IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v50y2019ics1062940819300737.html
   My bibliography  Save this article

Integrated measurement of liquidity risk and market risk of company bonds based on the optimal Copula model

Author

Listed:
  • Lin, Saiyan
  • Chen, Rongda
  • Lv, Zhihong
  • Zhou, Tianqing
  • Jin, Chenglu

Abstract

The bond market is an important part of the capital market, reflecting the debtor-creditor relationship. Correspondingly, the P2P network lending platform, which plays a vital role in emerging Internet Finance, represents the same relationship. In both markets, the risks in investment and financing channels are complex and diverse, including liquidity risk, market risk, tax risk and so on. All the risks do not exist alone, performed as an integrated risk. This paper establishes an index for measuring corporate bonds’ liquidity, by using a Copula-GARCH approach and generating empirical distribution to integrate the liquidity risk and market risk of corporate bonds. Particularly, according to the Likelihood function test results, t-Copula is the optimum Copula function. The model can also be applied to measure the integrated risk of the P2P network lending platform after improvement.

Suggested Citation

  • Lin, Saiyan & Chen, Rongda & Lv, Zhihong & Zhou, Tianqing & Jin, Chenglu, 2019. "Integrated measurement of liquidity risk and market risk of company bonds based on the optimal Copula model," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    • Handle: RePEc:eee:ecofin:v:50:y:2019:i:c:s1062940819300737
    DOI: 10.1016/j.najef.2019.101004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940819300737
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2019.101004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liudmila Zavolokina & Mateusz Dolata & Gerhard Schwabe, 2016. "The FinTech phenomenon: antecedents of financial innovation perceived by the popular press," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-16, December.
    2. Cai, Xiao Jing & Tian, Shuairu & Yuan, Nannan & Hamori, Shigeyuki, 2017. "Interdependence between oil and East Asian stock markets: Evidence from wavelet coherence analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 206-223.
    3. Narayan, Paresh Kumar & Liu, Ruipeng & Westerlund, Joakim, 2016. "A GARCH model for testing market efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 121-138.
    4. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
    5. Goldstein, Itay & Jiang, Hao & Ng, David T., 2017. "Investor flows and fragility in corporate bond funds," Journal of Financial Economics, Elsevier, vol. 126(3), pages 592-613.
    6. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    7. Chen, Rongda & Yu, Lean, 2013. "A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions," Economic Modelling, Elsevier, vol. 35(C), pages 796-804.
    8. Miralles-Quirós, José Luis & Miralles-Quirós, María del Mar, 2017. "The Copula ADCC-GARCH model can help PIIGS to fly," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 1-12.
    9. Feldhütter, Peter & Hotchkiss, Edith & Karakaş, Oğuzhan, 2016. "The value of creditor control in corporate bonds," Journal of Financial Economics, Elsevier, vol. 121(1), pages 1-27.
    10. Wang, Zong-Run & Chen, Xiao-Hong & Jin, Yan-Bo & Zhou, Yan-Ju, 2010. "Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH–EVT-Copula model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4918-4928.
    11. Guidolin, Massimo & Orlov, Alexei G. & Pedio, Manuela, 2017. "The impact of monetary policy on corporate bonds under regime shifts," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 176-202.
    12. Dorfleitner, Gregor & Priberny, Christopher & Schuster, Stephanie & Stoiber, Johannes & Weber, Martina & de Castro, Ivan & Kammler, Julia, 2016. "Description-text related soft information in peer-to-peer lending – Evidence from two leading European platforms," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 169-187.
    13. Chen, Rongda & Yu, Jingjing & Jin, Chenglu & Bao, Weiwei, 2019. "Internet finance investor sentiment and return comovement," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 151-161.
    14. Imen Zorgati & Faten Lakhal & Elmoez Zaabi, 2019. "Financial contagion in the subprime crisis context: A copula approach," Post-Print hal-02052406, HAL.
    15. Zorgati, Imen & Lakhal, Faten & Zaabi, Elmoez, 2019. "Financial contagion in the subprime crisis context: A copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 269-282.
    16. Mr. Tonny Lybek & Mr. Abdourahmane Sarr, 2002. "Measuring Liquidity in Financial Markets," IMF Working Papers 2002/232, International Monetary Fund.
    17. Kim, Jong-Min & Jung, Hojin, 2016. "Linear time-varying regression with Copula–DCC–GARCH models for volatility," Economics Letters, Elsevier, vol. 145(C), pages 262-265.
    18. Hendrik Bessembinder & Stacey Jacobsen & William Maxwell & Kumar Venkataraman, 2018. "Capital Commitment and Illiquidity in Corporate Bonds," Journal of Finance, American Finance Association, vol. 73(4), pages 1615-1661, August.
    19. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    20. Sensarma, Rudra & Bhattacharyya, Indranil, 2016. "The impact of monetary policy on corporate bonds in India," Journal of Policy Modeling, Elsevier, vol. 38(3), pages 587-602.
    21. Abdul Aziz, Nor Syahilla & Vrontos, Spyridon & M. Hasim, Haslifah, 2019. "Evaluation of multivariate GARCH models in an optimal asset allocation framework," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 568-596.
    22. Yang, Lu & Cai, Xiao Jing & Li, Mengling & Hamori, Shigeyuki, 2015. "Modeling dependence structures among international stock markets: Evidence from hierarchical Archimedean copulas," Economic Modelling, Elsevier, vol. 51(C), pages 308-314.
