Coverart for item
The Resource Advances in financial machine learning, Marcos Lopez de Prado, (electronic book)

Advances in financial machine learning, Marcos Lopez de Prado, (electronic book)

Label
Advances in financial machine learning
Title
Advances in financial machine learning
Statement of responsibility
Marcos Lopez de Prado
Creator
Author
Subject
Language
eng
Summary
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations.
Member of
Cataloging source
  • StDuBDS
  • StDuBDS
http://library.link/vocab/creatorName
Lopez de Prado, Marcos Mailoc
Dewey number
332.0285631
Index
no index present
LC call number
HG104
Literary form
non fiction
http://library.link/vocab/subjectName
  • Finance
  • Information theory in finance
  • Machine learning
Summary expansion
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance
Target audience
specialized
Label
Advances in financial machine learning, Marcos Lopez de Prado, (electronic book)
Instantiates
Publication
Carrier category
online resource
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
<p>About the Author</p> <p>Preamble</p> <p>1. Financial Machine Learning as a Distinct Subject</p> <p>Part 1: Data Analysis</p> <p>2. Financial Data Structures</p> <p>3. Labeling</p> <p>4. Sample Weights</p> <p>5. Fractionally Differentiated Features</p> <p>Part 2: Modelling</p> <p>6. Ensemble Methods</p> <p>7. Cross-validation in Finance</p> <p>8. Feature Importance</p> <p>9. Hyper-parameter Tuning with Cross-Validation</p> <p>Part 3: Backtesting</p> <p>10. Bet Sizing</p> <p>11. The Dangers of Backtesting</p> <p>12. Backtesting through Cross-Validation</p> <p>13. Backtesting on Synthetic Data</p> <p>14. Backtest Statistics</p> <p>15. Understanding Strategy Risk</p> <p>16. Machine Learning Asset Allocation</p> <p>Part 4: Useful Financial Features</p> <p>17. Structural Breaks</p> <p>18. Entropy Features</p> <p>19. Microstructural Features</p> <p>Part 5: High-Performance Computing Recipes</p> <p>20. Multiprocessing and Vectorization</p> <p>21. Brute Force and Quantum Computers</p> <p>22. High-Performance Computational Intelligence and Forecasting Technologies</p> <p><i>Dr. Kesheng Wu and Dr. Horst Simon</i></p> <p>Index</p>
Control code
AH33641335
Extent
384 pages
Form of item
electronic
Governing access note
After 5 minutes Preview, click on &#x32;Request Access&#x33;, fill in a form with your details. If triggered, the book will be loaned and tied to the one user for 1 week, during which time users can read or download as they choose. 4th user request triggers auto-purchase
Isbn
9781119482086
Media category
computer
Media MARC source
rdamedia
Specific material designation
remote
Label
Advances in financial machine learning, Marcos Lopez de Prado, (electronic book)
Publication
Carrier category
online resource
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
<p>About the Author</p> <p>Preamble</p> <p>1. Financial Machine Learning as a Distinct Subject</p> <p>Part 1: Data Analysis</p> <p>2. Financial Data Structures</p> <p>3. Labeling</p> <p>4. Sample Weights</p> <p>5. Fractionally Differentiated Features</p> <p>Part 2: Modelling</p> <p>6. Ensemble Methods</p> <p>7. Cross-validation in Finance</p> <p>8. Feature Importance</p> <p>9. Hyper-parameter Tuning with Cross-Validation</p> <p>Part 3: Backtesting</p> <p>10. Bet Sizing</p> <p>11. The Dangers of Backtesting</p> <p>12. Backtesting through Cross-Validation</p> <p>13. Backtesting on Synthetic Data</p> <p>14. Backtest Statistics</p> <p>15. Understanding Strategy Risk</p> <p>16. Machine Learning Asset Allocation</p> <p>Part 4: Useful Financial Features</p> <p>17. Structural Breaks</p> <p>18. Entropy Features</p> <p>19. Microstructural Features</p> <p>Part 5: High-Performance Computing Recipes</p> <p>20. Multiprocessing and Vectorization</p> <p>21. Brute Force and Quantum Computers</p> <p>22. High-Performance Computational Intelligence and Forecasting Technologies</p> <p><i>Dr. Kesheng Wu and Dr. Horst Simon</i></p> <p>Index</p>
Control code
AH33641335
Extent
384 pages
Form of item
electronic
Governing access note
After 5 minutes Preview, click on &#x32;Request Access&#x33;, fill in a form with your details. If triggered, the book will be loaned and tied to the one user for 1 week, during which time users can read or download as they choose. 4th user request triggers auto-purchase
Isbn
9781119482086
Media category
computer
Media MARC source
rdamedia
Specific material designation
remote

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