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Financial Signal Processing and Machine Learning

2016-04-21 Technology & Engineering
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Release : 2016-04-21
Genre : Technology & Engineering
Kind : eBook
Book Rating : 639/5 ( reviews)

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Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu. This book was released on 2016-04-21. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Financial Signal Processing and Machine Learning

2016-05-09 Technology & Engineering
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Release : 2016-05-09
Genre : Technology & Engineering
Kind : eBook
Book Rating : 618/5 ( reviews)

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Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu. This book was released on 2016-05-09. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Financial Signal Processing and Machine Learning

2016-05-31 Technology & Engineering
Download Financial Signal Processing and Machine Learning PDF Online Free

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Release : 2016-05-31
Genre : Technology & Engineering
Kind : eBook
Book Rating : 671/5 ( reviews)

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Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu. This book was released on 2016-05-31. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advances in Financial Machine Learning

2018-01-23 Business & Economics
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Release : 2018-01-23
Genre : Business & Economics
Kind : eBook
Book Rating : 119/5 ( reviews)

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Book Synopsis Advances in Financial Machine Learning by : Marcos Lopez de Prado

Download or read book Advances in Financial Machine Learning written by Marcos Lopez de Prado. This book was released on 2018-01-23. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multiscale Financial Signal Processing and Machine Learning

2022
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Release : 2022
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Multiscale Financial Signal Processing and Machine Learning by : Zhengde Zhao

Download or read book Multiscale Financial Signal Processing and Machine Learning written by Zhengde Zhao. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt: Financial time series such as market indices and asset prices are shown to be driven by multiscale factors, ranging from long-term market regimes to rapid fluctuations. Multiscale analysis and signal processing not only reveal latent behaviors embedded in financial time series, but also help machine learning prediction tasks. In this thesis we focus on two different approaches tailored for daily and intraday financial time series respectively. In the first study, Hilbert-Huang transform is applied to daily prices and index values to reveal the underlying multiscale dynamics. In addition, a novel machine learning framework is proposed for identifying useful predictive features. An adaptive algorithm for highly nonstationary time series was introduced and applied to cryptocurrencies to show embedded structure and spectral properties. In the second study, we inspect the relations between statistical properties at different timescales, with the application to intraday high-frequency price data with noise. Functions describing the multiscale behaviors of volatility and correlation are defined and computed using empirical data. Models for high-frequency price processes are proposed and compared against empirical observations.

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