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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

Markov method for imputation

In real-world scenarios, data is never perfect. There will be anomalies that a trained eye will be able to spot. Issues with data may occur due to the way the data is being sourced and as a result of the process used to store it. Data-retrieval issues related to technology, level of understanding of the data, the audited and controlled process for extraction, archiving issues, and understanding the data requirements of the business can further impact data quality. These are just a few examples of what can go wrong while trying to ensure that a firm has the best data quality. Thankfully, help is at hand when left with missing or poor quality data. Using various statistical methods, imputation can be performed to ensure there are no missing values. Imputation of missing values is an important step prior to modeling as a lot of the statistical procedures...

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