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A Signal Processing Perspective On Financial Engineering
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Book Synopsis A Signal Processing Perspective of Financial Engineering by : Yiyong Feng
Download or read book A Signal Processing Perspective of Financial Engineering written by Yiyong Feng and published by Now Publishers. This book was released on 2016-08-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Signal Processing Perspective of Financial Engineering provides straightforward and systematic access to financial engineering for researchers in signal processing and communications
Book Synopsis A Signal Processing Perspective on Financial Engineering by : Yiyong Feng
Download or read book A Signal Processing Perspective on Financial Engineering written by Yiyong Feng and published by . This book was released on 2016 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial engineering and electrical engineering are seemingly different areas that share strong underlying connections. Both areas rely on statistical analysis and modeling of systems; either modeling the financial markets or modeling wireless communication channels. Having a model of reality allows us to make predictions and to optimize the strategies. It is as important to optimize our investment strategies in a financial market as it is to optimize the signal transmitted by an antenna in a wireless link. This monograph provides a survey of financial engineering from a signal processing perspective, that is, it reviews financial modeling, the design of quantitative investment strategies, and order execution with comparison to seemingly different problems in signal processing and communication systems, such as signal modeling, filter/beamforming design, network scheduling, and power allocation.
Book Synopsis A Primer for Financial Engineering by : Ali N. Akansu
Download or read book A Primer for Financial Engineering written by Ali N. Akansu and published by Academic Press. This book was released on 2015-03-25 with total page 156 pages. Available in PDF, EPUB and Kindle. 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
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 and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. 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.
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 and published by Wiley-IEEE Press. This book was released on 2016-05-09 with total page 312 pages. 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.
Book Synopsis Multi-factor Models and Signal Processing Techniques by : Serges Darolles
Download or read book Multi-factor Models and Signal Processing Techniques written by Serges Darolles and published by John Wiley & Sons. This book was released on 2013-08-02 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages “embedded” quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented “risk assessment-based” practices. This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an interesting alternative to the selection of factors (both fundamentals and statistical factors) and can provide more efficient estimation procedures, based on lq regularized Kalman filtering for instance. With numerous illustrative examples from stock markets, this book meets the needs of both finance practitioners and graduate students in science, econometrics and finance. Contents Foreword, Rama Cont. 1. Factor Models and General Definition. 2. Factor Selection. 3. Least Squares Estimation (LSE) and Kalman Filtering (KF) for Factor Modeling: A Geometrical Perspective. 4. A Regularized Kalman Filter (rgKF) for Spiky Data. Appendix: Some Probability Densities. About the Authors Serge Darolles is Professor of Finance at Paris-Dauphine University, Vice-President of QuantValley, co-founder of QAMLab SAS, and member of the Quantitative Management Initiative (QMI) scientific committee. His research interests include financial econometrics, liquidity and hedge fund analysis. He has written numerous articles, which have been published in academic journals. Patrick Duvaut is currently the Research Director of Telecom ParisTech, France. He is co-founder of QAMLab SAS, and member of the Quantitative Management Initiative (QMI) scientific committee. His fields of expertise encompass statistical signal processing, digital communications, embedded systems and QUANT finance. Emmanuelle Jay is co-founder and President of QAMLab SAS. She has worked at Aequam Capital as co-head of R&D since April 2011 and is member of the Quantitative Management Initiative (QMI) scientific committee. Her research interests include SP for finance, quantitative and statistical finance, and hedge fund analysis.
Book Synopsis Design and Analysis of Analog Filters by : Larry D. Paarmann
Download or read book Design and Analysis of Analog Filters written by Larry D. Paarmann and published by Springer Science & Business Media. This book was released on 2005-12-30 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Analog Filters: A Signal Processing Perspective includes signal processing/systems concepts as well as implementation. While most books on analog filter design briefly present the signal processing/systems concepts, and then concentrate on a variety of filter implementation methods, the present book reverses the emphasis, stressing signal processing concepts. Filter implementation topics are presented in Part II: passive filters, and operational amplifier active filters. However, greater emphasis on signal processing/systems concepts is included in Part I of the book than is typical. This emphasis makes the book very appropriate as part of a signal processing curriculum. Useful Aspects of Design and Analysis of Analog Filters: A Signal Processing Perspective extensive use of MATLAB® throughout, with many homework problems involving the use of MATLAB. over 200 figures; over 100 examples; a total of 345 homework problems, appearing at the ends of the chapters; complete and thorough presentation of design characteristics; complete catalog of design approaches. Audience: Design and Analysis of Analog Filters: A Signal Processing Perspective will interest anyone with a standard electrical engineering background, with a B.S. degree or beyond, or at the senior level. While designed as a textbook, its numerous practical examples make it useful as a reference for practicing engineers and scientists, particularly those working in systems design or communications. MATLAB® Examples: A valuable relationship between analog filter theory and analysis and modern digital signal processing is made by the application of MATLAB to both the design and analysis of analog filters. Throughout the book, computer-oriented problems are assigned. The disk that accompanies this book contains MATLAB functions and m-files written specifically for this book. The MATLAB functions on the disk extend basic MATLAB capabilities in terms of the design and analysis of analog filters. The m-files are used in a number of examples in the book. They are included on the disk as an instructional aid.
