Financial Signal Processing and Machine Learning

Nonfiction, Science & Nature, Technology, Engineering
Cover of the book Financial Signal Processing and Machine Learning by , Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9781118745632
Publisher: Wiley Publication: April 21, 2016
Imprint: Wiley-IEEE Press Language: English
Author:
ISBN: 9781118745632
Publisher: Wiley
Publication: April 21, 2016
Imprint: Wiley-IEEE Press
Language: English

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches.

Key features:

  • Highlights signal processing and machine learning as key approaches to quantitative finance.
  • Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems.
  • Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques.
  • Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches.

Key features:

More books from Wiley

Cover of the book Aligned to Achieve by
Cover of the book Canon EOS 7D Mark II For Dummies by
Cover of the book Discrete Mechanics by
Cover of the book Persons and Things by
Cover of the book CAPEX Excellence by
Cover of the book Atlas of Oral and Maxillofacial Radiology by
Cover of the book Creating Business Agility by
Cover of the book God's Zeal by
Cover of the book Raspberry Pi For Kids For Dummies by
Cover of the book Economics for Investment Decision Makers Workbook by
Cover of the book A Theory of Shopping by
Cover of the book Trading Risk by
Cover of the book Scriptural Interpretation by
Cover of the book Engineering Quantum Mechanics by
Cover of the book Presenting Data: How to Communicate Your Message Effectively by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy