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, herding behavior is a critical phenomenon that significantly affects market dynamics. This behavior occurs when investors make decisions not based on their independent analysis or information but by imitating the actions of others. Understanding herding behavior can provide valuable insights into the formation of bubbles in stock markets and contribute to improving capital market efficiency. Herding often leads to price distortions, creating a gap between market prices and their intrinsic values, ultimately affecting market stability. This study explores the relationship between monetary policies, exchange rate changes, and herding behavior among shareholders in the Tehran Stock Exchange (TSE).
Method: To measure herding behavior, the study uses the model developed by Chang et al. (2000), which identifies herding when the deviation of stock returns from the market return decreases, signaling that investors are following market trends rather than making independent decisions. Monetary policy variables are assessed using seasonal changes in liquidity volume, while exchange rate changes are evaluated based on monthly exchange rate fluctuations. This research relies on time-series data spanning from 2011 to 2021, covering 133 companies listed on the TSE. Multivariate regression analysis was employed to test the hypotheses, offering a comprehensive examination of the factors driving herding behavior over a significant period.
Findings: The findings indicate that exchange rate fluctuations are a key driver of herding behavior in the Tehran Stock Exchange. As exchange rates fluctuate, investors are more likely to mimic the behavior of others rather than rely on their independent assessments. Additionally, changes in liquidity volume also appear to influence herding behavior; however, these results are not statistically significant. This suggests that while liquidity changes may play a role, they are insufficient on their own to trigger significant herding behavior. The study underscores the importance of maintaining exchange rate stability to mitigate irrational collective behaviors and preserve market discipline.
Conclusion: Herding behavior increases the divergence between market prices and the intrinsic values of stocks, leading to higher risks of price crashes and reduced capital market efficiency. This behavior can create conditions for bubbles and subsequent market collapses. Research shows that herding is more prevalent during stable market conditions—whether rising or falling—than in times of volatility and uncertainty. This suggests that investors are more inclined to follow collective trends during predictable market phases, while volatile conditions encourage more individualistic decision-making. To prevent the adverse effects of herding, policymakers should intervene early during stable market conditions, before the onset of financial crises or the formation of bubbles. Proactive measures, such as regulatory frameworks to enhance market transparency and ensure the dissemination of accurate information, are essential. Based on the results of this study, it is recommended that stock market regulators leverage the impact of exchange rate fluctuations to guide investor behavior, steer the market toward intrinsic values, and prevent bubble formation or excessive market collapses. Additionally, policymakers, including the central bank and legislators, must account for the limitations of rational models when designing monetary policies. They should also consider behavioral, psychological, and cognitive factors influencing market participants to ensure policies are more effective in managing market dynamics.

Keywords

References

Amador, M., & Weill, P.-O. (2010). Learning from Prices: Public Communication and Welfare. Journal of Political Economy, 118(5), 866-907.
Armstrong, C. S., Guay, W. R., & Weber, J. P. (2010). The Role of Information and Financial Reporting in Corporate Governance and Debt Contracting. Journal of Accounting and Economics, 50(2-3), 179-234.
Baker, M., & Wurgler, J. (2006). Investor Sentiment and the Cross‐Section of Stock Returns. The Journal of Finance, 61(4), 1645-1680.
Bikhchandani, S., & Sharma, S. (2000). Herd Behavior in Financial Markets. IMF Staff papers, 47(3), 279-310.
 Chang, E. C., Cheng, J. W., & Khorana, A. (2000). An Examination of Herd Behavior in Equity Markets: An International Perspective. Journal of Banking & Finance, 24 )10), 1651-1679.
Chiang, T. C., & Zheng, D. (2010). An Empirical Analysis of Herd Behavior in Global Stock Markets. Journal of Banking & Finance, 34(8), 1911-1921.
Choi, N., & Sias, R. W. (2009). Institutional Industry Herding. Journal of Financial Economics, 94(3), 469-491.
Christie, W. G., & Huang, R. D. (1995). Following the Pied Piper: Do Individual Returns Herd around the Market? Financial Analysts Journal, 51(4), 31-37.
De la Horra, L. P., Perote, J., & De La Fuente, G. (2021). Monetary Policy and Corporate Investment: A Panel-Data Analysis of Transmission Mechanisms in Contexts of High Uncertainty. International Review of Economics & Finance, 75, 609-624.
