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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 FREE CHAPTER 2. Forecasting Stock Prices and Portfolio Decisions using Time Series 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

Who this book is for

The book introduces statistical models in the finance industry in a simplified manner. It has real-world examples supported by data and code that reproduces the models. The chapters explain the relevance of the models to business problems, and the discussions about the diagnostics explains how the models can be implemented. The book uses various graphical illustrations, rather than having a focus on equations, to help the reader understand complex models. The book is designed to be a quick introduction to various modeling techniques by explaining their key concepts.

The intended reader is someone aspiring to work in the financial industry, or one of the many financial industry professionals who want to explore its various facets. The reader could also be a student curious to know how theoretical knowledge is applied in the industry, or a finance professional who wants to up-skill and move on to another role. The book's audience may also include any individual who works as a data analyst, data scientist, data architect, data engineer, analytics and insights professional, business analyst, or someone who integrates the outputs of models in business strategy but isn't aware of how problems are solved.

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