Book Synopsis Genomic Signal Processing and Statistics by : Edward R. Dougherty
Download or read book Genomic Signal Processing and Statistics written by Edward R. Dougherty and published by Hindawi Publishing Corporation. This book was released on 2005 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in genomic studies have stimulated synergetic research and development in many cross-disciplinary areas. Processing the vast genomic data, especially the recent large-scale microarray gene expression data, to reveal the complex biological functionality, represents enormous challenges to signal processing and statistics. This perspective naturally leads to a new field, genomic signal processing (GSP), which studies the processing of genomic signals by integrating the theory of signal processing and statistics. Written by an international, interdisciplinary team of authors, this invaluable edited volume is accessible to students just entering this emergent field, and to researchers, both in academia and in industry, in the fields of molecular biology, engineering, statistics, and signal processing. The book provides tutorial-level overviews and addresses the specific needs of genomic signal processing students and researchers as a reference book. The book aims to address current genomic challenges by exploiting potential synergies between genomics, signal processing, and statistics, with special emphasis on signal processing and statistical tools for structural and functional understanding of genomic data. The first part of this book provides a brief history of genomic research and a background introduction from both biological and signal-processing/statistical perspectives, so that readers can easily follow the material presented in the rest of the book. In what follows, overviews of state-of-the-art techniques are provided. We start with a chapter on sequence analysis, and follow with chapters on feature selection, classification, and clustering of microarray data. We then discuss the modeling, analysis, and simulation of biological regulatory networks, especially gene regulatory networks based on Boolean and Bayesian approaches. Visualization and compression of gene data, and supercomputer implementation of genomic signal processing systems are also treated. Finally, we discuss systems biology and medical applications of genomic research as well as the future trends in genomic signal processing and statistics research.
Book Synopsis Introduction to Applied Statistical Signal Analysis by : Richard Shiavi
Download or read book Introduction to Applied Statistical Signal Analysis written by Richard Shiavi and published by Elsevier. This book was released on 2010-07-19 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically. Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain.
Book Synopsis Timing Analysis and Simulation for Signal Integrity Engineers by : Greg Edlund
Download or read book Timing Analysis and Simulation for Signal Integrity Engineers written by Greg Edlund and published by Pearson Education. This book was released on 2007-10-22 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every day, companies call upon their signal integrity engineers to make difficult decisions about design constraints and timing margins. Can I move these wires closer together? How many holes can I drill in this net? How far apart can I place these chips? Each design is unique: there’s no single recipe that answers all the questions. Today’s designs require ever greater precision, but design guides for specific digital interfaces are by nature conservative. Now, for the first time, there’s a complete guide to timing analysis and simulation that will help you manage the tradeoffs between signal integrity, performance, and cost. Writing from the perspective of a practicing SI engineer and team lead, Greg Edlund of IBM presents deep knowledge and quantitative techniques for making better decisions about digital interface design. Edlund shares his insights into how and why digital interfaces fail, revealing how fundamental sources of pathological effects can combine to create fault conditions. You won’t just learn Edlund’s expert techniques for avoiding failures: you’ll learn how to develop the right approach for your own projects and environment. Coverage includes • Systematically ensure that interfaces will operate with positive timing margin over the product’s lifetime–without incurring excess cost • Understand essential chip-to-chip timing concepts in the context of signal integrity • Collect the right information upfront, so you can analyze new designs more effectively • Review the circuits that store information in CMOS state machines–and how they fail • Learn how to time common-clock, source synchronous, and high-speed serial transfers • Thoroughly understand how interconnect electrical characteristics affect timing: propagation delay, impedance profile, crosstalk, resonances, and frequency-dependent loss • Model 3D discontinuities using electromagnetic field solvers • Walk through four case studies: coupled differential vias, land grid array connector, DDR2 memory data transfer, and PCI Express channel • Appendices present a refresher on SPICE modeling and a high-level conceptual framework for electromagnetic field behavior Objective, realistic, and practical, this is the signal integrity resource engineers have been searching for. Preface xiii Acknowledgments xvi About the Author xix About the Cover xx Chapter 1: Engineering Reliable Digital Interfaces 1 Chapter 2: Chip-to-Chip Timing 13 Chapter 3: Inside IO Circuits 39 Chapter 4: Modeling 3D Discontinuities 73 Chapter 5: Practical 3D Examples 101 Chapter 6: DDR2 Case Study 133 Chapter 7: PCI Express Case Study 175 Appendix A: A Short CMOS and SPICE Primer 209 Appendix B: A Stroll Through 3D Fields 219 Endnotes 233 Index 235