Deng, X., Hung, S., & Qiao, Z. (2018). Mutual Fund Herding and Stock Price Crashes. Journal of Banking & Finance, 94, 166-184.
Devenow, A., & Welch, I. (1996). Rational Herding in Financial Economics. European Economic Review, 40(3-5), 603-615.
Espinosa-Méndez, C., Araya-Castillo, L., Jara Bertín, M., & Gorigoitía, J. (2021). International Diversification, Ownership Structure and Performance in an Emerging Market: Evidence from Chile. Economic Research-Ekonomska Istraživanja, 34(1), 1202-1223.
Farhadi, H., Nadiri, M., & Saranj, A. (2022). Investigating the Effect of Herd Behavior in the Iranian Economy on the Efficiency Criteria of the Asset Pricing Model. Islamic Economics & Banking, 11(38), 113-136.
Fratzscher, M., Lo Duca, M., & Straub, R. (2016). Ecb Unconventional Monetary Policy: Market Impact and International Spillovers. IMF Economic Review, 64, 36-74.
Gaballo, G. (2016). Rational Inattention to News: The Perils of Forward Guidance. American Economic Journal: Macroeconomics, 8(1), 42-97.
Galariotis, E., Makrichoriti, P., & Spyrou, S. (2018). The Impact of Conventional and Unconventional Monetary Policy on Expectations and Sentiment. Journal of Banking & Finance, 86, 1-20.
Gambacorta, L., Hofmann, B., & Peersman, G. (2014). The Effectiveness of Unconventional Monetary Policy at the Zero Lower Bound: A Cross‐Country Analysis. Journal of Money, Credit and Banking, 46(4), 615-642.
GhaziAskari, S., Neshat, N., & Jafari Nodoushan, A. (2022). Sustainable Policy-Making of Financial Systems in Crisis Situations with Modelling Based on Artificial Neural Networks. Financial Management Perspective, 12(38), 103-129. https://doi.org/10.52547/jfmp.12.38.103
Gong, P., & Dai, J. (2017). Monetary Policy, Exchange Rate Fluctuation, and Herding Behavior in the Stock Market. Journal of Business Research, 76, 34-43.
Hau, H., & Rey, H. (2006). Exchange Rates, Equity Prices, and Capital Flows. The Review of Financial Studies, 19(1), 273-317.
Heidari, H., & Farzanegan, E. (2021). Evaluating the Herding Effect on Idiosyncratic Volatility in the Industries of the Tehran Stock Exchange. Financial Accounting Research, 13(2), 57-77. https://doi.org/10.22108/far.2021.125918.1690
Hong, H., & Stein, J. C. (1999). A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets. The Journal of Finance, 54(6), 2143-2184.
Hsieh, S.-F., Chan, C.-Y., & Wang, M.-C. (2020). Retail Investor Attention and Herding Behavior. Journal of Empirical Finance, 59, 109-132.
Hwang, S., & Salmon, M. (2009). Sentiment and Beta Herding. SSRN: http://ssrn. com/abtract, 299919.
Khan, A. (2018). A Behavioral Approach to Financial Supervision, Regulation, and Central Banking. International Monetary Fund.
KOMIJANI, A., & HAERI, M. (2013). The Role of Housing Prices in the Transmission Mechanism of Monetary Policy. Economic Strategy, 2(5), -. https://econrahbord.csr.ir/article_103234_67409ce1314762b44982e8dc8b461931.pdf
Koushki, A., Osoolian, M., & Sharif, S. J. S. (2023). An Uncertainty Measure Based on Pearson Correlation as Well as a Multiscale Generalized Shannon-Based Entropy with Financial Market Applications. International Journal of Nonlinear Sciences and Numerical Simulation, 24(5), 1821-1839. https://doi.org/doi:10.1515/ijnsns-2021-0096
Kremer, S., & Nautz, D. (2013). Causes and Consequences of Short-Term Institutional Herding. Journal of Banking & Finance, 37(5), 1676-1686.
Krokida, S.-I., Makrychoriti, P., & Spyrou, S. (2020). Monetary Policy and Herd Behavior: International Evidence. Journal of Economic Behavior & Organization, 170, 386-417.
Lakonishok, J., Shleifer, A., & Vishny, R. W. (1992). The Impact of Institutional Trading on Stock Prices. Journal of Financial Economics, 32(1), 23-43.
