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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.
Product Details :
Genre |
: Technology & Engineering |
Author |
: Ali N. Akansu |
Publisher |
: John Wiley & Sons |
Release |
: 2016-04-21 |
File |
: 312 Pages |
ISBN-13 |
: 9781118745632 |
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BOOK EXCERPT:
This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial markets. The book builds from the fundamentals, with the help of simple examples, clearly explaining the concepts to the level needed by an engineer, while showing their practical significance. Topics covered include an in depth examination of market microstructure and trading, a detailed explanation of High Frequency Trading and the 2010 Flash Crash, risk analysis and management, popular trading strategies and their characteristics, and High Performance DSP and Financial Computing. The book has many examples to explain financial concepts, and the presentation is enhanced with the visual representation of relevant market data. It provides relevant MATLAB codes for readers to further their study. Please visit the companion website on http://booksite.elsevier.com/9780128015612/ - Provides engineering perspective to financial problems - In depth coverage of market microstructure - Detailed explanation of High Frequency Trading and 2010 Flash Crash - Explores risk analysis and management - Covers high performance DSP & financial computing
Product Details :
Genre |
: Technology & Engineering |
Author |
: Ali N. Akansu |
Publisher |
: Academic Press |
Release |
: 2015-03-25 |
File |
: 156 Pages |
ISBN-13 |
: 9780128017500 |
eBook Download
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.
Product Details :
Genre |
: Technology & Engineering |
Author |
: Ali N. Akansu |
Publisher |
: Wiley-IEEE Press |
Release |
: 2016-05-09 |
File |
: 312 Pages |
ISBN-13 |
: 1118745612 |
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BOOK EXCERPT:
Product Details :
Genre |
: Neural networks (Computer science) |
Author |
: |
Publisher |
: |
Release |
: 1999 |
File |
: 584 Pages |
ISBN-13 |
: UOM:39015047426260 |
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BOOK EXCERPT:
Product Details :
Genre |
: Image processing |
Author |
: |
Publisher |
: |
Release |
: 1992 |
File |
: 776 Pages |
ISBN-13 |
: UOM:39015029457978 |
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BOOK EXCERPT:
The proceedings of the Symposium on Adaptive Systems for Signal Processing, Communications, and Control, 2000. It addresses fundamentals of adaptive and learning systems; signal processing; radar/sonar; wireless communications; pattern recognition; chaos; and more.
Product Details :
Genre |
: Technology & Engineering |
Author |
: |
Publisher |
: Institute of Electrical & Electronics Engineers(IEEE) |
Release |
: 2000 |
File |
: 512 Pages |
ISBN-13 |
: UOM:39015054417996 |
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BOOK EXCERPT:
Offers an alternative technique in forecasting to the traditional techniques used in trading and dealing. The book explains the shortcomings of traditional techniques and shows how neural networks overcome many of the disadvantages of these traditional systems.
Product Details :
Genre |
: Business & Economics |
Author |
: Dirk Emma Baestaens |
Publisher |
: Pitman Publishing |
Release |
: 1994 |
File |
: 274 Pages |
ISBN-13 |
: CORNELL:31924075313316 |
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BOOK EXCERPT:
Product Details :
Genre |
: Artificial intelligence |
Author |
: |
Publisher |
: |
Release |
: 1997 |
File |
: 332 Pages |
ISBN-13 |
: UOM:39015081521380 |
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BOOK EXCERPT:
This completely updated version of the classic first edition offers a wealth of new material reflecting the latest developments in teh field. For investment professionals seeking to maximize this exciting new technology, this handbook is the definitive information source.
Product Details :
Genre |
: Business & Economics |
Author |
: Robert R. Trippi |
Publisher |
: Irwin Professional Publishing |
Release |
: 1996 |
File |
: 872 Pages |
ISBN-13 |
: UCSD:31822025890054 |
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BOOK EXCERPT:
"This book presents a variety of practical applications of neural networks in two important domains of economic activity: finance and manufacturing"--Provided by publisher.
Product Details :
Genre |
: Business & Economics |
Author |
: Joarder Kamruzzaman |
Publisher |
: IGI Global |
Release |
: 2006 |
File |
: 308 Pages |
ISBN-13 |
: IND:30000077955650 |