Almeida, R.J. & U. Kaymak. (2009). Probabilistic Fuzzy Systems in Value‐At‐Risk Estimation. Intelligent Systems in Accounting, Finance and Management, 16(1‐2): 49-70. ##Balthazar, L. (2006). From Basel 1 to Basel 3. In From Basel 1 to Basel 3: The Integration of State-of-the-Art Risk Modeling in Banking Regulation (pp. 209-213). Palgrave Macmillan UK. ##Daníelsson, J. (2011). Financial risk forecasting: the theory and practice of forecasting market risk with implementation in R and Matlab (Vol. 588). John Wiley & Sons. ##De Cooman, G. (1997). Possibility Theory I: the Measure-and integral-Theoretic Groundwork. International Journal of General Systems, 25(4): 291-323. ##Dubois, D. & H. Prade. (2012). Possibility Theory: An Approach to Computerized Processing of Uncertainty. Springer Science & Business Media. ##Embrechts, P., A. McNeil & D. Straumann. (2002). Correlation and Dependence in Risk Management: Properties and Pitfalls. Risk Management: Value at Risk and Beyond, 176-223. ##Fama, E.F. (1965). The Behavior of Stock-Market Prices. The journal of Business, 38(1): 34-105. ##Gupta, P., M.K. Mehlawat, M. Inuiguchi & S. Chandra. (2014). Fuzzy Portfolio Optimization. Studies in Fuzziness and Soft Computing, 316. ##Heyde, C.C. (1999). A Risky Asset Model with Strong Dependence Through Fractal Activity Time. Journal of Applied Probability, 1234-1239. ##Hosking, J., G. Bonti & D. Siegel. (2000). Beyond the Lognormal. RISK-London-Risk Magazine Limited-, 13(5): 59-62. ##Huang, C. & C. Moraga. (2002). A Fuzzy Risk Model and Its Matrix Algorithm. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(04): 347-362. ##Huang, X. (2010). What Is Portfolio Analysis. In Portfolio Analysis (pp. 1-9). Springer Berlin Heidelberg. ##Katagiri, H., T. Uno, K. Kato, H. Tsuda & H. Tsubaki. (2014). Random Fuzzy Bilevel Linear Programming Through Possibility-Based Value at Risk Model. International Journal of Machine Learning and Cybernetics, 5(2): 211-224. ##Kaufman, A. & M.M. Gupta. (1991). Introduction to Fuzzy Arithmetic. Van Nostrand Reinhold Company. ##Klir, G. & B. Yuan. (1995). Fuzzy Sets and Fuzzy Logic (Vol. 4). New Jersey: Prentice hall. ##Koenig, M. & J. Meissner. (2015). Value-at-Risk Optimal Policies for Revenue Management Problems. International Journal of Production Economics, 166: 11-19. ##Konno, H. & H. Yamazaki. (1991). Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market. Management Science, 37(5): 519-531. ##Kupiec, P. (1995). Techniques for Verifying the Accuracy of Risk Management Models. The Journal of Derivatives, 3: 73-84. ##Lee, L.W. & S.M. Chen. (2008). Fuzzy Risk Analysis Based on Fuzzy Numbers with Different Shapes and Different Deviations. Expert Systems with Applications, 34(4): 2763-2771. ##Liu, B. (2006). A Survey of Credibility Theory. Fuzzy Optimization and Decision Making, 5(4): 387-408. ##Liu, B. (2007). Uncertainty Theory, 2nd. ##Liu, B. (2004). Uncertainty Theory: An Introduction to its Axiomatic Foundations. ##Liu, B. & B. Liu. (2002). Theory and Practice of Uncertain Programming (pp. 78-81). Heidelberg: Physica-verlag. ##Liu, B. & Y.K. Liu. (2002). Expected value of Fuzzy Variable And Fuzzy Expected Value Models. IEEE Transactions on Fuzzy Systems, 10(4): 445-450. ##Liu, Y. & J. Gao. (2007). The Independent of Fuzzy Variables in Credibility Theory and Its Applications. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15: 1-20. ##Mandelbrot, B.B. (1997). The Variation of Certain Speculative Prices. InFractals and Scaling in Finance (pp. 371-418). Springer New York. ##Markowitz, H. (1952). Portfolio Selection. The journal of Finance, 7(1): 77-91. ##McNeil, A.J. & R. Frey. (2000). Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: An Extreme Value Approach. Journal of empirical finance, 7(3): 271-300. ##Moussa, A.M., J.S. Kamdem & M. Terraza. (2014). Fuzzy Value-at-Risk and Expected Shortfall for Portfolios with Heavy-Tailed Returns. Economic Modelling, 39: 247-256. ##Nahmias, S. (1978). Fuzzy variables. Fuzzy Sets and Systems, 1(2): 97-110. ##Peng, J. (2008). Measuring Fuzzy Risk by Credibilistic Value at Risk. InInnovative Computing Information and Control, 2008. ICICIC'08. 3rd International Conference on (pp. 270-270). IEEE. ##Peng, J. (2011). Credibilistic Value and Average Value at Risk in Fuzzy Risk Analysis. Fuzzy Information and Engineering, 3(1): 69-79. ##Rachel, C., H. Ronald & K. Kess. (1999). Optimal Portfolio Selection in a Value-at Risk Frame Work, Journal of Banking and Finance, 25: 117. ##Wang, B., S. Wang & J. Watada. (2011a). Fuzzy-Portfolio-Selection Models with Value-at-Risk. IEEE Transactions on Fuzzy Systems, 19(4): 758-769. ##Wang, S. & J. Watada. (2011b). Two-Stage Fuzzy Stochastic Programming with Value-at-Risk Criteria. Applied Soft Computing, 11(1): 1044-1056. ##Whitworth, B. L. (2003). U.S. Patent No. 6,622,129. Washington, DC: U.S. Patent and Trademark Office. ##Xu, D. & U. Kaymak. (2008). Value-at-Risk Estimation by Using Probabilistic Fuzzy Systems. In Fuzzy Systems, 2008. FUZZ-IEEE 2008.(IEEE World Congress on Computational Intelligence). IEEE International Conference on (pp. 2109-2116). IEEE. ##Xu, Z., S. Shang, W. Qian & W. Shu. (2010). A Method for Fuzzy Risk Analysis Based on the New Similarity of Trapezoidal Fuzzy Numbers. Expert Systems with Applications, 37(3): 1920-1927. ##Zimmermann, H.J. (1996). Fuzzy Control. In Fuzzy Set Theory and Its Applications (pp. 203-240). Springer Netherlands. ##
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