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Market risk valuation modeling for the European countries at the financial crisis of 2008

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  • Shcherba, Alexandr

    ()
    (National Research University Higher School of Economics, Moscow)

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    Abstract

    The work is dedicated to VaR models, estimated on the equities quotes of the six European countries. The time series cover three economic periods — pre crisis, crisis and post crisis, where the crisis period is the financial crunch of the 2008 year. The volatility estimation is based on the four APARCH(1,1) models and six distribution functions. The results of the investigation show the connection of the model with country's economic development and its financial condition at the different periods of time.

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    File URL: http://pe.cemi.rssi.ru/pe_2012_3_20-35.pdf
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    Bibliographic Info

    Article provided by Publishing House "SINERGIA PRESS" in its journal Applied Econometrics.

    Volume (Year): 27 (2012)
    Issue (Month): 3 ()
    Pages: 20-35

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    Handle: RePEc:ris:apltrx:0176

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    Web page: http://appliedeconometrics.cemi.rssi.ru/

    Related research

    Keywords: VaR; APARCH; market risk; financial crisis 2008;

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    1. Roxana Chiriac & Winfried Pohlmeier, 2010. "How Risky Is the Value at Risk?," Working Paper Series 07_10, The Rimini Centre for Economic Analysis.
    2. Jondeau, Eric & Rockinger, Michael, 2003. "Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements," Journal of Economic Dynamics and Control, Elsevier, vol. 27(10), pages 1699-1737, August.
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    4. Sentana, Enrique, 1995. "Quadratic ARCH Models," Review of Economic Studies, Wiley Blackwell, vol. 62(4), pages 639-61, October.
    5. Xin Zhao & Carl John Scarrott & Marco Reale & Les Oxley, 2009. "Bayesian Extreme Value Mixture Modelling for Estimating VaR," Working Papers in Economics 09/15, University of Canterbury, Department of Economics and Finance.
    6. Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
    7. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
    8. 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.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    11. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    12. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.
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    Cited by:
    1. Shcherba, Alexandr, 2014. "Comparing «Realized volatility» models in the VaR calculation for the Russian equity market," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 34(2), pages 120-136.

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