A parametric approach to counterparty and credit risk

被引:0
|
作者
Orlando, Giuseppe [1 ,2 ]
Haertel, Maximilian [3 ,4 ]
机构
[1] Allianz Asset Management, D-80335 Munich, Germany
[2] Univ Bari Aldo Moro, Dept Econ & Math Methods, I-70124 Bari, Italy
[3] IDS GmbH Anal & Reporting Serv, D-80802 Munich, Germany
[4] Univ Munich, Dept Math, D-80333 Munich, Germany
来源
JOURNAL OF CREDIT RISK | 2014年 / 10卷 / 04期
关键词
D O I
暂无
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
We present the results of a business solution on how to measure credit and counter-party risk, with the main focus on over-the-counter derivatives. Moreover, we use this approach to include the measurement of liquidity risk exposure. While there are very sophisticated approaches to credit/counterparty risk, these have many disadvantages (eg, cost, implementation time, model risk, complexity). On the other hand, the "current exposure method" approach suggested by the regulator is quite simplistic and has been widely criticized since it does not model the risk "properly". Instead, we present a working model that lies in the middle (ie, it is simple without being simplistic, not very expensive/time-consuming to implement, able to solve the shortfalls that the add-on approach has, etc) and is able to capture the liquidity risk from collateral requirements. In particular, we explain how we measure the exposure for each counterparty with netting arrangements and collaterals. We introduce the concept of potential future exposure and explain why we opted for a parametric approach. We then develop the concepts of credit loss and default probability as a result of a Poisson process and we use the concept of unexpected loss in order to derive the economic capital as the difference between the unexpected loss and the credit loss. Finally, we show how this approach can be applied as a refinement of liquidity risk measurement by considering collateral requirements, so as to enhance the monitoring of liquidity congruence between funds' assets and liabilities, particularly under stressed market conditions.
引用
收藏
页码:97 / 133
页数:37
相关论文
共 50 条
  • [31] BASEL III Counterparty Risk and Credit Value Adjustment: Impact of the Wrongway Risk
    Noh, Jaesun
    [J]. GLOBAL ECONOMIC REVIEW, 2013, 42 (04) : 346 - 361
  • [32] Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model
    Anagnostou, Ioannis
    Kandhai, Drona
    [J]. RISKS, 2019, 7 (02)
  • [33] Locally Risk-Minimizing Hedging of Counterparty Risk for Portfolio of Credit Derivatives
    Lijun Bo
    Claudia Ceci
    [J]. Applied Mathematics & Optimization, 2020, 82 : 799 - 850
  • [34] Investor behavior, information disclosure strategy and counterparty credit risk contagion
    Wang, Lei
    Li, Shouwei
    Chen, Tingqiang
    [J]. CHAOS SOLITONS & FRACTALS, 2019, 119 : 37 - 49
  • [35] Analytical Expressions to Counterparty Credit Risk Exposures for Interest Rate Derivatives
    Li, Shuang
    Peng, Cheng
    Bao, Ying
    Zhao, Yan-long
    Cao, Zhen
    [J]. ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES, 2022, 38 (02): : 254 - 270
  • [36] Coherent global market simulations and securitization measures for counterparty credit risk
    Albanese, Claudio
    Bellaj, Toufik
    Gimonet, Guillaume
    Pietronero, Giacomo
    [J]. QUANTITATIVE FINANCE, 2011, 11 (01) : 1 - 20
  • [37] PRICING CATASTROPHE OPTIONS WITH COUNTERPARTY CREDIT RISK IN A REDUCED FORM MODEL
    Xu, Yajuan
    Wang, Guojing
    [J]. ACTA MATHEMATICA SCIENTIA, 2018, 38 (01) : 347 - 360
  • [38] Analytical Expressions to Counterparty Credit Risk Exposures for Interest Rate Derivatives
    Shuang Li
    Cheng Peng
    Ying Bao
    Yan-long Zhao
    Zhen Cao
    [J]. Acta Mathematicae Applicatae Sinica, English Series, 2022, 38 : 254 - 270
  • [39] Analytical Expressions to Counterparty Credit Risk Exposures for Interest Rate Derivatives
    Shuang LI
    Cheng PENG
    Ying BAO
    Yan-long ZHAO
    Zhen CAO
    [J]. Acta Mathematicae Applicatae Sinica, 2022, (02) : 254 - 270
  • [40] Pricing counterparty risk at the trade level and credit valuation adjustment allocations
    Pykhtin, Michael
    Rosen, Dan
    [J]. JOURNAL OF CREDIT RISK, 2010, 6 (04): : 3 - 38