The Asymmetric Effect of Macroeconomic Variables on Stock Price Index: Quantile ARDL  Approach

Balounejad Nouri, Roozbeh; farhang, amirali

doi:10.52547/jemr.12.45.163

Volume 12, Issue 45 (11-2021) jemr 2021, 12(45): 163-198 | Back to browse issues page

‎ 10.52547/jemr.12.45.163

‎ 20.1001.1.22286454.1400.12.45.5.4

Mendeley

Zotero

RefWorks

Balounejad Nouri R, farhang A. The Asymmetric Effect of Macroeconomic Variables on Stock Price Index: Quantile ARDL Approach. jemr 2021; 12 (45) : 5
URL: http://jemr.khu.ac.ir/article-1-2227-en.html

The Asymmetric Effect of Macroeconomic Variables on Stock Price Index: Quantile ARDL Approach

Roozbeh Balounejad Nouri¹

, Amirali Farhang ^*

1- Economic Affairs Research Institute
2- Payame Noor University , s_farhang@pnu.ac.ir

Abstract: (3555 Views)

This paper aims at investigating the asymmetric impact of long-term and short-term macroeconomic variables on the capital market prices of Iran.Macroeconomic variables are inflation, exchange rate, non-oil trade balance and crude oil prices. In order to investigate these relationships, the quantile autoregressive distributed lag (QARDL) method introduced by Cho et al. (2015) has been used. For this purpose, monthly data related to Iran's economy in the period 2008: M9-2021: M6, have been used. Findings show that in the short run, the macro variables used except the trade balance and oil prices have an asymmetric effect on the capital market price index. In the long run, all variables except oil price have an asymmetric effect on the stock price index and the effect of oil price is symmetrical and significant. This conclusion shows that in situations where the stock market price index is in a state of prosperity, recession or normal, except for oil prices, the effect of research variables on this index is not the same and even this effect is different in the short and long term.

Article number: 5

Keywords: Macroeconomic Variables, Stock Price, Quntile Regression, QARDL

Full-Text [PDF 500 kb] (1671 Downloads)

Type of Study: توسعه ای | Subject: پولی و مالی
Received: 2021/12/30 | Accepted: 2022/07/28 | Published: 2022/11/6

References

1. Abbasinejad,H,. Mohammadi,S,. Ebrahimi ,S. (2017). Dynamics of the Relation between Macroeconomic Variables and Stock Market Index, Asset Management and Financing, 5(1), 61-82, (in persian).

2. Abbass, K., Sharif, A., Song, H., Ali, M.A., Khan, F. & Amin, N. (2022). Do geopolitical oil price risk, global macroeconomic fundamentals relate Islamic and conventional stock market? Empirical evidence from QARDL approach, Resources Policy, 77, 1-16. [DOI:10.1016/j.resourpol.2022.102730]

3. Ajaz, T., Nain, M. Z., Kamaiah, B., & Sharma, N. K. (2017). Stock prices, exchange rate and interest rate: Evidence beyond symmetry. Journal of Financial Economic Policy, 9(1), 2-19. [DOI:10.1108/JFEP-01-2016-0007]

4. Al Refai, H., Zeitun, R., & Eissa, M. A. A. (2021). Impact of global health crisis and oil price shocks on stock markets in the GCC. Finance Research Letters, 102130. [DOI:10.1016/j.frl.2021.102130]

5. Alam, I., Mohsin, M., Latif, K., & Zia-ur-Rehman, M. (2020). The Impact of Macroeconomic Factors on Stock Market: An Evidence from China and Pakistan. NICE Research Journal, 1-26. [DOI:10.51239/nrjss.v0i0.171]

6. Alamgir, F. & Amin, S.B. (2021).The nexus between oil price and stock market: Evidence from South Asia. Energy Reports, 7, 693-703. [DOI:10.1016/j.egyr.2021.01.027]

7. Alisu, A. A., Swaray, R., & Oloko, T. (2019). Improving the predictability of the oil-US stock nexus: The role of macroeconomic variables. Economic Modelling, 76, 153-171 [DOI:10.1016/j.econmod.2018.07.029]

8. Antonakakis, N., Gupta, R., & Tiwari, A. K. (2018). Time-varying correlations between trade balance and stock prices in the United States over the period 1792 to 2013. Journal of Economics and Finance, 42(4), 795-806. [DOI:10.1007/s12197-018-9428-z]

9. Apergis, N., & Miller, S. M. (2009). Do structural oil-market shocks affect stock prices?, Energy Economics, 31, 569-575. [DOI:10.1016/j.eneco.2009.03.001]

10. Badri, A., Davallou,M., Dorri Nokourani,M. (2016). The Effect of Macroeconomic Variables on the Performance of the Stock Market, Financial Management Perspective, 6(13), 9-35, (in persian).

