Following the Crowd: Unveiling the Impact of Macroeconomic Shocks and Monetary Policy Shifts on Herding Dynamics in the Bangladesh Equity Market

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1.  In the introduction, Clearly state (1) what existing studies lack (e.g., joint role of macro shocks and monetary policy in herding in frontier markets), (2) why Bangladesh is a relevant case, and (3) what is novel in this study.

2. Reorganize the review into subsections: (a) General herding studies, (b) Herding and macro variables, (c) Herding and monetary policy, (d) Gap in Bangladesh context. Add a table summarizing past studies (author, country, method, findings) to highlight novelty.

3. Justify methodological choices more explicitly (why quantile regression captures heterogeneity better).

4. Provide robustness checks to ensure robustness of the results.

5. Clarify how “crisis” and “extended crisis” were defined. why need such definition?

6. Provide stronger theoretical interpretation of asymmetric effects (e.g., behavioral finance mechanisms like loss aversion, panic selling).

7. Discuss external/global influences that may interact with Bangladesh’s market.

8. Expand on practical regulatory measures. Also include the direction for future studies for the research.

Author Response

Response to the Comments of the Esteemed Reviewer 1

Comment 1: In the introduction, Clearly state (1) what existing studies lack (e.g., joint role of macro shocks and monetary policy in herding in frontier markets), (2) why Bangladesh is a relevant case, and (3) what is novel in this study.

Response: Although herding in equity markets has been extensively studied in behavioral finance research, most of the studies are conducted on developed markets and emphasize on market microstructures or firm-specific aspects, including market volatility, up or down markets, returns, and trading volume. There is a paucity of research on the combined impact of macroeconomic shocks and monetary policy changes on herding behavior, especially in frontier markets, where market structures and investor psychology could vary considerably from those of developed equity markets. This study addresses a knowledge gap on how structural vulnerabilities and policy interventions interact to impact investors’ tendencies to follow the collective market behavior.

Being a frontier equity market, Bangladesh is an ideal case for examining herding behavior, where information asymmetry, a lack of institutional depth, and an increased sensitivity to policy and economic shocks can intensify the impact of behavioral biases. In filling this gap, this research examines the combined effect of macroeconomic shocks and monetary policy adjustments in determining herding behavior in the Bangladesh equity market. This market framework provides a rare chance to comprehend investor psychology in a setting where there is a high financial growth and policy developments are underway.

It is to mention that at the end of introduction part, we provide the novel contribution of the study, particularly within the framework of frontier equity markets.

Comment 2: Reorganize the review into subsections: (a) General herding studies, (b) Herding and macro variables, (c) Herding and monetary policy, (d) Gap in Bangladesh context. Add a table summarizing past studies (author, country, method, findings) to highlight novelty.

Response: The comment has been systematically incorporated in the Literature Review section of the Manuscript.

Comment 3: Justify methodological choices more explicitly (why quantile regression captures heterogeneity better).

Response: The herding is identified by quantile regression since the method enables an investigation of the complete conditional distribution of the market returns, as opposed to the mean [as is done by ordinary least squares (OLS) regression]. Herding behavior can be state dependent, so that it will not be the same when the market is under very extreme conditions (e.g., when large positive or negative returns happen) or between investors of different risk exposures. The research uses quantile regression to include heterogeneity in market conditions and returns distribution and a more accurate image of herding between the bottom, median, and upper quantile of returns. This is especially effective in frontier markets such as Bangladesh, where market microstructure aspects, investor behavior as well as liquidity vary under different conditions in the market.

Once it has been verified that herding does exist via quantile regression, the Cross-Sectional Absolute Deviation (CSAD) model is used to investigate how macroeconomic shocks and monetary policy changes will affect herding behavior. The CSAD framework can be used to measure the individual stock return dispersion in comparison to the market return and this dispersion is lower in the case of herding. The inclusion of macroeconomic and policy variables in the CSAD model helps the study to establish the extent to which external economic shocks or policy interventions induce investor herding behavior. Such a mix of quantile regression to identify herding and the CSAD to capture external macroeconomic and monetary forces offers a holistic, state-dependent, and policy-relevant perspective of herding dynamics in the environment of a frontier equity market. This two-stage methodological framework confirms the robust presence of herding in first before examining its relationship to real macroeconomic and policy shocks, which minimizes the misinterpretation risk.

Comment 4: Provide robustness checks to ensure robustness of the results.

Response: The study systematically classifies the Bangladesh equity market into several market-states like bullish, bearish, crisis, extended crisis, and COVID-19. In order to test robustness, the herding results are checked through the application of alternative thresholds to classify the market states, so it is guaranteed that the results are not sensitive to the selected classification scheme.

