Analyzing VaR: The Case for Wavelet Methods in the Moroccan Food Industry[Analyse de la VaR : le cas des méthodes d'ondelettes dans l'industrie alimentaire marocaine]

The quantification of credit portfolio losses using the wavelet approach offers an innovative methodology for assessing the financial risks associated with credit. This approach uses advanced mathematical techniques to analyse temporal fluctuations in credit data. In terms of quantifying losses, the wavelet approach allows the decomposition of loss time series into different time scales. This makes it possible to identify short-and long-term trends as well as irregular variations. By analysing these scales, analysts can better understand the dynamics of credit losses and identify the underlying factors that contribute to fluctuations. To quantify credit portfolio losses, the cumulative loss function is approximated by a finite combination of wavelet basis functions by computing the coefficients of the wavelet approximation (WA). Wavelet approximation is an accurate, robust and fast method that enables VaR to be estimated much more quickly than with other loss quantification methods, such as the Monte Carlo MC method.