THE TORQUE COMPARISON OF THE EXTREME DISTRIBUTION MODELS AND THE DIFFERENCE IN THE RATIO OF FAILURE PATTERNS OF DIFFERENT TIME MODELS OF TEHRAN STOCK EXCHANGE
Subject Areas : Financial engineeringAli Rezaian 1 , Hamidreza Vakilifard 2 , Maryam Khalili Araghi 3
1 - Department of Financial Management, Faculty of management and economic, Science and Research Branch, Islamic Azad university, tehran, iran.
2 - Department of Accounting, Faculty of management and economic, Science and Research Branch, Islamic Azad university, tehran, iran.
3 - department of Business Management, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran, Iran
Keywords: Key words: Torque modeling, Extreme risk models, Error Ratio, Block maximum,
Abstract :
THE TORQUE COMPARISON OF THE EXTREME DISTRIBUTION MODELS AND THE DIFFERENCE IN THE RATIO OF FAILURE PATTERNS OF DIFFERENT TIME MODELS OF TEHRAN STOCK EXCHANGEExtreme risk assessment and the use of more efficient risk estimation models in today's financial world are of secondary importance. In this paper, appropriate partial statistical model and the optimal time pattern for estimating a constant and variable periodic risk index in time were selected using the new method of L-Moment torque index for positive and negative extreme values of Tehran Stock Exchange index (maximum block approach) and Estimation of the conditional Extreme risk in different time patterns. The results of the torque study of Extreme distribution models in both positive and negative (minimum and maximum) series showed that the optimal matching model with logarithm of return efficiency of Tehran Stock Exchange are often the GEV model and sometimes the GL model and from among the different time patterns, the daily and weekly pattern at a 90% confidence level, have less estimated errors.Key words: Torque modeling, Extreme risk models, Error Ratio, Block maximum.
راعی، رضا و احمد بنی‌زاده. 1392. آزمون توزیع بازده سهام در بورس اوراق بهادار تهران بین سال‌های 90-1380. فصلنامه راهبرد مدیریت مالی. سال اول، شماره 1، 18-1.
رهنمای رودپشتی، فریدون و سید رضا میرغفاری. 1390. ارزیابی عملکرد پورتفوی در بورس اوراق بهادار تهران: کاربرد ارزش در معرض خطر (Value at Risk). مهندسی مالی و مدیریت اوراق بهادار، دوره 2 شماره 8، 76-51.
زمانی، شیوا، اسلامی بیدگلی، سعید و معین کاظمی. 1392. محاسبه ارزش در معرض ریسک شاخص بورس اوراق بهادار تهران با استفاده از نظریه ارزش فرین. فصلنامه بورس اوراق بهادار، سال ششم، شماره 21، 152-136.
سجاد، رسول، هدایتی، شراره و شهره هدایتی. 1393. برآورد ارزش در معرض خطر با استفاده از نظریه ارزش فرین در بورس اوراق بهادار تهران. دانش سرمایه‌گذاری. دوره 3، شماره 9.
فلاح‌پور، سعید و ثمینه فیض‌اله. 1395. انتخاب پورتفوی سهام با استفاده از وابستگی دنباله پائینی و تئوری مقدار حدی. دانش مالی تحلیل اوراق بهادار، سال 4 شماره 30، 54-33.
فلاح‌پور، سعید و مهدی یاراحمدی. 1391. برآورد ارزش در معرض ریسک با استفاده از تئوری مقدار حدی در بورس اوراق بهادار تهران. مهندسی مالی و مدیریت اوراق بهادار، دوره 4 شماره 13، 122-103.
فلاح شمس، میرفیض و سمیرا غضنفری. 1395. بررسی ریسک نامطلوب (مقدار ارزش حدی) و بازده در بورس اوراق بهادار تهران با رویکرد تئوری ارزش حدی. مهندسی مالی و مدیریت اوراق بهادار (مدیریت پورتفوی). دوره 7 شماره 27، 154-137.
