FINANCIAL MODELING AND FORECASTING OF CONSUMER DEMAND BASED ON UTILITY FUNCTIONS

Abstract

This article explores the financial modeling of consumer behavior based on utility functions and its application to demand analysis and forecasting under budget constraints. At the microeconomic level, the study addresses rational consumer choice, where individuals allocate income across goods to maximize utility under specific price conditions and resource limitations.
The research evaluates various economic-mathematical models of consumer behavior, including logarithmic utility functions, Stone-type models, and generalized multiplicative utility functions. Different modeling approaches apply to the same economic object depending on analytical objectives, data availability, and market conditions. The paper examines consumer choice problems related to forming optimal bundles of goods and services, taking into account income, price structures, and individual preferences.
For each model, demand functions are derived via optimization methods, analyzing the relationships among income, prices, and consumption patterns. Particular attention is dedicated to identifying conditions under which goods are classified as normal, inferior, or Giffen goods, as well as analyzing substitution and complementarity effects.
An approach for applying utility-based models to financial demand forecasting is proposed, enabling consumer behavior evaluation under diverse economic scenarios and uncertainty factors. A numerical example illustrates the framework’s practical applicability and confirms its relevance for real-world analysis.
Ultimately, the results support market analysis, demand forecasting, and managerial decision-making in pricing, planning, and resource allocation under economic uncertainty and market volatility.