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Enterprise Cash Flow Forecasting

Student: Kazarina Ekaterina

Supervisor: Marina V. Radionova

Faculty: Faculty of Economics, Management, and Business Informatics

Educational Programme: Information Analytics in Enterprise Management (Master)

Year of Graduation: 2021

The master's final qualifying paper is completed by a student of IAUP-19-1 Kazarina Ekaterina. The topic of the current research is “Enterprise Cash Flow Forecasting.” The paper is dedicated to developing a cash flow forecasting model for company X. Company X is an intermediary in online-games market by transaction model. The market is an important segment of digital industry with its own specific, which has to be considered in cash flow forecasting. Cash flow forecasting is a necessary part of solving the optimization cash balance problem, which every firm faces in operation management. Among wide range of forecasting methods and instruments it is maсhine learning technics, that are unique and allow to have a good performance without making any presumptions for variables’ distributions or their relations. The cash flow forecasting model developed in the paper is based on predicting of revenue in the projects of company X’ partners, commissions from which form the company X cash flow-in. The model uses a Gradient Boosting Regressor on decision trees and project characteristics as predicting factors, including revenues with a time lag. The final model has a sufficient performance and describes 75% of the depend variable variation for the test dataset. The paper consists of 98 pages, 22 pictures, 12 tables, 23 formulas and 9 annexes. 88 bibliographic sources were used.

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