Inferences from Portfolio Theory and Efficient Market Hypothesis to the Impact of Social Media on Sovereign Debt: Colombia, Ecuador, and Peru

Round 1

Reviewer 1 Report

This paper examined that the impact of EMBI for Latin America countries such as Columbia, Ecuador and Peru. The results of this paper can provide some marginal contributions, so that this paper can publish. However, there are several issues in this study that need to be addressed before it is ready to be published for a publication in a journal.

 

• Summarize key empirical finding results in introduction with concise manner.
• Please rewrite the abstract, because it is so confusing.
• Please emphasize the novelty of this paper. In line 428, you said that “the impact of the variables related to the FX of the local currency v.s. the U$ on the EMBI spread.” However, this is proved already by many previous studies.
• Please delete line 49- line 55, which is not relevant for this study.
• Once again, please delete line 117-line 123.

• Please rewrite Hypothesis 1 to Hypothesis 3. It is very confusing. Please keep clear and concise manner.
• The author should provide robustness check of empirical results.
• Please explain why the empirical results are different among 3 Latin American countries.
• Please clarify the line 381, “Moreover, the DW statistic….” It is very confusing.

Author Response

Reviewer 1.

 

• Summarize key empirical finding results in introduction with concise manner.

 

I have redacted as suggested

 

• Please rewrite the abstract, because it is so confusing.

 

I have made it more concise and to the point.  Thank you for your suggestion:

 

For three countries of similar economic characteristics, I ratify previous studies of the impact of fundamental macroeconomic and foreign exchange variables having an effect on country risk, as captured by the Emerging Market Bond Index (EMBI).  I contribute to existing research, first by calculating a proxy of risk I call endogenous risk that analyzes the quarterly variability of economic activity, and second, by calculating a variable of sentiment from Twitter activity to gauge the impact of both on the country risk metric.  Foreign exchange variables are the most significant determinants of risk for the countries of Colombia and Peru who actively manage their currency, while Ecuador’s country risk is mostly affected by endogenous risk and macroeconomic fundamentals.

 

• Please emphasize the novelty of this paper. In line 428, you said that “the impact of the variables related to the FX of the local currency v.s. the U$ on the EMBI spread.” However, this is proved already by many previous studies.

The variables contributed relate to the impact calculation of Twitter activity and what I call the Endogenous Risk by computing the variability of economic activity by ISIC (quarterly)

• Please delete line 49- line 55, which is not relevant for this study.

I have redacted as suggested.

• Once again, please delete line 117-line 123.

I have redacted as suggested.

 

• Please rewrite Hypothesis 1 to Hypothesis 3. It is very confusing. Please keep clear and concise manner.

 

I have reorganized the Hypothesis and placed them in a more organized fashion, as suggested.

• The author should provide robustness check of empirical results.

I have provided robustness checks for multicollinearity and unit root (ADF)

 

• Please explain why the empirical results are different among 3 Latin American countries

The time frame selected for analysis (2000-2019) is a period immediately after Ecuador adopted the US Dollar as its official currency, resulting in an experimental setting conducive for research of these three geographically neighboring, but more importantly from a research question perspective, all three are commodity dependent countries with differing exchange rate policies ranging from substantially non-existent (as a result of Ecuador’s dollarization of its economy) to inflation targeting monetary policy and exchange rate management in Colombia and Peru. 

 

• Please clarify the line 381, “Moreover, the DW statistic….” It is very confusing.

I have redacted as suggested and eliminated that portion

Author Response File: Author Response.docx

Reviewer 2 Report

The present form is not acceptable it requires major modification to improve the novelty.

Author Response

Reviewer 2

 

The present form is not acceptable it requires major modification to improve the novelty.

 

I have thoroughly expanded and redacted the article with the help of colleagues and reviewers suggestions and changes.  Please look over my revised article.  Thank you.

