This topic is of high relevance due to the fact that many market risk assessment mathematical models currently available contain many limitations for their effective use. However, these limitations are often not feasible, which leads to a decrease in forecast accuracy. To avoid this, more accurate models are necessary. Neural network-based models can show a more accurate result due to their basic property – nonlinearity. The goal of this paper is to build a model that can enable us to assess a market risk for a company.