11. Balounejad Nouri ,R.,Farhang,A.A. (2022). The Effect of Financial Inclusion on Financial Efficiency and sustainability: an Application of Multidimensional Indexing Approach, Journal of New Economy and Commerce, 16(2), 57-83,(in persian).

12. Basher, S. A., Haug, A. A., & Sadorsky, P. (2018). The impact of oil-market shocks on stock returns in major oil-exporting countries. Journal of International Money and Finance, 86, 264-280.. [DOI:10.1016/j.jimonfin.2018.05.003]

13. Bhuiyan, E. M., & Chowdhury, M. (2020). Macroeconomic Variables and Stock Market Indices: Asymmetric Dynamics in the US and Canada. The Quarterly Review of Economics and Finance. Finance, 77, 62-74 [DOI:10.1016/j.qref.2019.10.005]

14. Bhutto, N. A., & Chang, B. H. (2019). The effect of the global financial crisis on the asymmetric relationship between exchange rate and stock prices. High Frequency, 2(3-4), 175-183. [DOI:10.1002/hf2.10033]

15. Bianconi, M., Esposito, F., & Sammon, M. (2021). Trade policy uncertainty and stock returns. Journal of International Money and Finance, 119, 102492. [DOI:10.1016/j.jimonfin.2021.102492]

16. Camilleri, S. J., Scicluna, N., & Bai, Y. (2019). Do stock markets lead or lag macroeconomic variables? Evidence from select European countries. The North American Journal of Economics and Finance, 48, 170-186. [DOI:10.1016/j.najef.2019.01.019]

17. Chang, B. H. (2020). Oil prices and E7 stock prices: an asymmetric evidence using multiple threshold nonlinear ARDL model. Environmental Science and Pollution Research, 27(35), 44183-44194. [DOI:10.1007/s11356-020-10277-2]

18. Chang, B. H., & Rajput, S. K. O. (2018). Do the changes in macroeconomic variables have a symmetric or asymmetric effect on stock prices? Evidence from Pakistan. South Asian Journal of Business Studies, 7(3), 312-331. [DOI:10.1108/SAJBS-07-2018-0077]

19. Chang, B. H., Meo, M. S., Syed, Q. R., & Abro, Z. (2019). Dynamic analysis of the relationship between stock prices and macroeconomic variables. South Asian Journal of Business Studies, 8(3), 229-245. [DOI:10.1108/SAJBS-06-2018-0062]

20. Chang, B. H., Sharif, A., Aman, A., Suki, N. M., Salman, A., & Khan, S. A. R. (2020). The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach. Resources Policy, 65, 101571. [DOI:10.1016/j.resourpol.2019.101571]

21. Cheikh, N. B., Naceur, S. B., Kanaan, O., & Rault, C. (2021). Investigating the asymmetric impact of oil prices on GCC stock markets. Economic Modelling, 102, 105589. [DOI:10.1016/j.econmod.2021.105589]

22. Cheikh, N.B., Naceur, S.B, Kanaan, O. & Rault, C. (2021). Investigating the asymmetric impact of oil prices on GCC stock markets. Economic Modelling, 102, 1-18. [DOI:10.1016/j.econmod.2021.105589]

23. Chen, N. F., Roll, R., & Ross, S. (1986). Economic forces and thestock market. Journal of Business, 59, 83-403. [DOI:10.1086/296344]

24. Chkir, I., Guesmi, K., Brayek, A. B., & Naoui, K. (2020). Modelling the nonlinear relationship between oil prices, stock markets, and exchange rates in oil-exporting and oil-importing countries. Research in International Business and Finance, 54, 101274. [DOI:10.1016/j.ribaf.2020.101274]

25. Cho, J. S., Kim, T.-H., & Shin, Y. (2015). Quantile cointegration in the autoregressive distributed-lag modeling framework. Journal of Econometrics, 188(1), 281-300. [DOI:10.1016/j.jeconom.2015.05.003]

26. Daliri H.(2021). Factors Affecting on the Business Cycles in OPEC Countries: Evidence from the Quantile Panel Regressions Model. JEMR; 12 (43) :237-270, (in persian).

