The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Price connectedness between green bond and financial markets
Abstract
Abstract We study price connectedness between the green bond and financial markets using a structural vector autoregressive (VAR) model that captures direct and indirect transmission of financial shocks across markets. Using heteroskedasticity to identify the structural VAR model parameters, our empirical findings reveal that the green bond market is closely linked to the fixed-income and currency markets, receiving sizeable price spillovers from those markets and transmitting negligible reverse effects. We also show that, in contrast, the green bond market is weakly tied to the stock, energy and high-yield corporate bond markets. These findings have implications in terms of portfolio and risk management decisions for environmentally aware investors holding positions in green bonds.
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Cites
Distribution of the Estimators for Autoregressive Time Series with a Unit Root
Dickey, D. A., & Fuller, W. A. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10482531 · Cited by 23,211
Testing the null hypothesis of stationarity against the alternative of a unit root
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992) · Journal of Econometrics · doi:10.1016/0304-4076(92)90104-y · Cited by 12,633
Generalized impulse response analysis in linear multivariate models
Pesaran, H. H., & Shin, Y. (1998) · Economics Letters · doi:10.1016/s0165-1765(97)00214-0 · Cited by 6,097
Better to give than to receive: Predictive directional measurement of volatility spillovers
Diebold, F. X., & Yilmaz, K. (2012) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2011.02.006 · Cited by 5,756
On the network topology of variance decompositions: Measuring the connectedness of financial firms
Diebold, F. X., & Yılmaz, K. (2014) · Journal of Econometrics · doi:10.1016/j.jeconom.2014.04.012 · Cited by 4,642
The effect of pro-environmental preferences on bond prices: Evidence from green bonds
Zerbib, O. D. (2019) · Journal of Banking & Finance · doi:10.1016/j.jbankfin.2018.10.012 · Cited by 1,379
Do shareholders benefit from green bonds?
Tang, D. Y., & Zhang, Y. (2020) · Journal of Corporate Finance · doi:10.1016/j.jcorpfin.2018.12.001 · Cited by 1,131
Identification Through Heteroskedasticity
Rigobon, R. (2003) · Review of Economics and Statistics · doi:10.1162/003465303772815727 · Cited by 912
Sadorsky, P. (2012) · Energy Economics · doi:10.1016/j.eneco.2011.03.006 · Cited by 874
Oil prices and the stock prices of alternative energy companies
Henriques, I., & Sadorsky, P. (2008) · Energy Economics · doi:10.1016/j.eneco.2007.11.001 · Cited by 840
Cited by
Green finance, fintech and environmental protection: evidence from China
Muganyi, T., Yan, L., & Sun, H.-P. (2021) · Environmental Science and Ecotechnology · doi:10.1016/j.ese.2021.100107 · Cited by 626
Le, T.-L., Abakah, E. J. A., & Tiwari, A. K. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120382 · Cited by 420
Does green finance inspire sustainable development? Evidence from a global perspective
Wang, K.-H., Zhao, Y.-X., Jiang, C.-F., & Li, Z.-Z. (2022) · Economic Analysis and Policy · doi:10.1016/j.eap.2022.06.002 · Cited by 361
Huynh, T. L. D., Hille, E., & Nasir, M. A. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120188 · Cited by 336
Are green bonds a different asset class? Evidence from time-frequency connectedness analysis
Ferrer, R., Shahzad, S. J. H., & Soriano, P. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.125988 · Cited by 253
Metadata
- Authors
- Reboredo, J. C., & Ugolini, A.
- Venue
- Economic Modelling
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 88
- Pages
- 25-38
- ISSN
- 0264-9993 (ISSN-L)
- OpenAlex
- W2972458016
- Cited by
- 521
- References
- 36
- FWCI
- 46.46
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
