Modeling the properties of price distribution in the gold market

This article explores the properties of price distribution in the gold market using various statistical models, including mixtures of normal distributions (Gaussian), gamma distributions, beta distributions, Student's t-distributions, triangular distributions, and von Mises distributions. The analysis is based on gold price data for the period from 2015 to 2022. Each of the models used allowed for identifying specific features of price dynamics, such as central tendency, dispersion, asymmetry, heavy tails, and multimodality. Mixtures of von Mises distributions demonstrated particularly high accuracy of approximation, effectively capturing cyclical patterns in the data. The obtained results deepen the understanding of the statistical properties of gold price distribution and lay the foundation for further research and practical applications in the field of financial market modeling and forecasting.