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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

Inflation Forecasting for Financial Planning

There isn't a standard way of forecasting inflation in the industry. In the risk-modeling world, the models have to be submitted to a regulatory body to receive the approval for using an advanced modeling approach for credit risk. This has somehow ensured that, across the world, analysts and modelers are using a similar suite of statistical techniques to manage risk. However, in the case of inflation, there isn't much exchange of ideas or a platform available from where we can choose the best modeling technique. Usually, the central bank publishes some inflation figures and these can be used as a benchmark for inflation-forecasting accuracy checks. Most of the models built by organizations are proprietary in nature. Moreover, these organizations are chiefly concerned about benchmarking a model to the central bank inflation...

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