Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Price discovery analysis of green equity indices using robust asymmetric vector autoregression

Cummins, Mark orcid logoORCID: 0000-0002-3539-8843, Garry, Oonagh and Kearney, Claire (2014) Price discovery analysis of green equity indices using robust asymmetric vector autoregression. International Review of Financial Analysis, 35 . pp. 261-267. ISSN 1057-5219

Abstract
Covering the first commitment period of the Kyoto Protocol (2008-2012), we per7 form a price discovery analysis to determine Granger causality relationships for a range 8 of prominent green equity indices with the broader equity and commodity markets. 9 Three pivotal contributions are made. Firstly, an expanded database is used that gives 10 greater depth to the price discovery analysis relative to previous literature. Prominent 11 global, regional and sectoral green equity indices are considered, as well as a broader 12 set of commodities including crude oil, natural gas and emissions. The inclusion of 13 natural gas recognises its role as the transition fossil fuel to a low carbon economy. 14 In addition to the main European Union Allowance traded under the EU Emissions 15 Trading Scheme, Certified Emissions Reduction (CER) prices are also included in the 16 emissions database to capture activities under the global Clean Development Mecha17 nism. Secondly, a problem with conventional symmetric vector autoregression is that 18 its implementation commonly leads to large occurrences of insignificant parameters. 19 Therefore, as a first layer of robustness, we utilise an asymmetric vector autoregres20 sion model to perform the Granger causality testing, which addresses this limitation 21 by means of allowing different lag specifications among the system variables. Thirdly, 22 explicit recognition is made in our study of the multiple comparisons bias inherent 23 in our high-dimensional testing framework, which is the non-negligible likelihood ofidentifying statistically significant results by pure chance alone. As a second layer of 25 robustness, we utilise a generalised Holm correction method to control this source of 26 bias. At conventional statistical significance levels, we find that the FTSE 100 and 27 FTSE Global Small Cap equity indices have a causal effect on all of the green equity 28 indices, with limited evidence of causality in the opposite direction. Within the green 29 equity markets, we find evidence that the chosen sectoral index has a Granger causal 30 effect on one of the two global indices considered and also the regional index. This price 31 transmission provides modest evidence that the global green economy is becoming ever 32 more integrated. NBP gas is shown to have a causal effect on all of the green equity 33 indices, whereas we find no such evidence for Brent oil. The former observation may 34 reflect the increasing role of gas as the transition fuel to a low carbon economy, play35 ing a key role in decisions on power generation mix and associated capital investment. 36 Finally, we find no evidence that EUA or CER emissions prices have a causal effect 37 on green stocks, consistent with previous findings and likely reflecting the excessively 38 low prices being commanded for compliance permits in the European emissions markets.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:green equity indices; asymmetric vector autoregression; Granger causality; multiple hypothesis testing; multiple comparisons bias
Subjects:Business > Finance
DCU Faculties and Centres:DCU Faculties and Schools > DCU Business School
Publisher:Elsevier
Official URL:http://dx.doi.org/10.1016/j.irfa.2014.10.006
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:26465
Deposited On:15 Nov 2021 10:18 by Fran Callaghan . Last Modified 21 Feb 2022 13:38
Documents

Full text available as:

[thumbnail of FINAL_PAPER_AcceptedManuscriptVersion.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
328kB
Metrics

Altmetric Badge

Dimensions Badge

Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record