estimation of value at risk of return in tehran stock exchange using wavelet analysis

financial companies are constantly exposed to the dangers of risk. in the last few years for various reasons, measuring value at risk (var) has become increasingly important for financial firms. the study of multiple measures of risk, var measure with a new approach provides the ground for calculation of market risk. common approaches to risk measurement due to complicated, nonlinear and changing nature of risk have both weak explanatory power and limited functionality. thus, the current study presents a new semi-parametric paradigm combining wavelet analysis and garch models which uses wavelet analysis to deal with properties of multi-scale data. experimental results show the superiority of the proposed method in this paper compared to traditional approaches, such that this method leads to a higher degree of reliability and accuracy of the estimates of the value at risk.