Price Index Modeling and Risk Prediction of Sharia Stocks in Indonesia
Round 1
Reviewer 1 Report
In this paper, Geometric Brownian Motion (GBM) and Value at Risk (with Monte Carlo Simulation approach) are applied to the daily closing price of the Jakarta Islamic Index (JKII) for the period 01/04/20 – 13/08/21 to predict the price and loss risk of JKII for the period 16/08/21 – 23/08/21. The empirical findings are very accurate in predicting the JKII price according to Mean Absolute Percentage Error, a measure of prediction accuracy.
The paper is not acceptable for publication in its present form. The points for improvement are given below:
Major
- In the introduction section, the research purpose and its importance are not clearly stated
- The data used in estimations (Table 3) are not tested for the presence of unit root and structural break
- Equation 4 might be written with a mistake. Please recheck it once
- The Conclusion section is very short and incomplete. The important findings of the paper, the difference between these findings and other studies, the possible implications, research advantages and limitations, the future research tasks should be incorporated in the Conclusion section.
- The language of the paper should be proofread
Minor
- For abbreviations (GBM, VaR, ARIMA-GARCH, AIC, etc.), the first time while mentioned, the full description should be given; after that, the abbreviations should be used
- Some pieces of literature are not given in the references. For example, Si (2020)
- The citation of the literature used in the paper should be adjusted according to the journal’s rule
- Some words are given repeatedly in line 116
- The quality of the tables should be improved
Author Response
In the introduction, the research objectives and interests are not clearly stated (fixed)
The results of price predictions and predictions of risk of loss are expected to be an accurate reference and consideration for investors who will use their funds to invest in Islamic stocks traded on IDX.
The data used in the estimation (Table 3) were not tested for the presence of unit roots and structural breaks (fixed)
besides doing normality test, we need to perform a unit root test on the In-sample return of JKII data. This test aims to see whether the data is stationar. If the data is not stationary, it means that the mean and variance are not constant. So the data is not suitable to be modeled using GBM which requires that the data must be normally distributed with constant mean and variance.
on the results of the ADF test, the t-statistics value obtained is -18,985 with p-value equal to 0.000. Because of the p-value is less than α, then H0 is rejected. so we can conclude that the data return is stationary
Equation 4 may be written with an error. Please check back once (Revised)
The Conclusion section is very short and incomplete. Important findings of the paper, differences between these findings and other studies, possible implications, advantages and limitations of the study, future research assignments should be included in the Conclusions section.
In addition, the results show that when the JKII returns are normally distributed, the GBM model can predict the JKII price index very accurately. This is because theoretically the GBM model will indeed provide maximum prediction results for an asset price when the return data is normally distributed. Then, the results of the VaR risk prediction through the Monte Carlo Simulation approach at a confidence level of 90% - 99% are in the range of 2%-9% of the total funds invested. The main difference between the results of this study and other studies that discuss the prediction of the JKII price index is that the prediction results of the price index are directly interpreted as the final result of the study. While in this study, the prediction results of the price index are used as a reference to measure the value of risk of loss, which as we all know that risk of loss is also an important indicator in a financial instrument.
The possible implication is that if the return in sample data that we have are not normally distributed but are still used for price predictions using the GBM model, the prediction results will be inaccurate and cannot be justified. This implication indirectly also becomes a limitation in this study, namely that the GBM and VaR Monte Carlo models are highly dependent on the assumption of normality returns, so if the return data is not normally distributed, the method cannot be used. Further research that can be developed is to model the JKII price index data if the historical return data is not normally distributed, one of the models that can be used is the GBM with Jump Model.
In addition, the results of the study show that when the return of the JKII price index is normally distributed, the GBM model can predict the JKII price index very accurately. This is because theoretically the GBM model will provide maximum prediction results for an asset price when the return data is normally distributed. Then, the results of the VaR risk prediction through the Monte Carlo Simulation approach at a confidence level of 90% - 99% are in the range of 2%-9% of the total funds invested. The main difference between the results of this study and other studies that discuss the prediction of the JKII price index is that the prediction results of the price index are directly interpreted as the final result of the study. While in this study, the prediction results of the price index are used as a reference to measure the value of risk of loss, which as we all know that risk of loss is also an important indicator in a financial instrument.
The possible implication is that if the return in sample data that we have are not normally distributed but are still used for price predictions using the GBM model, the prediction results will be inaccurate and cannot be justified. This implication indirectly also becomes a limitation in this study, namely that the GBM and VaR Monte Carlo models are highly dependent on the assumption of normality returns, so if the return data is not normally distributed, the method cannot be used. Further research that can be developed is to model the JKII price index if the historical return data is not normally distributed, one of the models that can be used is the GBM with Jump Model.
Reviewer 2 Report
Authors study the predcition of JKII pricie using GBM and VaR.
They propose new approach to extend the previous works, and show accurate prediction of JKII pricie.
The topic is interesting, and the paper provides clearly experimental results.
After some revisions, I recommend this manuscript for a publication in Economies.
