دوره 28، شماره 1 - ( بهار 1402 )                   دوره28 شماره 1 صفحات 75-53 | برگشت به فهرست نسخه ها

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Osmani F, Cheshomi A, Salehnia N, Ahmadi Shadmehri M T. (2023). The Reaction of Stock Returns of Iranian Different Industries to Inflation and Interest Rates with the Panel-ARDL Approach. JPBUD. 28(1), 53-75. doi:10.61186/jpbud.28.1.53
URL: http://jpbud.ir/article-1-2155-fa.html
عثمانی فریبا، چشُمی علی، صالح نیا نرگس، احمدی شادمهری محمدطاهر. واکنش بازده سهام صنایع مختلف ایران به تورم و نرخ بهره با رویکرد Panel-ARDL فصلنامه برنامه ریزی و بودجه 1402; 28 (1) :75-53 10.61186/jpbud.28.1.53

URL: http://jpbud.ir/article-1-2155-fa.html

واکنش بازده سهام صنایع مختلف ایران به تورم و نرخ بهره با رویکرد Panel-ARDL
فریبا عثمانی1 ، علی چشُمی1 ، نرگس صالح نیا1 ، محمدطاهر احمدی شادمهری* 2
1- گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، ایران.
2- گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، ایران. ، Shadmhri@um.ac.ir
چکیده:   (514 مشاهده)
با توجه به روند صعودی نرخ تورم و تثبیت نسبی نرخ بهره اسمی در ایران، این پرسش اهمیت می‌یابد که بازده سهام صنایع مختلف چه واکنشی نسبت به این دو متغیر اقتصاد کلان داشته‌اند؟ در این پژوهش، به صورت تجربی با داده‌های ماهانه از فروردین 1389 تا اسفند 1400 با استفاده از مدل Panel-ARDL تاثیر تورم و نرخ بهره بر بازده سهام صنایع مختلف ایران بررسی می‌شود. ابتدا برای امکان مقایسه بین شاخص‌های سهام صنایع مختلف، این شاخص‌ها بر اساس ماه پایه همگن شد و سپس مدل برآورد گردید. نتایج تجربی نشان می‌دهد که تورم در کوتاه‌مدت و بلندمدت اثر مثبت و معناداری بر بازده اسمی سهام صنایع مختلف در دوره مورد مطالعه دارد، اما تورم بر بازده واقعی در بلندمدت اثر منفی و معناداری دارد. نرخ بهره اسمی در کوتاه‌مدت و بلندمدت سبب کاهش بازده اسمی و واقعی سهام صنایع مختلف می‌شود. علاوه بر این، متغیرهای نرخ ارز، قیمت جهانی نفت و نقدینگی نیز به عنوان متغیرهای کنترلی در نظر گرفته شده ‏اند. این نتایج، به سرمایه‌گذاران نشان می‌دهد سهام در بلندمدت نتوانسته محافظ مناسبی در مقابل تورم باشد و مقامات پولی هنگام مدیریت نرخ بهره باید به اثرات آن بر بازار سهام توجه کنند.
