Author: | Huang, He |
Title: | Predicting company sales with transactional E-receipts : aggregated and disaggregated data |
Degree: | DFinTech |
Year: | 2022 |
Subject: | Sales forecasting Sales management -- Data processing Hong Kong Polytechnic University -- Dissertations |
Department: | Faculty of Business |
Pages: | 94 pages : color illustrations |
Language: | English |
Abstract: | In this study the author performs prediction of company sales in a linear manner by incorporating transactional e-receipts data in large panels. The consistent and frequent updates of the datasets provide both granularity of consumer purchase trends and persistent signals of the company’s performance, and it allows estimation processes to happen in real time. Additionally, this paper documents the approach of using both disaggregated and aggregated data to predict and evaluate company performance in actual use cases for the capital markets. The results have major implications for investors that use alternative data as a trading strategy, and demonstrate how transactional e-receipts data can serve as a real time predictive tool. |
Rights: | All rights reserved |
Access: | restricted access |
Files in This Item:
File | Description | Size | Format | |
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6733.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.96 MB | Adobe PDF | View/Open |
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