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Probability and Statistical Models

  • David Ruppert
Part of the Springer Texts in Statistics book series (STS)

Abstract

It is assumed that the reader is already at least somewhat familiar with the basics of probability and statistics. The goals of this chapter are to
  1. 1.

    review these basics;

     
  2. 2.

    discuss more advanced; topics needed in our empirical study of financial markets data such as random vectors, covariance matrices, best linear prediction, heavy-tailed distributions, maximum likelihood estimation, and likelihood ratio tests;

     
  3. 3.

    provide glimpses of how probability and statistics are applied to finance problems in this book; and

     
  4. 4.

    introduce notation that is used throughout the book.

     

Keywords

Probability Density Function Cumulative Distribution Function Pareto Distribution Normal Probability Plot Tail Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • David Ruppert
    • 1
  1. 1.School of Operations Research and Industrial EngineeringCornell UniversityIthacaUSA

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