* زمانی، شیوا, اسلامی، بیدگلی، سعید, کاظمی، معین. (1392). محاسبه ارزش در معرض ریسک شاخص بورس اوراق بهادار تهران با استفاده از نظریه ارزش فرین، فصل نامه بورس اوراق بهادار.6(21)، 115-136.
* سارنج، علیرضا، نوراحمدی، مرضیه. (1395). تخمین ارزش در معرض ریسک (VaR) و ریزش مورد انتظار (ES) استفاده از رویکرد ارزش فرین شرطی در بورس اوراق بهادار تهران. مجله تحقیقات مالی، 3(18)،437-460.
* لطفعلی پور، محمدرضا، نصرتی، مهدیه، قدیری مقدم، ابوالفضل، فیلسرایی، مهدی. (1396). اندازهگیری ارزش در معرض ریسک شرطی پرتفوی با روش FIGARCH-EVTدر بورس اوراق بهادار تهران. 8(31)، 281-295.
* Acerbi, C., & Tasche, D. (2002). Expected shortfall: a natural coherent alternative to value at risk. Economic notes, 31(2), 379-388.
* Ayusuk, A. and Sriboonchitta, S., (2016) Copula Based Volatility Models and Extreme Value Theory for Portfolio Simulation with an Application to Asian Stock Markets. In Causal Inference in Econometrics, 14(2), 279-293.
* Balkema, A. A., & De Haan, L. (1974). Residual life time at great age. The Annals of probability, 792-804.
* Chrétien, S., Coggins, F., & Trudel, Y. (2010). Performance of monthly multivariate filtered historical simulation value-at-risk. Journal of Risk Management in Financial Institutions, 3(3): 259-277.
* Christoffersen, P. F. (1998). “Evaluating interval forecasts”. International economic review, 841-862.
* Fisher, R. A., & Tippett, L. H. (1928). Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proceeding of Cambridge Philosophical Society, 24, 180-190.
* Gelper, S., Fried, R., & Croux, C. (2010). Robust forecasting with exponential and Holt–Winters smoothing. Journal of forecasting, 29(3), 285-300.
* Gencay, R., & Selcuk, F. (2004). Extreme value theory and Value-at-Risk: Relative performance in emerging markets. International Journal of Forecasting, 20(2), 287-303.
* Gilli, M. (2006). An application of extreme value theory for measuring financial risk. Computational Economics, 27(2-3), 207-228.
* Haan, L., Jansen, D. W., Koedijk, K., & de Vries, C. G. (1994). Safety first portfolio selection, extreme value theory and long run asset risks. In Extreme value theory and applications. Springer US, 471-487.
* Jansen, D. W., & De Vries, C. G. (1991). On the frequency of large stock returns: Putting booms and busts into perspective. The review of economics and statistics, 18-24.
* 15.Karmakar, M. (2017). Dependence structure and portfolio risk in Indian foreign exchange market: A GARCH-EVT-Copula approach. The Quarterly Review of Economics and Finance, 64, 275-291.
* Karmakar, M., & Paul, S. (2016). Intraday risk management in International stock markets: A conditional EVT approach. International Review of Financial Analysis, 44, 34-55.
* Kupiec, P. H. (1995). “Techniques for verifying the accuracy of risk measurement models”. The J. of Derivatives, 3(2).
* Lopez, J. A. (1999). Methods for evaluating value-at-risk estimates. Economic Review-Federal Reserve Bank of San Francisco, (2), 3.
* Messaoud, S. B., & Aloui, C. (2015). Measuring Risk of Portfolio: GARCH-Copula Model. Journal of Economic Integration, 172-205.
* Nortey, E. N., Asare, K., & Mettle, F. O. (2015). Extreme value modelling of Ghana stock exchange index. SpringerPlus, 4(1), 696.
* Singh, A. K., Allen, D. E., & Powell, R. J. (2011). Value at risk estimation using extreme value theory.
* Soltane, H. B., Karaa, A., & Bellalah, M. (2012). Conditional VaR Using GARCH-EVT Approach: Forecasting Volatility in Tunisian Financial Market. Journal of Computations & Modelling, 2(2), 95-115.
* Youssef, M., Belkacem, L., & Mokni, K. (2015). Value-at-Risk estimation of energy commodities: A long-memory GARCH–EVT approach. Energy Economics, 51, 99-110