Assessing Investor Belief: An Analysis of Trading for Sustainable Growth of Stock Markets
Round 1
Reviewer 1 Report
It is not enough to announce an impressive specialized literature without being processed, the relevant ideas selected and the positioning personalized towards them. Many of the references are in the style of the academic language of the "publish or perish" period (e.g. As shown by [1] and [2], we accept that the distribution of expectations is normal. [3] and [4] argue that there is no consensus in the literature. specialized, but we accept the idea of ​​normal distribution because it is easier to model). There are some rather categorical statements such as "investors' beliefs are usually unobservable", not followed by the necessary clarifications. Although it is mentioned that a unique method of estimation is used, there are no solid arguments in favor of its originality and no other relevant methods with which the corresponding comparisons can be made. The delineation between informed traders, market makers, and noise traders should be made better. It should be more clearly explained how variables such as the quality of the firm's financial reporting, operation opacity and analyst's coverage can be quantified so that they do not introduce more volatility into the algorithms used. It is not quite clear whether there is an objective method to validate the opinions of players on the stock market. It is only opinions, which in turn influence what they believe and how other agents transact, and then the actions of the latter influence the actions of the former (a self-sustaining mechanism ... that is, opinions that give rise to other opinions).
Should the article also show whether there is an objective test and an end point for this process. Opinions can be informed or less informed (ideas that authors go for), but they can also be characterized as right or wrong. Moreover, the market tends to eliminate the individuals who make mistakes, through losses, and to give more weight to those who were right (the profit obtained means they have more resources to manage in the next trading round and therefore have a higher a harder word to say). It seems to me that if one only analyzes the reversal of the covariance (the way of quantifying the players' opinions), it is not said much and relevantly argumentative.
If we were to look beyond the mathematical model and try to verbalize in a sentence the idea behind this type of analysis, I think that the authors cannot say anything other than - Since the information is not interpreted as all participants in the market - especially if we also take into account the fact that some are more aware of the cause than others and that the information changes from day to day. I recommend that the authors also focus on explaining how players on the stock exchange permanently change the price at which they are willing to buy or sell securities. Authors should standardize their citation style. In some places it only mentions a number of orders in straight brackets (see rows 49 - 63), and in other parts it also adds the names of the authors (see rows 487 - 504). Also, in turn 50 is a "typo" (traded should be replaced with trades).
Author Response
General Comment
It is not enough to announce an impressive specialized literature without being processed, the relevant ideas selected and the positioning personalized towards them. Many of the references are in the style of the academic language of the "publish or perish" period (e.g. As shown by [1] and [2], we accept that the distribution of expectations is normal. [3] and [4] argue that there is no consensus in the literature specialized, but we accept the idea of normal distribution because it is easier to model). There are some rather categorical statements such as "investors' beliefs are usually unobservable", not followed by the necessary clarifications. Although it is mentioned that a unique method of estimation is used, there are no solid arguments in favor of its originality and no other relevant methods with which the corresponding comparisons can be made. The delineation between informed traders, market makers, and noise traders should be made better. It should be more clearly explained how variables such as the quality of the firm's financial reporting, operation opacity and analyst's coverage can be quantified so that they do not introduce more volatility into the algorithms used. It is not quite clear whether there is an objective method to validate the opinions of players on the stock market. It is only opinions, which in turn influence what they believe and how other agents transact, and then the actions of the latter influence the actions of the former (a self-sustaining mechanism ... that is, opinions that give rise to other opinions).
Should the article also show whether there is an objective test and an end point for this process. Opinions can be informed or less informed (ideas that authors go for), but they can also be characterized as right or wrong. Moreover, the market tends to eliminate the individuals who make mistakes, through losses, and to give more weight to those who were right (the profit obtained means they have more resources to manage in the next trading round and therefore have a higher a harder word to say). It seems to me that if one only analyzes the reversal of the covariance (the way of quantifying the players' opinions), it is not said much and relevantly argumentative.
If we were to look beyond the mathematical model and try to verbalize in a sentence the idea behind this type of analysis, I think that the authors cannot say anything other than - Since the information is not interpreted as all participants in the market - especially if we also take into account the fact that some are more aware of the cause than others and that the information changes from day to day. I recommend that the authors also focus on explaining how players on the stock exchange permanently change the price at which they are willing to buy or sell securities.
Response: We really appreciate the comments and we have revised the paper to cope with the comments.
Specific Comment
Authors should standardize their citation style. In some places it only mentions a number of orders in straight brackets (see rows 49 - 63), and in other parts it also adds the names of the authors (see rows 487 - 504).
Response: For the rows 487-504, the reason we put the authors name is that we followed the authors’ regression and their measures. Therefore, it is essential to put their names there.
Specific Comment
Also, in turn 50 is a "typo" (traded should be replaced with trades).
Response: We have corrected this typo.
Reviewer 2 Report
The authors estimate the (unobservable) belief of investors based on their Bayesian learning model. The methodology they used seems concrete. Their finding is consistent with their model and contributes in many ways to a specific area of finance literature.
However, I wonder what implications can be provided by this study to sustainability research areas. The authors need to be very careful about the link to sustainability, from a definition to applications, based on literatures of that area.
Specific comments:
Line 84. What do the authors think the main purpose is of the development? Give some examples of the “other purposes.”
Neither the Bayesian learning, nor market microstructure model are good for making inferences 84 about traders’ beliefs, because these models have been developed for other purposes; however, these 85 models do describe different aspects of traders’ beliefs.
Line 63. What is the formal definition of “sustainable returns”? Is this an expression normally acceptable by finance researchers, or a new term that the authors define in this study? I cannot find any methodological explanation about the measurement of sustainable returns. How do the authors measure the sustainability? The authors need to follow a reference or be based on a concrete definition.
Lines 98-102 seem to have some editorial errors.
Author Response
General Comment
The authors estimate the (unobservable) belief of investors based on their Bayesian learning model. The methodology they used seems concrete. Their finding is consistent with their model and contributes in many ways to a specific area of finance literature.
However, I wonder what implications can be provided by this study to sustainability research areas. The authors need to be very careful about the link to sustainability, from a definition to applications, based on literatures of that area.
Response:
We add a new paragraph as the first paragraph and address the contribution of this study to sustainability.
Specific Comments:
Line 84. What do the authors think the main purpose is of the development? Give some examples of the “other purposes.”
Neither the Bayesian learning, nor market microstructure model are good for making inferences about traders’ beliefs, because these models have been developed for other purposes; however, these models do describe different aspects of traders’ beliefs.
Response: This paragraph is not well connected with the context. We intended to elaborate on the pros. and cons. of the Bayesian learning and market microstructure models. Detailed comparisons of these two schools of models are beyond the scope of this paper. In order to avoid confusion, we have deleted this sentence.
Specific comment
Line 63. What is the formal definition of “sustainable returns”? Is this an expression normally acceptable by finance researchers, or a new term that the authors define in this study? I cannot find any methodological explanation about the measurement of sustainable returns. How do the authors measure the sustainability? The authors need to follow a reference or be based on a concrete definition.
Response: The sustainable returns here refers to the sustainable growth of financial markets and has been changed accordingly.
Specific Comment:
Lines 98-102 seem to have some editorial errors.
Response: This paragraph has been rewritten.
Round 2
Reviewer 1 Report
I appreciate that the authors have treated the recommendations made very carefully and, at this point, the paper is much improved.
Reviewer 2 Report
I think that this manuscript can be published in present form.