Book Synopsis Electrical Measurement, Signal Processing, and Displays by : John G. Webster
Download or read book Electrical Measurement, Signal Processing, and Displays written by John G. Webster and published by CRC Press. This book was released on 2003-07-15 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: The CRC Principles and Applications in Engineering series is a library of convenient, economical references sharply focused on particular engineering topics and subspecialties. Each volume in the series comprises chapters carefully selected from CRC's bestselling handbooks, logically organized for optimum convenience, and thoughtfully priced to fit
Book Synopsis Topological Signal Processing by : Michael Robinson
Download or read book Topological Signal Processing written by Michael Robinson and published by Springer Science & Business Media. This book was released on 2014-01-07 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal processing is the discipline of extracting information from collections of measurements. To be effective, the measurements must be organized and then filtered, detected, or transformed to expose the desired information. Distortions caused by uncertainty, noise, and clutter degrade the performance of practical signal processing systems. In aggressively uncertain situations, the full truth about an underlying signal cannot be known. This book develops the theory and practice of signal processing systems for these situations that extract useful, qualitative information using the mathematics of topology -- the study of spaces under continuous transformations. Since the collection of continuous transformations is large and varied, tools which are topologically-motivated are automatically insensitive to substantial distortion. The target audience comprises practitioners as well as researchers, but the book may also be beneficial for graduate students.
Book Synopsis Probability, Random Processes, and Statistical Analysis by : Hisashi Kobayashi
Download or read book Probability, Random Processes, and Statistical Analysis written by Hisashi Kobayashi and published by Cambridge University Press. This book was released on 2011-12-15 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Itô process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum–Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals.
Book Synopsis A Wavelet Tour of Signal Processing by : Stephane Mallat
Download or read book A Wavelet Tour of Signal Processing written by Stephane Mallat and published by Elsevier. This book was released on 1999-09-14 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and École Polytechnique in Paris. Provides a broad perspective on the principles and applications of transient signal processing with wavelets Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection, multifractal analysis, and time-varying frequency measurements Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet Content is accessible on several level of complexity, depending on the individual reader's needs New to the Second Edition Optical flow calculation and video compression algorithms Image models with bounded variation functions Bayes and Minimax theories for signal estimation 200 pages rewritten and most illustrations redrawn More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics
Book Synopsis An Introduction to Statistical Signal Processing by : Robert M. Gray
Download or read book An Introduction to Statistical Signal Processing written by Robert M. Gray and published by Cambridge University Press. This book was released on 2004-12-02 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.
Download or read book Wavelets written by Charles K. Chui and published by SIAM. This book was released on 1997-01-01 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelets continue to be powerful mathematical tools that can be used to solve problems for which the Fourier (spectral) method does not perform well or cannot handle. This book is for engineers, applied mathematicians, and other scientists who want to learn about using wavelets to analyze, process, and synthesize images and signals. Applications are described in detail and there are step-by-step instructions about how to construct and apply wavelets. The only mathematically rigorous monograph written by a mathematician specifically for nonspecialists, it describes the basic concepts of these mathematical techniques, outlines the procedures for using them, compares the performance of various approaches, and provides information for problem solving, putting the reader at the forefront of current research.
Book Synopsis Sparse Representations for Radar with MATLAB Examples by : Peter Knee
Download or read book Sparse Representations for Radar with MATLAB Examples written by Peter Knee and published by Springer Nature. This book was released on 2022-05-31 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB® examples to emphasize the practical implementations both inside and outside the radar field. Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar
