Investigating The Leverage effect and The Volatility Spillover among Exchange rate, pharmaceutical and Food industry index in Tehran stock market

Document Type : Original Article

Authors

1 Assistant Prof, Department of Management and Accounting, University of Shahid Beheshti, Tehran, Iran

2 Associate Prof, Department of Department of Accounting, University of Semnan, Semnan, Iran.

3 Ph.D. Candidate in Financial Engineering, University of Semnan, Semnan, Iran

4 Ph.D. Candidate in Financial Engineering, University of Semnan, Semnan, Iran.

Abstract

One of the factors affecting the efficiency of the pharmaceutical and food industry index in developing countries such as Iran, which has a high degree of uncertainty in macroeconomic variables, is the exchange rate (dollar). The pharmaceutical and food industry is considered one of the strategic industries in the country in terms of its direct relationship with people's health, therefore managers and policymakers have always paid attention to it. Various factors affect the food and pharmaceutical industries, one of the most important of which is exchange rate fluctuations. The main purpose of this study is to investigate the contagion of fluctuations between the return of the dollar and the return of the pharmaceutical and food industry index due to the importance of these two industries in the country's economy. In this study, first, ARMA (1,1) model was used to extract the residuals.Then, GJR-GARCH model was used to check the Leverage effects, and finally, The DECO-GARCH model was used to check the contagion of volatilities between the dollar return, pharmaceutical and food industry indices. Also, the data used in this research was extracted daily from the Bourseview.com website for the period of March 25, 2020, to November 4, 2023. The result of GJR coefficient, which is positive and significant for all return series leverage effects exist. AlsoThe results of DECO-GARCH model estimation indicate the existence of a spillover effect between the dollar return and the pharmaceutical and food industry indices.

Keywords


  1. Allen, D., Amram, R., & McAleer, M. (2011). Volatility spillovers from the Chinese stock market to economic neighbors. Mathematics and Computers in Simulation, 94, 238-257.
  2. Bauwens, L., Laurent, S., & Rombouts, J. V. (2006). Multivariate GARCH models: a survey. Journal of applied econometrics, 21(1), 79-109.
  3. Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A capital asset pricing model with time-varying covariances. Journal of political Economy, 96(1), 116-131
  4. Cappiello, L., Engle, R., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4, 537–572.
  5. Einabadi, J., & moradi, N. (2021). The effects of exchange rate appreciation on the stock value of pharmaceutical companies based on the estimated value obtained from the evaluation models of cash dividend discount, free cash flow and residual profit and real price. Journal of Business Management, 13(52), 467-485. (In Persian)
  6. Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized Auttoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350.
  7. Engle, R.F., Sheppard, K., 2001. Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH. Working Paper. University of California, San Diego.
  8. Hamao, Y., Masulis, R. W., & Ng, V. (1990). Correlations in price changes and volatility across international stock markets. The review of financial studies, 3(2), 281-307.
  9. Heidari, H., Mohammadzadeh, Y., & Refah-Kahriz, A. (2018). An Investigation of the Effect of Exchange Rate on the Pharmaceutical Industry Stock Return in Tehran Stock Exchange: An Application of the Markov Switching Approach. Journal of Asset Management and Financing, 6(2), 35-56. doi: 10.22108/amf.2017.21420(In Persian)
  10. Hou, Y. G., & Li, S. (2020). Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China. International Review of Economics & Finance, 66, 166-188.
  11. Koutmos, G., & Spillover Effect On Different industries For Capital MarketBooth, G. G. (1995). Asymmetric volatility transmission in international stock markets. Journal of international Money and Finance, 14(6), 747-762.
  12. Shams Safa, F., Daman keshideh, M., Afsharirad, M., HadiNejad, M., & Daghighi Asl, A. (2022). The Effects of Exchange Rate Volatility and Entry of Real Shareholders on the Return on Assets in the Food and Drink Companies of Tehran Stock Exchange (Dynamic Panel Data Approach). Financial Management Perspective, 12(39), 121-145. doi: 10.52547/JFMP.12.39.121(In Persian)
  13. Shokri, N., Sahab Khodamoradi, M., & Hajiloo moghadam, A. H. (2021). Investigating the effects of financial volatility spillover between digital currencies (application of multivariate GARCH approach). Financial Management Perspective, 11(35), 143-172. doi: 10.52547/jfmp.11.35.143(In Persian(
  14. Y, Jiang, F, Yuyuan, R, Weihuan. (2019). Risk Spillover and Portfolio management between precious metal and BRICS stock markets. Physica A (534)
  15. Yadav, N., Singh, A. B., & Tandon, P. (2023). Volatility Spillover Effects between Indian Stock Market and Global Stock Markets: A DCC-GARCH Model. FIIB Business Review.