互联网环境下的理财产品信用价差影响因素研究
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摘要
互联网理财产品信用价差受到了广泛关注,本文从探究系统性、非系统性和互联网等风险因子所隐含的信息出发,分析各风险因子对互联网理财产品信用价差大小的贡献程度,找出影响信用价差大小的关键因素.其中,互联网金融理财产品的信用价差利用Nelson-Siegel-Svensson模型构建无风险收益序列并结合零波动率价差法计算得到,并根据文献建立了系统性、非系统性和互联网等风险因子体系.实证结果表明,互联网金融发展指数对互联网金融理财产品信用价差存在显著影响;利率期限结构调整的债券市场收益率、银行业景气指数、采购经理人指数、居民消费指数、非系统性债券指数波动率也对互联网金融理财产品信用价差存在显著影响.然而,反映股票市场系统性风险因子的上证综指、非系统性股票波动率、广义货币供应量对互联网金融理财产品信用价差无显著影响.
The credit spregad of financial products under Internet environment has received extensive attention. This paper starts with the analysis of information implied by risk factors such as systematic,non-systematic,and Internet. Then,the degrees of contribution of various risk factors to the size of credit spread of financial products under Internet environment have been investigated. Precisely, the NelsonSiegel-Svensson model is applied to construct a risk-free return sequence, and then Zero volatility spread method is applied to calculate credit spreads of Internet financial products. According to the literature,a system of systematic, non-systematic, and Internet risk factors is established. The empirical results show that the Internet financial development index has a significant impact on the credit spread; the bond market rate of return for adjusted term structure of the interest rate, the banking industry climate index,the purchasing manager index, the resident consumer index, and the non-system bond index volatility also have significant impacts on the credit spread of Internet financial products. However, the Shanghai Composite Index, non-systematic stock volatility, and broad money supply(M2) have no significant effect on the credit spread of Internet financial products.
The credit spregad of financial products under Internet environment has received extensive attention. This paper starts with the analysis of information implied by risk factors such as systematic,non-systematic,and Internet. Then,the degrees of contribution of various risk factors to the size of credit spread of financial products under Internet environment have been investigated. Precisely, the NelsonSiegel-Svensson model is applied to construct a risk-free return sequence, and then Zero volatility spread method is applied to calculate credit spreads of Internet financial products. According to the literature,a system of systematic, non-systematic, and Internet risk factors is established. The empirical results show that the Internet financial development index has a significant impact on the credit spread; the bond market rate of return for adjusted term structure of the interest rate, the banking industry climate index,the purchasing manager index, the resident consumer index, and the non-system bond index volatility also have significant impacts on the credit spread of Internet financial products. However, the Shanghai Composite Index, non-systematic stock volatility, and broad money supply(M2) have no significant effect on the credit spread of Internet financial products.
引文
[1] BCBS—Basel Committee on Banking Supervision. Strengthening the resilience of the banking sector[R].Consultative Document, Basel, 2009.
[2] BCBS—Basel Committee on Banking Supervision. Basel III counterparty credit risk frequently asked questions[R]. Basel, 2011.
[3] Chen H. Macroeconomic conditions and the puzzles of credit spreads and capital structure[J]. Journal of Finance,2010, 65(6):2171-2212.
[4] Eom Y, Helwege J, Huang J. Structural models of corporate bond pricing:An empirical analysis[J]. Review of Financial Studies, 2004, 17(1):499-504.
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[6] Chen L, Collin-Dufresne R, Collin-Dufresne P, et al. On the relation between the credit spread puzzle and the equity premium puzzle[J]. Review of Financial Studies, 2009, 22(3):3367-3409.
[7] Jones E, Mason S, Rosenfield E. Contigent claims analysis of corporate capital structures:An empirical investi?gation[J]. Journal of Finance, 1984, 39(3):611-627.
[8] Lonstaf F, Schwartz E. A simple approach to valuing risky fixed and floating rate debt[J]. Journal of Finance,1995, 50(3):789-819.
[9] Delianedis G, Geske R. The components of corporate credit spreads:Default recovery, tax, jumps, liquidity and market factors[C]//The Anderson School at UCLA, 2001.
[10] Huang J, Huang M. How much of the corporate-treasury yield spread is due to credit risk[R]. Working Paper,Stanford, University, 2003.
[11] Driessen J. Is default event risk priced in corporate bonds?[R]. University of Amesterdam, 2003.
[12] Gilchrist S, Zakrajsek E. Credit spreads and business cycle fluctuations[J]. American Economic Review, 2012,102(4):1692-1720.