 

Author Response File: Author Response.docx

Reviewer 3 Report

Please attend the next mandatory suggestions:

1. The author Didn't explain with are the three countries of interest selected. please, give a strong foundation to your selection.
2. The statements of lines 34 to 41 about the pricing of risk-premiums i.e. EMBI indexes, need references. Otherwise is the author's mere opinion without support. please give your references (Academic research papers or history research books).
3. The introduction section is too short. I should see the author's hypothetical position or hypothesis to be tested and why is the author doing what it is doing in the paper. Please, expand.
4. The Sovereign debt markets are not as old as the 17th Century. The author must expand his historical perspective with other Financial markets references besides Ferguson. The Sovereign debt market dates back to the 14th Century with Florence. Amsterdam is the place of the first stock market. Please correct and expand your references.
5. The previous literature review looks strong but it needs enhancements. There is a vague link between your work and the motivations it receives from the cited references. Also in that literature review, I can't see how your model variables are related (motivated) with these previous references and how does the author expands the literature with his work. Please, expand your references and relate them to your work.
6. The link Twiter sentiment-Fixed income markets, Twitter sentiment-EMBI spreads are too weak (one reference). There is more work published in Fixed income markets or other security markets about the impact of social media sentiment. Please, expand your references and relate these works with yours as motivations for your tests.
7. Section 3 "The data" looks more like a bullets list or a sort of list. you give general detail but you didn't say how did you process the input data. Please write this section as a description of your test for Scientific replication purposes.
8. Also related to the previous suggestion, because you didn't detail your motivations in the literature review, there is no link or foundation of your list of variables. With due respect, your work is good but this list of variables looks more like an "I think that these variables look good in my test..." I no it is not the case of your paper, but you must be careful of how do you write it in journals of high projection and potential as JFRM. Please attend this.
9. In section 3.4 I finally read the hypothesis. Please, keep in mind that, when someone reads your abstract, she or he reads the conclusions next and, if there's more interest in your paper, she or he reads the introduction section. Your introduction section sells poorly your work and it doesn't say "what are you doing, how are you doing it, what will our tests be and what do you expect from these". The abstract should say "what did you do, how did you do it, what are your main findings and contributions" and your conclusions should say the same of the abstract, enhanced with the guidelines for further research. These guidelines, given the limitations or opportunity areas that you find in your work. The literature review gives strength to your tests and variables selection. Please, enhance those sections as suggested.
10. Your hypothesis could look better if they are of the type "There is a positive (or negative) relation between X and Y with Z" (general hypothesis) and some particular ones for each variable (X and Y). You also must highlight your theoretical position in the discussion of these hypotheses.
11. You didn't specify clearly (or I missed it with a lot of information) the periodicity and length (start and end dates), and if you used the raw data, their original units, and if you used logs, log differences, etc. please, complete that description.
12. You didn't mention if you made a unit root test. It is important because you are dealing with time series in an OLS multivariate regression. You are using the EMBI first differences. Why first differences and not log-differences that are less prone to heteroskedasticity than the former? please explain or make either the unit root tests, along with a strong explanation. In my personal experience (with due respect) It is more comfortable to work with log first differences. The scale is more homogeneous, the effect of unit roots disappears and your factor betas are interpreted as "elasticities" a Delta% change in X leads to a Delta% change in Y. This is even consistent with other factor models either in Classical Financial Economics (Sharpe, Fama, and Co.) or Behavioral Financial Economics that is the research area that your work belongs with the Twitter sentiment measure.
13. In your literature review, please include some recent behavioral Financial Economics papers. If you depart from the "rational" equilibrium models in which market sentiment is not considered, you must discuss in your literature, previous works in this area, how do these motivate the inclusion of Twitter sentiment, and how do you expand the literature with your work.
14. There is a potential drawback and potential risk in your tests: you didn't use robust standard error such as the ones of Newey-West. Also, you didn't explain if there is a risk of multicollinearity in your regressors. Please make the proper multicollinearity tests (if applicable) and robust standard error estimation. If your conclusions do not change, please explain in the answer letter with the two regression tables: your current ones and the robust estimation ones to see that really the p-values didn't change significantly and that your conclusions hold.
15. Please make a brief corollary in your results section. This means that your results section must be organized as follows:
    1. 3.1 input data processing
    2. 3.3 Results discussion
    3. 3.4 Corollary of results and comparison among countries.
16. In the conclusions section, please mention how are your results useful in Academia and for practitioners (also in the abstract that shouldn't be more than 180 words).
17. In the same section, please mention the guidelines for further research. That is, how can someone improve your tests, or what are the next research tests to be made with your results. What improvements can be done to your research?
18. Appendix A and B are not necessary. Those are for mathematical proofs or algorithms that your paper does not have. Those appendices must be in the data processing section. Also, section 4 of materials and methods is not necessary. Please check that with the Editor.
19. These are some suggested works that could be included in your references:

