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Monetary behavior theory in long-term and turbulent conditions on the Russian Ruble | ||
| Journal of Mathematics and Modeling in Finance | ||
| مقاله 10، دوره 2، شماره 1، مهر 2022، صفحه 183-194 اصل مقاله (191.12 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22054/jmmf.2022.14572 | ||
| نویسندگان | ||
| Farzad Jafari* 1؛ Amir Hamooni2؛ Saeid Tajdini3؛ Mohammad Qezelbash4؛ Niloufar Ebrahimiyan5 | ||
| 1University of Tehran, Tehran,Iran | ||
| 2Ph.D. candidate in Economics Department, University of Tehran, Tehran, Iran | ||
| 3Postdoc of Finance, Faculty of Economics, University of Tehran, Tehran, Iran | ||
| 4Ph.D. student in Financial Engineering, Allameh Tabataba'i University, Tehran, Iran. | ||
| 5Master of Science in Financial Management, Alzahra University, Tehran, Iran. | ||
| چکیده | ||
| In this study, based on the monetary behavior theory, which considers the mean and standard deviation of GDP per capita besides the inflation difference between two countries, we first present a model for determining the fair value of the Russian ruble in the long run from 1999 to 2021 based on macroeconomic indicators including inflation, and GDP per capita. And then we modeled the effect of widespread Russian economic sanctions on the value of the Russian ruble during the turbulent days of February 9 to April 9. Our research results show that there is not much difference between market value and fair value in the long run. Also, by observing the behavior of the ruble during the turbulent days of February 25, 2022, to April 26, 2022, and by entering the conditional risk factor and weighted average of the ruble, the USD to ruble equality between 76.23 and 91.6 was evaluated | ||
| کلیدواژهها | ||
| monetary behavior theory؛ inflation؛ sanctions؛ IGARH؛ GARCH؛ EGARCH | ||
| مراجع | ||
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[1] Abdelaal, M. A., (2011). Modelling and forecasting time-varying stock return volatility in the Egyptian stock market. International Research Journal of Finance and Economics 78(4):96-113. [2] AndreeaCristina, P., Stelian, S. (2017). Empirical results of modeling EUR/RON exchange rate using ARCH, GARCH, EGARCH, TARCH and PARCH models, Romanian Statistical Review 65(1), 57-72. [3] Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31(3) 307-327. [4] Coffie, W., Tackie, G., Bedi, I. F., Aboagye-Otchere. (2017). Alternative Models for the Conditional Heteroscedasticity and the Predictive Accuracy of variance Models Emprical Evidence from East and North Africa Stock Markets. Journal of Accounting and Finance,17(2). [5] Daniel, K., R. J. Hodrick, and Z. Lu . (2017). The Carry Trade: Risks and Drawdowns. Critical Finance Review. 6, 211-262. [6] Della Corte, P., A. Jeanneret, and E. Patelli. (2020). A Credit-Based Theory of the Currency Risk Premium, Working Paper. [7] Della Corte, P., L. Sarno, and I. Tsiakas. (2009). An Economic Evaluation of Empirical Exchange Rate Models. Review of Financial Studies, 22, 3491-3530. [8] Dritsaki, Ch.(2017) An empirical Evaluation in GARCH Volatility Modeling: Evidence from the Stockholm Stock Exchange. Journal of Mathematical Finance.7, 366-390. [9] Dhamija, AK., and VK. Bhalla. (2010), Financial time series forecasting: comparison of neural networks and ARCH models, International Research Journal of Finance and Management,49(1), 159-172. [10] Guris, B. and Traolu M. (2018). The Validity of Purchasing Power Parity in BRICS Countries, Prague Economic Papers, 27(4), 1-10. [11] Gyam , E.N. (2017). Testing the Validity of Purchasing Power Parity in the BRICS: Further Evidence. Euro Economic, 2(35), 1582-8859. [12] James R. Lothian. (2016). Purchasing power parity and the behavior of prices and nominal exchange rates across exchange-rate regimes, Journal of International Money and Finance,69, 5-21. [13] Guo, Z.