The goal of the paper is to present the framework for combining clustering and classification for churn management in … approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable … structure. The proposed approach is continuous since the results of market segmentation and rules for churn prediction can be …

This paper investigates the clustering or dependency of extremes in financial returns by estimating the extremal index … value, in which smaller values of the extremal index correspond to more clustering. We apply the interval estimator method … results show that clustering occurs in the emerging and developed markets under several threshold values. This study will shed …

, monetary model for engineering features that quantify investor behaviours, and unsupervised machine learning clustering …

, while affecting it significantly in the short run. However, prediction of the exchange rate is very complicated. In this …

applied in other economies. One of the characteristics of the prediction model is that a date drives the estimation. Thus, the … application of the prediction models to cross-economies' consolidated financial statements is biased. …

prediction performance of random walk without drift. More specifically, this paper applies the random forest, support vector …

Bankruptcy prediction is always a topical issue. The activities of all business entities are directly or indirectly …

prediction accuracy in both conditions is equal, yet shorter time availability results in assessments that are more negative. We …