[13] Chen R, Yang L, Wang W, et al. Discovering the impact of systemic and idiosyncratic risk factors on credit spread of corporate bond within the framework of intelligent knowledge management[J]. Annals of Operations Research, 2015, 234(1):3-15.
[14] Thakur B P S, Kannadhasan M, Goyal V. Determinants of corporate credit spread:Evidence from India[J].Decision, 2018, 5(18):1-15.
[15] Gemmill G, Keswani A. Downside risk and the size of credit spreads[J]. Journal of Banking&Finance, 2011, 35:2021-2036.
[16]林建浩,胡毅,马键,等.FF因子与宏观因子是潜在风险因子的良好代理吗?[J].系统工程理论与实践,2014, 34(s1):83-91.Lin J H, Hu Y, Ma J, et al. Are the FamarFrench and macroeconomic factors good proxies for latent risk factors?[J]. Systems Engineering—Theory&Practice, 2014, 34(s1):83-91.
[17]任兆璋,李鹏·流动性风险对可违约债券信用利差期限结构的影响[J].系统工程理论方法应用,2006, 15(3):251-255.Ren Z Z, Li P. Impact of liquidity risk on the term structure of credit spreads[J]. Journal of Systems&Management, 2006, 15(3):251-255.
[18]刘桂梅,杨晨.金融危机下Fama-French多因子模型在中国债券市场的应用[J]·浙江大学学报(理学版),2010, 37(4):396-400.Liu G M,Yang C. Application of Fama-French multi-factor model in China's bond market during recent financial crisis[J]. Journal of Zhejiang University(Science Edition), 2010, 37(4):396-400.
[19]冯宗宪,郭建伟,孙克.企业债的信用价差及其动态过程研究[J].金融研究,2009, 26(3):54-71.Feng Z X,Guo J W, Sun K.The study of credit spread and dynamic process of corporate bond[J]. Journal of Financial Research, 2009, 26(3):54-71.
[20]周荣喜,杨杰,杨丰梅.基于仿射过程的企业债信用价差期限结构模型[J].系统工程理论与实践,2013, 33(12):3061-3067.Zhou R X, Yang J, Yang F M. Term structure model of corporate bond credit spread based on affine processes[J].Systems Engineering—Theory&Practice, 2013, 33(12):3061-3067.
[21]刘善存,牛伟宁,周荣喜.基于SV模型的我国债券信用价差动态过程研究[J].管理科学学报,2014, 17(3):37-48.Liu S C, Niu W N, Zhou R X. Research on the dynamic process of credit spreads of China's bonds based on SV model[J]. Journal of Management Sciences in China, 2014, 17(3):37-48.
[22]牛华伟.代理成本与“信用价差之谜”[J].管理科学学报,2016, 19(8):54-66.Niu H W. Agency costs and credit spread puzzle[J]. Journal of Management Sciences in China, 2016, 19(8):54-66.
[23]韦起,魏云捷.基于Markov-vine copula的我国网贷平台对传统金融机构风险传染效应研究[J].系统工程理论与实践,2018, 38(2):317-328.Wei Q, Wei Y J. An empirical study of contagion effect from the Internet lending platform of China to the traditional financial institutions based on Markov-vine copula[J]. Systems Engineering—Theory&Practice,2018, 38(2):317-328.
[24] Nelson C R, Siegel A F. Parsimonious Modeling of yield curves[J]. Journal of Business, 1987, 60:473-489.
[25] Svensson L E O. Estimating and interpreting forward interest rates:Sweden 1992-1994[R]. NBER Working Paper No. 4871, http://www.nber.org/papers/w4871, 1994.
[26] Duffie D. Defaultable term structure models with fractional recovery of par[R]. Working Paper, Stanford Uni?versity, https://www.darrellduffie.com/uploads/working/DuffieDefaultableTermModelsl998.pdf, 1998.
[2] BCBS—Basel Committee on Banking Supervision. Basel III counterparty credit risk frequently asked questions[R]. Basel, 2011.
[3] Chen H. Macroeconomic conditions and the puzzles of credit spreads and capital structure[J]. Journal of Finance,2010, 65(6):2171-2212.
[4] Eom Y, Helwege J, Huang J. Structural models of corporate bond pricing:An empirical analysis[J]. Review of Financial Studies, 2004, 17(1):499-504.
[5] Duffie D, Singleton K J. Credit risk:Pricing, measurement, and management[M]. Princeton, NJ:Princeton University Press, 2003.
[6] Chen L, Collin-Dufresne R, Collin-Dufresne P, et al. On the relation between the credit spread puzzle and the equity premium puzzle[J]. Review of Financial Studies, 2009, 22(3):3367-3409.
[7] Jones E, Mason S, Rosenfield E. Contigent claims analysis of corporate capital structures:An empirical investi?gation[J]. Journal of Finance, 1984, 39(3):611-627.