واژه‌های کلیدی: تورم، نرخ بهره، شاخص سهام، صنایع، رویکرد Panel-ARDL
متن کامل [PDF 797 kb]   (90 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: اقتصاد مالی
دریافت: 1401/7/21 | پذیرش: 1401/12/3 | انتشار الکترونیک: 1402/3/27
فهرست منابع
1. Abzari, M., Sameti, M., & Delbari, M. (2003). Applying "Analysis of Hierarchical Process" Model (AHP) in Considering Appropriate Criteria for Selecting Stocks in Tehran Stock Exchange. Planning and Budgeting, 7(5), 3-27. [In Farsi] [http://jpbud.ir/article-1-226-fa.html]
2. Alqaralleh, H. (2020). Stock Return-Inflation Nexus; Revisited Evidence Based on Nonlinear ARDL. Journal of Applied Economics, 23(1), 66-74. [DOI:10.1080/15140326.2019.1706828]
3. Antonakakis, N., Gupta, R., & Tiwari, A. K. (2017). Has the Correlation of Inflation and Stock Prices Changed in the United States over the Last Two Centuries? Research in International Business and Finance, 42(1), 1-8. [DOI:10.1016/j.ribaf.2017.04.005]
4. Asiedu, E. L., Mireku-Gyimah, D., Kamasa, K., & Otoo, H. (2021). Interest Rate, Inflation and Stock Market Performance in Ghana: A Sector Based Vector Error Correction Model Perspective. African Journal of Business and Economic Research, 16(1), 185. [DOI:10.31920/1750-4562/2021/v16n1a8]
5. Azimi, S. R., Miri, A. A., Taghizadeh, K., & Samadi, R. (2013). The Study of Trend and Causes of Iran's Inflation During (2010 -2012) and Measures Fulfilled to Subdue It. Quarterly Journal of Fiscal and Economic Policies, 1(1), 25-58. [In Farsi] [http://qjfep.ir/article-1-22-fa.html]
6. Bai, Z. (2014). Study on the Impact of Inflation on the Stock Market in China. International Journal of Business and Social Science, 5(7), 261-271.
7. Belsley, D. A., Kuh, E., & Welsch, R. E. (2005). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity: John Wiley & Sons.
8. Breusch, T. S., & Pagan, A. R. (1980). The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), 239-253. [DOI:10.2307/2297111]
9. Das, D., & Kannadhasan, M. (2020). The Asymmetric Oil Price and Policy Uncertainty Shock Exposure of Emerging Market Sectoral Equity Returns: A Quantile Regression Approach. International Review of Economics & Finance, 69(1), 563-581. [DOI:10.1016/j.iref.2020.06.013]
10. Fama, E. F. (1981). Stock Returns, Real Activity, Inflation, and Money. The American Economic Review, 71(4), 545-565.
11. Feldstein, M. (1983). Inflation and the Stock Market. In Inflation, Tax Rules, and Capital Formation (pp. 186-198): University of Chicago Press. [DOI:10.7208/chicago/9780226241791.001.0001]
12. Geetha, C., Mohidin, R., Chandran, V. V., & Chong, V. (2011). The Relationship between Inflation and Stock Market: Evidence from Malaysia, United States and China. International Journal of Economics and Management Sciences, 1(2), 1-16.
13. Gokmenoglu, K., Eren, B. M., & Hesami, S. (2021). Exchange Rates and Stock Markets in Emerging Economies: New Evidence Using the Quantile-on-Quantile Approach. Quantitative Finance and Economics, 5(1), 94-110. [DOI:10.3934/QFE.2021005]
14. Gordon, M. J. (1962). The Investment, Financing, and Valuation of the Corporation: RD Irwin. [DOI:10.2307/1926621]
15. Hadipour, H., Paytakhti Oskooe, A., & Rahmani, K. (2021). Factors Affecting the Instability Index in Tehran Stock Exchange. Planning and Budgeting, 26(3), 131-154. [In Farsi] [http://jpbud.ir/article-1-2029-fa.html] [DOI:10.52547/jpbud.26.3.131]
16. Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica: Journal of the Econometric Society, 46(6), 1251-1271. [DOI:10.2307/1913827]
17. Hewett, W. W. (1930). The Theory of Interest, as Determined by Impatience to Spend Income and Opportunity to Invest It: JSTOR.
