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A feltétel nélküli normalitás egyszerű alternatívái a kockáztatott érték számításában
[The simple alternatives of unconditional normality in the calculation of value at risk]

Author

Listed:
  • Kóbor, Ádám

Abstract

A piaci kockázatmérés fontosságának a ténye, a nemzetközi szinten elterjedt módszerek meglehetősen gyorsan beépültek a hazai pénzügyi szakma gondolkodásába. Napjaink legnépszerűbb elemzési rendszerét a kockáztatott érték (Value at Risk-VaR) számításához kapcsolódó módszerek jelentik. A kereskedési könyvi szabályozás hatályba lépésével a VaR-számítás és a hozzá kapcsolódó ismeretek elterjedése még ütemesebbé válhat. Ugyancsak közismert az a tény, hogy a legtöbb pénzügyihozam-idősor nem felel meg a normalitás szigorú követelményének; a piaci hozamok eloszlásai ,,vastag szélekkel" jellemezhetők. Jelen tanulmánynak a célja, hogy áttekintsen és bemutasson az alkalmazás illusztrálásával olyan módszereket, amelyek könnyen implementálhatók, azonban a VaR-becslések hatékonyságát mégis nagyban növelhetik. Végül a tanulmány a különböző eljárásokat hatékonyságuk szerint hasonlítja össze; ehhez tőzsdeindexekre (BUX és DJIA) végzett VaR-becslések szolgálnak segítségül. Az összehasonlításokból természetesen csak úgy lehet általánosabb következtetéseket leszűrni, hogy szem előtt tarjuk a választott termékek és időszak konkrétságát és egyediségét.

Suggested Citation

  • Kóbor, Ádám, 2000. "A feltétel nélküli normalitás egyszerű alternatívái a kockáztatott érték számításában [The simple alternatives of unconditional normality in the calculation of value at risk]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 878-898.
    • Handle: RePEc:ksa:szemle:354
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    References listed on IDEAS

    as
    1. Subu Venkataraman, 1997. "Value at risk for a mixture of normal distributions: the use of quasi- Bayesian estimation techniques," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 21(Mar), pages 2-13.
    2. Beckers, Stan, 1981. "A Note on Estimating the Parameters of the Diffusion-Jump Model of Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(1), pages 127-140, March.
    3. Fernández, C. & Steel, M.F.J., 1996. "On Bayesian Modelling of Fat Tails and Skewness," Other publications TiSEM 0991c197-c9e8-4904-8119-3, Tilburg University, School of Economics and Management.
    4. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
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    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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