27. Delgado, N. A. B., Delgado, E. B., & Saucedo, E. (2018). The relationship between oil prices, the stock market and the exchange rate: Evidence from Mexico. The North American Journal of Economics and Finance.45, 266-275. [DOI:10.1016/j.najef.2018.03.006]

28. Dornbusch, R., & Fisher S. (1980). Exchange Rates and the Current Account. American Economic Review, 70, 960-971.

29. Duangin, S., Yamaka, W., Sirisrisakulchai, J., & Sriboonchitta, S. (2018). Macroeconomic News Announcement and Thailand Stock Market. In International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (pp. 408-419). Springer, Cham. [DOI:10.1007/978-3-319-75429-1_34]

30. Fama, E. F. (1981). Stock Returns, Real Activity, Inflation, and Money. The American Economic Review, 71(4), 545-565.

31. Fasanya, I. O., Oyewole, O. J., Adekoya, O. B., & Badaru, F. O. (2021). Oil price and stock market behaviour in GCC countries: do asymmetries and structural breaks matter?. Energy Strategy Reviews, 36, 100682. [DOI:10.1016/j.esr.2021.100682]

32. Feldstein, M. (1980). Inflation, tax rules, and the prices of land and gold. Journal of Public Economics, 14(3), 309-317. [DOI:10.1016/0047-2727(80)90029-8]

33. Fernandez-Perez, A., Fernández-Rodríguez, F., & Sosvilla-Rivero, S. (2014). The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market. International Review of Economics & Finance, 31, 21-33 [DOI:10.1016/j.iref.2013.12.004]

34. Fisher, I. (1930). The theory of interest (p. 43). New York, NY: Augustus M. Kelley.

35. Fratzscher, M., & Straub, R. (2010). Asset prices, news shocks and the current account. CEPR Discussion Papers 8080. [DOI:10.2139/ssrn.1255462]

36. Gay, R. D. (2016). Effect of macroeconomic variables on stock market returns for four emerging economies: Brazil, Russia, India, and China. The International Business & Economics Research Journal (Online), 15(3), 119. [DOI:10.19030/iber.v15i3.9676]

37. Godil, D. I., Sarwat, S., Sharif, A., & Jermsittiparsert, K. (2020). How oil prices, gold prices, uncertainty and risk impact Islamic and conventional stocks? Empirical evidence from QARDL technique. Resources Policy, 66, 101638. [DOI:10.1016/j.resourpol.2020.101638]

38. González, M., Nave, J., & Rubio, G. (2018). Macroeconomic determinants of stock market betas. Journal of Empirical Finance, 45, 26-44. [DOI:10.1016/j.jempfin.2017.10.003]

39. Granger, C. W., Huangb, B.-N., & Yang, C.W. (2000). A bivariate causality between stock prices and exchange rates: Evidence from recent Asianflu. The Quarterly Review of Economics and Finance, 40(3), 337-354. [DOI:10.1016/S1062-9769(00)00042-9]

40. Hammoudeh, S., Mensi, W. & Cho, J.S. (2022). Spillovers between exchange rate pressure and CDS bid-ask spreads, reserve assets and oil prices using the quantile ARDL model, International Economics, 170, 66-78. [DOI:10.1016/j.inteco.2022.01.007]

41. Hashmi, S. M., & Chang, B. H. (2021). Asymmetric effect of macroeconomic variables on the emerging stock indices: A quantile ARDL approach. International Journal of Finance & Economics. [DOI:10.1002/ijfe.2461]

42. Hashmi, S. M., Chang, B. H., & Shahbaz, M. (2021). Asymmetric effect of exchange rate volatility on India's cross‐border trade: Evidence from global financial crisis and multiple threshold nonlinear autoregressive distributed lag model. Australian Economic Papers, 60(1), 64-97. [DOI:10.1111/1467-8454.12194]

43. Hashmi, S.M., Chang, B.H, Huang, L. & Uche, E. (2022). Revisiting the relationship between oil prices, exchange rate, and stock prices: An application of quantile ARDL model, Resources Policy, 75, 1-19. [DOI:10.1016/j.resourpol.2021.102543]

44. Hirigoyen, A., Acuna, M., Rachid-Casnati, C., Franco, J., & Navarro-Cerrillo, R. (2021). Use of Optimization Modeling to Assess the Effect of Timber and Carbon Pricing on Harvest cheduling, Carbon Sequestration, and Net Present Value of Eucalyptus Plantations. Forests, 12(6), 651. [DOI:10.3390/f12060651]

45. Hogan, K., Melvin, M., Roberts, D. J.,( 1991). Trade Balance News and Exchange Rates: Is There a Policy Signal?, Journal of International Money and Finance, 10 (1, Supple), S90-S99. [DOI:10.1016/0261-5606(91)90048-O]

46. Hortamani, M. Karimkhani, M. Abdoli, (2016). The effect of macroeconomic variables on total efficiency of the securities market Approach using state - space, Journal of Development Economics and Planning, 4(1), 83, (in persian).

