Demand Forecasting and Cross Elasticity Analysis Based on Stochastic Processes

Yuanzhe Li; Jin Li

doi:10.54097/2r2r9j24

Authors

Yuanzhe Li
Jin Li

DOI:

https://doi.org/10.54097/2r2r9j24

Keywords:

Stochastic process, cross-elasticity analysis, demand response.

Abstract

This study investigates a dynamic demand forecasting model based on stochastic processes, employing adaptive filtering and multilevel correlation analysis for regression forecasting of time-series data. The model utilizes cross-elasticity principles to construct a demand response structure and systematically analyzes elasticity fluctuations across multiple periods and states. By incorporating risk control and sensitivity analysis, the model evaluates decision robustness under market uncertainty. Results demonstrate that the model has strong adaptability in handling high-dimensional data, providing a theoretical foundation for complex time-series demand forecasting.

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