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SAS for Finance

You're reading from   SAS for Finance Forecasting and data analysis techniques with real-world examples to build powerful financial models

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788624565
Length 306 pages
Edition 1st Edition
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Author (1):
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Harish Gulati Harish Gulati
Author Profile Icon Harish Gulati
Harish Gulati
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Table of Contents (9) Chapters Close

Preface 1. Time Series Modeling in the Financial Industry 2. Forecasting Stock Prices and Portfolio Decisions using Time Series FREE CHAPTER 3. Credit Risk Management 4. Budget and Demand Forecasting 5. Inflation Forecasting for Financial Planning 6. Managing Customer Loyalty Using Time Series Data 7. Transforming Time Series – Market Basket and Clustering 8. Other Books You May Enjoy

Market basket analysis

Remember, a successful analyst must not be guided by the methodology but instead think about the business problem, and only thereafter about the methodology that could provide the answers. Most practitioners of analysis/modeling think of the time series methodology as one where the final modeling dataset has a variable with a date or date-time stamp. But there could be other instances where time-stamped data might be transformed to conduct an analysis. Remember, transforming does not mean that the time element isn't important to the analysis methodology or insights generated. We will use this transformation for both market basket analysis (MBA) and clustering in this chapter. Let's look at data transformation in MBA to provide some context.

MBA's goal is to find common purchase items across customer's basket. It is also at times referred...

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