Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data
Author
Abstract
Suggested Citation
Download full text from publisher
Other versions of this item:
- Segnon Mawuli & Lau Chi Keung & Wilfling Bernd & Gupta Rangan, 2022. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 73-98, February.
- Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers 201739, University of Pretoria, Department of Economics.
References listed on IDEAS
- Haugom, Erik & Ullrich, Carl J., 2012. "Forecasting spot price volatility using the short-term forward curve," Energy Economics, Elsevier, vol. 34(6), pages 1826-1833.
- Chan, Kam Fong & Gray, Philip & van Campen, Bart, 2008. "A new approach to characterizing and forecasting electricity price volatility," International Journal of Forecasting, Elsevier, vol. 24(4), pages 728-743.
- Lux, Thomas, 2008.
"The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
- Lux, Thomas, 2004. "The Markov-switching multi-fractal model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2004-11, Christian-Albrechts-University of Kiel, Department of Economics.
- Lux, Thomas, 2006. "The Markov-Switching Multifractal Model of asset returns: GMM estimation and linear forecasting of volatility," Economics Working Papers 2006-17, Christian-Albrechts-University of Kiel, Department of Economics.
- Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
- Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
- Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015.
"Forecasting day-ahead electricity prices: Utilizing hourly prices,"
Energy Economics, Elsevier, vol. 50(C), pages 227-239.
- Eran Raviv & Kees E. Bouwman & Dick van Dijk, 2013. "Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices," Tinbergen Institute Discussion Papers 13-068/III, Tinbergen Institute.
- Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
- Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
- Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
- Nowotarski, Jakub & Raviv, Eran & Trück, Stefan & Weron, Rafał, 2014.
"An empirical comparison of alternative schemes for combining electricity spot price forecasts,"
Energy Economics, Elsevier, vol. 46(C), pages 395-412.
- Jakub Nowotarski & Eran Raviv & Stefan Trueck & Rafal Weron, 2013. "An empirical comparison of alternate schemes for combining electricity spot price forecasts," HSC Research Reports HSC/13/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Kristiansen, Tarjei, 2012. "Forecasting Nord Pool day-ahead prices with an autoregressive model," Energy Policy, Elsevier, vol. 49(C), pages 328-332.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- repec:bla:ecnote:v:39:y:2010:i:s1:p:47-63 is not listed on IDEAS
- 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.
- Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
- repec:qut:auncer:2012_5 is not listed on IDEAS
- 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.
- Calvet, Laurent & Fisher, Adlai, 2001.
"Forecasting multifractal volatility,"
Journal of Econometrics, Elsevier, vol. 105(1), pages 27-58, November.
- Laurent Calvet & Adlai Fisher, 1999. "Forecasting Multifractal Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-017, New York University, Leonard N. Stern School of Business-.
- Laurent-Emmanuel Calvet & Adlai J. Fisher, 2001. "Forecasting multifractal volatility," Post-Print hal-00477952, HAL.
- Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
- Laurent E. Calvet, 2004.
"How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes,"
Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 49-83.
- Laurent-Emmanuel Calvet & Adlai J. Fisher, 2004. "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes," Post-Print hal-00478472, HAL.
- Weron, Rafał, 2002.
"Estimating long-range dependence: finite sample properties and confidence intervals,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 285-299.
- Rafal Weron, 2001. "Estimating long range dependence: finite sample properties and confidence intervals," HSC Research Reports HSC/01/03, Hugo Steinhaus Center, Wroclaw University of Technology.
- Michael McAleer & Marcelo Medeiros, 2008.
"Realized Volatility: A Review,"
Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
- Michael McAleer & Marcelo Cunha Medeiros, 2006. "Realized volatility: a review," Textos para discussão 531 Publication status: F, Department of Economics PUC-Rio (Brazil).
- Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996.
"Fractionally integrated generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
- Tom Doan, "undated". "RATS programs to replicate Baillie, Bollerslev, Mikkelson FIGARCH results," Statistical Software Components RTZ00009, Boston College Department of Economics.
- Maciejowska, Katarzyna & Nowotarski, Jakub & Weron, Rafał, 2016.
"Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging,"
International Journal of Forecasting, Elsevier, vol. 32(3), pages 957-965.