The 25th, 50th and 75th quantile regressions are also estimated with market returns. Robustness is validated by the comparison of the results obtained with these quantiles, ensuring that the behavior of herding is always reflected in the entire returns distribution.

The quantile regression model (to identify herding) and the CSAD model (to estimate the effect of the macroeconomic and monetary policy variables) were estimated to include the AR(1) term to explain serial correlation in the returns of the market. The adjustment was made to avoid biasing the estimated coefficients with autocorrelation, which is a common aspect in a financial time-series data.

Although the study used the CSAD model of Chang et al. (2000) to connect macroeconomic and monetary policy issues to herding effects, alternative return dispersion measure of CSSD is also tested to provide the robustness of the desired result. This validates the fact that the relationships observed are not isolated to a given herding measure. As we observe the similar results under both CSSD and CSAD, the study only reports the CSAD findings.

Comment 5: Clarify how “crisis” and “extended crisis” were defined. why need such definition?

Response: The two classifications of crisis and extended crisis markets were made in order to reflect the unique market conditions of the 2010-2011 market collapse of the Bangladesh equity market that was one of the worst and longest market falls in the history of the capital market in the country. The period of crisis (July 2010 June 2011) is specifically at the stage of the market determined by exorbitant price drops, the increased volatility, and panic trading activities. The extended crisis period (January 2010- December 2011) was set to capture the likely spillover and adjustment effects prior to and after this sharp contraction and thus included 6 months’ time before and after the central period of crisis.

This broad definition enables the study of investor behavior in the run up and in the recovery of the crisis whereby herding behavior and market sentiment can be noted to develop prior to the observable crash and continue into the period the market is recovering. The study will distinguish between the short-term crisis and the extended crisis phase to offer a more detailed view on how the psychology of the investors will vary in the entire range of market distress: from the anticipation to response and the gradual stabilization.

Comment 6: Provide stronger theoretical interpretation of asymmetric effects (e.g., behavioral finance mechanisms like loss aversion, panic selling).

Response: The theoretical interpretation of the asymmetric nature of herding behavior that is witnessed in this research can be attributed to the following behavioral finance mechanisms that govern the decision of investors in different market conditions.

The prospect theory of information by Kahneman and Tversky (1979) suggests that an investor becomes more sensitive to losses than to the same magnitude gains. Whenever the market is declining, the threat of losses causes a panic reaction of intense emotional reaction, which causes investors to act based on the crowd as a psychological defense mechanism to respond to uncertainty. This causes greater herding in the declining markets than the rising markets.

When minimal news and market speculations went viral, investors followed the decisions of others to sell not to incur a greater loss. This combined selling strengthens the co-movement of prices and increases the behavior of herding.

Bangladesh is a typical example of a frontier market that has information asymmetry, poor protection of investors, and low transparency in the market. Investors in this kind of environment are much dependent on market indicators observable as price changes or institutional trading especially at times of macroeconomic or monetary shock. The negative conditions make herding to be stronger when the information asymmetry is high, because uncertainty of fundamentals is heightened.

Asymmetric investor reactions can also be caused by expansionary monetary policy or liquidity injections. The more relaxed monetary policies can become a source of speculative optimism and short-term herding in times of recovery whereas contractionary policy or an increase in interest rates can worsen fear-based herding as investors seek to liquidate risky assets.

Comment 7: Discuss external/global influences that may interact with Bangladesh’s market.

Response: The Bangladesh equity market is not in isolation similar to other frontier markets. The external or global factors might have a strong impact on the domestic investor behavior and be a contributor to herding effects. The herding behavior of Bangladesh equity market is not purely domestic but it is also affected by external and international financial forces. The observation that the depreciation of Bangladeshi Taka has a crucial impact on the herding gives a clear indication of such external connections.

The movements of the exchange rates usually indicate the pressure of the global economy such as international capital flows, trade imbalances, and changes in world commodity prices. The depreciation of the Taka is normally an indicator of increasing import prices, inflation, and possible foreign reserve crunch-reasons that increase the uncertainty of investors. In this case, investors are likely to go with the general market trends instead of focusing on personal analysis, intensifying herding behavior.

In addition, external shocks tend to incite or exacerbate depreciation, including tightening of the U.S. monetary policy, global oil price spikes, or geopolitical tensions which disrupt trade and remittances. The events-containing analysis in these global events brings in contagion effect which causes investors in the frontier markets such as Bangladesh to imitate the responses of the foreign market or undertake defensive portfolio adjustments resulting into synchronous trading movements.

Since the effect of exchange rate depreciation on herding is observed, which proves the opinion that the world financial trends and external shocks indirectly affect the psychology of domestic investors in Bangladesh. This observation highlights the need to consider herding as a behavioral phenomenon within the domestic context, but also a component of a larger global contagion process that is spread via currency and financial channels.

