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Measurement of the Market Risk- the Value at Risk Method

Listed author(s):
  • Agata Gemzik-Salwach
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    The Value at Risk (VaR) method permits to define, with a certain accepted probability, the maximum loss to which the investor can be exposed within a given time horizon. This measurement opens wide interpretation possibilities and can be used both to quantify all kinds of financial risk and to measure risks other than the market-related ones. It also permits to assess the diversification of the portfolio and the capital adequacy, as well as to adjust the operation effectiveness by the factor of the risk being run at the level of both the whole institution and its individual parts. Prior to the VaR calculation, the user must arbitrarily choose the time horizon for which the risk is to be estimated and the confidence level at which the calculation is to be performed. The choice of these parameters has a strong influence on the obtained result. The confidence level determines the reliability degree of the statistical estimation being made. Along with increase in the calculation probability, there is increase in the value of VaR. The time horizon means the time range for which the VaR is calculated, i.e. the period over which the calculated potential loss on the portfolio can take place. The longer the adopted time horizon, the higher the value at risk is. When using the VaR method, its limitations must be kept in mind. The presented analytical method assumes that the risk is subject to normal distribution. It also assumes that the composition of the portfolio does not undergo any change over the given time horizon. In reality, such conditions often are difficult to meet.

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    Article provided by Faculty of Economic Sciences, University of Warsaw in its journal Ekonomia journal.

    Volume (Year): 8 (2002)
    Issue (Month): ()

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    Handle: RePEc:eko:ekoeko:8_118
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    1. William F. Sharpe, 1963. "A Simplified Model for Portfolio Analysis," Management Science, INFORMS, vol. 9(2), pages 277-293, January.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. anonymous, 1996. "Atlanta Fed's risk management activities reorganized," Financial Update, Federal Reserve Bank of Atlanta, issue Oct, pages 1-4.
    4. anonymous, 1996. "Risk-management plans must make the grade," Financial Update, Federal Reserve Bank of Atlanta, issue Apr, pages 1-2.
    5. 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.
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