Our study closes a research gap on cash flow revisions in large, multinational corporations. Specifically, we explore how revisions relate to forecast accuracy and how patterns in revision processes can be quantified and leveraged to reduce prediction errors in forecasts of foreign exchange exposure. We suggest novel metrics to determine patterns in revision processes related to the concentration of revision volume and show that these measures have higher explanatory power with regard to how forecast error is related to forecast revisions (point on time, volume) and exposure than previously used measures solely relying on correlations among revisions and error. Our results suggest that accounting for these patterns improves the accuracy of foreign exchange exposure forecasts.
|Title of host publication||Multikonferenz Wirtschaftsinformatik (MKWI) 2016: Prescriptive Analytics in IS|
|Editors||V. Nissen, D. Stelzer, S. Straßburger, D. Fischer|
|Place of Publication||Ilmenau, Germany|
|Pages||1217 - 1228|
|Publication status||Published - 2016|
Austrian Classification of Fields of Science and Technology (ÖFOS)
- 502050 Business informatics