18. Huy, D. T. N., Nhan, V. K., Bich, N. T. N., Hong, N. T. P., Chung, N. T., & Huy, P. Q. (2021). Impacts of Internal and External Macroeconomic Factors on Firm Stock Price in an Expansion Econometric Model-A Case in Vietnam Real Estate Industry. Data Science for Financial Econometrics, 189-205. [DOI:10.1007/978-3-030-48853-6_14]
19. Jareño, F., Ferrer, R., & Miroslavova, S. (2016). US Stock Market Sensitivity to Interest and Inflation Rates: A Quantile Regression Approach. Applied Economics, 48(26), 2469-2481. [DOI:10.1080/00036846.2015.1122735]
20. Jelilov, G., Iorember, P. T., Usman, O., & Yua, P. M. (2020). Testing the Nexus between Stock Market Returns and Inflation in Nigeria: Does the Effect of COVID‐19 Pandemic Matter? Journal of Public Affairs, 20(4), e2289. [DOI:10.1002/pa.2289] [PMID] [PMCID]
21. Kao, C. (1999). Spurious Regression and Residual-Based Tests for Cointegration in Panel Data. Journal of Econometrics, 90(1), 1-44. [DOI:10.1016/S0304-4076(98)00023-2]
22. Kollias, C., Kyrtsou, C., & Papadamou, S. (2013). The Effects of Terrorism and War on the Oil Price-Stock Index Relationship. Energy Economics, 40(1), 743-752. [DOI:10.1016/j.eneco.2013.09.006]
23. Lucey, B. M., Sharma, S. S., & Vigne, S. A. (2017). Gold and Inflation (s)-A Time-Varying Relationship. Economic Modelling, 67(1), 88-101. [DOI:10.1016/j.econmod.2016.10.008]
24. Mankiw, N. G. (2015). Yes, r> g. So What? American Economic Review, 105(5), 43-47. [DOI:10.1257/aer.p20151059]
25. Mehdiabadi, M., & Mohammadipour, R. (2019). Determining the Nonlinear Effect of the Money Market Interest Rate on the Tehran Stock Exchange by the Means of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Model and Smooth Transition Regression (STR) Model. Financial Engineering and Portfolio Management, 10(40), 126-151. [In Farsi] [https://fej.ctb.iau.ir/article_668059.html?lang=en]
26. Modigliani, F., & Cohn, R. A. (1979). Inflation, Rational Valuation and the Market. Financial Analysts Journal, 35(2), 24-44. [DOI:10.2469/faj.v35.n2.24]
27. Mosavi, M. H., & Ragheb, M. (2014). The Effect of Inflation Rate on the Performance of the Stock Market in Iran. Journal of Monetary and Banking Research, 7(19), 125-142. [In Farsi]
28. Okorie, I., Akpanta, A., Ohakwe, J., Chikezie, D., Onyemachi, C., & Ugwu, M. (2021). Modeling the Relationships across Nigeria Inflation, Exchange Rate, and Stock Market Returns and Further Analysis. Annals of Data Science, 8, 295-329. [DOI:10.1007/s40745-019-00206-7]
29. Osmani, F., Cheshomi, A., Salehnia, N., & Ahmadi Shadmehri, M. T. (2022). Investigating the Effect of Time Varying Inflation on the Industry Index (Evidence from Iran's Stock Market). Quarterly Journal of Industrial Economics Researches, 6(20), 27-39. [In Farsi] [DOI:10.30473/jier.2023.65219.1344]
30. Papadamou, S., Sidiropoulos, M., & Spyromitros, E. (2017). Interest Rate Dynamic Effect on Stock Returns and Central Bank Transparency: Evidence from Emerging Markets. Research in International Business and Finance, 39(1), 951-962. [DOI:10.1016/j.ribaf.2016.01.020]
31. Pashaeefam, R., & Omidipour, R. (2009). The Effect of Inflation Rate on Real Stock Return in Iran Economy. Quarterly Journal of Economic Research and Policies, 17(50), 93-113. [In Farsi] [http://qjerp.ir/article-1-258-fa.html]
32. Pedroni, P. (1999). Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors. Oxford Bulletin of Economics and Statistics, 61(S1), 653-670. [DOI:10.1111/1468-0084.61.s1.14]
33. Pesaran, M. H. (2007). A Simple Panel Unit Root Test in the Presence of Cross‐Section Dependence. Journal of Applied Econometrics, 22(2), 265-312. [DOI:10.1002/jae.951]
34. Pesaran, M. H., & Shin, Y. (1995). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis (Vol. 9514): Department of Applied Economics, University of Cambridge Cambridge.
