9780979757662-0979757665-Solutions Manual - A Linear Algebra Primer for Financial Engineering (Financial Engineering Advanced Background Series)

Solutions Manual - A Linear Algebra Primer for Financial Engineering (Financial Engineering Advanced Background Series)

ISBN-13: 9780979757662
ISBN-10: 0979757665
Author: Dan Stefanica
Publication date: 2016
Publisher: FE Press, LLC
Format: Paperback 280 pages
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Book details

ISBN-13: 9780979757662
ISBN-10: 0979757665
Author: Dan Stefanica
Publication date: 2016
Publisher: FE Press, LLC
Format: Paperback 280 pages

Summary

Solutions Manual - A Linear Algebra Primer for Financial Engineering (Financial Engineering Advanced Background Series) (ISBN-13: 9780979757662 and ISBN-10: 0979757665), written by authors Dan Stefanica, was published by FE Press, LLC in 2016. With an overall rating of 4.0 stars, it's a notable title among other Job Hunting (Careers, Financial Engineering, Finance) books. You can easily purchase or rent Solutions Manual - A Linear Algebra Primer for Financial Engineering (Financial Engineering Advanced Background Series) (Paperback) from BooksRun, along with many other new and used Job Hunting books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $3.97.

Description

Every exercise from the book ``A Linear Algebra Primer for Financial Engineering“ is solved in detail in the Solutions Manual.

The addition of this Solutions Manual offers the reader the opportunity of rigorous self-study of the linear algebra concepts presented in the NLA Primer, and of achieving a deeper understanding of the financial engineering applications therein.

Financial Applications

• The Arrow—Debreu one period market model

• One period index options arbitrage

• Covariance and correlation matrix estimation from time series data

• Ordinary least squares for implied volatility computation

• Minimum variance portfolios and maximum return portfolios

• Value at Risk and portfolio VaR

Linear Algebra Topics

• LU and Cholesky decompositions and linear solvers

• Optimal solvers for tridiagonal symmetric positive matrices

• Ordinary least squares and linear regression

• Linear Transformation Property

• Efficient cubic spline interpolation

• Multivariate normal random variables

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