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Article
Peer-Review Record

Evidence of Economic Policy Uncertainty and COVID-19 Pandemic on Global Stock Returns

J. Risk Financial Manag. 2022, 15(1), 28; https://doi.org/10.3390/jrfm15010028
by Thomas Chinan Chiang
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3: Anonymous
J. Risk Financial Manag. 2022, 15(1), 28; https://doi.org/10.3390/jrfm15010028
Submission received: 30 September 2021 / Revised: 10 December 2021 / Accepted: 14 December 2021 / Published: 10 January 2022
(This article belongs to the Special Issue Volatility Modelling and Forecasting)

Round 1

Reviewer 1 Report

In the article the authors try to connect economic policy uncertainty indexes (EPU) with stock market behaviour. The results are quite interesting but calculation cross correlations over such long period of time - 30 years may significantly average the results and thus destroys any potentially interesting informations. Additionally, there is quite well known effect of strong correlations between stock markets during high volatility, usually connected with market crashes. In this context the highest cross-correlations observed during years 2008-2010 are not surprising. It is a pity that The covered data ends on April 2019. I will recommend to extend it to 2021 and see what effect have the Covid market crash on all markets in USD. It affected returns distributions and sparked correlations in stock markets see for example "Financial Return Distributions: Past, Present, and COVID-19" Entropy 2021, 23, 884. https://doi.org/10.3390/e23070884. There are no axis labels in Figs 1-4. Additionally there are many lines which crossed each other and thus they are hardly visible. Maybe it will be good idea to put less lines on each figure or calculate values for correlation matrix which contains all indexes like eigenvalues and eigenvectors. Especially the dynamic behaviour of largest eigenvalue and is eigenvector would v bvc give the information about collective behaviour of the stock indexes. The main results presented in Tab 6 were calculated over whole considered period and thus the value of such information could be low low, because different factors over 30 years were averaged. It will be more informative to perform such analysis also in rolling window. Minor issues: Tables 1-3 are really big and should be moved to the appendix.

Author Response

See attached

Author Response File: Author Response.docx

Reviewer 2 Report

The paper requires thorough corrections. Please find my remarks and comments below:

  1. The contribution of the study is not clearly justified. One of the literature review objectives is to identify the gap in the existing literature and develop a hypothesis to fill that gap. The contribution is not clear neither the research hypothesis.
  2. The form of the article should be improved. There is no adequately developed Research Methodology section, in which the authors will indicate the aim of the research, research hypotheses, describe all the research methods used (including formulas) and the data used for the study (including the time for which the analysis is performed). The Research Results section should contain only the description of the results, not the introduction of formulas.
  3. The research period is not precisely indicated. Why is the data used for the research not covering the time of the COVID-19 pandemic? A significant contribution to the study would be to show the impact on the research results of taking into account the time of instability, high uncertainty, which was undoubtedly the time of the new coronavirus pandemic.
  4. The justification of the applied models is not presented. Why did the authors decide to choose these models? Do the models fit the data? Are there other models that also might be applied for the research? Critical discussion of the selected method is missing.
  5. The authors did not check the properties of the studied variables, i.e. their stationarity. There is a lack of tests and diagnostics for unit roots, homogeneity, cointegration, structural stability and nonlinearity.
  6. It is hard to verify that the applied GARCH model is appropriate. I cannot find ARCH effect diagnostics, the sign and size bias test for asymmetric GARCH, and the choice of distribution of residuals (Gaussian, Student's t or GED).
  7. The paper lacks a discussion section. Are the results in line with the other studies? The results need to be presented fully, interpreted with the direct link of the existing literature and theories.
  8. The conclusion section should be corrected. The authors should provide the purpose of the study, main findings, the significance and relevance of the results, limitation of the research and the plan for future research on the topic.
  9. The article requires English proofreading.

Author Response

See attached

Author Response File: Author Response.docx

Reviewer 3 Report

The article is well structured and clearly presented. The objective of this work is presented in a precise manner, although the methodology used is very basic and the conclusions of this work could have been further elaborated. It would be advisable for future works a greater deepening that would enrich the conclusions.

Author Response

See attached

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors satisfied all my remarks.

Reviewer 2 Report

The authors responded to all of my comments and remarks. I accept the paper in the present form.

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