Yes / We discuss the modelling of corporate bank accounts using a proprietary dataset. We thus
offer a principled treatment of a genuine industrial problem. The corporate bank accounts
in our study constitute spare, irregularly-spaced time series that may take both positive and
negative values. We thus builds on previous models where the underlying is real-valued. We
describe an intra-monthly effect identified by practitioners whereby account uncertainty is
typically lowest at the beginning and end of each month and highest in the middle. However,
our theory also allows for the opposite effect to occur. In-sample applications demonstrate
the statistical significance of the hypothesised monthly effect. Out-of-sample forecasting
applications offer a 9% improvement compared to a standard SARIMA approach.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18503 |
| Date | 24 May 2021 |
| Creators | Fry, John, Griguta, V., Gerber, L., Slater-Petty, H., Crockett, K. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2021 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license. |
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