The Resource Big data and machine learning in quantitative investment, Tony Guida

Big data and machine learning in quantitative investment, Tony Guida

Label
Big data and machine learning in quantitative investment
Title
Big data and machine learning in quantitative investment
Statement of responsibility
Tony Guida
Creator
Author
Subject
Language
eng
Summary
  • "Get to know the "why" and "how" of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, its a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance. The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning. Gain a solid reason to use machine learning Frame your question using financial markets laws Know your data Understand how machine learning is becoming ever more sophisticated Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment and this book shows you how"--
  • "Sales handles: ACTIONABLE CONTENT: it is the only book on the subject written by practitioners for practitioners, focusing on the "why" and "how" of using machine learning and big data in finance. It is not a book on mathematical demonstration or coding HIGH-CALIBER AUTHOR TEAM with wide networks within the Quant community. Great opportunities for promotion and possibly buybacks HOT TOPIC: machine learning and artificial intelligence are of huge interest to finance institutions looking to gain an edge Marketing Decription: Each of the authors is well known and respected in the Quant Finance field; each has a wide professional network, and speaks regularly at major Quant conferences around the world. They are also members of Quant finance organisations such as Opalesque, London Quant group, Inquire, CFA Financial Journal, EDHEC Risk, QuantCon and Re-Work Deep learning"--
Member of
Assigning source
  • Provided by publisher
  • Provided by publisher
Cataloging source
DLC
http://library.link/vocab/creatorDate
1979-
http://library.link/vocab/creatorName
Guida, Tony
Dewey number
332.60285/631
Index
index present
LC call number
HG4521
LC item number
.G795 2019
Literary form
non fiction
Nature of contents
bibliography
Series statement
Wiley finance series
http://library.link/vocab/subjectName
  • Investments
  • Machine learning
  • Big data
  • BUSINESS & ECONOMICS / Finance
  • Big data
  • Investments
  • Machine learning
  • Finance and Accounting
Label
Big data and machine learning in quantitative investment, Tony Guida
Instantiates
Publication
Copyright
Note
Machine generated contents note: Chapter 1: Do algorithms dream about artificial alphas? Chapter 2: Taming Big data Chapter 3: State of machine learning applications in investment management Chapter 4: Implementing alternative data in an investment Process Chapter 5: Using alternative and Big Data to trade macro assets Chapter 6: Big is beautiful: How email receipt data can help predict company sales Chapter 7: Ensemble learning applied to quant equity: gradient boosting in a multi-factor framework Chapter 8: A social media analysis of corporate culture Chapter 9: Machine Learning & Event Detection for Trading Energy Futures Chapter 10: Natural language processing of financial news Chapter 11: Support-Vector-Machine Based Global Tactical Asset Allocation Chapter 12: Reinforcement learning in finance Chapter 13: Deep learning in Finance: Prediction of stock returns with long short term memory networks Biography of contributors
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Dimensions
25 cm.
Extent
vi, 285 pages
Isbn
9781119522195
Lccn
2018036097
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
System control number
  • (OCoLC)1065543275
  • (YBP)ybp15204579
Label
Big data and machine learning in quantitative investment, Tony Guida
Publication
Copyright
Note
Machine generated contents note: Chapter 1: Do algorithms dream about artificial alphas? Chapter 2: Taming Big data Chapter 3: State of machine learning applications in investment management Chapter 4: Implementing alternative data in an investment Process Chapter 5: Using alternative and Big Data to trade macro assets Chapter 6: Big is beautiful: How email receipt data can help predict company sales Chapter 7: Ensemble learning applied to quant equity: gradient boosting in a multi-factor framework Chapter 8: A social media analysis of corporate culture Chapter 9: Machine Learning & Event Detection for Trading Energy Futures Chapter 10: Natural language processing of financial news Chapter 11: Support-Vector-Machine Based Global Tactical Asset Allocation Chapter 12: Reinforcement learning in finance Chapter 13: Deep learning in Finance: Prediction of stock returns with long short term memory networks Biography of contributors
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Dimensions
25 cm.
Extent
vi, 285 pages
Isbn
9781119522195
Lccn
2018036097
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
System control number
  • (OCoLC)1065543275
  • (YBP)ybp15204579

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