ISSN 0253-2778

CN 34-1054/N

Open AccessOpen Access JUSTC Original Paper

Analyzing and measuring loan-to-value ratios of the stock repurchase agreement

Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2015.03.010
  • Received Date: 22 September 2013
  • Accepted Date: 18 February 2014
  • Rev Recd Date: 18 February 2014
  • Publish Date: 30 March 2015
  • Establishing the loan-to-value (LTV) ratios of the stock repurchase agreement is important for securities traders to resist risks and get new revenue streams.In order to calculate the LTV ratios of this kind of agreements, an LTV model was employed. In addition, simulated loans on SHSE-SZSE300 index yield were tested using different discount rates with two methods, the historical simulation method and the generalized Pareto distribution (GPD) method, to compare corresponding LTV ratios.The study shows that the LTV ratios using the LTV model and the two calculation methods are basically reasonable, and limiting LTV up to 60% is meaningful,but the impacts of the two VaR methods on LTV ratios are not comparable.The backtesting which used historical data can determine the performance of simulated loans, thus improving the quality of loans under different terms.
    Establishing the loan-to-value (LTV) ratios of the stock repurchase agreement is important for securities traders to resist risks and get new revenue streams.In order to calculate the LTV ratios of this kind of agreements, an LTV model was employed. In addition, simulated loans on SHSE-SZSE300 index yield were tested using different discount rates with two methods, the historical simulation method and the generalized Pareto distribution (GPD) method, to compare corresponding LTV ratios.The study shows that the LTV ratios using the LTV model and the two calculation methods are basically reasonable, and limiting LTV up to 60% is meaningful,but the impacts of the two VaR methods on LTV ratios are not comparable.The backtesting which used historical data can determine the performance of simulated loans, thus improving the quality of loans under different terms.
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    Jokivuolle E, Peura S. Incorporating collateral value uncertainty in loss given default estimates and loan-to-value ratios [J]. European Financial Management, 2003, 9(3): 299-314.
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    Cossin D, Huang Z J, Aunon-Nerin D. A framework for collateral risk control determination[J].European Central Bank Working Paper Series, 2003, 239:1-47.
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    Winsen J K. An overview of project finance binomial loan valuation[J]. Review of Financial Economics, 2010, 19(2): 84-89.
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    王志诚,唐国正,史树中.金融风险分析的VaR方法[J].科学,1999,51(6):15-18.
    [5]
    Li Yixue, Xu Yu, Chen Zhigang. On loan-to-value ratios of stock-pledging loan[J]. Systems Engineering, 2006, 24(10): 55-58.
    李毅学,徐渝,陈志刚.股票质押贷款业务的贷款价值比率[J].系统工程,2006, 24(10): 55-58.
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    王安民,汪丽华,薛荣年,等.约定收益股票回购创新业务探析[J].中国证券,2013(3): 55-61.
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    Gibson M. Incorporating event risk into value-at-risk[R]. Washington D C: Federal Reserve Board, 2001: FEDS Discussion Paper No.2001-17.
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    Jorion P. Value at Risk: The New Benchmark for Controlling Market Risk[M]. New York: McGraw-Hill, 1997.
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    Hsieh D A. Chaos and nonlinear dynamics: Application to financial markets[J]. The Journal of Finance, 1991, 46(5): 1 839-1 877.
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    Saita F. Value at Risk and Bank Capital Management: Risk Adjusted Performances, Capital Management and Capital Allocation Decision Making[M]. London: Academic Press, 2010.
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    Longin F M. From value at risk to stress testing: The extreme value approach[J]. Journal of Banking & Finance, 2000, 24(7): 1 097-1 130.
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    Longin F. The choice of the distribution of asset returns: How extreme value theory can help?[J]. Journal of Banking & Finance, 2005, 29(4): 1 017-1 035.
    [14]
    Ouyang Zisheng, Gong Shuming. GPD model as a risk management tool[J]. The Theory and Practice of Finance and Economics, 2005, 26(5): 88-92.
    欧阳资生, 龚曙明. 广义帕累托分布模型: 风险管理的工具[J]. 财经理论与实践, 2005, 26(5): 88-92.
    [15]
    Balkema A A, de Haan L. Residual life time at great age[J]. The Annals of Probability, 1974, 2(5):792-804.
    [16]
    Pickands Ⅲ J. Statistical inference using extreme order statistics[J]. The Annals of Statistics, 1975, 3(1): 119-131.
    [17]
    Wang Chunfeng, Wan Haihui, Zhang Wei. The model of market risk measurement: VaR[J]. Journal of Systems Engineering, 2000, 15(1): 67-75.
    王春峰, 万海晖, 张维. 金融市场风险测量模型——VaR[J]. 系统工程学报,2000, 15(1): 67-75.
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    Hill B M. A simple general approach to inference about the tail of a distribution[J]. The Annals of Statistics, 1975: 1 163-1 174.
    [19]
    Basel Committee on Banking Supervision. The Basel Ⅲ Accord[EB/OL].[2013-08-01] http:// www.Basel-iii-accord.com.
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Catalog