• http://review-rper.com/index.php/rper/article/view/69/215
• https://www.emerald.com/insight/content/doi/10.1108/978-1-80071-070-220211009/full/html 
• https://www.sciencedirect.com/science/article/pii/S0148296321008559 
• https://link.springer.com/article/10.1007/s13278-020-00709-9 

Please, mark in blue your changes in the new paper's version.

Author Response

Reviewer 3

 

1. The author Didn't explain with are the three countries of interest selected. please, give a strong foundation to your selection.

 

The time frame selected for analysis (2000-2019) is a period immediately after Ecuador adopted the US Dollar as its official currency, resulting in an experimental setting conducive for research of these three geographically neighboring, but more importantly from a research question perspective, all three are commodity dependent countries with differing exchange rate policies ranging from substantially non-existent (as a result of Ecuador’s dollarization of its economy) to inflation targeting monetary policy and exchange rate management in Colombia and Peru. 

 

1. The statements of lines 34 to 41 about the pricing of risk-premiums i.e. EMBI indexes, need references. Otherwise is the author's mere opinion without support. please give your references (Academic research papers or history research books).

 

Morgan, J.P., 1999. Introducing the JP Morgan Emerging Markets Bond Index Global (EMBI Global). Methodology Brief (August).  Please review the expanded section which delves into the details. 

 

 

1. The introduction section is too short. I should see the author's hypothetical position or hypothesis to be tested and why is the author doing what it is doing in the paper. Please, expand.

 

I have expanded the introduction and reorganized the section to include the hypotheses expectations.

 

 

1. The Sovereign debt markets are not as old as the 17th Century. The author must expand his historical perspective with other Financial markets references besides Ferguson. The Sovereign debt market dates back to the 14th Century with Florence. Amsterdam is the place of the first stock market. Please correct and expand your references.

 

I believe I was misunderstood because of my convoluted writing (apologies).  I believe I have written it more clearly after your comment.  I must add that I am in effect referring to the fact that the debt market predates the stock market.  I have corrected and expanded my references.

 

 

1. The previous literature review looks strong but it needs enhancements. There is a vague link between your work and the motivations it receives from the cited references. Also in that literature review, I can't see how your model variables are related (motivated) with these previous references and how does the author expands the literature with his work. Please, expand your references and relate them to your work.

 

I have included research and literature pertinent to market sentiment notions. 

 

 

1. The link Twiter sentiment-Fixed income markets, Twitter sentiment-EMBI spreads are too weak (one reference). There is more work published in Fixed income markets or other security markets about the impact of social media sentiment. Please, expand your references and relate these works with yours as motivations for your tests.

 

I have included research and literature pertinent to market sentiment notions. 

 

 

 

1. Section 3 "The data" looks more like a bullets list or a sort of list. you give general detail but you didn't say how did you process the input data. Please write this section as a description of your test for Scientific replication purposes.

 

I have expanded the explanation of my variable selection and used existing research to motivate the selection of my fourteen variables, specifically the selection of variables derives from the 3 categories of research as described by Mari del Cristo and Gómez-Puig (2017).