فلاح طلب، حسین و محمدرضا عزیزی. 1393. کاربرد تئوری مقادیر فرین در پیش‌بینی ارزش در معرض ریسک. دانش سرمایه‌گذاری، دوره 3 شماره 12، 180-159.
Assaf, A, (2009). Extreme observations and risk assessment in the equity markets of MENA region: tail measures and Value-at-Risk. Journal of international review of financial analysis. 18 (3), 109-116.
Christoffersen P, Errunza V, Jacobs K, Longlois H (2012). Is the potential for international diversification disappearing? A dynamic copula approach. The Review of financial studies. 25(12), 3711-3751.
Dominicy Y, Ilmonen P, Veredas D. (2015). Multivariate Hill estimators. International statistical Review banner. 85(1), 108-142.
Gency, Ramazan, and Faruk Selcuk (2004). Extreme value theory and Value-at-Risk: Relative performance in emerging markets Ramazan. International Journal of Forecasting 21, 287-303.
Gencay, R., Selcuk, F., (2004). Extreme Value Theory and Value-at-risk: relative performance in emerging markets. International Journal of Forecasting.20 (2), 284-303.
Gettinby, G., Sinclair, C., Power, D., Brown, R., (2006). An analysis of the distribution of extreme share returns in the UK from 1952 to 2000. Journal of Business Finance and Accounting. 31(5-6), 607-646.
Gilli, Manfred and Evis Kellezi. 2006. An Application of Extreme Value Theory for Measuring Financial Risk. Computational Economics, vol. 27, issue 2, 207-228.
Gumbel, E.J. (1954). Statistical theory of extreme values and some practical applications. Applied Mathematics series. 33 (1st ed.). U.S. Department of Commerce, National Bureau of Standards.
Hasan, H. Ahmad Radi, N. F., & Kassim, S. (2012). Modeling the distribution of extreme share return in Malaysia using generalized extreme value (GEV) distribution. The 5th international conference on research and education in mathematics. Volume 1450, 82-89 (2012); doi: 10.1063/1.4724321.
Hosking, J. R., (1990). L-moments: analysis and estimation of distributions using linear combinations of order statistics. Journal of Royal statistical society. 52(1), 105-124.
Hussain, Saiful I. 2016. Modelling Extreme Returns in Chinese Stock Market Using Extreme Value Theory and Copula Approach. PhD Thesis of Actuarial Science. College of Business, Universiti Kebangsaan Malaysia.
Karmakar, M., & Shukla, G, K. (2015). Managing extreme risk in some major stock markets: An extreme values approach. International Review of Economics & Finance, 35, 1-25.
Kelvin, A.K, Mung’atu, J.K., (2016). Extreme Values Modelling of Nairobi Securities Exchange Index. American Journal of Theoretical and Applied Statistics. 5(4), 234-241.
Kittia karasakun, J. & Tse, Y. (2011). Modeling the Fat Tails in Asian Stock Markets. International review of economics and finance, 20(3), 430-440.
Longin, F. M., (1996). The asymptotic distribution of extreme stock market returns. Journal of Business. 69(3), 383-408.
Maghyerch, A. & Al-Zoubi, H. 2006. Value-at-Risk under Extreme Values: The Relative Performance in MENA Emerging Stock Markets. International journal of managerial finance. 154-172.
Matu, S., Balogh, P., Moldovan, D., (2011). The Efficiency of at Risk models on Central and Eastern European stock markets. International journal of mathematics and computers in Simulation. Issue 2, Vol. 5, 110-117.
McNeil A, Frey R. (2000). Estimation of Tail-Related Risk Measures for heteroscedastic financial time series: an extreme value Approach. Journal of Empirical finance. 7(3-4), 271-300.
Minkah, R. 2016. An application of extreme value theory to the management of a hydroelectric dam. Springerplus. 5: 96.
