Document Type : Original Article
Authors
1
Associate Professor of Accounting, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran. kebrahimi@semnan.ac.ir
2
Ph.D. Candidate in Financial Engineering, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran. y.heyvadi@semnan.ac.ir
10.22075/mmsd.2026.39947.1030
Abstract
Background and Objectives: The resilience of financial markets against non-financial shocks is a fundamental pillar for achieving sustainable development goals in modern economies. Due to the structural interdependence of strategic industries (such as steel and petrochemicals) on energy resources, Iran's economy is severely exposed to escalating risks arising from composite energy imbalances (electricity and gas). These imbalances, occurring primarily during peak consumption seasons (summer and winter), have evolved beyond a mere operational challenge into a novel source of systematic risk. By disrupting production, they threaten firms' future cash flows and the stability of the capital market. The primary objective of this paper is to critically evaluate existing literature and identify methodological gaps in modeling the time-varying effects of spatial and seasonal imbalance shocks on the dynamic correlation structure of assets, with a particular focus on sustainable development requirements.
Materials and Methods: This study is a systematic review employing a qualitative and analytical-critical approach, grounded in a gap analysis between leading international literature and domestic empirical research. No quantitative analysis or statistical testing on real-world data is performed in this paper; instead, the focus remains on the theoretical elucidation of advanced econometric models. Accordingly, the framework of the Dynamic Conditional Correlation model with spatial-seasonal exogenous variables (DCC-GARCH-X) is introduced and its components are detailed as a standard analytical tool. Within this proposed model, the application of the GJR-GARCH model to control for asymmetric volatility (leverage effects) and the integration of seasonal dummy variables and regional imbalance indices into the correlation dynamics equation are theoretically explicated.
Results and Conclusion: Findings from the critical review of literature indicate that domestic studies have predominantly focused on univariate and static models, failing to simultaneously model the seasonal and spatial dimensions of risk. The DCC-GARCH-X theoretical framework, by introducing the concept of "Dynamic Systematic Beta," facilitates the transformation of energy imbalance risk into a pricable factor within the Arbitrage Pricing Theory (APT). The final conclusion suggests that energy imbalances lead to time-varying increases in correlations during crisis seasons. By providing this framework, the paper establishes a research agenda for future scholars to empirically and quantitatively test these relationships, thereby contributing to enhanced transparency and sustainability in the capital market.
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