AbstractWe use mixture of percentile functions to model credit spread evolution, which allows to obtain a flexible description of indices and their components at the same time. We show regularity results in order to extend mixture percentile to the dynamic case. We characterize the stochastic differential equation of the flow of cumulative distribution function and we link it with the ordered list of the components of the credit index. The main financial goal is to introduce a functional version of Bollinger bands. The crossing of bands by the spread is associated with a trading signal. Finally, we show the richness of the signals produced by functional Bollinger bands compared with standard one with a practical example in credit asset.