Further, since the presence of foreign investors in the Dhaka Stock Exchange is limited, foreign institutional investors are able to influence the market dynamics due to portfolio rebalancing and risk-off behavior. Under the influence of global outflows, especially affecting emerging or frontier markets, local investors can take such a move as negative and copy the trading behavior, further increasing the effect of herding under the pressure of outflows in the world markets.

Comments 8: Expand on practical regulatory measures. Also include the direction for future studies for the research.

Response:

Practical Regulatory Measures: This research has several significant regulatory implications for policymakers and market authorities in Bangladesh. The presence of herding behavior, especially in a down market and during times of macroeconomic or monetary instability, highlights the necessity of proactive mechanisms to monitor the market and provide security to investors.

The Securities and Exchange Commission (BSEC) in Bangladesh and other regulators must enhance real time surveillance systems in the market to detect abnormal co movement of the trade as well as any possible panic sell-offs. Investor bias is minimized through improving investor education programs by influencing informed and independent decision-making.

Regulators might contemplate temporary circuit breakers, short-selling caps or specific liquidity support in periods of macroeconomic uncertainties or acute depreciation of the exchange rate to stabilize the situation and to replenish investor confidence. Furthermore, the central bank and the securities regulator can be more coordinated to ensure that the communication of the monetary policy is aligned with the targets of capital market stability, reducing behavioral spillovers of the policy changes.

Lastly, information asymmetry, which is one of the major causes of herding in frontier markets as seen in Bangladesh, can be reduced through facilitating improved institutional variance, better market transparency, and higher standards of information disclosure.

Future Research Direction: The results of this research can be extended in future research to investigate a number of extensions that can enhance the understanding of herding dynamics in various market settings. First, the researchers could study the issue of herding by including a broader range of macro-financial variables, including investor sentiment, credit spreads, and monetary transmission variables, to measure the greater behavioral-financial connections driving market coordination. Also, further research may utilize more complex econometric or machine learning methods to identify nonlinear herding behavior, especially when the financial markets are facing financial crisis or the change in regulatory inflexions. Cross-frontier, and emerging equity markets comparative analyses may also be interesting to understand the role that institutional frameworks and market efficiency plays in the intensity and persistence of herding. Lastly, integrating the behavioral survey data with market level indicators would provide a more complete picture of the psychological foundations behind collective investor behavior that would lead to a more sophisticated

Reviewer 2 Report

Comments and Suggestions for Authors

My comments on the paper – Following the Crowd: Unveiling the Impact of Macroeconomic  Shocks and Monetary Policy Shifts on Herding Dynamics in  the Bangladesh Equity Market - are as follows.

The paper presents an interesting analysis and we consider that the research is of interest.

The title of the paper is clear. The abstract is clear, presents the purpose of the paper and main results. The keywords are appropriately chosen. The introduction provides the necessary background information and states the objectives, and the added value of the paper.

The whole content of the paper has a logical flow

The research methodology used by the author is adequate for the approached subject.

The structure of the paper is appropriate.

The analysis undertaken by the author is clear and pertinent.

The conclusions are significant and result from the undertaken research.

In the introduction section, the structure of the paper on sections is not provided.

We recommend that the results obtained from the study should be compared with the results obtained in the case of similar researches from the academic literature.

The author does not mention the limits of the research. We consider that the authors can show the limitations of the analysis carried out in their paper.

We recommend that authors revise the manuscript to improve sentence structure. In the text, "This" appears too often, and it is suggested that it should be adjusted (see the  line 82, 86, 92, 97, 99... etc).

Author Response

Response to the Comments of the Esteemed Reviewer 2

Comment 1:The paper presents an interesting analysis and we consider that the research is of interest.

Comment 2: The title of the paper is clear. The abstract is clear, presents the purpose of the paper and main results. The keywords are appropriately chosen. The introduction provides the necessary background information and states the objectives, and the added value of the paper.

Comment 3: The whole content of the paper has a logical flow

Comment 4: The research methodology used by the author is adequate for the approached subject.

Comment 5: The structure of the paper is appropriate.

Comment 6: The analysis undertaken by the author is clear and pertinent.

Comment 7: The conclusions are significant and result from the undertaken research.

Response: Response the comments 1 through comment 7 are not requires as the esteemed reviewer provided his feedback with full satisfaction.

Comment 8: In the introduction section, the structure of the paper on sections is not provided.

Response: The structure of the paper has now been included at the end of the introduction section of the manuscript.

Comment 9: We recommend that the results obtained from the study should be compared with the results obtained in the case of similar researches from the academic literature.

