Ймовірнісні методи інтелектуального аналізу та моделювання фінансових часових рядів

Abstract

The work proposes a probabilistic approach to personal financial data analysis and forecasting. The developed full-stack web application implements probability distribution parameters for transaction categorization, time series analysis with stochastic models, and adaptive predictive algorithms for goal achievement estimation. API integration with banking systems ensures automatic data collection, while probabilistic algorithms provide personalized financial analytics with confidence intervals. Experimental results demonstrate the effectiveness of the proposed approach for financial planning and management.