Investigation of the role of macroeconomic variables in Tehran Stock Exchange uncertainty using risk filtering, MCMC simulation and ARDL approaches.

Subject Areas : Journal of Investment Knowledge

Amir Sarabadani ¹ (Department of Economics and Accounting, Tehran South Branch, Islamic Azad University, Tehran, Iran.)
Ali Baghani ² (Department of Economics and Accounting, Tehran South Branch, Islamic Azad University, Tehran, Iran)
mohsen hamidian ³ (Department of Economics and Accounting, Tehran South Branch, Islamic Azad University, Tehran, Iran.)
Ghodratollah Emamverdi ⁴ (Department of Economics and Accounting, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Norooz Noroolahzadeh ⁵ (Department of Economics and Accounting, Tehran South Branch, Islamic Azad University, Tehran, Iran.)

Received: 2021-01-03 Accepted : 2021-01-16 Published : 2024-03-20

Keywords: Uncertainty, autoregressive distributed lag (ARDL), Markov chain Monte Carlo (MCMC), Risk Filtration, Generalized Dynamic Factor Model (GDFM),

Abstract :

AbstractIn the present study a new total uncertainty criterion in Tehran Stock Exchange was estimated and the impact of macroeconomic variables on this uncertainty was addressed. Risk filtering with an approach to GDFM was first used to detect specific component of 25 time series of the main indices of the Tehran Stock Exchange over 10 years. In the next step, the conditional volatility of the remaining time series’ specific components were estimated using Stochastic volatility (SV) model and finally conditional volatility simulated using Markov chain Monte Carlo (MCMC) approach was averaged to obtain total uncertainty of the Tehran Stock exchange. The ARDL results showed that Tehran Stock Exchange uncertainty is dependent on independent variables such as inflation rate, banks' real interest rate, exchange rate in free Exchange market, liquidity, tax revenue and oil price. According to the results, however, no significant correlation exists between unemployment rate and stock market uncertainty.

References:

امیدی پور، رضا؛ پژویان، جمشید. (1396). فرار مالیاتی در پایه مالیات بر درآمد اشخاص حقوقی در ایران (برآوردهای سالانه 1392-1352). اقتصاد مالی, 11(39), 27-56.

پورباباگل، حمزه، نیری، محمد حسین. (1393)." کاربرد تحلیل عاملی در مدل ترکیبی DEA فازی با مدل مارکوویتز در تعیین پرتفویی از کاراترین شرکت‌ها در بورس اوراق بهادار تهران". دانش مالی تحلیل اوراق بهادار، 7(24), 117-145.

جعفری صمیمی، احمد؛ اعظمی، کوروش. (1391)." نااطمینانی اقتصاد کلان و اندازه دولت: شواهد کشورهای منتخب در حال توسعه". فصـلنامه راهبرد اقتصادی، شماره 3، ص 149-168.

علیقلی, منصوره, حسینی, سید مهدی. (1396). چگونگی اثرگذاری نوسانات شاخص قیمت سهام بر تغییرات رشد اقتصادی در ایران ( 96-1371). اقتصاد مالی, 11(41), 201-224.

کریمی، مجتبی؛ صراف، فاطمه؛ امام وردی، قدرت اله؛ باغانی، علی. (1398). همبستگی شرطی پویای نوسانات قیمت نفت و بازار سهام کشورهای حوزه خلیج فارس با تاکید بر سرایت بحران مالی. اقتصاد مالی, 13(49), 101-130.

مرادپور اولادی، مهدی؛ ابراهیمی، محسـن و عباسـیون، وحیـد. (1387)." بررسـی اثـر عـدم اطمینـان نـرخ ارز واقعـی بـر سرمایه گذاریهای بخش خصوصـی ". فصـلنامه پـژوهش اقتصادی ایران، شماره 35، ص 159-176.

مرفوع، محمد، عدل زاده، مرتضی. (1394). عدم اطمینان اطلاعاتی و واکنش کمتر از حد سرمایه گذاران. پژوهش های تجربی حسابداری4(1), 169-177.‎

مشکی میاوقی، مهدی، اشرفی، حسین. (1393). تأثیر سطح عدم اطمینان بر واکنش قیمت سهام به اخبار خوب و اخبار بد در طول،‎های تجاری. فصلنامه علمی-پژوهشی بررسیهای حسابداری وحسابرسی 21(1), 89-108.

 

Aghion, P., Angeletos, G.M., Banerjee, A., & Manova, K. (2010). Volatility and growth: credit constraints and the composition of investment. Journal of Monetary Economics, 57(3), 246-265.

Andrieș, A. M., Căpraru, B., Ihnatov, I., & Tiwari, A. K. (2017). The relationship between exchange rates and interest rates in a small open emerging economy: The case of Romania. Economic modelling, 67, 261-274

Bai, J., & Ng, S. (2002). Determining the number of factors in approximate factor models. Econometrica, 70(1), 191-221.‏

Bai, J., & Ng, S. (2007). Determining the number of primitive shocks in factor models. Journal of Business & Economic Statistics, 25(1), 52-60.‏

Bai, J., & Ng, S. (2007). Determining the number of primitive shocks in factor models. Journal of Business & Economic Statistics, 25(1), 52-60.‏

Banerjee, A., Dolado, J. J., Galbraith, J. W., & Hendry, D. (1993). Co-integration, error correction, and the econometric analysis of non-stationary data. OUP Catalogue.

Bansal, R., & Yaron, A. (2004). Risks for the long run: a potential resolution of asset pricing puzzles. Journal of Finance, 59(4), 1481–1509.