 

1. Also related to the previous suggestion, because you didn't detail your motivations in the literature review, there is no link or foundation of your list of variables. With due respect, your work is good but this list of variables looks more like an "I think that these variables look good in my test..." I no it is not the case of your paper, but you must be careful of how do you write it in journals of high projection and potential as JFRM. Please attend this.

 

I have expanded the explanation of my variable selection and used existing research to motivate the selection of my fourteen variables, specifically the selection of variables derives from the 3 categories of research as described by Mari del Cristo and Gómez-Puig (2017).

 

 

1. In section 3.4 I finally read the hypothesis. Please, keep in mind that, when someone reads your abstract, she or he reads the conclusions next and, if there's more interest in your paper, she or he reads the introduction section. Your introduction section sells poorly your work and it doesn't say "what are you doing, how are you doing it, what will our tests be and what do you expect from these". The abstract should say "what did you do, how did you do it, what are your main findings and contributions" and your conclusions should say the same of the abstract, enhanced with the guidelines for further research. These guidelines, given the limitations or opportunity areas that you find in your work. The literature review gives strength to your tests and variables selection. Please, enhance those sections as suggested.

 

I have rewritten the abstract and reorganized the hypothesis to be placed in the introduction.  I also have strengthened my introduction section and concluded it with an overview of the organization of the paper. 

 

 

1. Your hypothesis could look better if they are of the type "There is a positive (or negative) relation between X and Y with Z" (general hypothesis) and some particular ones for each variable (X and Y). You also must highlight your theoretical position in the discussion of these hypotheses.

 

I have placed the hypothesis in a different section and believe this to be a better flow of the paper.

 

1. You didn't specify clearly (or I missed it with a lot of information) the periodicity and length (start and end dates), and if you used the raw data, their original units, and if you used logs, log differences, etc. please, complete that description.

 

I have clarified the period selected in the introduction and in the data and methodology.

 

1. You didn't mention if you made a unit root test. It is important because you are dealing with time series in an OLS multivariate regression. You are using the EMBI first differences. Why first differences and not log-differences that are less prone to heteroskedasticity than the former? please explain or make either the unit root tests, along with a strong explanation. In my personal experience (with due respect) It is more comfortable to work with log first differences. The scale is more homogeneous, the effect of unit roots disappears and your factor betas are interpreted as "elasticities" a Delta% change in X leads to a Delta% change in Y. This is even consistent with other factor models either in Classical Financial Economics (Sharpe, Fama, and Co.) or Behavioral Financial Economics that is the research area that your work belongs with the Twitter sentiment measure.

 

You make a great point about the logs (no offense taken).  I did do log differences but precisely for concerns of spurious correlation, I had also performed the following for the dependent: (1) a mean (expected value) of EMBI spread for the quarterly period, and (2) a standard deviation of the EMBI spread for the quarterly period.  The spread of daily observations averaged (expected value of the quarter) over the quarterly period were stationary for the dependent of Ecuador Peru and Colombia. In any event, I have performed logs and log differences and ran an ADF test to check for non-stationarity and have kept the Average EMBI Spread over the quarter as it is a stationary variable.

 

Below is the output from ADF for all relevant Ys.

 

ADF Test-Colombia Qrtr. AVG. EMBIG (basis points)
criteria	aic
drift	yes
trend	yes
lag	2
alpha	0.05
tau-stat	-3.767121037
tau-crit	-3.485755462
stationary	yes
aic	10.78909986
bic	10.93643202
lags	1
coeff	-0.350564093
p-value	0.025746664

 

 

 

ADF Test - Ecuador Qrtr. AVG. EMBIG (basis points)
criteria	aic
drift	yes
trend	yes
lag	2
alpha	0.05
tau-stat	-6.404796418
tau-crit	-3.465303031
stationary	yes
aic	14.691983
bic	14.81652706
lags	1
coeff	-0.432500423
p-value	< .01

 

ADF Test-Peru Qrtr. AVG. EMBIG (basis points)
criteria	aic
drift	yes
trend	yes
lag	2
alpha	0.05
	-4.165290363
tau-crit	-3.498968825
stationary	yes
aic	10.30898414
bic	10.46799643
lags	1
coeff	-0.400702977
p-value	< .01

 

 

1. In your literature review, please include some recent behavioral Financial Economics papers. If you depart from the "rational" equilibrium models in which market sentiment is not considered, you must discuss in your literature, previous works in this area, how do these motivate the inclusion of Twitter sentiment, and how do you expand the literature with your work.

