Energy commodities: A study on model selection for estimating Value-at-Risk
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
- Coletti, Donald & Lalonde, René & Masson, Paul & Muir, Dirk & Snudden, Stephen, 2021.
"Commodities and monetary policy: Implications for inflation and price level targeting,"
Journal of Policy Modeling, Elsevier, vol. 43(5), pages 982-999.
- Donald Coletti & René Lalonde & Paul Masson & Dirk Muir & Stephen Snudden, 2012. "Commodities and Monetary Policy: Implications for Inflation and Price Level Targeting," Staff Working Papers 12-16, Bank of Canada.
- Tak Kuen Siu, 2021. "The risks of cryptocurrencies with long memory in volatility, non-normality and behavioural insights," Applied Economics, Taylor & Francis Journals, vol. 53(17), pages 1991-2014, April.
- Ben-Salha, Ousama & Mokni, Khaled, 2022. "Detrended cross-correlation analysis in quantiles between oil price and the US stock market," Energy, Elsevier, vol. 242(C).
- Chowdhury, Mohammad Ashraful Ferdous & Meo, Muhammad Saeed & Uddin, Ajim & Haque, Md. Mahmudul, 2021. "Asymmetric effect of energy price on commodity price: New evidence from NARDL and time frequency wavelet approaches," Energy, Elsevier, vol. 231(C).
- Peter R. Hansen & Asger Lunde & James M. Nason, 2011.
"The Model Confidence Set,"
Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2010. "The Model Confidence Set," CREATES Research Papers 2010-76, Department of Economics and Business Economics, Aarhus University.
- Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017. "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, vol. 66(C), pages 523-534.
- Mohaddes, Kamiar & Pesaran, M. Hashem, 2017.
"Oil prices and the global economy: Is it different this time around?,"
Energy Economics, Elsevier, vol. 65(C), pages 315-325.
- Kamiar Mohaddes & M. Hashem Pesaran, 2016. "Oil prices and the global economy: is it different this time around?," Globalization Institute Working Papers 277, Federal Reserve Bank of Dallas.
- Kamiar Mohaddes & M. Hashem Pesaran, 2016. "Oil Prices and the Global Economy: Is It Different This Time Around?," Working Papers 1052, Economic Research Forum, revised 10 2016.
- Kamiar Mohaddes & M. Hashem Pesaran, 2016. "Oil Prices and the Global Economy: Is it Different this Time Around?," CESifo Working Paper Series 5992, CESifo.
- Mr. Kamiar Mohaddes & M. Hashem Pesaran, 2016. "Oil Prices and the Global Economy: Is It Different This Time Around?," IMF Working Papers 2016/210, International Monetary Fund.
- Kamiar Mohaddes & M. Hashem Pesaran, 2016. "Oil prices and the global economy: Is it different this time around?," CAMA Working Papers 2016-56, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Kamiar Mohaddes & M. Hashem Pesaran, 2016. "Oil Prices and the Global Economy: Is It Different This Time Around?," Cambridge Working Papers in Economics 1640, Faculty of Economics, University of Cambridge.
- Wang, Liping, 2022. "Research on the impact of energy price fluctuations on regional economic development based on panel data model," Resources Policy, Elsevier, vol. 75(C).
- Ferdous Mohammadi Basatini & Saeid Rezakhah, 2020. "Markov switch smooth transition HYGARCH model: Stability and estimation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(10), pages 2384-2409, May.
- Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
- Albulescu, Claudiu Tiberiu & Ajmi, Ahdi Noomen, 2021. "Oil price and US dollar exchange rate: Change detection of bi-directional causal impact," Energy Economics, Elsevier, vol. 100(C).
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
- Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 493-530.
- Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
- Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
- Hanson, Kenneth & Robinson, Sherman & Schluter, Gerald E., 1993.
"Sectoral Effects Of A World Oil Price Shock: Economywide Linkages To The Agricultural Sector,"
Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-21, July.
- Hanson, Kenneth & Robinson, Sherman & Schluter, Gerald, 1991. "Sectoral Effects of a World Oil Price Shock: Economywide Linkages to the Agricultural Sector," Staff Reports 278608, United States Department of Agriculture, Economic Research Service.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993.
"On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,"
Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
- Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
- Caporale, Guglielmo Maria & Zekokh, Timur, 2019.
"Modelling volatility of cryptocurrencies using Markov-Switching GARCH models,"
Research in International Business and Finance, Elsevier, vol. 48(C), pages 143-155.
- Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
- Chen, Sheng-Tung & Kuo, Hsiao-I & Chen, Chi-Chung, 2010. "Modeling the relationship between the oil price and global food prices," Applied Energy, Elsevier, vol. 87(8), pages 2517-2525, August.
- Ji, Qiang & Liu, Bing-Yue & Zhao, Wan-Li & Fan, Ying, 2020. "Modelling dynamic dependence and risk spillover between all oil price shocks and stock market returns in the BRICS," International Review of Financial Analysis, Elsevier, vol. 68(C).
- Enwereuzoh, Precious Adaku & Odei-Mensah, Jones & Owusu Junior, Peterson, 2021. "Crude oil shocks and African stock markets," Research in International Business and Finance, Elsevier, vol. 55(C).
- Chen, Jinyu & Zhu, Xuehong & Li, Hailing, 2020. "The pass-through effects of oil price shocks on China's inflation: A time-varying analysis," Energy Economics, Elsevier, vol. 86(C).
- Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
- Boateng, Ebenezer & Asafo-Adjei, Emmanuel & Addison, Alex & Quaicoe, Serebour & Yusuf, Mawusi Ayisat & Abeka, Mac Junior & Adam, Anokye M., 2022. "Interconnectedness among commodities, the real sector of Ghana and external shocks," Resources Policy, Elsevier, vol. 75(C).
- Wang, Yijing & Geng, Xueqing & Guo, Kun, 2022. "The influence of international oil price fluctuation on the exchange rate of countries along the “Belt and Road”," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
- Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
- Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
- 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.
- Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
- Alfonso J. Bello & Julio Mulero & Miguel A. Sordo & Alfonso Suárez-Llorens, 2020. "On Partial Stochastic Comparisons Based on Tail Values at Risk," Mathematics, MDPI, vol. 8(7), pages 1-12, July.
- 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.).
- Bauwens, Luc & Laurent, Sebastien, 2005.
"A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 346-354, July.
- BAUWENS, Luc & LAURENT, Sébastien, 2005. "A new class of multivariate skew densities, with application to generalized autoregressive conditional heteroscedasticity models," LIDAM Reprints CORE 1793, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Tom Doan, "undated". "LOGMVSKEWT: RATS procedure to compute function for log density of multivariate skew-t distribution," Statistical Software Components RTS00107, Boston College Department of Economics.
- Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
- Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
- Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
- Ahmed BenSaïda & Sabri Boubaker & Duc Khuong Nguyen & Skander Slim, 2018. "Value‐at‐risk under market shifts through highly flexible models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(8), pages 790-804, December.
- Oğuzhan Çepni & Selçuk Gül & Muhammed Hasan Yılmaz & Brian Lucey, 2021.
"The impact of oil price shocks on Turkish sovereign yield curve,"
International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 17(9), pages 2258-2277, February.
- Oguzhan Cepni & Selcuk Gul & Muhammed Hasan Yilmaz & Brian Lucey, 2021. "The Impact of Oil Price Shocks on Turkish Sovereign Yield Curve," Working Papers 2104, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
- Mawuli Segnon & Mark Trede, 2018.
"Forecasting market risk of portfolios: copula-Markov switching multifractal approach,"
The European Journal of Finance, Taylor & Francis Journals, vol. 24(14), pages 1123-1143, September.
- Mawuli Segnon & Mark Trede, 2017. "Forecasting Market Risk of Portfolios: Copula-Markov Switching Multifractal Approach," CQE Working Papers 6617, Center for Quantitative Economics (CQE), University of Muenster.
- Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022.
"Forecasting oil prices over 150 years: The role of tail risks,"
Resources Policy, Elsevier, vol. 75(C).
- Afees A. Salisu & Rangan Gupta & Qiang Ji, 2021. "Forecasting Oil Price over 150 Years: The Role of Tail Risks," Working Papers 202120, University of Pretoria, Department of Economics.
- Donghua Wang & Jin Ding & Guoqing Chu & Dinghai Xu & Tony S. Wirjanto, 2021. "Modelling asset returns in the presence of price limits with Markov-switching mixture of truncated normal GARCH distribution: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 53(7), pages 781-804, February.
- Chao Wang & Qian Chen & Richard Gerlach, 2019. "Bayesian realized-GARCH models for financial tail risk forecasting incorporating the two-sided Weibull distribution," Quantitative Finance, Taylor & Francis Journals, vol. 19(6), pages 1017-1042, June.
- Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
- Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
- N. Alemohammad & S. Rezakhah & S. H. Alizadeh, 2020. "Markov switching asymmetric GARCH model: stability and forecasting," Statistical Papers, Springer, vol. 61(3), pages 1309-1333, June.
- Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
- Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
- Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
- Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
- Caporale, Guglielmo Maria & Zekokh, Timur, 2019.
"Modelling volatility of cryptocurrencies using Markov-Switching GARCH models,"
Research in International Business and Finance, Elsevier, vol. 48(C), pages 143-155.
- Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
- Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
- Huang, Yirong & Luo, Yi, 2024. "Forecasting conditional volatility based on hybrid GARCH-type models with long memory, regime switching, leverage effect and heavy-tail: Further evidence from equity market," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
- Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
- Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
- Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
- Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
- Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
- Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022.
"On the volatility of cryptocurrencies,"
Research in International Business and Finance, Elsevier, vol. 62(C).
- Thanasis Stengos & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "On the volatility of cryptocurrencies," Working Papers 2202, University of Guelph, Department of Economics and Finance.
- Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
- Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
- Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
- Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
- Hasanov, Akram Shavkatovich & Burkhanov, Aktam Usmanovich & Usmonov, Bunyod & Khajimuratov, Nizomjon Shukurullaevich & Khurramova, Madina Mansur qizi, 2024. "The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks," Energy, Elsevier, vol. 293(C).
- Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
- Bei, Shuhua & Yang, Aijun & Pei, Haotian & Si, Xiaoli, 2023. "Price Risk Analysis using GARCH Family Models: Evidence from Shanghai Crude Oil Futures Market," Economic Modelling, Elsevier, vol. 125(C).
- Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
- Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
- Ke, Rui & Yang, Luyao & Tan, Changchun, 2022. "Forecasting tail risk for Bitcoin: A dynamic peak over threshold approach," Finance Research Letters, Elsevier, vol. 49(C).
More about this item
Keywords
commodities; Value-at-Risk; GARCH; Markov-switching; probability distributions;All these keywords.
JEL classification:
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
- P18 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Energy; Environment
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:apltrx:0456. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.