@article {13838, title = {Panel data modeling of bank deposits}, journal = {Annals of Finance}, volume = {17}, year = {2021}, pages = {247{\textendash}264}, abstract = {

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 (LaR) methodology.

Current models are based on 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 a novel 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.

}, url = {https://link.springer.com/article/10.1007/s10436-020-00373-1}, author = {Costa, S. and Faias, M. and J{\'u}dice, P. and Mota, P.} }