Vaibhav Lalwani
Personal Details
First Name: | Vaibhav |
Middle Name: | |
Last Name: | Lalwani |
Suffix: | |
RePEc Short-ID: | pla1103 |
[This author has chosen not to make the email address public] | |
http://www.vaibhavfin.com | |
Affiliation
Xavier Labour Relations Institute (XLRI)
Jamshedpur, Indiahttp://www.xlri.ac.in/
RePEc:edi:xlrijin (more details at EDIRC)
Research output
Jump to: ArticlesArticles
- Lalwani, Vaibhav, 2024. "Incorporating green assets in equity portfolios," Finance Research Letters, Elsevier, vol. 59(C).
- Vaibhav Lalwani & Vedprakash Vasantrao Meshram, 2022. "The cross-section of Indian stock returns: evidence using machine learning," Applied Economics, Taylor & Francis Journals, vol. 54(16), pages 1814-1828, April.
- Vaibhav Lalwani & Madhumita Chakraborty, 2020. "Aggregate earnings and gross domestic product: International evidence," Applied Economics, Taylor & Francis Journals, vol. 52(1), pages 68-84, January.
- Lalwani, Vaibhav & Chakraborty, Madhumita, 2018. "Asset pricing factors and future economic growth," Economics Letters, Elsevier, vol. 168(C), pages 151-154.
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
- Lalwani, Vaibhav, 2024.
"Incorporating green assets in equity portfolios,"
Finance Research Letters, Elsevier, vol. 59(C).
Cited by:
- Mohammed, Kamel Si & Serret, Vanessa & Urom, Christian, 2024. "The effect of green bonds on climate risk amid economic and environmental policy uncertainties," Finance Research Letters, Elsevier, vol. 62(PA).
- Vaibhav Lalwani & Vedprakash Vasantrao Meshram, 2022.
"The cross-section of Indian stock returns: evidence using machine learning,"
Applied Economics, Taylor & Francis Journals, vol. 54(16), pages 1814-1828, April.
Cited by:
- Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
- Antonio Marsi, 2023. "Predicting European stock returns using machine learning," SN Business & Economics, Springer, vol. 3(7), pages 1-25, July.
- Vaibhav Lalwani & Madhumita Chakraborty, 2020.
"Aggregate earnings and gross domestic product: International evidence,"
Applied Economics, Taylor & Francis Journals, vol. 52(1), pages 68-84, January.
Cited by:
- Thanh NGUYEN, Phong & Le Hoang Thuy To NGUYEN, Quyen, 2020. "Critical Factors Affecting Construction Price Index: An Integrated Fuzzy Logic and Analytical Hierarchy Process," MPRA Paper 103437, University Library of Munich, Germany, revised 31 May 2020.
- Lalwani, Vaibhav & Chakraborty, Madhumita, 2018.
"Asset pricing factors and future economic growth,"
Economics Letters, Elsevier, vol. 168(C), pages 151-154.
Cited by:
- José Clemente Jacinto Ferreira & Ana Paula Matias Gama & Luiz Paulo Fávero & Ricardo Goulart Serra & Patrícia Belfiore & Igor Pinheiro de Araújo Costa & Marcos dos Santos, 2022. "Economic Performance and Stock Market Integration in BRICS and G7 Countries: An Application with Quantile Panel Data and Random Coefficients Modeling," Mathematics, MDPI, vol. 10(21), pages 1-35, October.
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