ISBN: 9798195074494 - numerical linear algebra for quant finance: matrix methods for decomposition, optimization, and risk modeling (5 resultados)

Condición: New. Print on Demand.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. Reactive PublishingNumerical Linear Algebra for Quant Finance is a practical guide to the matrix-based methods used in modern quantitative finance. Written for analysts, quants, researchers, and technically minded finance professionals, this book explains how linear algebra supports portfolio construction, risk modeling, optimization, factor analysis, and high-dimensional financial computation.The book covers core numerical concepts such as matrix operations, vector spaces, decompositions, conditioning, eigenvalue methods, least squares, covariance structures, and numerical stability. Rather than treating linear algebra as an abstract mathematical subject, it connects each method to practical financial applications, including portfolio risk, dimensionality reduction, model calibration, regression systems, and large-scale quantitative workflows.Readers will learn how numerical linear algebra helps solve real problems in finance where datasets are large, relationships are multidimensional, and computational accuracy matters. The emphasis is on clarity, implementation logic, and applied understanding rather than unnecessary theory or inflated promises.This book is designed for readers who want a rigorous but accessible foundation in the numerical methods behind quantitative finance systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. Reactive PublishingNumerical Linear Algebra for Quant Finance is a practical guide to the matrix-based methods used in modern quantitative finance. Written for analysts, quants, researchers, and technically minded finance professionals, this book explains how linear algebra supports portfolio construction, risk modeling, optimization, factor analysis, and high-dimensional financial computation.The book covers core numerical concepts such as matrix operations, vector spaces, decompositions, conditioning, eigenvalue methods, least squares, covariance structures, and numerical stability. Rather than treating linear algebra as an abstract mathematical subject, it connects each method to practical financial applications, including portfolio risk, dimensionality reduction, model calibration, regression systems, and large-scale quantitative workflows.Readers will learn how numerical linear algebra helps solve real problems in finance where datasets are large, relationships are multidimensional, and computational accuracy matters. The emphasis is on clarity, implementation logic, and applied understanding rather than unnecessary theory or inflated promises.This book is designed for readers who want a rigorous but accessible foundation in the numerical methods behind quantitative finance systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…