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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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Toc

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

Data preparation for MBA

The time series data was transformed to ensure that each row of data represented the customer's purchase basket. A sample of 500 active customers was selected for the analysis. The definition of active stipulated that the customer had used at least one product or service in the last 12 months and had at least one open product at the time of selection. Only customers with multiple products/services were chosen for the analysis.

The following is a snapshot of the customer data used for modeling:

Custid

Pr1

Pr2

Pr3

Pr4

Pr5

1

Residential_Mortgage

Insurance

Personal_Current_Account

Savings_Account

Premium_Current_Account

2

Personal_Current_Account

Credit_Card

Premium_Current_Account

3

Locker

Residential_Mortgage

Insurance

Credit_Card

Currency_Services

4

Personal_Current_Account

Trading_Account...

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