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.
