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Integrating Artificial Intelligence in Pension Fund Management to Mitigate Capital Market Volatility: A Risk Governance Framework
Conference paper   Open access   Peer reviewed

Integrating Artificial Intelligence in Pension Fund Management to Mitigate Capital Market Volatility: A Risk Governance Framework

Jingdong Huang, Xinyi Zhang and Hao Jin
Proceedings of the 2026 3rd Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, pp.125-130
Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, 3rd (Dongguan, China, 15-May-2026–17-May-2026)
Association for Computing Machinery
2026
DOI: https://doi.org/10.1145/3837873.3837894
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Abstract

Finance services capital market volatility deep reinforcement learning dynamic asset allocation pension fund management risk governance
The increasing integration of pension funds into capital markets exposes contemporary financial systems to systemic vulnerabilities, particularly during periods of extreme market volatility. To address the inherent limitations of traditional static asset allocation models, this paper proposes an AI-Driven Risk Governance Framework specifically tailored for pension fund management. We systematically extend conventional portfolio theories by integrating a Deep Reinforcement Learning (DRL) architecture to continuously calibrate dynamic investment strategies. However, to resolve the opaque "black box" nature of pure algorithmic trading, our framework structurally couples the neural network with strict macro-prudential regulatory constraints. Utilizing multi-dimensional temporal feature extraction, the AI agent autonomously balances risk-adjusted returns with counter-cyclical market stabilization. Comprehensive theoretical analysis and simulations demonstrate that static benchmarks systematically fail to envelop asymmetric shocks, whereas the proposed AI-governance architecture successfully mitigates portfolio-level exposure to systemic volatility. Ultimately, synthesizing dynamic deep parameterization with strict risk governance allows institutional capital to maintain robust solvency during market crises, ensuring long-term fund sustainability without exacerbating pro-cyclical market fluctuations.

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