The Designing Early Warning System of Financial Crisis Outbreak in Tehran Stock Exchange by Logit & Probit Model

Subject Areas : Financial Knowledge of Securities Analysis

alireza gholizadeh ¹ , Mir Feiz Fallah Shams ² , Mohammad Ali Afshar Kazemi ³

1 - Ph.D. Student in Financial Management, Department of Financial Management, Islamic Azad University, Tehran-Central Branch, Tehran, Iran
2 - Associate Professor Department of Financial Management, Tehran Central Branch, Islamic Azad University, Tehran, Iran
3 - Associate Professor of Financial Management Department, Tehran Central Branch Islamic Azad

Received: 2021-05-04 Accepted : 2021-05-04 Published : 2021-02-19

Keywords: Financial Crisis, Early Warning System, price index, exchange rate, Global Gold Price, oil price,

Abstract :

Encountering with financial crises of supervision and predicting such these events which are necessary to decrease their negative effects on finanicial and economical markets. The current paper is aimed to review the designing the early warning system of financial crisis outbreak in Tehran stock Exchange. Due to this purpose, it’s used the weekly datas during the years from 1997 to 2019 (1121 weeks). The mean of crises in this present papper is the falling more than 15% of price index (TEPIX) toward last three months. Hence, it’s been used the dummy variable for operating the dependent variable. It’s been used the residual of auto regressive integrated moving average (ARIMA) for measuring the shocks caused by the price of stocks, exchange rate, price of oil and gold. The result is modeled by Logit & Probit model and showed that probability of the crisis outbreak is increased by decreasing the stock price in past period as well as the outbreaking of crisis in past period after reviewing and analyzing the data. While the decreasing of exchange rate, increasing of the gold price, and decreasing of oil price don’t affect on crisis outbreak in current periods as meaningfully. Based on weekly data, 44 crisis has occurred which both models have predicted 36 crisis. The power of crisis predicting is 82% and the power of predicting for total model is about 99%.

References:

*      احمدیان، اعظم(1394)، «طراحی سیستم هشدار سریع جهت پیش بینی زمان در معرض ورشکستگی قرار گرفتن بانک‌ها»، فصلنامه علمی پژوهشی نظریه‌های کاربردی اقتصاد، دوره 2، شماره 4، زمستان 1394.

*      درخشان، مسعود  (1387)، ماهیت و علل بحران مالی 2008 و تاثیر آن بر اقتصاد ایران، مرکز تحقیقات استراتژیک مجمع تشخیص مصلحت نظام، پژوهشنامه شماره 9.

*      رحیمی باغی، علی و همکاران (1397)،" تعیین تاریخ وقوع بحرانهای مالی شکل گرفته در بورساوراق بهادار تهران به شیوهای مستقیم با تأکید بر عامل تورم" 44 - فصلنامه حسابداری مالی/سال دهم/ شماره 73 /بهار 1397.

*      زارعی، ژاله و کمیجانی، اکبر(1394). « شناسایی و پیش بینی بحران های بانکی در ایران » فصلنامه مدل سازی اقتصادی، سال نهم، شماره1، بهار 1394.

*      سوری، علی،  اقتصاد سنجی همراه با کاربرد ایویوز، جلد 2، انتشارات فرهنگ شناسی، چاپ ششم،  1396، صص 1178-1211.

*      صارم، مهدی(1389)، " بحران مالی در جهان: دلایل و نتایج وقوع آن" تازه های اقتصاد، سال هشتم، شماره 129.

*      صیادنیا طیبی، عزت اله و همکاران(1391)، « تبیین یک سیستم هشداردهنده جهت شناسایی بحرانهای مالی در ایران» فصلنامه پول و اقتصاد، شماره 6، زمستان 13، ص 169-211.

*      ﮐﺮﯾﻢزاده، ﻣﺼﻄﻔﯽ (1385)، »ﺑﺮرﺳﯽ راﺑﻄﻪ ﺑﻠﻨﺪ ﻣﺪت ﺷﺎﺧﺺ ﻗﯿﻤﺖ ﺳﻬﺎم ﺑﻮرس ﺑﺎ ﻣﺘﻐﯿﺮﻫﺎی ﮐﻼن ﭘﻮﻟﯽ ﺑﺎ اﺳﺘﻔﺎده از روش ﻫﻢ ﺟﻤﻌﯽ در اﻗﺘﺼﺎد اﯾﺮان«، ﻓﺼﻠﻨﺎﻣﻪ ﭘﮋوﻫﺶﻫﺎی اﻗﺘﺼﺎدی، 8(26).

*      نادری، مرتضی (1382)، "ارائه سیستم هشدار پیش از موعد برای بحران های مالی دراقتصاد ایران" فصلنامه پژوهش های اقتصادی ایران / شماره 17 / زمستان 1382.

*      نادمی، یونس و همکاران(1394)، " ارائه یک الگوی هشدار پیش از وقوع نوسانات شدید در بازار سهام تهران: رویکرد مارکوف سوئیچینگ گارچ " فصلنامه علمی پژوهشی دانش مالی تحلیل اوراق بهادار سال هشتم، شماره بیست و هشتم زمستان 1394.

