Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing Michael Robbins – Ebook Instant Download/Delivery ISBN(s): 9781264258444,1264258445,9781264258451,1264258453
Product details:
- ISBN 10: 1264258453
- ISBN 13: 9781264258451
- Author: Michael Robbins
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.
Table contents:
PART I. PLANNING OUR WORK
1. Choosing Our Product: Fit for Purpose
2. The Investment Process: How to Invest
3. Leadership and Governance: Be Accountable
PART II. DATA, FEATURES, AND RESPONSE
4. Asset Types: A (Not So) Quick Tour
5. Financial Data: Deceptively Insidious
6. Features: Separating the Wheat from the Chaff
7. Financial and Economic Factors: Isolating the Drivers of Risk and Return
8. Creating Factor Forecasts: Look Forward, Not Backward
9. Strategy, Objective, and Conditions: What Are We Trying to Achieve?
10. Time Series and Cross-Sectional Analysis for Financial Markets for Part II: What Works
PART III. BUILDING OUR PROCESS
11. Alpha and Risk Models: Greater Than the Sum of Their Parts
12. Asset Allocation: Choosing Investments Holistically
13. Security Selection: Details Can Dominate
14. Backtesting: Predicting Risk and Performance
15. Transaction Costs and Fees: Details That Matter
16. Rebalancing and Taxes: The Cost of Doing Business
17. Time Series and Cross-Sectional Analysis for Financial Markets for Part III: What Works
PART IV. WORKING OUR PLAN
18. Performance and Risk Measurement: Tracking Our Progress
19. Investment, Risk, and Cash Management: Improving Our Process
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