Bekaert, G., Engstrom, E., & Xing, Y. (2009). Risk, uncertainty, and asset prices. Journal of Financial Economics, 91(1), 59–82.

Bernstein, P. L., & Bernstein, P. L. (1996). Against the gods: The remarkable story of risk (pp. 1269-1275). New York: Wiley.

‏Brainard, W. (1967). Uncertainty and the effectiveness of policy. The American Economic Review, 57(2), 411–425.

Chau, F., Deesomsak, R., & Wang, J. (2014). Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries. Journal of International Financial Markets, Institutions and Money, 28, 1-19.

Chen, S. S. (2010). Do higher oil prices push the stock market into bear territory?. Energy Economics, 32(2), 490-495.

Christiano, L.J., Eichenbaum, M., & Evans, C. (2005). Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy, 113(1),1-45.

Christou, C., Gabauer, D., & Gupta, R. (2019). Time-Varying impact of uncertainty shocks on macroeconomic variables of the united kingdom: Evidence from over 150 years of monthly data. Finance Research Letters, 101363.

Chuliá, H., Guillén, M., & Uribe, J. M. (2017). Measuring uncertainty in the stock market. International Review of Economics & Finance, 48, 18-33.

Dunn Cavelty, M. (2020). From Predicting to Forecasting: Uncertainties, Scenarios, and their (Un-) Intended Side Effects. In The Politics and Science of Prevision: Governing and Probing the Future (pp. 89-103). Routledge.

Fendoǧlu, S. (2014). Optimal Monetary policy rules, financial amplification, and uncertain business cycles. Journal of Economics Dynamics and Control, 46, 271-305.

Forni, M., & Reichlin, L. (1998). Let's get real: a factor analytical approach to disaggregated business cycle dynamics. The Review of Economic Studies, 65(3), 453-473.

Forni, M., Hallin, M., Lippi, M., & Reichlin, L. (2000). The generalized dynamic-factor model: Identification and estimation. Review of Economics and statistics, 82(4), 540-554.

Forni, M., Hallin, M., Lippi, M., & Zaffaroni, P. (2015). Dynamic factor models with infinite-dimensional factor spaces: One-sided representations. Journal of Econometrics, 185(2), 359-371.

Hammoudeh, S., & McAleer, M. (2015). Advances in financial risk management and economic policy uncertainty: An overview. International Review of Economics & Finance, 40, 1-7.

Jurado, K., Ludvigson, S. C., & Ng, S. (2014). Measuring uncertainty: supplementary material.

Jurado, K., Ludvigson, S. C., & Ng, S. (2015). Measuring uncertainty. American Economic Review, 105(3), 1177-1216.

Kastner, G., & Frühwirth-Schnatter, S. (2014). Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models. Computational Statistics & Data Analysis, 76, 408-423.‏

Knight, F. (1921). Risk, uncertainty, and profit. Boston: Hart, Schaffner & Marx; Houghton Mifflin Co.

Nelson, S. C., & Katzenstein, P. J. (2014). Uncertainty, risk, and the financial crisis of 2008. International Organization, 68(2), 361-392.‏

Nneji, I. D. (2020). Development of the Nigerian Economy; a Model of Treasury Bill Rate, Stock Prices, Exchange Rate, and Oil Production (Doctoral dissertation, Trident University International).

Pesaran, M. H., & Shin, Y. (1996). Cointegration and speed of convergence to equilibrium. Journal of econometrics, 71(1-2), 117-143.

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.

Raghutla, C., Sampath, T., & Vadivel, A. (2020). Stock prices, inflation, and output in India: An empirical analysis. Journal of Public Affairs, 20(3), e2052.

Ramey, G., & Ramey, V.A. (1995). Cross-country evidence on the link between volatility and growth. American Economic Review, 85(5), 1138-1151.

Romer, C.D. (1990). The great crash and the onset of the great depression. Quarterly Journal of Economics, 105(3), 597-624.

Saltzman, B., & Yung, J. (2018). A machine learning approach to identifying different types of uncertainty. Economics Letters, 171, 58-62.

Singhal, S., Choudhary, S., & Biswal, P. C. (2019). Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico. Resources Policy, 60, 255-261.

Sims, C. A. (1980). Macroeconomics and reality. Econometrica: journal of the Econometric Society, 1-48.‏

Stock, J.H., and M.W. Watson (2002b), “Macroeconomic Forecasting Using Diffusion Indexes,” Journal of Business and Economic Statistics, 20, 147-162.

Stock, J.H., and M.W. Watson, (2002a), “Forecasting Using Principal Components from a Large Number of Predictors,” Journal of the American Statistical Association, 97, 1167-1179.

Stock, J.H., and M.W. Watson. (2011). Dynamic factor models. Oxford handbook on economic forecasting, 2011.

Teera, J. M., & Hudson, J. (2004). Tax performance: a comparative study. Journal of international development, 16(6), 785-802.

Ter Braak, C. J. (2006). A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces. Statistics and Computing, 16(3), 239-249.‏

Tourani‐Rad, A., Liu, M. H., & Shrestha, K. M. (2008). Analysis of the long‐term relationship between macro‐economic variables and the Chinese stock market using heteroscedastic cointegration. Managerial Finance.

Williams, N. (2012). Monetary policy under financial uncertainty. Journal of Monetary Economics, 59(5), 449-465.

Xu, B., Zhang, S., & Chen, X. (2020). Uncertainty in financing interest rates for startups. Industrial Marketing Management.

Zhang, X. (2006). Information uncertainty and stock returns. The Journal of Finance, 61(1), 105-137.