47. Huang, Q., Wang, X., & Zhang, S. (2021). The effects of exchange rate fluctuations on the stock market and the affecting mechanisms: Evidence from BRICS countries. The North American Journal of Economics and Finance, 56, 101340. [DOI:10.1016/j.najef.2020.101340]

48. Huy, D. T. N., Loan, B. T. T., & Pham, T. A. (2020). Impact of selected factors on stock price: a case study of Vietcombank in Vietnam. Entrepreneurship and Sustainability Issues, 7(4), 2715. [DOI:10.9770/jesi.2020.7.4(10)]

49. Ibrahim, M. (2003). Macroeconomic forces and capital market integration A VAR analysis for Malaysia.Journal of the Asia Pacific Economy, 8(1), 19-40. [DOI:10.1080/1354786032000045228]

50. Jiang, M., & Kong, D. (2021). The Impact of International Crude Oil Prices on Energy Stock Prices: Evidence From China. Energy RESEARCH LETTERS, 2(4), 28133. [DOI:10.46557/001c.28133]

51. Keswani, S., & Wadhwa, B. (2021). Association among the selected Macroeconomic factors and Indian stock returns. Materials Today: Proceedings.In Press, Corrected Proof [DOI:10.1016/j.matpr.2021.01.841]

52. Khodam M, Nosratian Nasab M, Jafari Samimi. A.(2021).Expected Shortfall in Tehran Stock Exchange (Dynamic Semi-Parametric Approach). JEMR; 12 (44) :191-212, (in persian).

53. Killian, L., & Park, C. (2009). The impact of price shocks on the U.S. stock market. International Economic Review, 50, 1267-1287 [DOI:10.1111/j.1468-2354.2009.00568.x]

54. King, A. (2021). The triangular purchasing power parity hypothesis: A comment. The World Economy, 44(3), 837-848. [DOI:10.1111/twec.13050]

55. Koenker, R. (2005). Quantile Regression (Econometric Society Monographs Book 38). Cambridge University Press; Illustrated edition. [DOI:10.1017/CBO9780511754098]

56. Koenker, R., & Hallock, K. F. (2001). Quantile regression. Journal of economic perspectives, 15(4), 143-156. [DOI:10.1257/jep.15.4.143]

57. Lazar, D. (2021). Investment and diversification opportunities in Indian and Chinese stock markets, International Journal of Finance, Entrepreneurship & Sustainability (IJFES), 1(1) ,1-9.

58. Li, J., Wang, H., & Yu, J. (2021). Aggregate expected investment growth and stock market returns. Journal of Monetary Economics, 117, 618-638 [DOI:10.1016/j.jmoneco.2020.03.016]

59. Liu, G., Fang, X., Huang, Y., & Zhao, W. (2021). Identifying the role of consumer and producer price index announcements in stock index futures price changes. Economic Analysis and Policy, 72, 87-101. [DOI:10.1016/j.eap.2021.07.009]

60. Maio, P., & Philip, D. (2015). Macro variables and the components of stock returns. Journal of Empirical Finance, 33, 287-308. [DOI:10.1016/j.jempfin.2015.03.004]

61. Mercereau, B., (2003). The Role of Stock Markets in Current Account Dynamics: a Time Series Approach. The B.E. Journal of Macroeconomics, 3 (1), 1-30. [DOI:10.2202/1534-5998.1063]

62. Nasrollahi,Z,.Nasrollahi,KH,.Mirzababaee,S.M. (2011). Examination of Relationship between Macroeconomic Variables and Stock Exchange Price Index in Iran Using VECM, Quarterly Journal of Quantitative Economics, 8(3), 89-103, (in persian).

