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Application of long-range correlation and multi-fractal analysis for the depiction of drought risk
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作者 侯威 颜鹏程 +2 位作者 李淑萍 涂刚 胡经国 《Chinese Physics B》 SCIE EI CAS CSCD 2016年第1期831-837,共7页
By using the multi-fractal detrended fluctuation analysis method, we analyze the nonlinear property of drought in southwestern China. The results indicate that the occurrence of drought in southwestern China is multi-... By using the multi-fractal detrended fluctuation analysis method, we analyze the nonlinear property of drought in southwestern China. The results indicate that the occurrence of drought in southwestern China is multi-fractal and long- range correlated, and these properties are indifferent to timescales. A power-law decay distribution well describes the return interval of drought events and the auto-correlation. Furthermore, a drought risk exponent based on the multi-fractal property and the long-range correlation is presented. This risk exponent can give useful information about whether the drought may or may not occur in future, and provide a guidance function for preventing disasters and reducing damage. 展开更多
关键词 multi-fractal detrended fluctuation analysis return intervals drought risk
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A Nonlinear Interval Portfolio Selection Model and Its Application in Banks 被引量:5
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作者 YAN Dawen HU Yaxing LAI Kin Keung 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2018年第3期696-733,共38页
In classical Markowitz's Mean-Variance model, parameters such as the mean and covari- ance of the underlying assets' future return are assumed to be known exactly. However, this is not always the case. The parameter... In classical Markowitz's Mean-Variance model, parameters such as the mean and covari- ance of the underlying assets' future return are assumed to be known exactly. However, this is not always the case. The parameters often correspond to quantities that fall within a range, or can be known ambiguously at the time when investment decision must be made. In such situations, investors determine returns on investment and risks etc. and make portfolio decisions based on experience and economic wisdom. This paper tries to use the concept of interval numbers in the fuzzy set theory to extend the classical mean-variance portfolio selection model to a mean-downside semi-variance model with consideration of liquidity requirements of a bank. The semi-variance constraint is employed to control the downside risk, filling in the existing interval portfolio optimization model based on the linear semi-absolute deviation to depict the downside risk. Simulation results show that the model behaves robustly for risky assets with highest or lowest mean historical rate of return and the optimal investment proportions have good stability. This suggests that for these kinds of assets the model can reduce the risk of high deviation caused by the deviation in the decision maker's experience and economic wisdom. 展开更多
关键词 Downside-risk management interval return portfolio selection semi-variance simulation.
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