 

I have included research and literature pertinent to market sentiment notions. 

 

 

1. There is a potential drawback and potential risk in your tests: you didn't use robust standard error such as the ones of Newey-West. Also, you didn't explain if there is a risk of multicollinearity in your regressors. Please make the proper multicollinearity tests (if applicable) and robust standard error estimation. If your conclusions do not change, please explain in the answer letter with the two regression tables: your current ones and the robust estimation ones to see that really the p-values didn't change significantly and that your conclusions hold.

 

Thank you for your valuable suggestion.  This changed my conclusions about the significant variables and I have redacted the section in the manuscript accordingly.

 

I used VIF (Variance Inflation Factor) to discard independent variables which exhibited unacceptable multicollinearity levels (VIF>5).  Below are the VIF tables for the Complete Regression (the first regressions ran using all independent variables possible) and below the regressions finally selected based on acceptable VIFs.

 

Colombia: Multicolinearity statistics (before removal of VIF>5):

 

	Endogenous Risk	Colombia STARTING A BUSINESS	Colombia CORRUPTION	Colombia FDI/GDP	Colombia Debt Svce./GDP	Colombia Reserves/GDP	Colombia FX DepR_AppR	STD. DEV of F/X	Colombia ALL Tweets	Colombia FIN Tweets	Colombia Bid Ask Spread (Liquidity)	Colombia AVERAGE PERIOD RATING
Tolerance	0.053	0.028	0.043	0.228	0.088	0.030	0.328	0.279	0.426	0.334	0.065	0.351
VIF	18.813	35.544	23.191	4.394	11.372	32.991	3.052	3.589	2.345	2.998	15.393	2.847

 

Colombia: Surviving Variables:

 

	Colombia FX DepR_AppR	STD. DEV of F/X	Colombia Bid Ask Spread (Liquidity)		Colombia AVERAGE PERIOD RATING
Tolerance	0.690	0.538		0.762		0.583
VIF	1.449	1.858		1.313		1.717

 

Source	t	Pr > |t|
Colombia FX DepR_AppR	4.647	<0.0001
STD. DEV of F/X	7.083	<0.0001
Colombia Bid Ask Spread (Liquidity)	1.721	0.098
Colombia AVERAGE PERIOD RATING	0.953	0.350

 

Ecuador: Multicolinearity statistics (before removal of VIF>5):

 

	Ecuador Endogenous Risk	Ecuador STARTING A BUSINESS	Ecuador CORRUPTION	Ecuador FDI/GDP	Ecuador Debt Svce./GDP	Ecuador Reserves/GDP	Ecuador ALL Tweets	Ecuador FIN Tweets	Ecuador AVERAGE PERIOD RATING
Tolerance	0.461	0.102	0.120	0.410	0.324	0.310	0.742	0.454	0.323
VIF	2.169	9.831	8.335	2.437	3.085	3.223	1.348	2.204	3.096

	Ecuador Endogenous Risk	Ecuador FDI/GDP	Ecuador Debt Svce./GDP	Ecuador Reserves/GDP	Ecuador ALL Tweets	Ecuador FIN Tweets	Ecuador AVERAGE PERIOD RATING
Tolerance	0.622	0.596	0.410	0.337	0.834	0.649	0.586
VIF	1.609	1.677	2.442	2.968	1.199	1.541	1.706

Ecuador: Surviving Variables:

 

 

 

