Financial risk assessment based on Extreme Value Theory and instantaneous data of Tehran Stock Exchange Index

Subject Areas : Journal of Investment Knowledge

Mehrdokht Mozaffari ¹ , Hashem Nikoomaram ²

1 - PHD.Student in Financial Management,Accounting Department,Science and Research Branch,Islamic Azad University,Tehran,Iran,
2 - Professor,Accounting Department,Science and Research Branch,Islamic Azad University,Tehran,

Received: 2017-12-01 Accepted : 2018-02-10 Published : 2019-12-22

Keywords: risk management, Value at risk, Extreme Value Theory, E-GARCH Model, Block Maxima Method,

Abstract :

Value at Risk is one of the most important criteria in financial markets for risk assessment. Various methods have been proposed for measuring this index. Extreme Value Theory is one of the new methods for calculating the value at risk that focuses on Distribution sequence of series, and instead of taking all data into account without considering the limiting assumptions such as the assumption of normalization. In this research, the logarithmic return of Tehran Stock Exchange index based on the data received during the time intervals of the day (due to the use of high frequency data) during the years 1392 to 1395 was summed up and the Block Maxima Approach was used in VaR measurement. Given the correlation between the variance and the time series of the data, the problem was first solved using the E-GARCH model. Then VaR index was calculated in three blocking conditions based on hourly, daily and monthly data. The results showed that the use of monthly data in calculating this index has a higher predictive accuracy.

References:

*       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.

*       سارنج، علیرضا و مرضیه نوراحمدی، 1396، رتبه بندی آماری مدلهای مختلف ارزش در معرض ریسک و ریزش مورد انتظار با استفاده از رویکرد مجموعه اطمینان مدل (MCS) برای صنعت بانکداری با تاکید بر رویکرد ارزش فرین شرطی، مهندسی مالی و مدیریت اوراق بهادار، دوره 8، شماره 30، 131-146.

*       عبده تبریزی، حسین و میثم رادپور، 1388. اندازه گیری و مدیریت ریسک بازار: رویکرد ارزش در معرض ریسک.تهران: پیشبرد.

*       کیانی، طاهره، فرید، داریوش و صادقی، حجت الله، (1393)، اندازه گیری ریسک با معیار ارزش در معرض ریسک از طریق مدل GARCH در صنعت سیمان، مدیریت مالی، انتشارات دانشگاه الزهرا، سال سوم، شماره دهم، صص 149-168.

*       هال، جان، 1384، مبانی مهندسی مالی و مدیریت ریسک، ترجمه سجاد سیاح و علی صالح، تهران، گروه رایانه تدبیرپرداز.

*       Black, F., Litterman, R.B., 1992. Global portfolio optimization. Financial Analysts Journal 48, 28–43.

*       Chan, N. H., S. Deng, L. Peng, and Z. Xia (2007). Interval estimation of Value-at-Risk based on GARCH models with heavy–tailed innovations. Journal of Econometrics 137,556–576.

*       Fernandez, Viviana,2003, Extreme Value Theory: Value at Risk and Returns Dependence Around the World. Http://www.dii unhile.cl/-ceges/publicaciones/

*       French K. R., Schwert G. W., and Staumbaugh R. F., (1987). "Expected Stock Returns and Volatility", Journal of Financial Economics, Vol. 19,pp. 3-29.

*       Fisher, R., Tippet, L. (1928) ‘Limiting forms of the frequency distribution of the largest or smallest member of a sample’, Proceedings of the Cambridge Philosophical Society, pp. 180-190.

*       Gilli,Manfred and Evis Kellezi,2006.An Application of Extreme  Value Theory for Measuring Financial Risk.Computational Economics,vol 27,issue 2,207-228.

*       Huiyu Huang  and Tae-Hwy Lee,(2013), Forecasting Value-at-Risk Using High-Frequency Information, Econometrics 2013, 01, 127-140; doi:10.3390/econometrics1010127.

*       Karmakar, M. & Shukla G. K. (2015). Managing extreme risk in some major stock markets: An extreme value approach. International Review of Economics and Finance,35, 1-25.

*       Liu, Yifang,2007.Measuring Financial Risk and External Dependence between Financial Markets in Taiwan. Economic theses. College of Social Science, National Chengchi University.Taipei,Taiwan.

*       Marimoutou, V. & Raggad, B. & Trabelsi, A. (2009). “Extreme Value Theory and Value at Risk: Application to Oil Market”. Energy Economics , 519-530.

*       Madhusudan Karmakar, Samit Paul.(2015), Intraday Value-at-Risk and Expected Shortfall using high frequency data inInternational stock markets: A conditional EVT approach, International Review of Financial Analysis, FINANA 917.

*       Marco Bee, Debbie J. Dupuis, Luca Trapin,(2016), Realizing the extremes: Estimation of tail-risk measures from a highfrequency perspective, Journal of Empirical Finance, EMPFIN 863.

*      Nelson, D.B. (1991). Conditional heteroscadasticity in asset returns: a new approach,Econometrica, 59(2), 347-70.