The Dynamic Correlation and Volatility Spillover among Green Bonds, Clean Energy Stock, and Fossil Fuel Market

Round 1

Reviewer 1 Report

 This manuscript needs further improvements, namely:

1.     The literature review needs to be updated with more recent references. For example:

·         https://doi.org/10.1016/j.eneco.2022.106429

·         https://doi.org/10.1016/j.resourpol.2022.103200

·         https://doi.org/10.1016/j.techfore.2022.122134

·         https://doi.org/10.1016/j.qref.2023.02.006

·         https://doi.org/10.1016/j.eneco.2022.106499

·         https://doi.org/10.1080/1331677X.2022.2077794

·         https://doi.org/10.1016/j.bir.2022.12.003

 2.     The authors used only standards unit root tests (ADF,  PP, and KPSS) tests to check  the stationarity of the variables. However, it's well known that this kind of tests may suffer from power deficiency in the presence of structural breaks. In consequence, It will be interesting for the manuscript to to add a recent test that allow for structural break(s), such as ZA, Lee and Strazicich (2013, 2003) LM, Narayan and Popp (2010), or RALS-LM (2014) tests. These tests are generally more accurate compared to the standard tests.

3.     In virtue of the update of the literature (point 1), the discussion of the obtained results and their comparison to the existing literature on the subject need to be improved. Did their findings confirm previous findings? Did their approach provide additional insight, beyond what other similar studies have provided?

4.     Policy implications are very general recommendations. Policy recommendations/ suggestions are the major focus of all researchers and policymakers, therefore improve this section. It would be interesting to expand the recommendations with more specific recommendations consistent with their findings. We note in the text the use of “policymakers should establish mechanisms”. What are they? Any further explanations will be recommended.

 

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

The paper as a whole does not look good and it looks very far from publication quality. There is no clear goal for the paper.

The paper states:

"This study offers two important contributions. First, it analyzes the changes in the volatility spillover effects among GBs CE, and fossil fuels in the short-term, medium-term, and long-term horizons. Second, it introduces a new method that combines the Bayesian DCC-MGARCH model and frequency connectedness method ([4] BK, 2018)."

For the first claimed contribution, there is no value on analyzing the changes of volatility spillover in terms of merit to publish the work as journal paper. It is a routine data analysis task.

For the second claimed contribution, more has to be done to really show (1) you accomplished what you claim you did, and (2) show clearly the results and their implications. This second claim has to be verified, and this requires the authors to show/share codes and datasets used to implement these computation workflow. The URLs provided in the section "Data Availability Statement" are not the proper way for showing data. Use online repositories such as GitHub or GoogleColab to make these datasets accessible. The same goes for the codes. The "Author Contributions" section shows "software", so there must be some code used for the data analytics workflow.

The overall quality of the paper is poor that reviewing it is very difficult to the eye and to the thought. Also, it is difficult to understand equations and graphs.

Author Response

Response to Reviewer 2 Comments

Point 1: The paper as a whole does not look good and it looks very far from publication quality. There is no clear goal for the paper.

Response 1: Thank you for the suggestion. According to your suggestion, we have made some modifications to the whole paper including a further explanation of the figures and implications, and our goal is to help investors or policymakers to achieve sustainable investment, which is illustrated in the ln95-98 of introduction: “ our goal is to propose sustainable investment recommendations to investors or policymakers who want to identify the importance of the GBs markets and deal with the price volatility risk involved in developing the GBs markets.”

 

Point 2: The paper states: "This study offers two important contributions. First, it analyzes the changes in the volatility spillover effects among GBs CE, and fossil fuels in the short-term, medium-term, and long-term horizons. Second, it introduces a new method that combines the Bayesian DCC-MGARCH model and frequency connectedness method ([4] BK, 2018)."

For the first claimed contribution, there is no value on analyzing the changes of volatility spillover in terms of merit to publish the work as journal paper. It is a routine data analysis task.

For the second claimed contribution, more has to be done to really show (1) you accomplished what you claim you did, and (2) show clearly the results and their implications. This second claim has to be verified, and this requires the authors to show/share codes and datasets used to implement these computation workflow.

Response 2: Thank you very much for the valuable comment.

 

This paper’s objective was not to introduce new analytical method but to apply a relatively new quantitative method on relationships among green bond and fossil fuel market. Thus, we revised the paper not to make the readers to understand that our paper’s contribution is in the methodology part explanation for the above two contributions, we apologize to misunderstand you. In order to remove

the misunderstanding, we have made some modifications to explain the above two contributions in ln105-109 and ln109-122 of introduction.

