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General Aspects Regarding the Methodology for Prediction Risk

Author

Listed:
  • Victoria Gabriela ANGHELACHE

    (Academy of Economic Studies, Bucharest)

  • Dumitru Cristian OANEA

    (Academy of Economic Studies, Bucharest)

  • Bogdan ZUGRAVU

    (Academy of Economic Studies, Bucharest)

Abstract

In order to measure the total risk to which an investor or a financial institution is exposed when they invest in a financial asset, there needs to be a tool to capture this risk. The most widely used tool in measuring the total risk is Value at Risk. The first parameter that must be estimated is represented by the decay factor, because based on its value we will estimate further the volatility and Value at Risk. However, we are not just interested in computing the VaR for all considered models, but moreover we want to test if models used in these estimations are accurate and able to predict the risk. To achieve this objective we will use two types of test: unconditional coverage test and conditional coverage test.

Suggested Citation

  • Victoria Gabriela ANGHELACHE & Dumitru Cristian OANEA & Bogdan ZUGRAVU, 2013. "General Aspects Regarding the Methodology for Prediction Risk," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(2), pages 66-72, May.
    • Handle: RePEc:rsr:supplm:v:61:y:2013:i:2:p:66-72
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    References listed on IDEAS

    as
    1. So, Mike K.P. & Yu, Philip L.H., 2006. "Empirical analysis of GARCH models in value at risk estimation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(2), pages 180-197, April.
    2. Hammoudeh, Shawkat & Malik, Farooq & McAleer, Michael, 2011. "Risk management of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 435-441.
    3. Giot, Pierre & Laurent, Sebastien, 2003. "Market risk in commodity markets: a VaR approach," Energy Economics, Elsevier, vol. 25(5), pages 435-457, September.
    4. Fernando Caio Galdi & Leonel Molero Pereira, 2007. "Value at Risk (VaR) Using Volatility Forecasting Models: EWMA, GARCH and Stochastic Volatility," Brazilian Business Review, Fucape Business School, vol. 4(1), pages 74-94, January.
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    Citations

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    Cited by:

    1. Dumitru-Cristian OANEA & Gabriela-Victoria ANGHELACHE, 2014. "Systemic Risk Caused By Romanian Financial Intermediaries During Financial Crisis: A Covar Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 14, pages 171-178, December.
    2. Gabriela Anghelache & Dumitru-Cristian Oanea, 2014. "Main Romanian Commercial Banks’ Systemic Risk during Financial Crisis: a CoVar Approach," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 6(2), pages 069-080, December.

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    More about this item

    Keywords

    financial instrument; prediction; risk metrics; risk prediction;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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