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Third Moment of Yield Probability Distributions for Instruments on Slovenian Financial Markets

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  • Srečko Devjak
  • Andraž Grum

Abstract

Due to the capital decree legislated by the Bank of Slovenia, Slovenian commercial banks can apply internal models for capital requirements calculation for currency risk and selected market risks (general position risk in line with debt and equity instruments, price change risk for commodities) as an alternative or in combination with standardised methodology. In risk management process banks consider the first and the second moment of a yield probability distribution as portfolio managers seek to achieve the best possible trade-off between risk represented by variance of returns and expected return. In cases when liquidity of instruments on financial markets is low, banks should consider also the third (skewness) and the fourth (kurtosis) moment of a yield probability distribution. All moments define the characteristics of yield probability distribution and therefore affect the risk measure value, being calculated on the basis of yield probability distribution function. The goal of this paper is to calculate the third moment of a yield probability distribution functions for a set of selected assets in financial market in Slovenia and to initiate implementation of a proper risk measure when yield distribution function is not elliptic.

Suggested Citation

  • Srečko Devjak & Andraž Grum, 2006. "Third Moment of Yield Probability Distributions for Instruments on Slovenian Financial Markets," Prague Economic Papers, Prague University of Economics and Business, vol. 2006(4), pages 364-373.
  • Handle: RePEc:prg:jnlpep:v:2006:y:2006:i:4:id:293:p:364-373
    DOI: 10.18267/j.pep.293
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    References listed on IDEAS

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    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," Center for Financial Institutions Working Papers 00-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Carlo Acerbi & Dirk Tasche, 2002. "Expected Shortfall: A Natural Coherent Alternative to Value at Risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(2), pages 379-388, July.
    3. Yamai, Yasuhiro & Yoshiba, Toshinao, 2002. "On the Validity of Value-at-Risk: Comparative Analyses with Expected Shortfall," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 20(1), pages 57-85, January.
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    More about this item

    Keywords

    skewness; risk management; value at risk; bank; yield propability distribution function; risk aversion;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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