*      نصراللهی، محمد و همکاران(1396)، " طراحی یک سیستم هشدار زودهنگام  بحران های ارزی در ایران: رویکرد رگرسیون لجستیک" ، تحقیقات اقتصادی / دوره 52 ، شمارة 1، بهار 96.

*      نعمتی، محمد و سلیمانی، محمد، بحران مالی 2008: ریشه ها، پیامد ها و راهکارها،انتشارات دانشگاه امام صادق، چاپ اول،1390، ص 317.

*      Acar,M. Karahoca,D. Karahoca,A. Designing an Early Warning System for Stock Market Crashes by Using ANFIS. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

*      Ahn, J, JooK Oh, K, Kim, T, Kim, D, 2011. Usefulness of support vector machine to develop an early warning system for financial crisis. J. Expert Systems with Applications 38(2011) 2966-2973.

*      Akbar, M & et al., 2019. Bayesian analysis of dynamic linkages among gold price, stock prices, exchange rate and interest rate in Pakistan. Resources Policy 62 (2019) 154–164.

*      Berg, A. and C. Pattillo. (1999a). Predicting Currency Crises: The Indicator Approach and an Alternative. Journal of International Money and Finance, August, PP. 561-586.

*      Bussiere, M, Fratzscher, M, 2002. Towards a new early warning system of financial crises. European central bank Working paper no. 145.

*      Caggiano, G, Calice, P, Leonida, L, 2014. Early warning systems and systemic banking crises in low income countries: A multinomial logit approach. Journal of Banking & Finance 47(2014) 258-269.

*      Candelon,­B., ­Dumitrescu,­E.-I.,­Hurlin,­C.,­2014.­Currency­ crises early arning systems: why they should be dynamic. Int. J. Forecast. 30, 1016–1029.

*      Chatzis a,S.P, et al, 2018. Forecasting stock market crisis events using deep and statistical machine learning techniques. Expert Systems With Applications 112 (2018) 353–371.

*      Claessens, S. & Kose, M. A, 2013, Financial Crises: Explanations, Types, and Implications, IMF Working Paper, No WP/13/28.

*      Fonseca, E. Ferreira, F. Muruganandam, P. Cerdeira, H. Identifying financial crises in real time.

*      Galbraith, J. The Great Crash 1929, 1988 edition, Houghton Mifflin Co. Boston, p.xii-xvi.

*      Gresnigt, F, Kole, E, Franses, PH, 2015. Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes. Journal of Banking & Finance 56(2015) 123-139.

*      Huang,Y, Kou, G, Peng, Y, 2017. Nonlinear manifold learning for early warnings in financial markets. J. European Journal of Operational Research 258(2017) 692-702.

*      Jain, A., Biswal, P.C., 2016. Dynamic linkages among oil price, gold price, exchange rate, and stock market in India. Resour. Pol. 49, 179–185.

*      Levy, M, 2008. Stock market crashes as social phase transitions. Journal of Economic Dynamics & Control 32 (2008) 137–155.

*      Kaminsky, G. and Lizondo, S., and M. Reinhart. (1998). Leading Indicator of Currency Crises. IMF Staff Papers, 45(1998), PP. 1-48.

*      Kaminsky, G.L. and Reinhart C.M, 1996. The Twin Crisis: The causes of Banking and Balance-of-Payments Problems. International Financial Discussion Paper, No.544(1996), Washington: Board of Governors of the Federal Reserve System.

*      Kindleberger , Charles P. & Aliber, R. (2005), Manias, Panics, and Crashes: A History of Financial Crises, 5th ed. Wiley, ISBN 0471467146.

*      Klopotan,L & et al, 2018. Early warning system in business, finance, and economics: Bibliometric and topic analysis, International Journal of Engineering Business Management, Volume 10: 1–12.

*      Kocaarslana,B.& et al., 2017.  Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets. Journal of Commodity Markets 7 (2017) 41–56.

*      Olbrys, J., and E. Majewska. (2014). Direct identification of crisis periods on the CEE stock markets: the influence of the 2007 U.S.

*      Raza, N., Shahzad, S.J.H., Tiwari, A.K., Shahbaz, M., 2016. Asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. Resour. Pol. 49, 290–301.

*      Neaime, S, 2016. "Financial crises and contagion vulnerability of MENA stock markets," Emerging Markets Review, Elsevier, vol. 27(C), pages 14-35.

*      Shein Lin, CH & et al. A new approach to modeling early warning systems for currency crises: Can a machine-learning fuzzy expert system predict the currency crises effectively?. Journal of International Money and FinanceVolume 27, Issue 7, November 2008, Pages 1098-1121.

*      Waidyanatha, Nuwan (2010). "Towards a typology of integrated functional early warning systems". International Journal of Critical Infrastructures. No 1. 6: 31–51.

*      Xuan Li, W, Sheng Chen, C, French, J, 2015. Toward an early warning system of financial crises: What can index futures and options tell us?. The Quarterly Review of Economics and Finance 55(2015) 87-99.

*      Zhang,R Xian,X Fang,H, 2019. The early warning system of stock market crises with investor sentiment: Evidence from China.wileyonlinelibrary.com/journal/ijfe, Int J Fin Econ. 2019;24:361–369.