[8] Lonstaf F, Schwartz E. A simple approach to valuing risky fixed and floating rate debt[J]. Journal of Finance,1995, 50(3):789-819.
[9] Delianedis G, Geske R. The components of corporate credit spreads:Default recovery, tax, jumps, liquidity and market factors[C]//The Anderson School at UCLA, 2001.
[10] Huang J, Huang M. How much of the corporate-treasury yield spread is due to credit risk[R]. Working Paper,Stanford, University, 2003.
[11] Driessen J. Is default event risk priced in corporate bonds?[R]. University of Amesterdam, 2003.
[12] Gilchrist S, Zakrajsek E. Credit spreads and business cycle fluctuations[J]. American Economic Review, 2012,102(4):1692-1720.
[13] Chen R, Yang L, Wang W, et al. Discovering the impact of systemic and idiosyncratic risk factors on credit spread of corporate bond within the framework of intelligent knowledge management[J]. Annals of Operations Research, 2015, 234(1):3-15.
[14] Thakur B P S, Kannadhasan M, Goyal V. Determinants of corporate credit spread:Evidence from India[J].Decision, 2018, 5(18):1-15.
[15] Gemmill G, Keswani A. Downside risk and the size of credit spreads[J]. Journal of Banking&Finance, 2011, 35:2021-2036.
[16]林建浩,胡毅,马键,等.FF因子与宏观因子是潜在风险因子的良好代理吗?[J].系统工程理论与实践,2014, 34(s1):83-91.Lin J H, Hu Y, Ma J, et al. Are the FamarFrench and macroeconomic factors good proxies for latent risk factors?[J]. Systems Engineering—Theory&Practice, 2014, 34(s1):83-91.
[17]任兆璋,李鹏·流动性风险对可违约债券信用利差期限结构的影响[J].系统工程理论方法应用,2006, 15(3):251-255.Ren Z Z, Li P. Impact of liquidity risk on the term structure of credit spreads[J]. Journal of Systems&Management, 2006, 15(3):251-255.
[18]刘桂梅,杨晨.金融危机下Fama-French多因子模型在中国债券市场的应用[J]·浙江大学学报(理学版),2010, 37(4):396-400.Liu G M,Yang C. Application of Fama-French multi-factor model in China's bond market during recent financial crisis[J]. Journal of Zhejiang University(Science Edition), 2010, 37(4):396-400.
[19]冯宗宪,郭建伟,孙克.企业债的信用价差及其动态过程研究[J].金融研究,2009, 26(3):54-71.Feng Z X,Guo J W, Sun K.The study of credit spread and dynamic process of corporate bond[J]. Journal of Financial Research, 2009, 26(3):54-71.
[20]周荣喜,杨杰,杨丰梅.基于仿射过程的企业债信用价差期限结构模型[J].系统工程理论与实践,2013, 33(12):3061-3067.Zhou R X, Yang J, Yang F M. Term structure model of corporate bond credit spread based on affine processes[J].Systems Engineering—Theory&Practice, 2013, 33(12):3061-3067.
[21]刘善存,牛伟宁,周荣喜.基于SV模型的我国债券信用价差动态过程研究[J].管理科学学报,2014, 17(3):37-48.Liu S C, Niu W N, Zhou R X. Research on the dynamic process of credit spreads of China's bonds based on SV model[J]. Journal of Management Sciences in China, 2014, 17(3):37-48.
[22]牛华伟.代理成本与“信用价差之谜”[J].管理科学学报,2016, 19(8):54-66.Niu H W. Agency costs and credit spread puzzle[J]. Journal of Management Sciences in China, 2016, 19(8):54-66.
[23]韦起,魏云捷.基于Markov-vine copula的我国网贷平台对传统金融机构风险传染效应研究[J].系统工程理论与实践,2018, 38(2):317-328.Wei Q, Wei Y J. An empirical study of contagion effect from the Internet lending platform of China to the traditional financial institutions based on Markov-vine copula[J]. Systems Engineering—Theory&Practice,2018, 38(2):317-328.
[24] Nelson C R, Siegel A F. Parsimonious Modeling of yield curves[J]. Journal of Business, 1987, 60:473-489.
[25] Svensson L E O. Estimating and interpreting forward interest rates:Sweden 1992-1994[R]. NBER Working Paper No. 4871, http://www.nber.org/papers/w4871, 1994.
[26] Duffie D. Defaultable term structure models with fractional recovery of par[R]. Working Paper, Stanford Uni?versity, https://www.darrellduffie.com/uploads/working/DuffieDefaultableTermModelsl998.pdf, 1998.