    23. Tian, Shuairu & Hamori, Shigeyuki, 2015. "Modeling interest rate volatility: A Realized GARCH approach," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 158-171.
    24. Zhu, Jie, 2009. "Testing for expected return and market price of risk in Chinese A and B share markets: A geometric Brownian motion and multivariate GARCH model approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2633-2653.
    25. Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price," Energy Economics, Elsevier, vol. 78(C), pages 412-427.
    26. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.
    27. Guangming Gong & Si Xu & Xun Gong, 2017. "Bond Covenants and the Cost of Debt: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(3), pages 587-610, March.
    28. Tamakoshi, Go & Hamori, Shigeyuki, 2014. "The conditional dependence structure of insurance sector credit default swap indices," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 122-132.
    29. Cubillos-Rocha, Juan S. & Gomez-Gonzalez, Jose E. & Melo-Velandia, Luis F., 2019. "Detecting exchange rate contagion using copula functions," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 13-22.
    30. Riza Emekter & Yanbin Tu & Benjamas Jirasakuldech & Min Lu, 2015. "Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 54-70, January.
    31. O’ Hara, Maureen & Wang, Yihui & (Alex) Zhou, Xing, 2018. "The execution quality of corporate bonds," Journal of Financial Economics, Elsevier, vol. 130(2), pages 308-326.
    32. Huaiqing Wang & Kun Chen & Wei Zhu & Zhenxia Song, 2015. "A process model on P2P lending," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-8, December.
    33. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin, Chenglu & Chen, Rongda & Cheng, Diandian & Mo, Sitian & Yang, Ke, 2020. "The dependency measures of commercial bank risks: Using an optimal copula selection method based on non-parametric kernel density," Finance Research Letters, Elsevier, vol. 37(C).
    2. Beladi, Hamid & Hu, May & Park, Jason & How, Janice, 2020. "Liquidity creation and funding ability during the interbank lending crunch," International Review of Financial Analysis, Elsevier, vol. 67(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Lu & Yang, Lei & Hamori, Shigeyuki, 2018. "Determinants of dependence structures of sovereign credit default swap spreads between G7 and BRICS countries," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 19-34.
    2. Kim, Jong-Min & Kim, Dong H. & Jung, Hojin, 2021. "Estimating yield spreads volatility using GARCH-type models," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    3. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    4. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    5. Andriosopoulos, Kostas & Galariotis, Emilios & Spyrou, Spyros, 2017. "Contagion, volatility persistence and volatility spill-overs: The case of energy markets during the European financial crisis," Energy Economics, Elsevier, vol. 66(C), pages 217-227.
    6. Lucas, André & Zhang, Xin, 2016. "Score-driven exponentially weighted moving averages and Value-at-Risk forecasting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 293-302.
    7. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    8. Oscar V. De la Torre-Torres & José Álvarez-García & María de la Cruz del Río-Rama, 2024. "An EM/MCMC Markov-Switching GARCH Behavioral Algorithm for Random-Length Lumber Futures Trading," Mathematics, MDPI, vol. 12(3), pages 1-21, February.
    9. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    10. Charfeddine, Lanouar & Al Refai, Hisham, 2019. "Political tensions, stock market dependence and volatility spillover: Evidence from the recent intra-GCC crises," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    11. Iglesias, Emma M., 2015. "Value at Risk and expected shortfall of firms in the main European Union stock market indexes: A detailed analysis by economic sectors and geographical situation," Economic Modelling, Elsevier, vol. 50(C), pages 1-8.
    12. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    13. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    14. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    15. Tarek Bouazizi & Zouhaier Hadhek & Fatma Mrad & Mosbah Lafi, 2021. "Changes in Demand for Crude Oil and its Correlation with Crude Oil and Stock Market Returns Volatilities: Evidence from Three Asian Oil Importing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 27-43.
    16. Lahmiri, Salim, 2017. "Asymmetric and persistent responses in price volatility of fertilizers through stable and unstable periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 405-414.
    17. Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023. "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, vol. 306(2), pages 968-985.
    18. Abakah, Emmanuel Joel Aikins & Addo, Emmanuel & Gil-Alana, Luis A. & Tiwari, Aviral Kumar, 2021. "Re-examination of international bond market dependence: Evidence from a pair copula approach," International Review of Financial Analysis, Elsevier, vol. 74(C).
    19. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & María de la Cruz Del Río-Rama & José Álvarez-García, 2022. "Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)," Mathematics, MDPI, vol. 10(8), pages 1-28, April.
    20. Liu, He & Qiao, Han & Wang, Shouyang & Li, Yuze, 2019. "Platform Competition in Peer-to-Peer Lending Considering Risk Control Ability," European Journal of Operational Research, Elsevier, vol. 274(1), pages 280-290.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:50:y:2019:i:c:s1062940819300737. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.