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Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage by [Michael Isichenko]

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Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage Kindle Edition

4.0 4.0 out of 5 stars 36 ratings

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From the Back Cover


“This is a wonderful book: deep, original, witty, and provocative. It is a survey of the most important ideas and methods of modern quantitative investment that should enthrall both seasoned and junior quants. A must-read that will no doubt become a classic.”

—Jean-Philippe Bouchaud, Chairman and Chief Scientist, Capital Fund Management; member of the French Academy of Sciences

“In his lively and clever style, Isichenko shares from his decades of experience at some of the top quantitative trading shops. Even seasoned veterans will find unfamiliar ideas, as he includes many concepts and models nowhere else in print.”

—Colin Rust, Quantitative Portfolio Manager, Cubist Systematic Strategies

“I encouraged Michael Isichenko not to seek publication of this book, a comprehensive and accurate survey of market structure and data and mathematical and computational approaches and results for systematic trading. I am grateful that he enlarged and extended it beyond a first draft. I now hope that competitors have so much to absorb that they'll misapply much and not eliminate all remaining avenues to profit for my firm.”

—Aaron Sosnick, Founder, Analytics, Research & Trading Advisors

An in-depth and telling handbook for quant portfolio management from a leading industry expert

Quantitative Portfolio Management is a complete and up-to-date exploration of the quantitative analysis process. You’ll find information about sourcing financial data, alpha generation approaches, dealing with risk, portfolio construction, and trade execution.

The book covers both theoretical and algorithmic machine learning subjects in the context of competition-based market efficiency that imposes limits on complexity and performance of quantitative trading models. In addition to foundational subjects that form the basis of quantitative finance, you’ll also learn about lesser-known machine learning algorithms and rarely discussed topics, like forecast combining and multi-period portfolio optimization. The author expertly balances practical observations drawn from his years as a practicing portfolio manager with financial and mathematical insights in statistics and machine learning.

--This text refers to the hardcover edition.

About the Author

MICHAEL ISICHENKO, PhD, is a theoretical physicist and a quantitative portfolio manager who worked at Kurchatov Institute, University of Texas, University of California, SAC Capital Advisors, Société Générale, and Jefferies. He received his doctorate in physics and mathematics from the Moscow Institute of Physics and Technology and is an expert in plasma physics, nonlinear dynamics, and statistical and chaos theory.

--This text refers to the hardcover edition.

Product details

  • ASIN ‏ : ‎ B09FZVTM64
  • Publisher ‏ : ‎ Wiley; 1st edition (Sept. 10 2021)
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 13760 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Sticky notes ‏ : ‎ On Kindle Scribe
  • Print length ‏ : ‎ 434 pages
  • Customer Reviews:
    4.0 4.0 out of 5 stars 36 ratings

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4.0 out of 5 stars
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36 global ratings

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4.0 out of 5 stars Excellent Introduction
Reviewed in the United Kingdom 🇬🇧 on November 4, 2022
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3.0 out of 5 stars Dust cover and black and white print
Reviewed in the United Kingdom 🇬🇧 on November 17, 2021
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3.0 out of 5 stars Leichte Lekture
Reviewed in Germany 🇩🇪 on December 1, 2022
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Pierre FAY
2.0 out of 5 stars Don't really know what to said... Mix filling about this book
Reviewed in France 🇫🇷 on December 22, 2021
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3.0 out of 5 stars Interesting but does not go very deep
Reviewed in France 🇫🇷 on June 18, 2022
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