Journals / BİLTÜRK Ekonomi ve İlişkili Çalışmalar Dergisi / 2021 / Cilt: 3 - Sayı: 2

Impact of Macroeconomic Variability on the Stock Market Volatility of Bangladesh

Pages
66–86
Publication Date
2021-04-30
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Therefore, the implication of these findings documents that both the stock market and macroeconomic forces becoming interdependent in Bangladesh.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Öz This study investigates the impact of macroeconomic variability on stock market volatility in Bangladesh covering the data ranging from January 2005 to December 2018 by using three steps of analysis.
📊
Key Findings & Data:The findings of the study evidence that increased volatility in Consumer Price Index, Treasury Bill Rates, and inflow in Foreign Remittance increases the stock return volatility whilst fluctuations in IP leads to a decrease in stock return volatility.
💡
Conclusion & Impact:Therefore, the implication of these findings documents that both the stock market and macroeconomic forces becoming interdependent in Bangladesh.
🔬Design:Modeling & Simulation
📍Scope:2005 Verileri
⚙️Variables:Anahtar Kelimeler Macroeconomic variability · Stock market volatility · EGARCH model

Özet

Öz This study investigates the impact of macroeconomic variability on stock market volatility in Bangladesh covering the data ranging from January 2005 to December 2018 by using three steps of analysis. Firstly, the univariate Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model is employed to estimate the time-varying conditional variance series for stock return and macroeconomic fundamentals. In the second phase, the volatility effect of macroeconomic forces on stock return is estimated by using the most recent standardized squared residuals of macroeconomic fundamentals as exogenous variables in the conditional variance equation of stock returns. Finally, Vector Auto Regression (VAR) model is used to examine the possible interaction between macroeconomic forces and stock price. The findings of the study evidence that increased volatility in Consumer Price Index, Treasury Bill Rates, and inflow in Foreign Remittance increases the stock return volatility whilst fluctuations in IP leads to a decrease in stock return volatility. Therefore, the implication of these findings documents that both the stock market and macroeconomic forces becoming interdependent in Bangladesh.

🔖

Cite This Article

ALİ, M. (2021). Impact of Macroeconomic Variability on the Stock Market Volatility of Bangladesh. BİLTÜRK Ekonomi ve İlişkili Çalışmalar Dergisi, Cilt: 3 - Sayı: 2, 66–86. https://ajindex.com/articles/137032

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (15)

  1. Abbas, G., Hammoudeh, S., Shahzad, S. J. H., Wang, S., & Wei, Y. (2019.) Return and volatility connectedness between stock markets and macroeconomic factors in the G-7 countries. Journal of Systems Science and Systems Engineering, 28, 1–36.
  2. Adjasi, C. K. D. (2009). Macroeconomic uncertainty and conditional stock-price volatility in frontier African Markets: Evidence from Ghana. The Journal of Risk Finance, 10(4), 333-349.
  3. Aliyu, S. U. R. (2012). Does inflation have an impact on stock returns and volatility? Evidence from Nigeria and Ghana. Applied Financial Economics, 22, 427-435.
  4. Asgharian, H., Hou, A. J., & Javed, F. (2013). The importance of the macroeconomic variables in forecasting stock return variance: A GARCH-MIDAS approach. Journal of Forecasting, 32, 600-612.
  5. Baroian, E. (2014). Can macroeconomic volatility affect stock market volatility? The case of 5 central and eastern European countries. Romanian Journal of Fiscal Policy, 5(2), 41-55.
  6. Beetsma, R., & Giuliodori, M. (2012). The changing macroeconomic response to stock market volatility shocks. Journal of Macroeconomics. 34(2), 281-293.
  7. Berndt, E., Hall, B., Hall, R., & Hausman, J. (1974). Estimation and inference in nonlinear structural models. Annals of Social Measurement, 3, 653-665.
  8. Bollerslev, T., & Wooldridge, J. M. (1992). Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances. Econometric Reviews, 11(2), 143-172.
  9. Chen, N., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of Business, 59, 383-403.
  10. Chen, J., Xiong, X., Zhu, J., & Zhu, X. ( 2017). Asset prices and economic fluctuations: the Implications of stochastic volatility. Economic Modelling, 64, 128–140.
  11. Chowdhury, S. S. H., & Rahman, M. A. (2004). On the empirical relation between macroeconomic volatility and stock market volatility of Bangladesh. The Global Journal of Finance and Economics, 1(2), 209-225.
  12. Corradi, V., Distaso, W., & Mele, A. (2013). Macroeconomic determinants of stock volatility and volatility premiums. Journal of Monetary Economics, 60, 203-220.
  13. Cutler, D. M., Poterba, J. M., & Summers, L. H. (1989). What moves stock prices? Journal of Portfolio Management, 15, 4-12.
  14. Dayıoğlu, T., & Aydın, Y. (2019). Relationship between the Volatility of Stock Returns and the Volatility of Macroeconomic Variables: A Case of Turkey. American Journal of Theoretical and Applied Business. 5 (2), 40-46.
  15. Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio stati