Source	t	Pr > |t|
Ecuador Endogenous Risk	-3.294	0.002
Ecuador FDI/GDP	0.054	0.957
Ecuador Debt Svce./GDP	2.979	0.005
Ecuador Reserves/GDP	1.569	0.126
Ecuador ALL Tweets	-1.661	0.106
Ecuador FIN Tweets	-1.894	0.067
Ecuador AVERAGE PERIOD RATING	-1.324	0.195

 

 

Peru: Multicolinearity statistics (before removal of VIF>5):

 

	Peru Endogenous Risk	Peru STARTING A BUSINESS	Peru CORRUPTION	Peru FDI/GDP	Peru Debt Svce./GDP	Peru Reserves/GDP	Peru FX DepR_AppR	STD. DEV of F/X	Peru ALL Tweets	Peru FIN Tweets	Peru Bid Ask Spread (Liquidity)	Peru AVERAGE PERIOD RATING	Peru AVG. Invest. Grd. (1) Or Not (0)-0	Peru AVG. Invest. Grd. (1) Or Not (0)-1
Tolerance	0.600	0.057	0.035	0.214	0.318	0.149	0.501	0.576	0.253	0.556	0.209	0.067	0.671	0.671
VIF	1.666	17.495	28.860	4.667	3.144	6.701	1.996	1.736	3.958	1.798	4.794	14.940	1.490	1.490

 

Peru: Surviving Variables

	Peru Endogenous Risk	Peru Debt Svce./GDP	Peru Reserves/GDP	Peru FX DepR_AppR	STD. DEV of F/X	Peru ALL Tweets	Peru FIN Tweets	Peru AVG. Invest. Grd. (1) Or Not (0)
Tolerance	0.666	0.823	0.561	0.691	0.802	0.472	0.658	0.874
VIF	1.502	1.215	1.784	1.446	1.247	2.119	1.520	1.144

 

Source	t	Pr > |t|
Peru Endogenous Risk	-0.541	0.593
Peru Debt Svce./GDP	-1.521	0.141
Peru Reserves/GDP	1.431	0.165
Peru FX DepR_AppR	-1.111	0.277
STD. DEV of F/X	3.070	0.005
Peru ALL Tweets	-0.308	0.761
Peru FIN Tweets	-1.599	0.123
Peru AVG. Invest. Grd. (1) Or Not (0)	-0.502	0.620

 

 

 

1. Please make a brief corollary in your results section. This means that your results section must be organized as follows:
1. 3.1 input data processing
2. 3.3 Results discussion
3. 3.4 Corollary of results and comparison among countries.

 

I have expanded the results to include the suggested organization.

 

1. In the conclusions section, please mention how are your results useful in Academia and for practitioners (also in the abstract that shouldn't be more than 180 words).

 

I have added the suggested redaction.

 

1. In the same section, please mention the guidelines for further research. That is, how can someone improve your tests, or what are the next research tests to be made with your results. What improvements can be done to your research?

 

I have added the suggested redaction in the Conclusions section.

 

 

1. Appendix A and B are not necessary. Those are for mathematical proofs or algorithms that your paper does not have. Those appendices must be in the data processing section. Also, section 4 of materials and methods is not necessary. Please check that with the Editor.

 

I have redacted and included this information in the data processing section.       

 

 

1. These are some suggested works that could be included in your references:

 

Thank you for your suggested review of literature, I have used two of them and added others which came form the references of the works you recommend. 

• http://review-rper.com/index.php/rper/article/view/69/215
• https://www.emerald.com/insight/content/doi/10.1108/978-1-80071-070-220211009/full/html 
• https://www.sciencedirect.com/science/article/pii/S0148296321008559 
• https://link.springer.com/article/10.1007/s13278-020-00709-9 

Please, mark in blue your changes in the new paper's version.

I have marked additions and your comments in blue and the sections moved to data in green.

