IDEAS home Printed from https://ideas.repec.org/e/pdh31.html
   My authors  Follow this author

Ajay Kumar Dhamija

Personal Details

First Name:Ajay
Middle Name:Kumar
Last Name:Dhamija
Suffix:
RePEc Short-ID:pdh31
http://www.akdhamija.webs.com/

Affiliation

DRDO (DRDO)

http://www.drdo.org/
Delhi , India

Research output

as
Jump to: Articles

Articles

  1. Ajay Kumar Dhamija & Surendra S. Yadav & P.K. Jain, 2017. "Carbon credit returns under EU ETS and its determinants: a multi-phase study," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 14(4), pages 481-526, October.
  2. Ajay K. Dhamija & Surendra S. Yadav & PK Jain, 2017. "Forecasting volatility of carbon under EU ETS: a multi-phase study," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(2), pages 299-335, April.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Ajay K. Dhamija & Surendra S. Yadav & PK Jain, 2017. "Forecasting volatility of carbon under EU ETS: a multi-phase study," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(2), pages 299-335, April.

    Cited by:

    1. Huang, Wenyang & Wang, Huiwen & Qin, Haotong & Wei, Yigang & Chevallier, Julien, 2022. "Convolutional neural network forecasting of European Union allowances futures using a novel unconstrained transformation method," Energy Economics, Elsevier, vol. 110(C).
    2. Liu, Tao & Guan, Xinyue & Wei, Yigang & Xue, Shan & Xu, Liang, 2023. "Impact of economic policy uncertainty on the volatility of China's emission trading scheme pilots," Energy Economics, Elsevier, vol. 121(C).
    3. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    4. Po Yun & Chen Zhang & Yaqi Wu & Yu Yang, 2022. "Forecasting Carbon Dioxide Price Using a Time-Varying High-Order Moment Hybrid Model of NAGARCHSK and Gated Recurrent Unit Network," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
    5. Yang Liu & Xueqing Yang & Mei Wang, 2021. "Global Transmission of Returns among Financial, Traditional Energy, Renewable Energy and Carbon Markets: New Evidence," Energies, MDPI, vol. 14(21), pages 1-32, November.
    6. Wen Zhang & Zhibin Wu, 2022. "Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 615-632, April.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Ajay Kumar Dhamija should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.