A simple linear alternative to multiplicative error models with an application to trading volume
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, vol. 13(2), pages 161-174, June.
- Moisan, Stella & Herrera, Rodrigo & Clements, Adam, 2018.
"A dynamic multiple equation approach for forecasting PM2.5 pollution in Santiago, Chile,"
International Journal of Forecasting, Elsevier, vol. 34(4), pages 566-581.
- Stella Moisan & Rodrigo Herrera & Adam Clements, 2017. "A Dynamic Multiple Equation Approach for Forecasting PM2.5 Pollution in Santiago, Chile," NCER Working Paper Series 117, National Centre for Econometric Research.
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011.
"Intra-daily Volume Modeling and Prediction for Algorithmic Trading,"
Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 489-518, Summer.
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Econometrics Working Papers Archive wp2009_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Soares, Lacir J. & Medeiros, Marcelo C., 2008. "Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 630-644.
- Peirson, John & Henley, Andrew, 1994. "Electricity load and temperature : Issues in dynamic specification," Energy Economics, Elsevier, vol. 16(4), pages 235-243, October.
- repec:bla:jfinan:v:43:y:1988:i:1:p:97-112 is not listed on IDEAS
- Bialkowski, Jedrzej & Darolles, Serge & Le Fol, Gaëlle, 2008.
"Improving VWAP strategies: A dynamic volume approach,"
Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1709-1722, September.
- Jedrzej Białkowski & Serge Darolles & Gaëlle Le Fol, 2006. "Improving VWAP strategies: A dynamical volume approach," Documents de recherche 06-08, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
- Jedrzej Bialkowski & Serge Darolles & Gaëlle Le Fol, 2008. "Improving VWAP strategies: A dynamic volume approach," Post-Print halshs-00676946, HAL.
- Jędrzej Białkowski & Serge Darolles & Gaëlle Le Fol, 2008. "Improving VWAP strategies: A dynamic volume approach," Post-Print hal-02877984, HAL.
- Clements, A.E. & Hurn, A.S. & Li, Z., 2016.
"Forecasting day-ahead electricity load using a multiple equation time series approach,"
European Journal of Operational Research, Elsevier, vol. 251(2), pages 522-530.
- Adam Clements & Stan Hurn & Zili Li, 2014. "Forecasting day-ahead electricity load using a multiple equation time series approach," NCER Working Paper Series 103, National Centre for Econometric Research, revised 06 May 2015.
- Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016.
"Exploiting the errors: A simple approach for improved volatility forecasting,"
Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
- Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
- Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
- Engle, Robert F. & Gallo, Giampiero M., 2006.
"A multiple indicators model for volatility using intra-daily data,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
- Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model For Volatility Using Intra-Daily Data," Econometrics Working Papers Archive wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model for Volatility Using Intra-Daily Data," NBER Working Papers 10117, National Bureau of Economic Research, Inc.
- Naimoli, Antonio & Storti, Giuseppe, 2019.
"Heterogeneous component multiplicative error models for forecasting trading volumes,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
- Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
- 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.
- Tom Doan, 2025. "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
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.- Cipollini, Fabrizio & Gallo, Giampiero M., 2025.
"Multiplicative Error Models: 20 years on,"
Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
- Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
- Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
- Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
- Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
- Harvey, Andrew & Palumbo, Dario, 2023.
"Score-driven models for realized volatility,"
Journal of Econometrics, Elsevier, vol. 237(2).
- Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
- Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
- Clements, Adam & Preve, Daniel P.A., 2021.
"A Practical Guide to harnessing the HAR volatility model,"
Journal of Banking & Finance, Elsevier, vol. 133(C).
- A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
- Catania, Leopoldo & Proietti, Tommaso, 2020.
"Forecasting volatility with time-varying leverage and volatility of volatility effects,"
International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
- Leopoldo Catania & Tommaso Proietti, 2019. "Forecasting Volatility with Time-Varying Leverage and Volatility of Volatility Effects," CEIS Research Paper 450, Tor Vergata University, CEIS, revised 06 Feb 2019.
- Ding, Yi & Engle, Robert & Li, Yingying & Zheng, Xinghua, 2025. "Multiplicative factor model for volatility," Journal of Econometrics, Elsevier, vol. 249(PB).
- Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
- Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2023.
"A Machine Learning Approach to Volatility Forecasting,"
Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1680-1727.
- Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
- Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2026. "A machine learning approach to volatility forecasting," Papers 2601.13014, arXiv.org.
- Luca Scaffidi Domianello & Giampiero M. Gallo & Edoardo Otranto, 2024.
"Smooth and Abrupt Dynamics in Financial Volatility: The MS‐MEM‐MIDAS,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 21-43, February.
- L. Scaffidi Domianello & G.M. Gallo & E. Otranto, 2022. "Smooth and Abrupt Dynamics in Financial Volatility: the MS-MEM-MIDAS," Working Paper CRENoS 202205, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- 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.
- Dumitru, Ana Maria H. & Hizmeri, Rodrigo & Izzeldin, Marwan, 2025. "Forecasting the realized variance in the presence of intraday periodicity," Journal of Banking & Finance, Elsevier, vol. 170(C).
- Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2017.
"Realized stochastic volatility with general asymmetry and long memory,"
Journal of Econometrics, Elsevier, vol. 199(2), pages 202-212.
- Asai, M. & Chang, C-L. & McAleer, M.J., 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Econometric Institute Research Papers TI 2017-038/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Manabu Asai & Chia-Lin Chang & Michael McAleer, 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Tinbergen Institute Discussion Papers 17-038/III, Tinbergen Institute.
- 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.
- Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
- Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
- Bekierman, Jeremias & Manner, Hans, 2018. "Forecasting realized variance measures using time-varying coefficient models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 276-287.
- Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024.
"Doubly multiplicative error models with long- and short-run components,"
Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
- Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
More about this item
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
- G00 - Financial Economics - - General - - - General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CWA-2021-12-20 (Central and Western Asia)
- NEP-ECM-2021-12-20 (Econometrics)
- NEP-ETS-2021-12-20 (Econometric Time Series)
- NEP-FOR-2021-12-20 (Forecasting)
- NEP-ORE-2021-12-20 (Operations Research)
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:tas:wpaper:38716. 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: Oscar Pavlov (email available below). General contact details of provider: https://edirc.repec.org/data/dutasau.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/p/tas/wpaper/38716.html