20% rabatt med Storytel
Du handlar alltid fysiska böcker till specialpriser om du har eller startar ett abonnemang.
Frakt från 0 kr
Snabb leverans med CityMail, Early Bird, Instabox, Budbee, PostNord eller DSV. Du ser alla fraktalternativ och priser i kassan.
Fria returer
Lämna tillbaka din bok kostnadsfritt med 14 dagars ångerrätt.
20% rabatt med Storytel
Du handlar alltid fysiska böcker till specialpriser om du har eller startar ett abonnemang.
Frakt från 0 kr
Snabb leverans med CityMail, Early Bird, Instabox, Budbee, PostNord eller DSV. Du ser alla fraktalternativ och priser i kassan.
Fria returer
Lämna tillbaka din bok kostnadsfritt med 14 dagars ångerrätt.
20% rabatt med Storytel
Du handlar alltid fysiska böcker till specialpriser om du har eller startar ett abonnemang.
Frakt från 0 kr
Snabb leverans med CityMail, Early Bird, Instabox, Budbee, PostNord eller DSV. Du ser alla fraktalternativ och priser i kassan.
Fria returer
Lämna tillbaka din bok kostnadsfritt med 14 dagars ångerrätt.
549 kr
I lager, skickas inom 4 till 5 vardagar
20% rabatt med Storytel
Du handlar alltid fysiska böcker till specialpriser om du har eller startar ett abonnemang.
Frakt från 0 kr
Snabb leverans med CityMail, Early Bird, Instabox, Budbee, PostNord eller DSV. Du ser alla fraktalternativ och priser i kassan.
Fria returer
Lämna tillbaka din bok kostnadsfritt med 14 dagars ångerrätt.
20% rabatt med Storytel
Du handlar alltid fysiska böcker till specialpriser om du har eller startar ett abonnemang.
Frakt från 0 kr
Snabb leverans med CityMail, Early Bird, Instabox, Budbee, PostNord eller DSV. Du ser alla fraktalternativ och priser i kassan.
Fria returer
Lämna tillbaka din bok kostnadsfritt med 14 dagars ångerrätt.
Utforska miljontals ljud- och e-böcker och upptäck stories i alla format. Med ett abonnemang får du 20% rabatt på fysiska böcker!
Machine learning is not just an advantage; it is becoming standard practice among top-performing trading firms. As traditional strategies struggle to navigate noise, complexity, and speed, ML-powered systems extract alpha by identifying transient patterns beyond human reach. This shift is transforming how hedge funds, quant teams, and algorithmic platforms operate, and now, these same capabilities are available to advanced practitioners.
This book is a practitioner's blueprint for building production-grade ML trading systems from scratch. It goes far beyond basic return-sign classification tasks, which often fail in live markets, and delivers field-tested techniques used inside elite quant desks. It covers everything from the fundamentals of systematic trading and ML's role in detecting patterns to data preparation, backtesting, and model lifecycle management using Python libraries. You will learn to implement supervised learning for advanced feature engineering and sophisticated ML models. You will also learn to use unsupervised learning for pattern detection, apply ultra-fast pattern matching to chartist strategies, and extract crucial trading signals from unstructured news and financial reports. Finally, you will be able to implement anomaly detection and association rules for comprehensive insights.
By the end of this book, you will be ready to design, test, and deploy intelligent trading strategies to institutional standards.
WHAT YOU WILL LEARN
● Build end-to-end machine learning pipelines for trading systems.
● Apply unsupervised learning to detect anomalies and regime shifts.
● Extract alpha signals from financial text using modern NLP.
● Use AutoML to optimize features, models, and parameters.
● Design fast pattern detectors from signal processing techniques.
WHO THIS BOOK IS FOR
This book is for robo traders, algorithmic traders, hedge fund managers, portfolio managers, Python developers, engineers, and analysts who want to understand, master, and integrate machine learning into trading strategies. Readers should understand basic automated trading concepts and have some beginner experience writing Python code.
549 kr
I lager, skickas inom 4 till 5 vardagar
Michael J. Mauboussin
Andrew Ross Sorkin
John Whittington
Andy Bounds
Tim Wu
Claus Grand Bang
Jonathan Hollow, Robin Powell
Glen B. Wheatley, Saras Sarasvathy
Rebecca Henderson
Scott Kupor
Elena Botelho, Kim Powell, Tahl Raz
Paul A. Baran, Paul M. Sweezy
Kirstin Ferguson
Erlend Alfnes, Odd Jøran Sagegg
Alex Ferguson
Simon Laffin
Deborah Gruenfeld
Richard Strozzi-Heckler
Daryl Fielding
John C. Maxwell
Charles H. Vogl
Robert Stone
Eric Schmidt III, Jonathan Rosenberg
Sarah Easter Collins
Frida Skybäck
Liz Moore
Colleen Hoover
Kristin Fägerskjöld
Armando Lucas Correa
Sharon Bolton
Ruth Lillegraven
Santa Montefiore
Kelly Rimmer
Martha Hall Kelly
Svenja O'Donnell
Nathan Harris
Holly Jackson
Louise Boije af Gennäs
Tina Norin
Kristin Fägerskjöld
Pernilla Lindroos
Anna Lönnqvist
Jessie Burton
Malin Nordström
Marc Levy
Emma Donoghue
Snezana Lindskog, Andie Lindskog
Tony Samuelsson
Andrev Walden
Tina Harnesk
Kathrine Nedrejord
Anthony Doerr
Marieke Lucas Rijneveld
Lauren Groff
Claire Messud
Claire Lynch
Sebastian Barry
Ray Celestin
Simon Stranger
Alice Munro
Linda Boström Knausgård
Marit Kapla
Ulf Stark
Sarah Easter Collins
Liz Moore
Ursula Scavenius
Colleen Hoover
Michel Jean