Nortey, Ezekiel N. N., Kwabena Asare, and Felix Okoe Mettle (2015). Extreme value modelling of Ghana stock exchange index. Springerplus 4: 696.
Saiful, IH, Li, S, (2015). Modeling the distribution of extreme returns in the Chinese stock market. Journal of international Financial Markets, institutions and money. 34(2015) 263-276.
Singh, A.K., Robert, P. J., (2013). Extreme market risk and extrene Value theory. Mathematics and computers in Simulation, VOL. 94, 310-328.
Soltane, H.B., Karna, A., Bellah, m. (2012). Conditional VaR using GARCH-EVT approach: forecasting Volatility in Tunisian Financial market. Journal of Computational & modelling, VoL2, no. 2, 95-115.
Tasi M, Chen L. (2011). The calculation of capital requirement using extreme value theory. Economic Modelling. 28(1-2), 390-395.
Tolikas, K., Gettinby, G. D., (2009). Modelling the distribution of the extreme share returns in Singapore. Journal of Empirical Finance. 16(2), 254-263.
Velasco, AAF., Lapuz, Dkp (2018). Extreme value modelling for measuring financial risk with application to selected Philippine stocks. A journal of computational mathematics. 7(3), 404.
_||_
Assaf, A, (2009). Extreme observations and risk assessment in the equity markets of MENA region: tail measures and Value-at-Risk. Journal of international review of financial analysis. 18 (3), 109-116.
Christoffersen P, Errunza V, Jacobs K, Longlois H (2012). Is the potential for international diversification disappearing? A dynamic copula approach. The Review of financial studies. 25(12), 3711-3751.
Dominicy Y, Ilmonen P, Veredas D. (2015). Multivariate Hill estimators. International statistical Review banner. 85(1), 108-142.
Fallah Shams, Mirfaiz and Samira Ghazanfari. 2015. Investigation of adverse risk (limit value value) and returns in Tehran Stock Exchange with the approach of limit value theory. Financial engineering and securities management (portfolio management). Volume 7, No. 27, 154-137.
Fallah Talab, Hossein and Mohammad Reza Azizi. 2013. The application of Frein's value theory in predicting value at risk. Investment Knowledge, Volume 3, Number 12, 159-180.
Fallahpour, Saeed and Mahdi Yarahmadi. 2013. Estimation of value at risk using limit value theory in Tehran Stock Exchange. Financial Engineering and Securities Management, Volume 4, Number 13, 103-122.
Fallahpour, Saeed and Samina Faizolah. 2015. Stock portfolio selection using lower sequence dependence and limit value theory. Financial Knowledge of Securities Analysis, Vol. 4, No. 30, 33-54.
Gencay, R., Selcuk, F., (2004). Extreme Value Theory and Value-at-risk: relative performance in emerging markets. International Journal of Forecasting.20 (2), 284-303.
Gency, Ramazan, and Faruk Selcuk (2004). Extreme value theory and Value-at-Risk: Relative performance in emerging markets Ramazan. International Journal of Forecasting 21, 287-303.
Gettinby, G., Sinclair, C., Power, D., Brown, R., (2006). An analysis of the distribution of extreme share returns in the UK from 1952 to 2000. Journal of Business Finance and Accounting. 31(5-6), 607-646.
Gilli, Manfred and Evis Kellezi. 2006. An Application of Extreme Value Theory for Measuring Financial Risk. Computational Economics, vol. 27, issue 2, 207-228.
Guide by Rudpashti, Fereydoun and Seyyed Reza Mirghafari. 2018. Evaluation of portfolio performance in Tehran Stock Exchange: Application of Value at Risk. Financial Engineering and Securities Management, Volume 2, Number 8, 51-76.
Gumbel, E.J. (1954). Statistical theory of extreme values and some practical applications. Applied Mathematics series. 33 (1st ed.). U.S. Department of Commerce, National Bureau of Standards.
