Peer Review History

Original SubmissionMarch 31, 2021
Decision Letter - Junhuan Zhang, Editor

PONE-D-21-10570

Bayesian neural networks for stock market forecasting  before and during COVID-19 pandemic

PLOS ONE

Dear Dr. Chandra,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jun 14 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Junhuan Zhang, PhD

Academic Editor

PLOS ONE

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2. Please ensure that you refer to Figure 5-8 and 10-13 in your text as, if accepted, production will need this reference to link the reader to the figure.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The abstract should be reformulated. This is a very important part of the article. The authors spend too much writing on background. Instead, the authors should better present their research, the main contributions and results, and the conclusions that might be drawn from these results.

In my opinion, the introduction is not well focused. Background should be brief. The originality (novelty) and relevancy of the study should be established with better efforts. My understanding is that this study is an empirical one. Thus, it is expected that the introduction should also include hypothesis and objectives of the study, followed by a justification of the methodology. The current manuscript needs much improvements on all these aspects.

In the introduction, authors claim to study stock market prediction using Bayesian neural networks. However, from the data description, I see the study actually only considers 4 stocks, each from a different country though. Predicting the stock price of a particular company is a very different task from stock market prediction. I believe the authors need more careful wording, and should articulate their research question in the introduction.

More on the data, I don't see any explanation as to why these companies are selected for experiments. Are there any criteria? Also, how to decide the date after which the stock price is affected by COVID-19. Moreover, the authors choose different dates for different stocks/countries. Reasons and justifications are expected here.

The abbreviation FNN-Adam and FNN-SGD are used without mentioning full names. Please check if the use of other abbreviations is of the same problem.

I think one of the main tasks of this study is to compare Bayesian neural network with other neural network methods in terms of forecasting performance. Is it sound to consider only one performance measure (RMSE) here?

From my perspective, the conclusion is quite weak. A more detailed conclusion is needed. The novel method applied here does not seem to outperform state-of-art machine learning methods, at least I can't see it from the conclusion part. The better performance prior COVID-19 is no surprise indeed, and thus does not add any weight to the conclusion part. I expect to see more intelligent conclusions such as the real advantages of this novel Bayesian neural network method. Probably, a comparison with other state-of-art studies would be helpful. This can also be added to the discussion part.

English writing must be carefully revised. Usually, use of WE/OUR in the academic writing should be avoided. I have encountered many grammar mistakes and typos while reading. I list them as below but there are probably more in the manuscript. Thought I am not a native speaker, I feel like the manuscript would benefit from a proof read by a native speaker.

Mistakes I have spotted:

Line 16, “Markov Chain Monte Carlo (MCMC) methods provides a means…”

Line 17, “As the size of model and data continues increases…”

Line 205-206, “The probabilistic neural network model employs the posterior distribution to provides uncertainty quantification on the predictions.”

Line 293, “…we set the burn-in rate is 0.5”

Line 376, “We good prediction accuracy is needed not just for the day ahead, …”

Line 430, “COVID-19 which is not surprising given internal market-crush”

Line 431, “…its is more challenging to provide forecasting during COVID-19…”

Reviewer #2: This paper applies a Bayesian neural networks for multi-step-ahead stock market forecasting before and during COVID-19. But in this version,I don't think the author has made it clear where their novelty ies, is it the novelty of method, or is it the novelty of predicting the stock price changes before and after covid-19? In the paper, the author mentioned that “In the literature, there has not much been done using Bayesian neural networks for stock markets that features robust uncertainty quantification. We can use them to harness power of neural networks that provides good prediction accuracy and also quantify uncertainty. Moreover, there has not been much work that shows how robust machine learning models such as neural networks perform post COVID-19 given major changes in the international stock market with disruptions in international trade and prediction.”,but actually in the listed or not listed references, there are some papers for forecasting in COVID-19. The authors should state exactly the difference of this paper from others, not in a general way. Besides, I list other questions for revision reference.

1. Why Bayes neural network is suitable(even superior)for stock price forecasting. The highlights of this paper should be further addressed.

2. The authors choose 4 stock prices from 4 countries. But I think the selected stocks are not the most representative market stock. Why these datasets are selected should be further clarified.

3. Two other methods are compared with the Bayes neural network, that is, FNN-Adam and FNN-SGD, whose full names should be given when they first appear.

4. The abstract is poorly written. The authors do not clearly show the highlights and significance of this work.

5. The parameter settings in the experiment is very important. I think the authors should give an illustration of parameters in different forecasting models.

6. “”In Setup-2, we include parts of the data during COVID-19 in the training set with all the training data from Setup-1.” What does ”parts” mean here? I suggest the authors to give an exact time period and data length to show them. Besides, what is the objective of Setup 2.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Revision 1

The authors thank reviewers for valuable comments. Pls find the response to review comments attached with the manuscript.

Attachments
Attachment
Submitted filename: ReviewPLOSoneBayes_stockmarket.pdf
Decision Letter - Junhuan Zhang, Editor

PONE-D-21-10570R1

Bayesian neural networks for stock market forecasting  before and during COVID-19 pandemic

PLOS ONE

Dear Dr. Chandra,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jul 09 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Junhuan Zhang, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The revised manuscript has addressed all my comments. I only have one additional suggestion. In the study, the authors use the novel method to predict stock prices of 4 individual companies, rather than market indices. I think it is more appropriate to describe it as "stock price forecasting" than "stock market forecasting". Thus, I suggest to revise the title and relevant parts in the main text.

Reviewer #2: The authors have carefully revised paper accorrdingt to my comments and other reviewr's comment. I suggest an

acceptance.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Revision 2

We attached it with the manuscript.

Attachments
Attachment
Submitted filename: finalreview.pdf
Decision Letter - Junhuan Zhang, Editor

Bayesian neural networks for stock price forecasting  before and during COVID-19 pandemic

PONE-D-21-10570R2

Dear Dr. Chandra,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Junhuan Zhang, PhD

Academic Editor

PLOS ONE

Formally Accepted
Acceptance Letter - Junhuan Zhang, Editor

PONE-D-21-10570R2

Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic

Dear Dr. Chandra:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

Dr. Junhuan Zhang

Academic Editor

PLOS ONE

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