Response: Our study results are widely in line with other equity market findings where herding is more pronounced during period of market stress and monetary policy shocks. Indicatively, Javaira and Hassan (2015) reported stronger herding in the Pakistan equity market during volatile times, whereas Amata et al. (2016) associated herding effects with the macroeconomic instability in Kenya. On the same note, Sibande (2024) observed that herding in the South African (ZAR) market intensified when the market experienced an extreme movement and was also affected by the dynamics of the monetary policy using both the CSAD and CSSD. Consistent with this comparison, our findings indicate herding behavior in Bangladesh is responsive to macroeconomic shocks and monetary policy changes especially in the states of crisis and extended crisis markets. Nevertheless, in contrast to these previous studies, our study provides a more detailed market classification, i.e., a bullish period, bearish period, crisis period, extended crisis period, and COVID-19 period that enables one to have a more detailed description of behavioral responses across various market states.

Comment 10: The author does not mention the limits of the research. We consider that the authors can show the limitations of the analysis carried out in their paper.

Response: This study highlights certain limitations that should be mentioned. Our analysis covers all listed stocks on the Dhaka Stock Exchange between 2010 and 2021, but the results are only applicable to Bangladesh and may not necessarily be generalizable to other frontier or emerging equity markets with different market structures, and investor composition. Second, the study concentrates on the chosen macroeconomic variables (exchange rate, interest rate) and monetary policy indicators (deposit rate, deposit reserve ratio) and does not consider any other possibly significant variables, including inflation, GDP growth, or shock in the global market, which may also affect herding behavior. Lastly, despite the market being classified into different phases to represent distinct market states, unobserved micro structural or firm-level forces may still enforce herding but it is not well encompassed in the existing framework. The identification of these limitations offers an avenue to the future research to increase the coverage of the variables, use alternative modeling techniques, or do cross-market comparisons to learn more about herding in frontier equity markets.

Comment 11: We recommend that authors revise the manuscript to improve sentence structure. In the text, "This" appears too often, and it is suggested that it should be adjusted (see the line 82, 86, 92, 97, 99... etc).

Response: These sentences have been corrected.

Reviewer 3 Report

Comments and Suggestions for Authors

• Please use the same font type for all text.
• Page 5: Eq. 8 and Eq. 9 are missing.
• The authors state multiple times that bullish and bearish markets are separated using the "Dow Theory." For the study to be fully reproducible, the authors should briefly elaborate on the specific rules they applied.
• Table 1 uses five asterisks (*****) and four asterisks (****), which deviates from the standard scientific notation where three (***) is the maximum.
• On page 10, the text references blank equations: "Table 4 furnishes the regression results based on equation () and ()…".
• The definition of monetary policy dummy variables (D1 to D5) on page 6 could be slightly clearer.

Author Response

Response to the Comments of the Esteemed Reviewer 3

Comment 1: Please use the same font type for all text.

Response: It has been corrected.

Comment 2: Page 5: Eq. 8 and Eq. 9 are missing.

Response: That was typo mistakes. Now, it has been corrected.

Comment 3: The authors state multiple times that bullish and bearish markets are separated using the "Dow Theory." For the study to be fully reproducible, the authors should briefly elaborate on the specific rules they applied.

Response: The study applied an innovative approach, the application of Dow Theory, to determine bullish and bearish market phases using the patterns of price movements on sustained basis, not short-term change of returns. According to this theory, the market trends are grouped into primary, secondary, and minor. The major trend has the general direction of the market in the long run, over a period of months or years, whereas the minor trend reflects the short-run corrections of the major trend, and the smaller trends represent the short run swings due to market noise or speculation. The theory stipulates that a bullish trend is a kind of higher highs and higher lows that are maintained over some time span, and a bearish trend is defined as lower highs and lower lows. There are multiple bullish and bearish intermediate trends developed over the study period depending on these long-term directional movements. These were then combined to have one bullish and bearish market classification to provide analytical consistency. This is a better and more behaviorally based market classification framework than previous works that only state market states as positive or negative returns which fail to capture the underlying persistence of trend or sentiment dynamics of investors.

Comment 4: Table 1 uses five asterisks (*****) and four asterisks (****), which deviates from the standard scientific notation where three (***) is the maximum.

Response: Now, it has been corrected.

Comment 5: On page 10, the text references blank equations: "Table 4 furnishes the regression results based on equation () and ()…".

Response: Now, it has been properly corrected.

Comment 6: The definition of monetary policy dummy variables (D1 to D5) on page 6 could be slightly clearer.

Response: To examine the effects of monetary policy on herding, the study considers five monetary policy dummy variables, each representing a unique policy action. D₁ takes the value 1 in a month when the deposit rates increase and 0 otherwise; D₂ takes value 1 when the deposit rates decrease, and 0 otherwise; D₃ and D₄ represent the changes in the deposit reserve ratio, taking the value 1 when it increases and decreases, respectively, and 0 otherwise. Lastly, D₅ represent a dummy variable that takes value 1 during monetary policy announcement month, and 0 otherwise.