The Role of GARCH Effect on the Prediction of Air Pollution
Author
Abstract
Suggested Citation
Download full text from publisher
References 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.
- Engle, Robert & Granger, Clive, 2015.
"Co-integration and error correction: Representation, estimation, and testing,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-276, March.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Christoffersen, Peter F & Diebold, Francis X, 1996.
"Further Results on Forecasting and Model Selection under Asymmetric Loss,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 561-571, Sept.-Oct.
- Christoffersen & Diebold, "undated". "Further Results on Forecasting and Model Selection Under Asymmetric Loss," Home Pages _059, University of Pennsylvania.
- Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.
- 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.
- Asger Lunde & Peter R. Hansen, 2005.
"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Kuei Tien Chou, 2015. "From Anti-Pollution to Climate Change Risk Movement: Reshaping Civic Epistemology," Sustainability, MDPI, vol. 7(11), pages 1-23, October.
- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
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.- Efimova, Olga & Serletis, Apostolos, 2014.
"Energy markets volatility modelling using GARCH,"
Energy Economics, Elsevier, vol. 43(C), pages 264-273.
- Olga Efimova & Apostolos Serletis, "undated". "Energy Markets Volatility Modelling using GARCH," Working Papers 2014-39, Department of Economics, University of Calgary, revised 24 Feb 2014.
- Rama K. Malladi & Prakash L. Dheeriya, 2021. "Time series analysis of Cryptocurrency returns and volatilities," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(1), pages 75-94, January.
- Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014.
"Time Series Models for Business and Economic Forecasting,"
Cambridge Books,
Cambridge University Press, number 9780521520911.
- Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707.
- Berger, Jurij & Dalheimer, Bernhard & Brümmer, Bernhard, 2021.
"Effects of variable EU import levies on corn price volatility,"
Food Policy, Elsevier, vol. 102(C).
- Berger, Jurij & Dalheimer, Bernhard & Bruemmer, Bernhard, 2019. "The Effect of Variable EU Import Levies on Corn Price Volatility," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 290922, Agricultural and Applied Economics Association.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005.
"Volatility Forecasting,"
PIER Working Paper Archive
05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc.
- Bai, Xiwen & Lam, Jasmine Siu Lee, 2021. "Freight rate co-movement and risk spillovers in the product tanker shipping market: A copula analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
- Minot, Nicholas, 2014.
"Food price volatility in sub-Saharan Africa: Has it really increased?,"
Food Policy, Elsevier, vol. 45(C), pages 45-56.
- Minot, Nicholas, 2012. "Food price volatility in sub-Saharan Africa: Has it really increased?," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 134146, International Association of Agricultural Economists.
- Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016.
"Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution,"
International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
- Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-921, CIRJE, Faculty of Economics, University of Tokyo.
- Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2015. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-975, CIRJE, Faculty of Economics, University of Tokyo.
- Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
- Harry-Paul Vander Elst, 2015.
"FloGARCH: Realizing Long Memory and Asymmetries in Returns Valitility,"
Working Papers ECARES
ECARES 2015-12, ULB -- Universite Libre de Bruxelles.
- Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
- Dutta, Shantanu & Essaddam, Naceur & Kumar, Vinod & Saadi, Samir, 2017. "How does electronic trading affect efficiency of stock market and conditional volatility? Evidence from Toronto Stock Exchange," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 867-877.
- Charles, Amélie, 2010.
"The day-of-the-week effects on the volatility: The role of the asymmetry,"
European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
- Amélie Charles, 2010. "The day-of-the week effects on the volatility: The role of the asymmetry," Post-Print hal-00771136, HAL.
- Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
- Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
- Osamah M. Al-Khazali, 2003. "Stock Prices, Inflation, and Output: Evidence from the Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 2(3), pages 287-314, September.
- repec:zbw:rwirep:0243 is not listed on IDEAS
- Pami Dua & Nishita Raje & Satyananda Sahoo, 2004.
"Interest Rate Modeling and Forecasting in India,"
Occasional papers
3, Centre for Development Economics, Delhi School of Economics.
- Pami Dua, 2008. "Interest Rate Modeling and Forecasting in India," Working Papers id:1521, eSocialSciences.
- Siem Jan Koopman & André Lucas & Marcel Scharth, 2016.
"Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models,"
The Review of Economics and Statistics, MIT Press, vol. 98(1), pages 97-110, March.
- Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
- Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
- Bernardi, Mauro & Costola, Michele, 2019. "High-dimensional sparse financial networks through a regularised regression model," SAFE Working Paper Series 244, Leibniz Institute for Financial Research SAFE.
- Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005.
"Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements,"
Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
- Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004. "Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements," Tinbergen Institute Discussion Papers 04-016/4, Tinbergen Institute.
- Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
More about this item
Keywords
GA-SVM; GARCH; PM 2.5 prediction; machine learning;All these keywords.
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:gam:jsusta:v:14:y:2022:i:8:p:4459-:d:789825. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.