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Panel data modeling of bank deposits

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Studying the dynamics of deposits is important for three reasons: first, it serves as an important component of liquidity stress testing; second, it is crucial to asset-liability management exercises and the allocation between liquid and illiquid assets; third, it is the support for a Liquidity at Risk methodology. Current models are based on \(\textit{AR}(1)\) processes that often underestimate liquidity risk. Thus, a bank relying on those models may face failure in an event of crisis. We propose an alternative approach for modeling deposits, using panel data and a momentum term. The model enables the simulation of a variety of deposit trajectories, including episodes of financial distress, showing much higher drawdowns and realistic liquidity at risk estimates, as well as density plots that present a wide range of possible values, corresponding to booms and financial crises. Therefore, this methodology is more suitable for liquidity management at banks, as well as for conducting liquidity stress tests.

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Marta Faias and Pedro Mota are pleased to acknowledge the financial support from the Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) through the project UIDB/00297/2020 (Centro de Matemática e Aplicações).

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Correspondence to Marta Faias.

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P. Júdice: this research is independent from Montepio Bank and does not reflect the views of this institution.

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Costa, S., Faias, M., Júdice, P. et al. Panel data modeling of bank deposits. Ann Finance 17, 247–264 (2021).

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