Profit-driven churn prediction for the mutual fund industry: A multisegment approach-Reference-Cited by-同舟云学术

Profit-driven churn prediction for the mutual fund industry: A multisegment approach

Published:2021-04 Issue: Volume:100 Page:102380
ISSN:0305-0483
Container-title:Omega
language:en
Short-container-title:Omega

Author:

Maldonado Sebastián,Domínguez Gonzalo,Olaya Diego,Verbeke Wouter

Funder

CONICYT

FONDECYT-Chile

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Strategy and Management

Reference51 articles.

1. Developing a hybrid model to predict student first year retention in stem disciplines using machine learning techniques;Alkhasawneh;Journal of STEM Education: Innovations and Research,2014

2. A novel cost-sensitive framework for customer churn predictive modeling;Bahnsen;Decision Analytics,2015

3. Bahnsen A.C., Aouada D., Ottersten B.E.. Ensemble of example-dependent cost-sensitive decision trees. CoRR; 2015b.

4. Selecting portfolios for mutual funds;Ballestero;Omega (Westport),2004

5. Customer lifetime value: marketing models and applications;Berger;Journal of interactive marketing,1998

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