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Advances in Financial Machine Learning | A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more (Financial Engineering Advanced Background Series) | A Primer For The Mathematics Of Financial Engineering, Second Edition (Financial Engineering Advanced Background Series) | Solutions Manual - A Primer For The Mathematics Of Financial Engineering, Second Edition | 150 Most Frequently Asked Questions on Quant Interviews (Pocket Book Guides for Quant Interviews) | A Practical Guide To Quantitative Finance Interviews | Stochastic Calculus for Finance II
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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