Li, Z., Diao, X., & Wu, C. (2022). The Influence of Mobile Trading on Return Dispersion and Herding Behavior. Pacific-Basin Finance Journal, 73, 101767.
Masciandaro, D., & Romelli, D. (2019). Behavioral Monetary Policymaking: Economics, Political Economy and Psychology. Behavioral Finance: The Coming Of Age, 285.
 Mirhasheminasab, S. A., Mohamadzadeh, A., Mohammadnoorbakhsh Langaroodi, M., & Akhoondi, N. (2019). A Model for Syntactic Investigation between Risk Taking, Personal and Cultural Properties on Herding Behavior in Tehran Stock Exchange. Financial Management Perspective, 9(28), 65-90. https://doi.org/10.52547/jfmp.9.28.65
Mohamadi, M., Azimi Yancheshme, M., Fouladi, M., & Farhadi, M. (2022). Designing a Model to Explain the Impact of Investors' Emotions on Financial Decisions, Stock Returns and Economic Volatility. Financial Management Perspective, 12(40), 145-171. https://doi.org/10.52547/jfmp.12.40.145
Mohanty, M. S. (2014). The Transmission of Unconventional Monetary Policy to the Emerging Markets-an Overview. BIS Paper(78a).
 Osoolian, M., & Koushki, A. (2021). Financial Market Risk Analysis before the Pandemic and During the Covid-19 Period. Strategic Studies of public policy, 11(40), 210-226. https://sspp.iranjournals.ir/article_247495_9cc76f9d49fc66892eaeb1a7f7e99a08.pdf
 Osoolian, M., & Koushki, A. (2020). Investigating the Crisis Forecasting Ability of the Cumulative Residual Entropy Measure by Using Logistic Map Simulation Data and Tehran Stock Exchange Overall Index. Financial Management Perspective, 10(31), 9-27. https://doi.org/10.52547/jfmp.10.31.9
Osoolian, M., & Koushki, A. (2021). Prediction of Crisis in Tehran Stock Exchange with Entropy and Analyzing the Identified Crises Such as Covid-19 [Research]. Planning and Budgeting, 26(2), 133-152. https://doi.org/10.52547/jpbud.26.2.133
Plakandaras, V., Gupta, R., Balcilar, M., & Ji, Q. (2022). Evolving United States Stock Market Volatility: The Role of Conventional and Unconventional Monetary Policies. The North American Journal of Economics and Finance, 60, 101666.
 Shams, S., & Esfandiari Moghadam, A. T. (2018). The Relationship between Mass Behavior and the Performance and Characteristics of Investment Companies. Financial Accounting and Auditing Research, 10(38), 47-66. https://faar.ctb.iau.ir/article_543478_d4357f6dc8d18bec81fb1a69a119e397.pdf
Shirazian, Z. (2019). Investigating of Effect Herding Behavior Types among Analysts on Stock Price by Network Analysis in Tehran Stock Exchange. Journal of Investment Knowledge, 8(30), 19-36. https://jik.srbiau.ac.ir/article_14422_1be1c1576a4f2b3b28f6a6d915bac0d4.pdf
Soroushyar, A., & Ali Ahmadi, S. (2016). The Investigation of the Role of Momentum and Investors' Sentiments on the Herding Behavior in Tehran Stock Exchange. Journal of Investment Knowledge, 5(18), 147-159. https://jik.srbiau.ac.ir/article_8622_44839f07444152971c33130d95980ae8.pdf
Tillmann, P. (2016). Unconventional Monetary Policy and the Spillovers to Emerging Markets. Journal of International Money and Finance, 66, 136-156.
Yang, Y., Peng, F., Wang, R., Guan, K., Jiang, T., Xu, G., Sun, J., & Chang, C. (2020). The Deadly Coronaviruses: The 2003 Sars Pandemic and the 2020 Novel Coronavirus Epidemic in China. Journal of Autoimmunity, 109, 102434.
Yang, Z., Lu, Y., & Tan, W. (2021). Monetary Policy Tightening, Accounting Information Comparability, and Underinvestment: Evidence from China. Economic Analysis and Policy, 70, 123-147.
Zhang, R., Yang, X., Li, N., & Khan, M. A. (2021). Herd Behavior in Venture Capital Market: Evidence from China. Mathematics, 9(13), 1509.
Financial Management Perspective
Volume 14, Issue 45
2024
Pages 59-83

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