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JOURNAL OF MONETARY ECONOMICS AND MANAGEMENT
Journals / JOURNAL OF MONETARY ECONOMICS AND MANAGEMENT / Issue 6, 2026 / Methods of adaptive demand forecasting in an unstable market environment based on the integration of macro- and microeconomic factors
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METHODS OF ADAPTIVE DEMAND FORECASTING IN AN UNSTABLE MARKET ENVIRONMENT BASED ON THE INTEGRATION OF MACRO- AND MICROECONOMIC FACTORS Methods of adaptive demand forecasting in an unstable market environment based on the integration of macro- and microeconomic factors

Published in JOURNAL OF MONETARY ECONOMICS AND MANAGEMENT · Pages 363–370 · Rubric: SCIENTIFIC ARTICLES
DOI: https://doi.org/10.26118/2782-4586-2026-363-370
Received: 22.06.2026 Accepted: 03.07.2026 Published: 03.07.2026
Authors
M.
M. I. Shibichenko
V.
V. A. Pavlov
ABSTRACT
Adaptive forecasting methods enable short-term forecasting of indicator dynamics, which is often crucial in dynamic and highly volatile economic environments. A comparative analysis of various adaptive approaches to demand forecasting is conducted, highlighting their limitations and advantages. A proprietary hybrid architecture for demand forecasting in an unstable market environment is proposed, based on the concept of a state space with hierarchical correction. The proposed architecture combines macroeconomic data and microeconomic indicators in a single state space, enabling the joint processing of disparate signals: macroeconomic shocks and operational microindicators, which in standard models typically require a choice. The statistical foundation is formed by a vector error correction model that captures stable long-term dependencies; nonlinear patterns are processed by LSTM networks and gradient boosting.
KEYWORDS
adaptive methods, demand, market, instability, data, neural network, accuracy
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