 

In ln105-109, we have added some explanation for making the readers to understand the first contributions: “First, it analyzes the changes in the volatility spillover effects among GBs CE, and fossil fuels in the short-term, medium-term, and long-term horizons for investors or policymakers to identify the price volatility spillover risk of another energy market on GBs markets from a frequency perspective to achieve sustainable investment. ”

 

Reviewer 3 Report

I have read the paper and checked the existing studies in the literature. I think that the paper quality is sufficient and it needs minor revisions before a possible publication. The comments and suggestions are given as below:
Comment 1: The abstract of the paper is not clear. It does not indicate the main methods and conclusions adopted in the paper.
Comment 2: Please check the expressions of the whole paper as there are some mistakes, such as the sentence in page 2 - line 16, in page 3 - line 8, in page 5 - line 23.
Comment 3: Figure 3 should be revised. It should be simpler and clearer. Figure 3 should be improved and not enough good to show that relations.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Dear authors,

Broadly, I am satisfied with the current version.

Author Response

Thank you very much for your valuable comment. 

Reviewer 2 Report

Manuscript: sustainability-2270567

Title: The Dynamic Correlation and Volatility Spillover among Green Bonds, Clean Energy Stock, and Fossil Fuel Market

 

Reviews:

The main issue with the work is that there is no proof of how the computations were done. The majority of published literature in the matter have the copies of codes and actual datasets used provided in the papers as an attachment supplementary material or some with links to repositories of the codes. One example is the work that pioneered the DCC-GARCH with this online url: https://sites.google.com/view/davidgabauer/econometric-code (David Gabauer) Gabauer, D. (2020). Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms. Journal of Forecasting, 39(5), 788-796.

 

The current paper is a subsequent paper to a paper published by the authors also in Sustainability MPDI. That paper “Tang, C.; Aruga, K. Relationships among the Fossil Fuel and Financial Markets during the COVID-19 Pandemic: Evidence from Bayesian DCC-MGARCH Models. Sustainability 2022, 14, 51. https://doi.org/10.3390/su14010051” did not even show how the data analytics were actually implemented in either a software or code-based implementation. This prior paper claims to have successfully implemented the DCC-MGARCH, but there was no show of an actual implementation, unlike the other published materials in the area like the one mentioned above on the DCC-GARCH.

 

Author Response

Response to Reviewer 2 Comments

The main issue with the work is that there is no proof of how the computations were done. The majority of published literature in the matter have the copies of codes and actual datasets used provided in the papers as an attachment supplementary material or some with links to repositories of the codes. One example is the work that pioneered the DCC-GARCH with this online url: https://sites.google.com/view/davidgabauer/econometric-code (David Gabauer) Gabauer, D. (2020). Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms. Journal of Forecasting, 39(5), 788-796.

The current paper is a subsequent paper to a paper published by the authors also in Sustainability MPDI. That paper “Tang, C.; Aruga, K. Relationships among the Fossil Fuel and Financial Markets during the COVID-19 Pandemic: Evidence from Bayesian DCC-MGARCH Models. Sustainability 2022, 14, 51. https://doi.org/10.3390/su14010051” did not even show how the data analytics were actually implemented in either a software or code-based implementation. This prior paper claims to have successfully implemented the DCC-MGARCH, but there was no show of an actual implementation, unlike the other published materials in the area like the one mentioned above on the DCC-GARCH.

Response:  Thank you very much for the valuable comment. According your suggestion, we will provide a attachment file to the sustainability office to make a online repositories to share the used code and data. By the way, the sustainability doesn’t require the authors to provide full code for the analyzes.  To facilitate readers' quick access to code and data information, we have added an explanation in the ln396-397:“For a detailed computations please see the links in the “Supplementary Material”.”and added“Supplementary Materials”in ln683-684.

 

Round 3

Reviewer 2 Report

The authors responded to the major review comment on availability of codes in this manner in the manuscript: "Supplementary Materials: The used code and data are available online at: “the links 669 will be provide from sustainability office if our paper is received".

This is not how peer-review for publication works. Everything including the codes, which in this kind of work is the core implementation of the conceptualized mathematical transformations. Before the paper can be published, the review process has to verify that the codes are in existence and can replicate the claimed results of the paper. Until then, the results are put to question.

Author Response

Dear reviewer 

We submitted the code and data source in the last revision along with the manuscript. Have you checked the supplementary file provided as a zip file? If not, the code and data source are submitted again as a supplementary file attached together with the manuscript. Please check the zip file provided with the submission.