Relationship monetary policies and changes in exchange rate with herding behavior

Document Type : Original Article

Authors

1 Assistant Professor, Department of Financial Management and Insurance, Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran

2 Master of Accounting, Department of Accounting, Ferdowsi University of Mashhad, Mashhad, Iran.

Abstract

Purpose: In financial markets and behavioral finance studies, the herding behavior of shareholders is considered an important variable. This behavior refers to a process in which capital market participants make decisions without relying on their own information and analysis, instead imitating the actions of others. Analyzing herding behavior can enhance our understanding of how bubbles form in stock markets and contribute to increased capital market efficiency. Herding behavior can distort asset prices, leading to deviations from their fundamental values, which subsequently impacts overall market stability. By understanding the factors that drive herding behavior, policymakers and market regulators can implement strategies to mitigate its adverse effects.
Method: Given the significance of collective behavior, this research examines the relationship between monetary policies, changes in exchange rates, and the herding behavior of shareholders. To measure herding behavior, we utilized the model proposed by Chang et al. (2000). According to this model, herding behavior is indicated when the deviation of stock returns from the market return decreases, suggesting that investors are following the market trend rather than making independent decisions. Furthermore, to measure monetary policy variables and exchange rate changes, we employed indicators of seasonal changes in liquidity volume and monthly changes in the exchange rate, respectively. Using time series data from 2011 to 2021, which includes information from 133 companies listed on the Tehran Stock Exchange, we applied multivariate regression analysis to test our hypotheses. This comprehensive dataset allowed us to capture various economic conditions and policy changes over a significant period.
Findings: The research results indicate that changes in the exchange rate lead to the formation of herding behavior in the Tehran Stock Exchange. This suggests that as the exchange rate fluctuates, investors tend to mimic the actions of others rather than rely on their own analysis. Additionally, while changes in liquidity volume also contribute to the emergence of herding behavior among shareholders, these results were not statistically significant. This implies that liquidity alone may not be a strong enough factor to drive herding behavior, or that other underlying factors may be influencing these outcomes. The findings highlight the importance of exchange rate stability in maintaining market discipline and preventing irrational collective behaviors.
Conclusion: The herding behavior of shareholders has increased the distance between the market price and the intrinsic value of the stock, leading to an increase in stock prices and impacting the efficiency of the capital market. This misalignment between market prices and intrinsic values can create conditions for market bubbles and subsequent crashes. Some studies show that herding behavior is more prevalent when markets are in a stable state (rising or falling) than during periods of chaos and uncertainty. This indicates that investors are more likely to follow the crowd during predictable market conditions, while in volatile times, individual decision-making becomes more pronounced. Policymakers aiming to influence mass behavior should make decisions and implement policies when markets are stable, before a financial crisis or bubble formation occurs. Proactive measures can include regulatory interventions to ensure market transparency and the dissemination of accurate information to all market participants. Considering the results of the research on the effect of exchange rate fluctuations on the formation of mass behavior, it is recommended that stock exchange organizations use this factor to improve investment behavior, guide the market towards intrinsic values, and prevent bubble formation and subsequent collapse. Market supervisors, lawmakers, and the central bank should consider the potential limitations of rational models when designing policies and making decisions related to monetary policies, including determining liquidity levels and controlling the exchange rate. Additionally, the behavioral elements of market attitudes and psychological and cognitive factors should be taken into account when making these decisions. By addressing these aspects, policymakers can better manage market dynamics and foster a more stable financial environment.

Keywords

References

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Financial Management Perspective
Volume 14, Issue 45
2024
Pages 59-83

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