Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing by Michael Robbins

Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing by Michael Robbins

Whether you are managing institutional portfolios or private wealth, augment your asset allocation strategy with machine learning and factor investing for unprecedented returns and growth In a straightforward and unambiguous fashion, Quantitative Asset Management shows how to take join factor investing and data science—machine learning and applied to big data. Using instructive anecdotes and practical examples, including quiz questions and a companion website with working code, this groundbreaking guide provides a toolkit to apply these modern tools to investing and includes such real-world details as currency controls, market impact, and taxes. It walks readers through the entire investing process, from designing goals to planning, research, implementation, and testing, and risk management. Inside, you’ll find: Cutting edge methods married to the actual strategies used by the most sophisticated institutions Real-world investment processes as employed by the largest investment companies A toolkit for investing as a professional Clear explanations of how to use modern quantitative methods to analyze investing options An accompanying online site with coding and apps Written by a seasoned financial investor who uses technology as a tool—as opposed to a technologist who invests—Quantitative Asset Management explains the author’s methods without oversimplification or confounding theory and math. Quantitative Asset Management demonstrates how leading institutions use Python and MATLAB to build alpha and risk engines, including optimal multi-factor models, contextual nonlinear models, multi-period portfolio implementation, and much more to manage multibillion-dollar portfolios. Big data combined with machine learning provide amazing opportunities for institutional investors. This unmatched resource will get you up and running with a powerful new asset allocation strategy that benefits your clients, your organization, and your career.

Robbins, Michael: -

Michael Robbins was born and raised in rural Upstate New York. After attending SUNY Purchase and graduating with a BFA in photography he worked for the Adirondack Mountain Club for a few seasons. He built and maintained trails all over the ADKs and the Catskills, working at remote sites with only hand tools on everything from bridges to rock staircases. A largely self-taught woodworker, Robbins settled in the Hudson Valley and began developing his own furniture line. Currently, he operates his woodshop out of a former garment factory in Philmont, NY. An avid outdoorsman, when he's not in the shop building or photographing his own work Robbins is most likely out backpacking or skiing.

SKU	Nicht verfügbar
ISBN 13	9781264258444
ISBN 10	1264258445
Titel	Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing
Autor	Michael Robbins
Buchzustand	Nicht verfügbar
Bindungsart	Hardback
Verlag	McGraw-Hill Education
Erscheinungsjahr	2023-07-18
Seitenanzahl	496
Hinweis auf dem Einband	Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
Hinweis	Nicht verfügbar