The article is devoted to the adaptation of VaR (EaR) method for the risk evaluation of intellectual assets (digital images) portfolio. We consider this method as the case of dynamic metadata analysis. The distribution of portfolio earnings random variables in a long period is investigated giving the peculiarities of market sales mechanism of this asset class. Information on sales statistics across the assets in portfolio analyzed for the first time. The hypothesis on earnings normal distribution was approved with the aid of data time scaling. Risk metrics calculated with the historical simulation method were approved by additional evaluations with the Monte Carlo methods. The adapted methodology allows to rather accurately performing dynamic quantitative portfolio risk analysis applying different time horizons with required confidence probability.