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Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering Tapa dura - 2022

Name: Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering
Price: 94.00 USD
Availability: InStock
Author: Kelliher, Chris
ISBN: 9781032014432

de Chris Kelliher

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Información de la editorial

Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors.

Features

Useful as both a teaching resource and as a practical tool for professional investors.
Ideal textbook for first year graduate students in quantitative finance programs, such as those in master's programs in Mathematical Finance, Quant Finance or Financial Engineering.
Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning.
Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432.

Detalles

Título Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering
Autor Chris Kelliher
Encuadernación Tapa dura
Páginas 659
Volúmenes 1
Idioma ENG
Editorial CRC Press
Fecha de publicación 2022-05-20
Ilustrado Sí
Features Bibliography, Illustrated, Index
ISBN 9781032014432 / 1032014431
Peso 3.12 libras (1.42 kg)
Dimensiones 10 x 7 x 1.5 pulgadas (25.40 x 17.78 x 3.81 cm)
Library of Congress subjects Python (Computer program language), Financial engineering
Número de catálogo de la Librería del Congreso de EEUU 2021056941
Dewey Decimal Code 332.6

Acerca del autor

Chris Kelliher is a Senior Quantitative Researcher in the Global Asset Allocation group at Fidelity Investments. In addition, Mr. Kelliher is a Lecturer in the Masters in Mathematical Finance and Financial Technology program at Boston University's Questrom School of Business. In this role he teaches multiple graduate level courses including Computational Methods in Finance, Fixed Income & Programming for Quant Finance. Prior to joining Fidelity in 2019, Mr. Kelliher served as a portfolio manager for RDC Capital Partners. Before joining RDC, Mr. Kelliher served as a principal and quantitative portfolio manager at a leading quantitative investment management firm, FDO Partners. Prior to FDO, Mr. Kelliher was a senior quantitative portfolio analyst and trader at Convexity Capital Management and a senior quantitative researcher at Bracebridge Capital. He has been in the financial industry since 2004. Mr. Kelliher earned a BA in Economics from Gordon College, where he graduated Cum Laude with Departmental Honours, and an MS in Mathematical Finance from New York University's Courant Institute.

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Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering

de Kelliher, Chris

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Hardcover

ISBN 10 / ISBN 13

9781032014432 / 1032014431

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Hardcover no dust jacket, as issued - text appears clean and unmarked, binding is square and tight, covers are clean but for light rubbing -- Dependable seller since 1994, daily shipping with tracking from our brick and mortar store in Madison, Wisconsin.

Precio

EUR 89.06

EUR 3.79 enviando a USA

Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering

de Chris Kelliher

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Encuadernación

Hardcover

ISBN 10 / ISBN 13

9781032014432 / 1032014431

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Southport, Merseyside, United Kingdom

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Descripción:

Hardback. New. Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master's programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of… Leer más