SAS for Finance

Harish Gulati

  • 出版商: Packt Publishing - ebooks Account
  • 出版日期: 2018-05-31
  • 售價: $1,482
  • 貴賓價: 9.5$1,408
  • 語言: 英文
  • 頁數: 337
  • 裝訂: Paperback
  • ISBN: 1788624564
  • ISBN-13: 9781788624565

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商品描述

Key Features

  • Leverage the power of SAS to analyze financial data with ease
  • Find hidden patterns in your data, predict future trends and optimize the risk management capabilities with this handy guide
  • Packed with examples and use-cases, this book will show you why the leading financial institutions rely on SAS for their financial analysis tasks

Book Description

SAS is the groundbreaking tool for advanced, predictive, and statistical analytics. Top banks and financial corporations demand analysis and insights from financial data like never before. With SAS financial intelligence you can consolidate, report, and plan quantitative financial data through dashboards letting you achieve transparency, ensure regulatory compliance, and gain predictive, analytic insight into financial performance.

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 the time series data to solve business solutions. 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 unique business needs. You will also be able to understand how each model can be integrated in the business strategy of the organisation to derive business goals.

What you will learn

  • Understand what is Time Series and its relevance in the financial industry
  • Build Time Series forecasting model in SAS using advanced modelling theories
  • Build models in SAS and infer using Regression and Markov chains
  • Forecast inflation by building a Econometric Model in SAS for your financial planning
  • Manage customer loyalty by building a Survival model in SAS using various groupings
  • Understand Similarity analysis and Clustering in SAS using Time Series data