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.
| Original language | English |
|---|---|
| Title of host publication | Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021 |
| Editors | Olga Valenzuela, Fernando Rojas, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas |
| Publisher | Springer, Cham |
| Pages | 123-142 |
| ISBN (Electronic) | 978-3-031-14197-3 |
| ISBN (Print) | 978-3-031-14196-6 |
| DOIs | |
| Publication status | Published - 2023 |
Publication series
| Series | Contributions to Statistics |
|---|
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Velasquez Gaviria, D., Mora-Valencia, A., & Perote, J. (2023). Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. In O. Valenzuela, F. Rojas, L. J. Herrera, H. Pomares, & I. Rojas (Eds.), Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021 (pp. 123-142). Springer, Cham. https://doi.org/10.1007/978-3-031-14197-3_9
Velasquez Gaviria, Daniel ; Mora-Valencia, Andrés ; Perote, Javier. / Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. editor / Olga Valenzuela ; Fernando Rojas ; Luis Javier Herrera ; Héctor Pomares ; Ignacio Rojas. Springer, Cham, 2023. pp. 123-142 (Contributions to Statistics).
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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{\textquoteright}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 Sz{\'e}kely for the expected shortfall. Our results indicate that the Student{\textquoteright}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{\textquoteright}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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Velasquez Gaviria, D, Mora-Valencia, A & Perote, J 2023, Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. in O Valenzuela, F Rojas, LJ Herrera, H Pomares & I Rojas (eds), Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. Springer, Cham, Contributions to Statistics, pp. 123-142. https://doi.org/10.1007/978-3-031-14197-3_9
Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. / Velasquez Gaviria, Daniel; Mora-Valencia, Andrés; Perote, Javier.
Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. ed. / Olga Valenzuela; Fernando Rojas; Luis Javier Herrera; Héctor Pomares; Ignacio Rojas. Springer, Cham, 2023. p. 123-142 (Contributions to Statistics).
Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic
TY - CHAP
T1 - Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices
AU - Velasquez Gaviria, Daniel
AU - Mora-Valencia, Andrés
AU - Perote, Javier
N1 - data source:
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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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BT - Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021
A2 - Valenzuela, Olga
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Velasquez Gaviria D, Mora-Valencia A, Perote J. Asymptotic Expansions for Market Risk Assessment: Evidence in Energy and Commodity Indices. In Valenzuela O, Rojas F, Herrera LJ, Pomares H, Rojas I, editors, Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. Springer, Cham. 2023. p. 123-142. (Contributions to Statistics). doi: 10.1007/978-3-031-14197-3_9