(2017) Models with short-term variations and long-term dynamics in risk management of commodity derivatives. EconStor Preprints 167619, ZBW - Leibniz Information Centre for Economics. [14] Guo, Z-Y. (2017). GARCH Models with the heavy-tailed Distributions and the Hong Kong Stock Market Returns, International Journal of Business and Management, 12(9). [15] Intaz, A., Subhrabaran, D., Niranjan R. (2016). Stock Market Volatility, Firm Size, and Returns: A Study of Automobile Sector of National Stock Exchange in India, International Journal of Innovative Research and Development, 5(4), 272-281. [16] Liu, H-ChunLiua., Hung, Jui-ch. (2010). Forecasting SandP-100 stock index volatility: The role of volatility asymmetry and distributional assumption in GARCH models, Expert Systems with Applications, 37(7), 4928-4934. [17] Lothian, J.R. Taylor, M.P. (2008). Real exchange rates over the past two centuries: how important is the HarrodBalassaSamuelson effect?, Economic Journal, 118, 1742-1763. [18] Mehrara, M., Tajdini, S. (2020). Comparison of pro tability of speculation in the foreign exchange market and investment in Tehran Stock Exchange during Iran's currency crisis using conditional Sharpe ratio. Advances in Mathematical Finance and Applications, 5(3), 271-284. [19] Nelson, D. B., Cao, C. Q. (1992). Inequality constraints in the univariate GARCH model. Journal of Business and Economic Statistics, 10(3), 229235. [20] Rogoff, K. (1996). Purchasing power parity puzzle. Journal of Economic Literature, 34, 647- 468. [21] Sarkar, S., Banerjee, A. (2006). Modeling daily volatility of the Indian stock market using intra-day data, Indian Institute of Management Calcutta, Working Paper Series, 1- 32. [22] Sarno, L. Taylor, M.P. (2002). Purchasing power parity and the real exchange rate. IMF Staff Papers, 49, 65-105. [23] Smolovi, J.C., Lipovina-Boovi, M Saa Vujoevi . (2017). GARCH models in value at risk estimation: empirical evidence from the Montenegrin stock exchange, Economic Research-Ekonomska Istraivanja, 30(1), 477-498. [24] Stephen A. Ross, Randolph W. Wester eld, Jeffrey Jaffe. (2011). Corporate Finance; CHAP-TER 31 Efficient Capital Markets and Behavioral Challenges. [25] Steven Yee and Miguel D. Ramirez. (2015). Purchasing Power Parity: A Time Series Analysis of the U.S. and Mexico, 1995 - 2007, Department of Econo. [26] Tajdini, S., Hamooni, A., Maghsoudi, J., Jafari, F., Lot Ghahroud, M. (2021). Trade War and the Balanced Trade-Monetary Theory. Journal of Mathematics and Modeling in Finance, Trinity College, Hartford, CT, 06106 USA. [27] Tajdini, S., Mehrara, M., Tehrani, R. (2019). Double-sided balanced conditional Sharpe Ratio, Cogent Economics and Finance, 2019,7(1). [28] Tajdini, S., Mehrara, M., Taiebnia, A. (2021). Investigating the uctuations of exchange rate based on monetarybehaviour approach. International Journal of Finance Economics, 2021, 2021, 10(3)19. [29] Tajdini, S., Mehrara, M. and Tehrani, R. (2021). "Hybrid Balanced Justi ed Treynor ratio",Managerial Finance, 47(1)1, 8697. [30] Taylor, M.P. (1995). The economics of exchange rates. Journal of Economic Literature, 33,13-47. [31] Taylor, M.P. Peel, D.A. (2000). Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals. Journal of International Money and Finance, 19, 33-53. [32] Truong, M. and Ha, T. (2018). Testing the Evidence of Purchasing Power Parity for Southeast Asia Countries. International Econometric Conference of Vietnam, 1061-1077. [33] Wu, J., Bahmani-Oskooee, M. and Chang, T. (2018). Revisiting purchasing power parity in G6 countries: an application of smooth time-varying cointegration approach. Empirica, Volume 45, Issue 1, 187-196. [34] Zayed, N. M., Chowdhury, F. N., and Hasan, K. R. (2018). Testing Balassa-Samuelson model to Examine purchasing power parity (ppp) of Bangladesh with reference to 1972-2016. Academy of Accounting and Financial Studies Journal 22 (1), 1-10. [35] Zhao. L and Zhao. Y. (2018). Purchasing Power Parity and PriceFluctuations in Russia before July 1937. Frontiers of Economics in Russia 13 (3), 458-484, 2018. | ||
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