Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing
Augment your asset allocation strategy with machine learning and factor investing for unprecedented returns and growth

Whether you’re managing institutional portfolios or private wealth, Quantitative Asset Management will open your eyes to a new, more successful way of investing—one that harnesses the power of big data and artificial intelligence.

This innovative guide walks you through everything you need to know to fully leverage these revolutionary tools. Written from the perspective of a seasoned financial investor making use of technology, it details proven investing methods, striking a rare balance between providing important technical information without burdening you with overly complex investing theory. Quantitative Asset Management is organized into four thematic sections:

  • Part I reveals invaluable lessons for planning and governance of investment decision-making.
  • Part 2 discusses quantitative financial modeling, covering important topics like overfitting, mitigating unrealistic assumptions, managing substitutions, enhancing minority classes, and missing data imputation.
  • Part 3 shows how to develop a strategy into an investment product, including the alpha models, risk models, implementation, backtesting, and cost optimization.
  • Part 4 explains how to measure performance, learn from mistakes, manage risk, and survive financial tragedies.

With Quantitative Asset Management, you have everything you need to build your awareness of other markets, ask the right questions and answer them effectively, and drive steady profits even through times of great uncertainty.

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Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing
Augment your asset allocation strategy with machine learning and factor investing for unprecedented returns and growth

Whether you’re managing institutional portfolios or private wealth, Quantitative Asset Management will open your eyes to a new, more successful way of investing—one that harnesses the power of big data and artificial intelligence.

This innovative guide walks you through everything you need to know to fully leverage these revolutionary tools. Written from the perspective of a seasoned financial investor making use of technology, it details proven investing methods, striking a rare balance between providing important technical information without burdening you with overly complex investing theory. Quantitative Asset Management is organized into four thematic sections:

  • Part I reveals invaluable lessons for planning and governance of investment decision-making.
  • Part 2 discusses quantitative financial modeling, covering important topics like overfitting, mitigating unrealistic assumptions, managing substitutions, enhancing minority classes, and missing data imputation.
  • Part 3 shows how to develop a strategy into an investment product, including the alpha models, risk models, implementation, backtesting, and cost optimization.
  • Part 4 explains how to measure performance, learn from mistakes, manage risk, and survive financial tragedies.

With Quantitative Asset Management, you have everything you need to build your awareness of other markets, ask the right questions and answer them effectively, and drive steady profits even through times of great uncertainty.

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Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing

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

Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing

by Michael Robbins

Hardcover

$72.00 
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Overview

Augment your asset allocation strategy with machine learning and factor investing for unprecedented returns and growth

Whether you’re managing institutional portfolios or private wealth, Quantitative Asset Management will open your eyes to a new, more successful way of investing—one that harnesses the power of big data and artificial intelligence.

This innovative guide walks you through everything you need to know to fully leverage these revolutionary tools. Written from the perspective of a seasoned financial investor making use of technology, it details proven investing methods, striking a rare balance between providing important technical information without burdening you with overly complex investing theory. Quantitative Asset Management is organized into four thematic sections:

  • Part I reveals invaluable lessons for planning and governance of investment decision-making.
  • Part 2 discusses quantitative financial modeling, covering important topics like overfitting, mitigating unrealistic assumptions, managing substitutions, enhancing minority classes, and missing data imputation.
  • Part 3 shows how to develop a strategy into an investment product, including the alpha models, risk models, implementation, backtesting, and cost optimization.
  • Part 4 explains how to measure performance, learn from mistakes, manage risk, and survive financial tragedies.

With Quantitative Asset Management, you have everything you need to build your awareness of other markets, ask the right questions and answer them effectively, and drive steady profits even through times of great uncertainty.


Product Details

ISBN-13: 9781264258444
Publisher: McGraw Hill LLC
Publication date: 06/16/2023
Pages: 496
Product dimensions: 6.36(w) x 9.24(h) x 1.61(d)

About the Author

Michael Robbins is the Chief Investment Officer of a large investment firm. This is his sixth CIO appointment, including one for a bank with 8½ million clients. He has managed pensions, endowments, family offices and was the Chief Risk Officer for the State of Utah’s systems. Michael sits on private equity boards of directors and he is a professor at Columbia University, where he teaches quantitative investing including graduate classes in Global Macroeconomic Tactical Asset Allocation (GTAA) and Environmental, Social, and Governance (ESG) Investing.
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