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Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices

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Theory and Applications of Time Series Analysis and Forecasting (ITISE 2021)

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

The increasing volatility experienced in financial and commodity markets has motivated the search of frequency functions with more complex attributes to characterize their asset returns distribution. In this research, two semi-nonparametric distributions are proposed and compared, the Gram-Charlier expansion and a novel Edgeworth expansion for the Student’s t, to estimate the value-at-risk and the expected shortfall in four indices related to energy, metals, mining, and physical commodities. Backtesting performance is assessed in terms of Kupiec and Independence tests for value at risk and the recent proposal by Acerbi and Székely for the expected shortfall. Our results indicate that the Student’s t expansion density adequately fits the returns of different indices and exhibits the best performance for value at risk and expected shortfall backtesting. Consequently, the Student’s t expansion density, which encompasses the Gram-Charlier distribution as the degrees of freedom parameter tends to infinity, reveals as a flexible and accurate methodology for risk management purposes in energy and commodity markets.

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Author information

Authors and Affiliations

  1. School of Business and Economics, Maastricht University, Maastricht, Netherlands

    Daniel Velásquez-Gaviria

  2. School of Management, Universidad de los Andes, Bogotá, Colombia

    Andrés Mora-Valencia

  3. School of Economics and Business, University of Salamanca, Salamanca, Spain

    Javier Perote

Authors
  1. Daniel Velásquez-Gaviria
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  2. Andrés Mora-Valencia
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  3. Javier Perote
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Corresponding author

Correspondence to Javier Perote .

Editor information

Editors and Affiliations

  1. Faculty of Sciences, University of Granada, Granada, Spain

    Olga Valenzuela

  2. ETSIIT, CITIC-UGR, University of Granada, Granada, Spain

    Fernando Rojas

  3. ETSIIT, CITIC-UGR, University of Granada, Granada, Spain

    Luis Javier Herrera

  4. ETSIIT, CITIC-UGR, University of Granada, Granada, Spain

    Héctor Pomares

  5. ETSIIT, CITIC-UGR, University of Granada, Granada, Spain

    Ignacio Rojas

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Velásquez-Gaviria, D., Mora-Valencia, A., Perote, J. (2023). Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. In: Valenzuela, O., Rojas, F., Herrera, L.J., Pomares, H., Rojas, I. (eds) Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-14197-3_9

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