Comments
1. Authors should add the figure of the return value of JKII(X_t).
2. Authors should add the figure of the simulation results by GBM model.
Author Response
Dear Reviewer
Thanks for your attention and review our article.
The author must add the return number JKII(X_t).
Already implemented
The author must add an image of the simulation results with the GBM model.
Sometimes, prediction results will be easier to understand if they are presented in tabular form. Therefore, here we present the prediction and return plots for JKII:
First of all, the research gap of the papers. Please improve this section in the introduction. The introduction is very general and does not align with the research findings, no discussion is given to get to the implications. The theoretical and pragmatic implications are unclear and need to be further harmonized with the theoretical foundations and processes proposed in this paper. In addition, there is not enough support and weak arguments to support the proposed objectives and the developed model. At the end of the introduction, the proposed purpose, originality and gaps that would be better covered. Also how the author will do the methodology.
Repair:
This analysis includes the prediction of the price index and the prediction of the loss risk for JKII. So far, there is no research that examines this problem. In fact, information about future price movements and the value of the loss risk is very important for investors and companies who are listed on JKII. For investors, this information can be used as a reference before deciding to invest. Then, for the company that's information will be a reference to improve the company's performance.
Thanks
Best Regard
Reviewer 3 Report
I am pleased to have the opportunity to review this research paper. This study attempted to explore Price Index Modelling and Risk Prediction of Sharia Stocks in Indonesia. Although the topic of this research study is interesting and fits within the journal scope, I think authors should apply the comments indicated below to increase the quality of research justification, contributions and findings. The manuscript know lacks in scientific style and structure.
First of all, paper research gap. Please improve this part in introduction section. Introduction is very general and lacked alignment to the research findings, no discussion was provided to derive the implication from. Theoretical and pragmatics implication are vague and need to be better aligned with this paper theoretical underpinnings and proposed process. Furthermore, there is insufficient support and weak arguments in support of the objective that is proposed as well as the model developed. In the final part of the introduction the objectives proposed, originality and gap that would be better covered. Also how the author will perform the methodology.
the topic of this research study is interesting and fits within the journal scope, I think authors should apply the comments indicated to increase the quality of research justification, contributions and findings
What is the originality of this research? Paper research gap and originality should be better presented at the end of introduction section
Please consider this structure for manuscript final part.
-Discussion
-Conclusion
-Managerial Implication
-Practical/Social Implications
-Discussion needs to be a coherent and cohesive set of arguments that take us beyond this study in particular, and help us see the relevance of what authors have proposed. Authors should create an independent “Discussion” section. Author need to contextualize the findings in the literature, and need to be explicit about the added value of your study towards that literature. Also other studies should be cited to increase the theoretical background of each of the method used. Findings should be contextualized in the literature and should be explicit about the added value of the study towards the literature. Limitations and future research
Questions to be answered:
What practical/professional and academic consequences will this study have for the future of scientific literature (theoretical contributions)?
Why is this study necessary? should make clear arguments to explain what is the originality and value of the proposed model. This should be stated in the final paragraphs of introduction and conclusion sections.
Author Response
Dear Reviewer,, thanks for your attention and review our article.
What is the originality of this research? The gaps in the paper's research and originality should be better presented at the end of the introduction section.
This analysis includes the prediction of the price index and the prediction of the loss risk for JKII. So far, there is no research that examines this problem. In fact, information about future price movements and the value of the loss risk is very important for investors and companies who are listed on JKII. For investors, this information can be used as a reference before deciding to invest. Then, for the company that's information will be a reference to improve the company's performance.
What practical/professional and academic consequences will this research have for the future of the scientific literature (theoretical contribution)?
Answers:
Combining the GBM Model and VaR Model with a Monte Carlo Simulation Approach for Price Index Prediction and Risk Loss Prediction
Why is this study necessary? must make clear arguments to explain what is the originality and value of the proposed model. This should be stated in the last paragraph of the introduction and conclusion section.
Answer:
information about future price movements and the value of the loss risk is very important for investors and companies who are listed on JKII. For investors, this information can be used as a reference before deciding to invest. Then, for the company that’s information will be a reference to improve the company's performance.
Thanks
Best Regard
Round 2
Reviewer 1 Report
The revised version is better and acceptable. The tables should be harmonized. The paper should be carefully proofread; it has some grammatical mistakes. For example, the third sentence of the abstract.
Author Response
Dear Reviewer
Thank you for the review given. Our articles become better after being revised according to the reviewer's suggestions. We have aligned the table according to the reviewer's suggestions and according to the journal template. We have tried to improve the grammar, especially in the third sentence of the abstract.
Thank you
Best Regard
Reviewer 3 Report
the work now has a better quality, it improved after the reviewers' comments. I think it can still improve even more if you pay attention to all the comments. Please review the introduction and conclusions.
Author Response
Dear Reviewer
Thank you for the review given. The quality of our articles is getting better after being revised according to the reviewers' suggestions. We have corrected the introduction and conclusion according to the suggestions of reviewers.
Thank you
Best Regard
Round 3
Reviewer 1 Report
The paper is acceptable.