 

 

Author Response File: Author Response.docx

Reviewer 4 Report

The literature review and theoretical derivation sections of this paper are very weak. This article could only be published if it were supplemented by a large number of up-to-date references and the logic of the first three sections were redesigned.

Author Response

Reviewer 4

 

The literature review and theoretical derivation sections of this paper are very weak. This article could only be published if it were supplemented by a large number of up-to-date references and the logic of the first three sections were redesigned.

 

I have thoroughly expanded and redacted the article with the help of colleagues and reviewers suggestions and changes.  Please look over my revised article.  Thank you.

 

 

my revised article.  Thank you.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

In revision, yes you provided VIF for Columbia. However, you should provide VIF for Ecuador and Peru as well.

Author Response

Date of this review

21 Mar 2022 02:13:39

 

Comments and Suggestions for Authors

In revision, yes you provided VIF for Columbia. However, you should provide VIF for Ecuador and Peru as well.

I have redacted accordingly and included Tables with VIF and Tolerance for the countries of Ecuador and Peru as well. 

Reviewer 3 Report

The paper has increased its quality significantly. Still, there should be a mistake or an issue in the paper's new version in the editing system (susy). I don't see the blue text and green that you mention in your letter. It makes me a little bit difficult to check the changes made. 

Also, the citing format is not the journal's one. Please, refer to the author guidelines section and change the citing format. Mendeley or Endnote could be of great help for this purpose if you are not using them.

Please, send that paper's new version that you mention in your letter and attend the last recommendation of suggested works in full.

Author Response

Comments and Suggestions for Authors

The paper has increased its quality significantly. Still, there should be a mistake or an issue in the paper's new version in the editing system (susy). I don't see the blue text and green that you mention in your letter. It makes me a little bit difficult to check the changes made. 

I will include the previous revision version with Tracked changes in the additional documents section. Please let me know if you are able to see it.

Also, the citing format is not the journal's one. Please, refer to the author guidelines section and change the citing format. Mendeley or Endnote could be of great help for this purpose if you are not using them.

I consulted with editor and they suggested that format (it was also strange to me) with Chicago 17^th with those parentheses at the beginning of the reference.

Please, send that paper's new version that you mention in your letter and attend the last recommendation of suggested works in full.

I have addressed it in full (please read below).  Please let me know if this is sufficient.

 

Submission Date

11 February 2022

Date of this review

18 Mar 2022 00:45:15

Reviewer 3 suggested: 

These are some suggested works that could be included in your references:

 

Thank you for your suggested review of literature, I have used two of them and added others which came form the references of the works you recommend. 

 

• http://review-rper.com/index.php/rper/article/view/69/215

 

I was able to read: Oscar, V, Dora Aguilasocho-Montoya, Leticia Bollain-Parra, and Amador Durán-Sánchez. 2022. "The impact of COVID-19 news and investor sentiment in European stock pricing, a regional, country, and economic sector review." RPER (60): 165-177, however found works related to bond (fixed income/debt instruments to be more relevant to my article)

 

• https://www.emerald.com/insight/content/doi/10.1108/978-1-80071-070-220211009/full/html 

 

I have read the abstract and article and decided to use a reference from work referred by your review below.

 

• https://www.sciencedirect.com/science/article/pii/S0148296321008559 

 

From this article I read I preferred to use the following article from the references of this work: Gan, Baoqing, Vitali Alexeev, Ron Bird, and Danny Yeung. 2020. "Sensitivity to sentiment: News vs social media." International Review of Financial Analysis 67: 101390. https://doi.org/10.1016/j.irfa.2019.101390. https://dx.doi.org/10.1016/j.irfa.2019.101390.

 

 

• https://link.springer.com/article/10.1007/s13278-020-00709-9 

 

Very interesting article about the term financial risk and the associations for data mining, but was satisfied with other selected works and included in the references.  Did not use this in the course of my description /redaction so was not able to cited.

Reviewer 4 Report

I have no further comments.

Author Response

Thank you for your review and improvements. All comments have been addressed.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.