35. Pourkazemi, M. H., Beiranvand, A., & Delfan, M. (2016). Designing a Warning System for Hyperinflation for Iran's Economy. Quarterly Journal of Economic Research and Policies, 23(76), 145-166. [In Farsi] [http://qjerp.ir/article-1-961-fa.html]
36. Rangan, G., & Inglesi-Lotz, R. (2012). Macro Shocks and Real US Stock Prices with Special Focus on the "Great Recession". Applied Econometrics and International Development, 12(2), 123-136.
37. Rapach, D. E., & Weber, C. E. (2004). Financial Variables and the Simulated Out‐of‐Sample Forecastability of US Output Growth since 1985: An Encompassing Approach. Economic Inquiry, 42(4), 717-738. [DOI:10.1093/ei/cbh092]
38. Rapach, D., & Zhou, G. (2013). Forecasting Stock Returns. In Handbook of Economic Forecasting (Vol. 2, pp. 328-383): Elsevier. [DOI:10.1016/B978-0-444-53683-9.00006-2]
39. South African Reserve Bank (2020). Financial Market Development, Monetary Policy and Financial Stability in Emerging Market Economies. BIS Papers Chapters, in: Bank for International Settlements (ed.), (Pages 293-305), Bank for International Settlements.
40. Sreenu, N., Rao, K. S., & Naik, S. (2022). Impact of Exchange Rate and Inflation Rate on Stock Market Return Volatility in India. Academy of Marketing Studies Journal, 26(1), 1-11.
41. Stock, J. H., & Watson, M. W. (2003). Forecasting Output and Inflation: The Role of Asset Prices. Journal of Economic Literature, 41(3), 788-829. [DOI:10.1257/jel.41.3.788]
42. Taieby Sani, E., & Nazeshti, A. (2022). Nonlinear Effects of Interest Rates on the Total Stock Market Index in the Iranian Economy Markov Switching Approach. Quarterly Journal of Fiscal and Economic Policies, 10(37), 113-136. [In Farsi] [http://qjfep.ir/article-1-1279-fa.html] [DOI:10.52547/qjfep.10.37.4]
43. Tangjitprom, N. (2012). The Review of Macroeconomic Factors and Stock Returns. International Business Research, 5(8), 107. [DOI:10.5539/ibr.v5n8p107]
44. Ugurlu‐Yildirim, E., Kocaarslan, B., & Ordu‐Akkaya, B. M. (2021). Monetary Policy Uncertainty, Investor Sentiment, and US Stock Market Performance: New Evidence from Nonlinear Cointegration Analysis. International Journal of Finance & Economics, 26(2), 1724-1738. [DOI:10.1002/ijfe.1874]
45. Valcarcel, V. J. (2012). The Dynamic Adjustments of Stock Prices to Inflation Disturbances. Journal of Economics and Business, 64(2), 117-144. [DOI:10.1016/j.jeconbus.2011.11.002]
46. Zafar, N., Urooj, S. F., & Durrani, T. K. (2008). Interest Rate Volatility and Stock Return and Volatility. European Journal of Economics, Finance and Administrative Sciences, 14(1), 135-140.
47. Zhu, H.-M., Li, R., & Li, S. (2014). Modelling Dynamic Dependence between Crude Oil Prices and Asia-Pacific Stock Market Returns. International Review of Economics & Finance, 29(1), 208-223. [DOI:10.1016/j.iref.2013.05.015]
48. تفضلی، فریدون (1393). اقتصاد و نظریه‌ها و سیاست های اقتصادی. چاپ دوم، انتشارات نی.
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