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SAS for Finance: Forecasting and data analysis techniques with real-world examples to build powerful financial models
Authors: Harish Gulati
ISBN-10 书号: 1788624564
ISBN-13 书号: 9781788624565
Publisher Finelybook 出版日期: 2018-05-30
Publisher Finelybook 出版社: Packt
pages 页数: 306 pages
Book Description
Leverage the analytical power of SAS to perform financial analysis efficiently
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.
What you will learn
Understand time series data and its relevance in the financial industry
Build a time series forecasting model in SAS using advanced modeling theories
Develop models in SAS and infer using regression and Markov chains
Forecast in?ation by building an econometric model in SAS for your financial planning
Manage customer loyalty by creating a survival model in SAS using various groupings
Understand similarity analysis and clustering in SAS using time series data
Contents
Preface
Chapter 1: Time Series Modeling in the Financial Industry
Chapter 2: Forecasting Stock Prices and Portfolio Decisions using Time Series
Chapter 3: Credit Risk Management
Chapter 4: Budget and Demand Forecasting
Chapter 5: Inflation Forecasting for Financial Planning
Chapter 6: Managing Customer Loyalty Using Time Series Data
Chapter 7
: Transforming Time Series-Market Basket and Clustering
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Index
