Econometric Models Used For Managing The Market Risk In The Romanian Banking System
AbstractTaking into account that one of the most important factors which have caused the financial crisis was the bad risk management practices in banks we want to confirm the need to develop more efficient risk management practices. The fact that return distributions are characterized by time varying vola- tility poses some challenges in the estimation, especially in the period of severe financial crisis. In order to remedy this problem we propose the Extreme Value Theory as an alternative to VaR for quan- tifying the banks’ exposures to interest rate risk. EVT models are more robust to fat-tailedness in the conditional distribution of returns and are preferred in the modeling of interest rate risk in periods with extreme variations. Finally, we assess the performance of the model analyzing the interest rate risk on the Romanian inter-bank market by measures that address its conservativeness, accuracy and efficiency, in the context of Basel II principles.
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Bibliographic InfoArticle provided by Alexandru Ioan Cuza University, Faculty of Economics and Business Administration in its journal Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi.
Volume (Year): 2011SE (2011)
Issue (Month): (july)
Contact details of provider:
Postal: Universitatea Al. I. Cuza; B-dul Carol I nr. 22; Iasi
Phone: 004 0232 201070
Fax: 004 0232 217000
Web page: http://anale.feaa.uaic.ro/anale/
More information through EDIRC
value at risk; time varying volatility; interest rate risk; extreme value theory;
Find related papers by JEL classification:
- G01 - Financial Economics - - General - - - Financial Crises
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
- Dowd, Kevin, 2000. "Adjusting for risk:: An improved Sharpe ratio," International Review of Economics & Finance, Elsevier, vol. 9(3), pages 209-222, July.
- Hasan, Iftekhar & Zazzara, Cristiano, 2006. "Pricing risky bank loans in the new Basel II environment," Research Discussion Papers 3/2006, Bank of Finland.
- Julia Schaumburg, 2010. "Predicting extreme VaR: Nonparametric quantile regression with refinements from extreme value theory," SFB 649 Discussion Papers SFB649DP2010-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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