Theoretical Analysis of an XGBoost Framework for Product Cannibalization

TL;DR

This paper provides a mathematical analysis of a three-stage XGBoost algorithm designed to forecast sales in scenarios where products cannibalize each other, extending previous empirical work with theoretical insights.

Contribution

It introduces a theoretical framework and mathematical reasoning for an existing XGBoost-based sales forecasting model in product cannibalization contexts.

Findings

Mathematical explanation of the XGBoost algorithm's effectiveness

Validation of the model's theoretical properties

Insights into the model's behavior under different scenarios

Abstract

This paper is an extension of our work where we presented a three-stage XGBoost algorithm for forecasting sales under product cannibalization scenario. Previously we developed the model based on our intuition and provided empirical evidence on its performance. In this study we would briefly go over the algorithm and then provide mathematical reasoning behind its working.