 23(12):26-31.
[14] Hung M W, Wang J Y. Pricing convertible bonds subject to default risk[J]. Journal of Derivatives, 2002, 10(2):75-87.
[15] Chambers D R, Lu Q. A tree model for pricing convertible bonds with equity, interest rate, and default risk[J]. Journal of Derivatives, 2007, 14(4):25-46.
[16] 庄新田, 周玲春. 基于双因素的可转换债券定价模型[J]. 东北大学学报(自然科学版), 2006, 27(3):320-323.Zhuang X T, Zhou L C. Two-factor pricing model for convertible bonds[J]. Journal of Northeastern University (Natural Science), 2006, 27(3):320-323.
[17] 朱艳芳, 张维. 引入利率风险的可转换债券定价模型及实证研究[J]. 天津大学学报(社会科学版), 2008, 10(6):510-515.Zhu Y F, Zhang W. Pricing model of convertible bonds with interest rate risk and its empirical research[J]. Journal of Tianjin University (Social Science), 2008, 10(6):510-515.
[18] 谢百帅, 张卫国, 廖萍康, 等. 基于三叉树模型带信用风险的可转债定价[J]. 系统工程, 2013, 31(9):18-23.Xie B S, Zhang W G, Liao P K, et al. The valuation of convertible bonds with credit risk by trinomial tree[J]. Systems Engineering, 2013, 31(9):18-23.
[19] Lu L, Xu W. A simple and efficient two-factor willow tree method for convertible bond pricing with stochastic interest rate and default risk[J]. The Journal of Derivatives, 2017, 25(1):37-54.
[20] Xu W, Hong Z W, Qin C X. A new sampling strategy willow tree method with application to path-dependent option pricing[J]. Quantitative Finance, 2013, 13(6):861-872.
[21] Curran M. Willow power:Optimizing derivative pricing trees[J]. Algo Research Quarterly, 2001, 4(4):15-24.
[22] 杨春梅, 梁朝晖. 基于多重期权法的中国可转债价值研究[J]. 大连理工大学学报(社会科学版), 2014, 35(3):50-55.Yang C M, Liang C H. Valuing Chinese convertible bonds with multiple options[J]. Journal of Dalian University of Technology (Social Science), 2014, 35(3):50-55.
[23] Liu Q. Approximating the embedded m out of n day soft-call option of a convertible bond:An auxiliary reversed binomial tree method[EB/OL].[2017-12-24]. http://ssrn.com/abstract=956813.
[24] Navin R L. Convertible bond valuation:20 out of 30 day soft-call[J]. Intelligence for Financial Engineering, 1999:198-217.
[25] Peter C, Wu L R. Analyzing volatility risk and risk premium in option contracts:A new theory[J]. Journal of Financial Economics, 2016, 120(1):1-20.

基金

国家自然科学基金(71971031,U1811462,71771175)
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