Algorithmic Trading and Quantitative Strategies

· CRC Press
eBook
400
āļŦāļ™āđ‰āļē
āļĄāļĩāļŠāļīāļ—āļ˜āļīāđŒ
āļ„āļ°āđāļ™āļ™āđāļĨāļ°āļĢāļĩāļ§āļīāļ§āđ„āļĄāđˆāđ„āļ”āđ‰āļĢāļąāļšāļāļēāļĢāļ•āļĢāļ§āļˆāļŠāļ­āļšāļĒāļ·āļ™āļĒāļąāļ™  āļ”āļđāļ‚āđ‰āļ­āļĄāļđāļĨāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄ

āđ€āļāļĩāđˆāļĒāļ§āļāļąāļš eBook āđ€āļĨāđˆāļĄāļ™āļĩāđ‰

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner’s hands-on experience. The focus on empirical modeling and practical know-how makes this book a valuable resource for students and professionals.

The book starts with the often overlooked context of why and how we trade via a detailed introduction to market structure and quantitative microstructure models. The authors then present the necessary quantitative toolbox including more advanced machine learning models needed to successfully operate in the field. They next discuss the subject of quantitative trading, alpha generation, active portfolio management and more recent topics like news and sentiment analytics. The last main topic of execution algorithms is covered in detail with emphasis on the state of the field and critical topics including the elusive concept of market impact. The book concludes with a discussion on the technology infrastructure necessary to implement algorithmic strategies in large-scale production settings.

A git-hub repository includes data-sets and explanatory/exercise Jupyter notebooks. The exercises involve adding the correct code to solve the particular analysis/problem.

āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļœāļđāđ‰āđāļ•āđˆāļ‡

Raja Velu is a professor of Finance and Analytics in Whitman School of Management at Syracuse University. He served as a Technical Architect at Yahoo! in the Sponsored Search Division and was a visiting scientist at IBM-Almaden, Microsoft Research, Google and JPMC. He has also held visiting positions at Stanford's Statistics department, Indian School of Business, the National University of Singapore, and Singapore Management University.

Maxence Hardy is a Managing Director and the Head of eTrading Quantitative Research for Equities and Futures at J.P.Morgan, based in New York. Mr. Hardy is responsible for the development of agency algorithmic trading strategies for the Equities and Futures divisions globally.

Daniel Nehren is a Managing Director and the Head of Statistical Modelling and Development for Equities at Barclays. Based in New York, Mr. Nehren is responsible for the development of algorithmic trading and analytics products. Mr. Nehren has more than19 years of experience in equity trading working for some of the most prestigious financial firms including Citadel, J.P Morgan, and Goldman Sachs.

āđƒāļŦāđ‰āļ„āļ°āđāļ™āļ™ eBook āļ™āļĩāđ‰

āđāļŠāļ”āļ‡āļ„āļ§āļēāļĄāđ€āļŦāđ‡āļ™āļ‚āļ­āļ‡āļ„āļļāļ“āđƒāļŦāđ‰āđ€āļĢāļēāļĢāļąāļšāļĢāļđāđ‰

āļ‚āđ‰āļ­āļĄāļđāļĨāđƒāļ™āļāļēāļĢāļ­āđˆāļēāļ™

āļŠāļĄāļēāļĢāđŒāļ—āđ‚āļŸāļ™āđāļĨāļ°āđāļ—āđ‡āļšāđ€āļĨāđ‡āļ•
āļ•āļīāļ”āļ•āļąāđ‰āļ‡āđāļ­āļ› Google Play Books āļŠāļģāļŦāļĢāļąāļš Android āđāļĨāļ° iPad/iPhone āđāļ­āļ›āļˆāļ°āļ‹āļīāļ‡āļ„āđŒāđ‚āļ”āļĒāļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļīāļāļąāļšāļšāļąāļāļŠāļĩāļ‚āļ­āļ‡āļ„āļļāļ“ āđāļĨāļ°āļŠāđˆāļ§āļĒāđƒāļŦāđ‰āļ„āļļāļ“āļ­āđˆāļēāļ™āđāļšāļšāļ­āļ­āļ™āđ„āļĨāļ™āđŒāļŦāļĢāļ·āļ­āļ­āļ­āļŸāđ„āļĨāļ™āđŒāđ„āļ”āđ‰āļ—āļļāļāļ—āļĩāđˆ
āđāļĨāđ‡āļ›āļ—āđ‡āļ­āļ›āđāļĨāļ°āļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒ
āļ„āļļāļ“āļŸāļąāļ‡āļŦāļ™āļąāļ‡āļŠāļ·āļ­āđ€āļŠāļĩāļĒāļ‡āļ—āļĩāđˆāļ‹āļ·āđ‰āļ­āļˆāļēāļ Google Play āđ‚āļ”āļĒāđƒāļŠāđ‰āđ€āļ§āđ‡āļšāđ€āļšāļĢāļēāļ§āđŒāđ€āļ‹āļ­āļĢāđŒāđƒāļ™āļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒāđ„āļ”āđ‰
eReader āđāļĨāļ°āļ­āļļāļ›āļāļĢāļ“āđŒāļ­āļ·āđˆāļ™āđ†
āļŦāļēāļāļ•āđ‰āļ­āļ‡āļāļēāļĢāļ­āđˆāļēāļ™āļšāļ™āļ­āļļāļ›āļāļĢāļ“āđŒ e-ink āđ€āļŠāđˆāļ™ Kobo eReader āļ„āļļāļ“āļˆāļ°āļ•āđ‰āļ­āļ‡āļ”āļēāļ§āļ™āđŒāđ‚āļŦāļĨāļ”āđāļĨāļ°āđ‚āļ­āļ™āđ„āļŸāļĨāđŒāđ„āļ›āļĒāļąāļ‡āļ­āļļāļ›āļāļĢāļ“āđŒāļ‚āļ­āļ‡āļ„āļļāļ“ āđ‚āļ›āļĢāļ”āļ—āļģāļ•āļēāļĄāļ§āļīāļ˜āļĩāļāļēāļĢāļ­āļĒāđˆāļēāļ‡āļĨāļ°āđ€āļ­āļĩāļĒāļ”āđƒāļ™āļĻāļđāļ™āļĒāđŒāļŠāđˆāļ§āļĒāđ€āļŦāļĨāļ·āļ­āđ€āļžāļ·āđˆāļ­āđ‚āļ­āļ™āđ„āļŸāļĨāđŒāđ„āļ›āļĒāļąāļ‡ eReader āļ—āļĩāđˆāļĢāļ­āļ‡āļĢāļąāļš