Ranking of exchange-traded funds (ETF) And value at risk approach (EVT) based on value-generating theory (VaR) risk approach

Subject Areas : Financial Knowledge of Securities Analysis

Gholamreza Zomorodian ¹ , Maryam Sohrabi ²

1 - Assistant Professor and Faculty Member of Faculty of Management, Islamic Azad University, Central Tehran Branch, Commercial Management Department, Tehran, Iran
2 - P.HD. Student, Financial engineering, Department of Management, Rasht Branch, Islamic Azad University Rasht, Iran

Received: 2017-12-24 Accepted : 2018-07-06 Published : 2019-12-22

Keywords: exchange-traded fund, Sharp Ratio, Value at risk, Extreme -Value Theory,

Abstract :

Given the importance of exchange-traded funds and their ever-increasing advancement in financial markets, it is important to review and explain their ranking based on criteria beyond the examination of returns. Also, considering that broad distribution sequences in financial data are of particular importance in measuring financial risk, in this study, based on criteria beyond the efficiency and considering the value of risk, based on the Extreme -Value Theory (EVT) and the modified Sharpe Ratio, the rating of exchange-traded funds has been dealt with. Then evaluation their models with different back testing such as Kupiec test, Christoffersen test. For the purpose of this study, the first period of September 2014 until the end of September 2017 was considered for the funds that were active in the capital market during this period. The results indicate the proper capabilities of VaR models which is based on GHARCH-EVT approach.

References:

*      زمردیان، غلامرضا (1394)، "مقایسه توان تبیین مدل‌های پارآمتریک (اقتصادسنجی) و ناپارآمتریک (مونت کارلو) در سنجش میزان ارزش درمعرض خطر پرتفوی شرکت‌های سرمایه‌گذاری جهت تعیین پرتفوی بهینه در بازار سرمایه ایران"، مجله مهندسی مالی و مدیریت اوراق بهادار، دوره 6،  بهار 1394 ، شماره بیست و دوم، صص: 164-147.

*      زمردیان، غلامرضا (1394)، "مقایسه توان تبیین مدل‌های ناپارآمتریک و مدل‌های شبکه عصبی در سنجش میزان ارزش در معرض خطر پرتفوی شرکت‌های سرمایه‌گذاری جهت تعیین پرتفوی بهینه در بازار سرمایه ایران"، مجله مهندسی مالی و مدیریت اوراق بهادار، پاییز 1394، دوره 6، شماره 24،  صص: 90-73. 

*      سجاد، رسول؛  شهره هدایتی؛ شراره هدایتی (1393)، "برآورد ارزش در معرض خطر با استفاده از نظریه ارزش فرین در بورس اوراق بهادار تهران"، فصلنامه دانش سرمایه‌گذاری، بهار 1393، دوره 3، شماره 9، صص:156-133.

*      کشاورز حداد، غلامرضا؛ حیرانی، مهرداد؛ (1393)، "برآورد ارزش در معرض ریسک با وجود ساختار وابستگی در بازدهی بازارهای مالی: رهیافت توابع کاپولا"، مجله تحقیقات اقتصادی، زمستان 1393، دوره 49، شماره 4، صص: 869-902

*      Aloui, C., Mabrouk, S., 2010. Value-at-risk estimations of energy commodities via longmemory, asymmetry and fat-tailed GARCH models. Energy Policy 38, 2326–2339.

*      Arouri, M., Lahiani, A., Lévy, A., Nguyen, D.K., 2012b. Forecasting the conditional volatility of oil spot and futures prices with structural breaks and longmemory models. Energy Econ. 34 (1), 283–293.

*      Baillie, R., Bollerslev, T., Mikkelsen, H., 1996. Fractionally integrated generalized autoregressive conditional heteroskedasticity. J. Econ. 74, 3–30.

*      Basel Committee on Banking Supervision, 1996. Supervisory framework for the use of “backtesting” in conjunction with the internal model-based approach to market risk capital requirements. Bank for International Settlements, Basel, Switzerland.

*      Basel Committee on Banking Supervision, 2004. International Convergence of Capital Measurement and Capital Standards. Bank for International Settlements, Basel,Switzerland.

*      Baur, D.G., McDermott, T.K., 2010. Is gold a safe haven? International evidence. J. Bank. Finance34, 1886–1898.

*      Bollerslev, T., 1986. Generalized autoregressive conditional heteroskedasticity. J. Econ. 31,307–327.

*      Browne, F., Cronin, D., 2010. Commodity prices, money and inflation. J. Econ. Bus. 62, 331–345.

*      Engle, R.F., 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of UK inflation. Econometrica 50, 987–1008.

*      Engle, R.F., Bollerslev, T., 1986. Modelling the persistence of conditional variances. Econ. Rev. 5, 1–50.

*      Aas, K., & Berg, D. (2009). Models for construction of multivariate dependence a comparison study. European Journal of Finance, 15(7–8), 639–659.

*      Embrechts, P., Lindskog, F., & McNeil, A. (2003). 8 modelling dependence with copulas and applications to risk management. In S. T. Rachev (Ed.), Handbook of heavy tailed distribution in finance (pp. 329–384). Elsevier.

*      Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.

*      Frees, E.W., Carriere, J., & Valdez, E. (1996). Annuity valuation with dependent mortality. The Journal of Risk and Insurance, 63(2), 229–261.

*      Laurent Favre and Jose-Antonio Galeano. Mean-Modified Value-at-Risk Optimization with Hedge Funds. Journal of Alternative Investment, Fall 2002, v 5.

*      Shivangi Agarwal, Nawazish Mirza(2017) A study on the risk-adjusted performance of mutual funds industry in India. Review of Innovation and Competitiveness, V3, i1

*      Arora, Kavita (2015). Risk-Adjusted Performance Evaluation of Indian Mutual Fund Schemes. SAGE Publications 19.1: 79-94.

*      Patel, Mahesh K and Kalpesh P. Prajapati.(2012), Comparative Study On Performance Evaluation of Mutual Fund Schemes Of Indian Companies, Researchers world, Journal of Arts, Science & Commerce Vol-III, Issue3(3),: 47-59