- Katarzyna Maciejowska & Jakub Nowotarski & Rafal Weron, 2014. "Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging," HSC Research Reports HSC/14/09, Hugo Steinhaus Center, Wroclaw University of Technology.
- Lux, Thomas & Segnon, Mawuli & Gupta, Rangan, 2016. "Forecasting crude oil price volatility and value-at-risk: Evidence from historical and recent data," Energy Economics, Elsevier, vol. 56(C), pages 117-133.
- Higgs, Helen & Worthington, Andrew, 2008. "Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: The Australian wholesale spot electricity market," Energy Economics, Elsevier, vol. 30(6), pages 3172-3185, November.
- Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
- Huisman, Ronald & Mahieu, Ronald, 2003.
"Regime jumps in electricity prices,"
Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
- Huisman, R. & Mahieu, R.J., 2001. "Regime Jumps in Electricity Prices," ERIM Report Series Research in Management ERS-2001-48-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
- Laurent E. Calvet & Adlai Fisher, 2008. "Multifractal Volatility: Theory, Forecasting and Pricing," Post-Print hal-00671877, HAL.
- Eric Hillebrand & Marcelo C. Medeiros, 2016.
"Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 23-41, January.
- Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
- 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.
- Koopman, Siem Jan & Ooms, Marius & Carnero, M. Angeles, 2007.
"Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices,"
Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 16-27, March.
- Siem Jan Koopman & Marius Ooms & M. Angeles Carnero, 2005. "Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 05-091/4, Tinbergen Institute.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Adam Misiorek & Rafal Weron, 2006. "Interval forecasting of spot electricity prices," HSC Research Reports HSC/06/05, Hugo Steinhaus Center, Wroclaw University of Technology.
- Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
- Apergis, Nicholas & Lau, Marco Chi Keung, 2015. "Structural breaks and electricity prices: Further evidence on the role of climate policy uncertainties in the Australian electricity market," Energy Economics, Elsevier, vol. 52(PA), pages 176-182.
- Tao Hong, 2014.
"Energy Forecasting: Past, Present, and Future,"
Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 32, pages 43-48, Winter.
- Tao Hong, 2013. "Energy forecasting: Past, present and future," HSC Research Reports HSC/13/15, Hugo Steinhaus Center, Wroclaw University of Technology.
- Jakub Nowotarski & Rafał Weron, 2015.
"Computing electricity spot price prediction intervals using quantile regression and forecast averaging,"
Computational Statistics, Springer, vol. 30(3), pages 791-803, September.
- Jakub Nowotarski & Rafal Weron, 2013. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," HSC Research Reports HSC/13/12, Hugo Steinhaus Center, Wroclaw University of Technology.
- Qu, Hui & Chen, Wei & Niu, Mengyi & Li, Xindan, 2016. "Forecasting realized volatility in electricity markets using logistic smooth transition heterogeneous autoregressive models," Energy Economics, Elsevier, vol. 54(C), pages 68-76.
- Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
- Helen Higgs & Andrew C. Worthington, 2005. "Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 23-42.
- Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997.
"A Multifractal Model of Asset Returns,"
Cowles Foundation Discussion Papers
1164, Cowles Foundation for Research in Economics, Yale University.
- Laurent Calvet & Adlai Fisher & Benoit Mandelbrot, 1999. "A Multifractal Model of Assets Returns," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-072, New York University, Leonard N. Stern School of Business-.
- Laurent-Emmanuel Calvet & Benoît B. Mandelbrot & Adlai J. Fisher, 2011. "A Multifractal Model of Asset Returns," Working Papers hal-00601870, HAL.
- Gerrit Reher & Bernd Wilfling, 2016. "A nesting framework for Markov-switching GARCH modelling with an application to the German stock market," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 411-426, March.
- Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.
- Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2017. "Modeling and forecasting the volatility of carbon dioxide emission allowance prices: A review and comparison of modern volatility models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 692-704.
- Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
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.- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018.
"Forecasting Inflation Uncertainty in the G7 Countries,"
Econometrics, MDPI, vol. 6(2), pages 1-25, April.
- Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018. "Forecasting Inflation Uncertainty in the G7 Countries," CQE Working Papers 7118, Center for Quantitative Economics (CQE), University of Muenster.
- Lux, Thomas & Segnon, Mawuli & Gupta, Rangan, 2015.
"Modeling and forecasting crude oil price volatility: Evidence from historical and recent data,"
FinMaP-Working Papers
31, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Thomas Lux & Mawuli K. Segnon & Rangan Gupta, 2015. "Modeling and Forecasting Crude Oil Price Volatility: Evidence from Historical and Recent Data," Working Papers 201511, University of Pretoria, Department of Economics.
- Charles, Amélie & Darné, Olivier, 2017.
"Forecasting crude-oil market volatility: Further evidence with jumps,"
Energy Economics, Elsevier, vol. 67(C), pages 508-519.
- Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
- Per B. Solibakke, 2022. "Step‐ahead spot price densities using daily synchronously reported prices and wind forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 17-42, January.
- Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2017. "Modeling and forecasting the volatility of carbon dioxide emission allowance prices: A review and comparison of modern volatility models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 692-704.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Nowotarski, Jakub & Weron, Rafał, 2018.
"Recent advances in electricity price forecasting: A review of probabilistic forecasting,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
- Jakub Nowotarski & Rafal Weron, 2016. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports HSC/16/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Rafal Weron & Florian Ziel, 2018.
"Electricity price forecasting,"
HSC Research Reports
HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
- Katarzyna Maciejowska & Rafal Weron, 2019. "Electricity price forecasting," HSC Research Reports HSC/19/01, Hugo Steinhaus Center, Wroclaw University of Technology.
- Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2021.
"High-Frequency Volatility Forecasting of US Housing Markets,"
The Journal of Real Estate Finance and Economics, Springer, vol. 62(2), pages 283-317, February.
- Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
- Qu, Hui & Duan, Qingling & Niu, Mengyi, 2018. "Modeling the volatility of realized volatility to improve volatility forecasts in electricity markets," Energy Economics, Elsevier, vol. 74(C), pages 767-776.
- Shadi Tehrani & Jesús Juan & Eduardo Caro, 2022. "Electricity Spot Price Modeling and Forecasting in European Markets," Energies, MDPI, vol. 15(16), pages 1-23, August.
- Avci, Ezgi & Ketter, Wolfgang & van Heck, Eric, 2018. "Managing electricity price modeling risk via ensemble forecasting: The case of Turkey," Energy Policy, Elsevier, vol. 123(C), pages 390-403.
- Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020.
"Comparing the forecasting performances of linear models for electricity prices with high RES penetration,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Papers 1801.01093, arXiv.org, revised Nov 2019.
- Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
- Nasr, Adnen Ben & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2016.
"Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching,"
International Review of Economics & Finance, Elsevier, vol. 45(C), pages 559-571.
- Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
- Ben Nasr, Adnen & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching," FinMaP-Working Papers 2, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Adnen Ben Nasr & Thomas Lux & Ahdi N. Ajmi & Rangan Gupta, 2014. "Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching," Working Papers 201412, University of Pretoria, Department of Economics.
- Adnen Ben Nasr & Thomas Lux & Ahdi Noomen Ajmi & Rangan Gupta, 2014. "Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching," Working Papers 2014-236, Department of Research, Ipag Business School.
- Scharth, Marcel & Medeiros, Marcelo C., 2009.
"Asymmetric effects and long memory in the volatility of Dow Jones stocks,"
International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
- Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil).
- Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
- Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2015.
"Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-type Volatility Models,"
FinMaP-Working Papers
46, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Mawuli Segnon & Thomas Lux & Rangan Gupta, 2015. "Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-Type Volatility Models," Working Papers 201550, University of Pretoria, Department of Economics.
- repec:bny:wpaper:0060 is not listed on IDEAS
- Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
More about this item
Keywords
Electricity price volatility; multifractal modeling; GARCH processes; volatility forecasting;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
NEP fields
This paper has been announced in the following NEP Reports:- NEP-DCM-2017-06-04 (Discrete Choice Models)
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:cqe:wpaper:6117. 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: Susanne Deckwitz (email available below). General contact details of provider: https://edirc.repec.org/data/cqmuede.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.