Hasan, H. Ahmad Radi, N. F., & Kassim, S. (2012). Modeling the distribution of extreme share return in Malaysia using generalized extreme value (GEV) distribution. The 5th international conference on research and education in mathematics. Volume 1450, 82-89 (2012); doi: 10.1063/1.4724321.
Hosking, J. R., (1990). L-moments: analysis and estimation of distributions using linear combinations of order statistics. Journal of Royal statistical society. 52(1), 105-124.
Hussain, Saiful I. 2016. Modelling Extreme Returns in Chinese Stock Market Using Extreme Value Theory and Copula Approach. PhD Thesis of Actuarial Science. College of Business, Universiti Kebangsaan Malaysia.
Karmakar, M., & Shukla, G, K. (2015). Managing extreme risk in some major stock markets: An extreme values approach. International Review of Economics & Finance, 35, 1-25.
Kelvin, A.K, Mung’atu, J.K., (2016). Extreme Values Modelling of Nairobi Securities Exchange Index. American Journal of Theoretical and Applied Statistics. 5(4), 234-241.
Kittia karasakun, J. & Tse, Y. (2011). Modeling the Fat Tails in Asian Stock Markets. International review of economics and finance, 20(3), 430-440.
Longin, F. M., (1996). The asymptotic distribution of extreme stock market returns. Journal of Business. 69(3), 383-408.
Maghyerch, A. & Al-Zoubi, H. 2006. Value-at-Risk under Extreme Values: The Relative Performance in MENA Emerging Stock Markets. International journal of managerial finance. 154-172.
Matu, S., Balogh, P., Moldovan, D., (2011). The Efficiency of at Risk models on Central and Eastern European stock markets. International journal of mathematics and computers in Simulation. Issue 2, Vol. 5, 110-117.
McNeil A, Frey R. (2000). Estimation of Tail-Related Risk Measures for heteroscedastic financial time series: an extreme value Approach. Journal of Empirical finance. 7(3-4), 271-300.
Minkah, R. 2016. An application of extreme value theory to the management of a hydroelectric dam. Springerplus. 5: 96.
Nortey, Ezekiel N. N., Kwabena Asare, and Felix Okoe Mettle (2015). Extreme value modelling of Ghana stock exchange index. Springerplus 4: 696.
Rai, Reza and Ahmed Banizadeh. 2013. Test of distribution of stock returns in Tehran Stock Exchange between 2010-2019. Financial Management Strategy Quarterly. First Year, No. 1, 1-18.
Saiful, IH, Li, S, (2015). Modeling the distribution of extreme returns in the Chinese stock market. Journal of international Financial Markets, institutions and money. 34(2015) 263-276.
Sajjad, Rasool, Hedayati, Sharara and Shahreh Hedayati. 2014. Estimation of value at risk using Ferin's value theory in Tehran Stock Exchange. Investment knowledge. Volume 3, Number 9.
Singh, A.K., Robert, P. J., (2013). Extreme market risk and extrene Value theory. Mathematics and computers in Simulation, VOL. 94, 310-328.
Soltane, H.B., Karna, A., Bellah, m. (2012). Conditional VaR using GARCH-EVT approach: forecasting Volatility in Tunisian Financial market. Journal of Computational & modelling, VoL2, no. 2, 95-115.
Tasi M, Chen L. (2011). The calculation of capital requirement using extreme value theory. Economic Modelling. 28(1-2), 390-395.
Tolikas, K., Gettinby, G. D., (2009). Modelling the distribution of the extreme share returns in Singapore. Journal of Empirical Finance. 16(2), 254-263.
Velasco, AAF., Lapuz, Dkp (2018). Extreme value modelling for measuring financial risk with application to selected Philippine stocks. A journal of computational mathematics. 7(3), 404.
Zamani, Shiva, Islami Bidgoli, Saeed and Moin Kazemi. 2012. Calculation of value at risk index of Tehran Stock Exchange using Frein's value theory. Stock Exchange Quarterly, Year 6, Number 21, 152-136.
