Economic Research and Perspectives

Economic Research and Perspectives

Prioritizing the Divestment of Pension Fund–Owned Enterprises Through Portfolio Optimization: New Evidence from the DCC–GARCH R² Decomposed Connectedness Approach

Document Type : مقالات علمی پژوهشی

Authors
Hasan Chenarani 1
Soheil Roudari 2
1 Assistant Professor, Department of Economics and Islamic Banking, Faculty of Economics, Kharazmi University, Tehran, Iran
2 PhD in Economics, Department of economics, Faculty of economics and administrative sciences, Ferdowsi University, Mashhad, Iran
10.48311/ecor.2025.115460.0
Abstract
Abstract
Pension funds in Iran, as intergenerational financial institutions, play a pivotal role in safeguarding retirees’ financial security. Over recent decades, these funds have encountered significant challenges stemming from government policies, macroeconomic crises, and managerial inefficiencies. A central concern has been the suboptimal performance of affiliated enterprises in generating value added and sustainably financing pension obligations. In light of persistent resource deficits and structural financial imbalances, reforming governance structures and optimizing investment portfolios have become increasingly urgent policy priorities. One criterion for valuing enterprises subject to privatization is market capitalization, which depends fundamentally on stock market performance. Accordingly, the optimal portfolio weight of each enterprise, hedging effectiveness, beta coefficient, and Sharpe ratio should be evaluated across alternative portfolio management strategies—including the Minimum Variance Portfolio (MVP), Minimum Correlation Portfolio (MCP), Minimum Connectedness Portfolio (MCOP), Minimum Bivariate R2 Portfolio (MRP), and Minimum R2 Decomposed Connectedness Portfolio (MPG). The model yielding the highest Sharpe ratio can then be identified as the optimal approach. Under such a framework, enterprises may be prioritized for accelerated or delayed divestiture based on their return–risk profiles, consistent with the mandates of the country’s Seventh Economic Development Plan. To date, this issue has not been examined using the aforementioned methodological approaches, despite its substantial policy relevance
Purpose/Aims:
The primary objective of this study is to determine the prioritization of divesting pension fund–owned enterprises using novel portfolio optimization techniques. The analysis draws on daily return data for the selected firms over a 10-year period and applies advanced econometric models to estimate their optimal portfolio weights. Based on performance indicators—most notably the Sharpe ratio—the study identifies divestiture priorities. Policymakers may thus target enterprises with lower optimal weights and inferior Sharpe ratios for earlier divestiture, an analytical dimension that has not previously been addressed in the literature.
Methodology & Framework:
This study employs the Time-Varying Parameter Vector Autoregression (TVP–VAR) model developed by Antonakakis, estimated via the Kalman filter, to analyze dynamic correlations among assets. Portfolio optimization is conducted using the Broadstock approach. The TVP–VAR framework, with time-varying coefficients, enables the identification of structural shocks and volatility spillovers. Derived measures—including the Generalized Impulse Response Function (GIRF), Generalized Forecast Error Variance Decomposition (GFEVD), Total Connectedness Index (TCI), and Pairwise Connectedness Index (PCI)—are utilized to assess portfolio sensitivity to shocks, the role of individual assets in risk transmission, and overall market connectedness.
In addition, the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity R-squared (DCC–GARCH R²) decomposed connectedness approach introduced by Cocca et al. (2024) is applied to estimate the MRP and MPG strategies. This integrated analytical framework provides detailed insights for dynamic and informed portfolio management, particularly in the context of state-owned enterprises.
Findings:
Conditional correlations among the examined symbols exhibit substantial time variation. Over the past year, FAKHAS displayed the lowest correlation with DERAZAK and the highest correlation with JAM. Conversely, JAM exhibited the lowest correlation with DERAZAK and the highest with FAKHAS. Over the past two years, FBAHONAR showed the highest conditional correlation with FAKHAS and the lowest with JAM. For DERAZAK, the minimum correlation occurred with JAM, while the maximum was observed primarily with FBAHONAR.
Overall, dynamic conditional correlations between FAKHAS and FBAHONAR and the other symbols were relatively high. This finding indicates that, in portfolios already containing JAM and DERAZAK, the inclusion of FAKHAS and FBAHONAR increases overall portfolio risk.
Regarding return transmission, FAKHAS and FBAHONAR emerged as the largest net transmitters of returns, whereas JAM and DERAZAK were identified as the largest net receivers.
In terms of hedging effectiveness, JAM exhibited negative hedging effectiveness, suggesting that the examined assets did not provide effective risk reduction for this asset. Under bullish market conditions, the DERAZAK/JAM combination demonstrated the highest hedging effectiveness, whereas FAKHAS/JAM exhibited the lowest. Under bearish conditions, the FAKHAS/FBAHONAR combination provided the highest hedging effectiveness, while DERAZAK/JAM showed the weakest performance.
Concerning the identification of the optimal portfolio strategy, the highest Sharpe ratio was achieved under the MRP approach. Accordingly, this method is identified as the optimal strategy for portfolio management and the prioritization of enterprise divestiture. Across all return scenarios, FAKHAS and FBAHONAR consistently received the lowest portfolio weights, indicating comparatively weak performance from a capital market perspective.
Discussion:
This study evaluates portfolio management and divestiture prioritization for four pension fund–owned enterprises—FBAHONAR, FAKHAS, JAM, and DERAZAK—over the period from January 1, 2015, to August 12, 2025, using the DCC–GARCH R2 Decomposed Connectedness framework proposed by Cocca et al. (2024).
The results demonstrate that FAKHAS and FBAHONAR exhibit relatively high dynamic conditional correlations with other assets, implying that their inclusion in portfolios containing JAM and DERAZAK increases aggregate risk exposure. Moreover, both FAKHAS and FBAHONAR function predominantly as net transmitters of returns within the connectedness network.
Conclusion & Implications:
From a comprehensive portfolio management perspective, the MRP approach yields the highest Sharpe ratio and is therefore identified as the optimal strategy for managing pension fund assets and prioritizing enterprise divestiture. Under this framework, FAKHAS and FBAHONAR consistently receive the lowest optimal weights across return scenarios, reflecting suboptimal performance in terms of risk-adjusted returns.
Given that return and risk constitute the fundamental pillars of investment decision-making, determining optimal asset weights under alternative portfolio strategies is essential. The findings of this study provide a rigorous and objective basis for prioritizing divestiture. Should sufficient institutional commitment to enterprise restructuring exist, the results offer a scientifically grounded criterion to guide policymakers in implementing divestment decisions consistent with national development objectives.

Keywords
DCC&ndash
GARCH.R²
Decomposed, Connectedness Approach, Investment Management, Pension Funds
Subjects
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