63. Oad Rajput, S. K., Ilyas, M., & Khan, J. (2020). Economic expectations and stock returns: Evidence from China Pakistan economic corridor. Retrieved from SSRN, 3525022 [DOI:10.2139/ssrn.3525022]

64. Olayeni, O. R., Tiwari, A. K., & Wohar, M. E. (2020). Global economic activity, crude oil price and production, stock market behaviour and the Nigeria-US exchange rate. Energy Economics, 92, 104938. [DOI:10.1016/j.eneco.2020.104938]

65. Olayeni, O. R., Tiwari, A. K., & Wohar, M. E. (2020). Global economic activity, crude oil price and production, stock market behaviour and the Nigeria-US exchange rate. Energy Economics, 92, 104938. [DOI:10.1016/j.eneco.2020.104938]

66. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326. [DOI:10.1002/jae.616]

67. Pesaran, M.H., Shin, Y. )1998(. An autoregressive distributed lag Modelling approach to cointegration analysis. In: Strøm, S. (Ed.), Econometrics and Economic Theory in The Twentieth Century: The Ragnar Frisch Centennial Symposium. Cambridge University Press, Cambridge, UK, 371-413. [DOI:10.1017/CCOL0521633230.011]

68. Raghutla, C., Sampath, T., & Vadivel, A. (2020). Stock prices, inflation, and output in India: An empirical analysis. Journal of Public Affairs, 20(3), e2052. [DOI:10.1002/pa.2052]

69. Rahman, M. L., & Uddin, J. (2009). Dynamic relationship between stock prices and exchange rates: Evidence from three south Asian countries. International Business Research, 2(2), 167. [DOI:10.5539/ibr.v2n2p167]

70. Razmi, S. F., Bajgiran, B. R., Behname, M., Salari, T. E., & Razmi, S. M. J. (2020). The relationship of renewable energy consumption to stock market development and economic growth in Iran. Renewable Energy, 145, 2019-2024. [DOI:10.1016/j.renene.2019.06.166]

71. Roston, M. (2021). A Portfolio Approach to Hedging Climate Risk. In Settling Climate Accounts, Palgrave Macmillan, Cham, 15-38. [DOI:10.1007/978-3-030-83650-4_2]

72. Roubaud, D., & Arouri, M. (2018). Oil prices, exchange rates and stock markets under uncertainty and regime-switching. Finance Research Letters, 27, 28-33. [DOI:10.1016/j.frl.2018.02.032]

73. Shahzad, S. J. H., Hurley, D., & Ferrer, R. (2020). US stock prices and macroeconomic fundamentals: Fresh evidence using the quantile ARDL approach. International Journal of Finance & Economics, DOI: 1002/10/ijfe.1976

74. Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in honor of Peter Schmidt . Springer, New York, NY. pp. 281-314 [DOI:10.1007/978-1-4899-8008-3_9]

75. Simo-Kengne, B., Miller, S., Gupta, R., Aye, G.,( 2015). Time-Varying Effects of Housing and Stock Returns on U.S. Consumption. The Journal of Real Estate Finance and Economics, 50 (3), 339-354. [DOI:10.1007/s11146-014-9470-3]

76. Wang, L., Ma, F., Niu, T., & He, C. (2020). Crude oil and BRICS stock markets under extreme shocks: New evidence. Economic Modelling, 86, 54-68. [DOI:10.1016/j.econmod.2019.06.002]

77. Wei, Y., Qin, S., Li, X., Zhu, S., & Wei, G. (2019). Oil price fluctuation, stock market and macroeconomic fundamentals: Evidence from China before and after the financial crisis. Finance Research Letters, 30, 23-29. [DOI:10.1016/j.frl.2019.03.028]

78. Yang, Z., Tu, A. H., & Zeng, Y. (2014). Dynamic linkages between Asian stock prices and exchange rates: New evidence from causality in quantiles. Applied Economics, 46(11), 1184-1201. [DOI:10.1080/00036846.2013.868590]

79. Yonesi,A., Farhang,A.A., Balounejad Nouri ,R. (2022). Banking income diversification and market power (PMG approach), Journal of Industrial Economics Research, 5(18), 73-88,(in persian).

80. You, W., Guo, Y., Zhu, H., & Tang, Y. (2017). Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression. Energy Economics, 68, 1-18. [DOI:10.1016/j.eneco.2017.09.007]

81. Yusof, R. M., & Majid, M. S. A. (2007). Macroeconomic variables and stock returns in Malaysia: An application of the ARDL bound testing approach. Savings and Development, 31, 449-469.

82. Zarainejad,M,. Motamedi,S. (2012). Investigating the relationship between macroeconomic variables and total stock price index in Tehran Stock Exchange, Economic Research Journal, 12 (46), 101,(in persian).