Segmentation is the process by which data is bundled together in segments or clusters. If there are a million customer records, and let's say we want to know what is common among those customers, to do this, we will start aggregating a few customer records or bunching some customers together based on similarities in their profiles. What we are essentially doing is forming close-knit clusters of customers. If all these customers were similar, then it would make the whole process easy. We would end up with one cluster and we could describe it easily. But this seldom happens. There are always some demographic or transactional properties by which we want to segregate customers. This is important as we want to customize our offerings to various clusters of customers. Remember the general rule of marketing: no two customers are the same in their intrinsic...
SAS for Finance
By :
SAS for Finance
By:
Overview of this book
SAS is a groundbreaking tool for advanced predictive and statistical analytics used by top banks and financial corporations to establish insights from their financial data.
SAS for Finance offers you the opportunity to leverage the power of SAS analytics in redefining your data. Packed with real-world examples from leading financial institutions, the author discusses statistical models using time series data to resolve business issues.
This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate financial models. You can easily assess the pros and cons of models to suit your unique business needs.
By the end of this book, you will be able to leverage the true power of SAS to design and develop accurate analytical models to gain deeper insights into your financial data.
Table of Contents (9 chapters)
Preface
Free Chapter
Time Series Modeling in the Financial Industry
Forecasting Stock Prices and Portfolio Decisions using Time Series
Credit Risk Management
Budget and Demand Forecasting
Inflation Forecasting for Financial Planning
Managing Customer Loyalty Using Time Series Data
Transforming Time Series – Market Basket and Clustering
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