- آذر، عادل. مؤمنی، منصور. (1386). آمار و کاربرد آن در مدیریت، تهران، سازمان مطالعه و تدوین کتب علوم انسانی دانشگاهها (سمت).
- ابریشمی، حمید. بهرادمهر، نفسیه. سیفی، طاهره. (1392). "پیشبینی قیمت نفت خام با استفاده از تبدیل موجک، مدلهای غیرخطی و مدلهای خطی". فصلنامه مطالعات اقتصادی کاربردی ایران، 2(7)، صص 41-62.
- ادبی فیروز جایی، باقر. مهر آرا، محسن. محمدی، شاپور. (1395). "پیشبینی و ارزیابی ارزش در معرض ریسک یک گام به جلو بورس اوراق بهادار تهران با استفاده از روش شبیهسازی زنجیره مارکف مونتکارلو(MCMC) ". مهندسی مالی و مدیریت اوراق بهادار، 7(26)، صص. 101-122.
- طبسی، ملیحه. فلاحپور، سعید. (1392). "برآورد ارزش در معرض ریسک با استفاده از مدل ترکیبی ماشین بردار پشتیبان و گارچ". راهبرد مدیریت مالی، (1)1، صص. 90-109.
- کیانی، طاهره. فرید، داریوش. صادقی، حجتالله. (1394). "اندازهگیری ریسک با معیار سنجش ارزش در معرض ریسک (VaR)، از طریق مدل GARCH (مطالعهای در سهام شرکتهای پذیرفتهشده در بورس اوراق بهادار تهران در صنعت سیمان)". راهبرد مدیریت مالی، 3(3)، صص. 149-168.
- Abrishami, H., Behradmehr, N., & Seyfi, T. (2013). “Forecasting of Crude Oil Price by Using Wavelet Transform, Non-Linear and Linear Models”. Journal of Applied Economics Studies in Iran, 2(7), pp.41-62. (in Persian).
- Adabi, B. Mehr Ara, M. & Mohammadi, Sh. (2016). “Prediction and assessment of value at risk is a step forward Stock Exchange Tehran Markov chain Monte Carlo simulation method. (MCMC)”. Journal of Financial engineering and management of securities, 7(26), pp.101-122. (in Persian).
- Azar, A. & Momeni, M. (2009). Statistics and Its Application in Management, Tehran, The Organization for Researching and Comoposing University Textbook in the Humanities. (in Persian).
- Kiani, T., Fareed, D., & Sadeghi, H. (2015). “The Measurement of Risk based on the Criterion of Value at Risk via Model of GARCH (A Study of Stock of Listed Companies in Tehran Stock Exchange (TSE) in the Cement Industry)”. Financial Management Strategy, 3(3), pp.149-168. (in Persian).
- Aloui, C., & Mabrouk, S. (2010). “Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models”. Energy Policy, 38(5), pp.2326-2339.
- Blanco, C., & Ihle, G.(1999). “How good is your VaR? Using backtesting to assess system performance”. Financial Engineering News, 11, pp.1-2.
-Best, P. (2000). Implementing value at risk. John Wiley & Sons.
- Bollerslev, T. (1986). “Generalized autoregressive conditional heteroskedasticity”. Journal of econometrics, 31(3), pp.307-327.
- 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), pp.259-277.
- Christoffersen, P. F. (1998). “Evaluating interval forecasts”. International economic review, 2(1), pp.841-862.
- Croux, C., Gelper, S., & Mahieu, K. (2011). “Robust control charts for time series data”. Expert Systems with Applications, 38(11), pp.13810-13815.
-Damodaran, A. (2010). Applied corporate finance. John Wiley & Sons.
- Gelper, S., Fried, R. and Croux, C. (2010), “Robust forecasting with exponential and Holt–Winters smoothing”. Journal of Forecast, 29(2), pp.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), pp.287-303.
- Gregoriou, G. N. (Ed.). (2009). “The VaR Implementation Handbook: Financial Risk and Applications in Asset Management, Measurement and Modeling”. Risk Measures and Their Applications in Asset Management. 32(6), pp.243-264.
- Holt, C. (1959). “Forecasting seasonals and trends by exponentially weighted moving averages”. ONR ResearchMemorandum, 4(1), pp.1-11.
- Kalekar, P. S. (2004). “Time series forecasting using holt-winters exponential smoothing”. Kanwal Rekhi School of Information Technology, pp.1-13.
- Kupiec, P. H. (1995). “Techniques for verifying the accuracy of risk measurement models”. The J. of Derivatives, 3(2), pp.10-19.
- Lopez, J. A. (1999). “Methods for evaluating value-at-risk estimates”. Economic Review-Federal Reserve Bank of San Francisco, (2), pp.3-12.
- Mabrouk, S. (2016). “Forecasting daily conditional volatility and h-step-ahead short and long Value-at-Risk accuracy: Evidence from financial data”. The Journal of Finance and Data Science, 2(2), pp.136-151.
Marimoutou, V., Raggad, B., & Trabelsi, A. (2009). “Extreme value theory and value at risk: application to oil market”. Energy Economics, 31(4), pp.519-530.
- Niguez, T. M. (2008). “Volatility and VaR forecasting in the Madrid stock exchange”. Spanish Economic Review, 10(3), pp.169-196.
- Phillips, P. C., & Perron, P. (1988). “Testing for a unit root in time series regression”. Biometrika, 75(2), pp.335-346.
- Sudheer & Suseelatha, A. (2015). “Short term load forecasting using wavelet transform combined with Holt–Winters and weighted nearest neighbor models”. International Journal of Electrical Power & Energy Systems, 64, pp.340-346.
- Tabasi, M., & Fallahpoor, S. (2014). “Evaluating Value at Risk Using a Hybrid Model of Support Vector Machine Based and the GARCH”. Financial Management Strategy, 1(1), pp.90-109. (in Persian).
- Tratar, L. F., & Strmčnik, E. (2016). “The comparison of Holt–Winters method and Multiple regression method: A case study”. Energy, 109, pp. 266-276.
- Winters, P. R. (1960). “Forecasting sales by exponentially weighted moving averages”. Management Science, 6(3), pp.324-342.
- Wu, L., Liu, S., & Yang, Y. (2016). “Grey double exponential smoothing model and its application on pig price forecasting in China”. Applied Soft Computing, 39, pp.117-123.