    [1]
    Jokivuolle E, Peura S. Incorporating collateral value uncertainty in loss given default estimates and loan-to-value ratios [J]. European Financial Management, 2003, 9(3): 299-314.
    [2]
    Cossin D, Huang Z J, Aunon-Nerin D. A framework for collateral risk control determination[J].European Central Bank Working Paper Series, 2003, 239:1-47.
    [3]
    Winsen J K. An overview of project finance binomial loan valuation[J]. Review of Financial Economics, 2010, 19(2): 84-89.
    [4]
    Wang Zhicheng, Tang Guozheng, Shi Shuzhong. VaR in financial risk analysis[J]. Science, 1999,51(6):15-18.
    王志诚,唐国正,史树中.金融风险分析的VaR方法[J].科学,1999,51(6):15-18.
    [5]
    Li Yixue, Xu Yu, Chen Zhigang. On loan-to-value ratios of stock-pledging loan[J]. Systems Engineering, 2006, 24(10): 55-58.
    李毅学,徐渝,陈志刚.股票质押贷款业务的贷款价值比率[J].系统工程,2006, 24(10): 55-58.
    [6]
    王安民,汪丽华,薛荣年,等.约定收益股票回购创新业务探析[J].中国证券,2013(3): 55-61.
    [7]
    Group of Thirty. Enhancing Financial Stability and Resilience: Macroprudential Policy, Tools, and Systems for the Future[M]. Washington D C: Group of Thirty, 2010.
    [8]
    Gibson M. Incorporating event risk into value-at-risk[R]. Washington D C: Federal Reserve Board, 2001: FEDS Discussion Paper No.2001-17.
    [9]
    Jorion P. Value at Risk: The New Benchmark for Controlling Market Risk[M]. New York: McGraw-Hill, 1997.
    [10]
    Hsieh D A. Chaos and nonlinear dynamics: Application to financial markets[J]. The Journal of Finance, 1991, 46(5): 1 839-1 877.
    [11]
    Saita F. Value at Risk and Bank Capital Management: Risk Adjusted Performances, Capital Management and Capital Allocation Decision Making[M]. London: Academic Press, 2010.
    [12]
    Longin F M. From value at risk to stress testing: The extreme value approach[J]. Journal of Banking & Finance, 2000, 24(7): 1 097-1 130.
    [13]
    Longin F. The choice of the distribution of asset returns: How extreme value theory can help?[J]. Journal of Banking & Finance, 2005, 29(4): 1 017-1 035.
    [14]
    Ouyang Zisheng, Gong Shuming. GPD model as a risk management tool[J]. The Theory and Practice of Finance and Economics, 2005, 26(5): 88-92.
    欧阳资生, 龚曙明. 广义帕累托分布模型: 风险管理的工具[J]. 财经理论与实践, 2005, 26(5): 88-92.
    [15]
    Balkema A A, de Haan L. Residual life time at great age[J]. The Annals of Probability, 1974, 2(5):792-804.
    [16]
    Pickands Ⅲ J. Statistical inference using extreme order statistics[J]. The Annals of Statistics, 1975, 3(1): 119-131.
    [17]
    Wang Chunfeng, Wan Haihui, Zhang Wei. The model of market risk measurement: VaR[J]. Journal of Systems Engineering, 2000, 15(1): 67-75.
    王春峰, 万海晖, 张维. 金融市场风险测量模型——VaR[J]. 系统工程学报,2000, 15(1): 67-75.
    [18]
    Hill B M. A simple general approach to inference about the tail of a distribution[J]. The Annals of Statistics, 1975: 1 163-1 174.
    [19]
    Basel Committee on Banking Supervision. The Basel Ⅲ Accord[EB/OL].[2013-08-01] http:// www.Basel-iii-accord.com.

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