Marginal and Functional Quantization of Stochastic Processes

Marginal and Functional Quantization of Stochastic Processes PDF Author: Harald Luschgy
Publisher: Springer Nature
ISBN: 3031454642
Category : Mathematics
Languages : en
Pages : 918

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Book Description
Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the 1960s, it evolved into an automatic classification technique for generating prototypes of extensive datasets. In modern terms, it can be recognized as a seminal contribution to unsupervised learning through the k-means clustering algorithm in data science. In contrast, Functional Quantization, a more recent area of study dating back to the early 2000s, focuses on the quantization of continuous-time stochastic processes viewed as random vectors in Banach function spaces. This book distinguishes itself by delving into the quantization of random vectors with values in a Banach space—a unique feature of its content. Its main objectives are twofold: first, to offer a comprehensive and cohesive overview of the latest developments as well as several new results in optimal quantization theory, spanning both finite and infinite dimensions, building upon the advancements detailed in Graf and Luschgy's Lecture Notes volume. Secondly, it serves to demonstrate how optimal quantization can be employed as a space discretization method within probability theory and numerical probability, particularly in fields like quantitative finance. The main applications to numerical probability are the controlled approximation of regular and conditional expectations by quantization-based cubature formulas, with applications to time-space discretization of Markov processes, typically Brownian diffusions, by quantization trees. While primarily catering to mathematicians specializing in probability theory and numerical probability, this monograph also holds relevance for data scientists, electrical engineers involved in data transmission, and professionals in economics and logistics who are intrigued by optimal allocation problems.

Marginal and Functional Quantization of Stochastic Processes

Marginal and Functional Quantization of Stochastic Processes PDF Author: Harald Luschgy
Publisher: Springer Nature
ISBN: 3031454642
Category : Mathematics
Languages : en
Pages : 918

Get Book Here

Book Description
Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the 1960s, it evolved into an automatic classification technique for generating prototypes of extensive datasets. In modern terms, it can be recognized as a seminal contribution to unsupervised learning through the k-means clustering algorithm in data science. In contrast, Functional Quantization, a more recent area of study dating back to the early 2000s, focuses on the quantization of continuous-time stochastic processes viewed as random vectors in Banach function spaces. This book distinguishes itself by delving into the quantization of random vectors with values in a Banach space—a unique feature of its content. Its main objectives are twofold: first, to offer a comprehensive and cohesive overview of the latest developments as well as several new results in optimal quantization theory, spanning both finite and infinite dimensions, building upon the advancements detailed in Graf and Luschgy's Lecture Notes volume. Secondly, it serves to demonstrate how optimal quantization can be employed as a space discretization method within probability theory and numerical probability, particularly in fields like quantitative finance. The main applications to numerical probability are the controlled approximation of regular and conditional expectations by quantization-based cubature formulas, with applications to time-space discretization of Markov processes, typically Brownian diffusions, by quantization trees. While primarily catering to mathematicians specializing in probability theory and numerical probability, this monograph also holds relevance for data scientists, electrical engineers involved in data transmission, and professionals in economics and logistics who are intrigued by optimal allocation problems.

Numerical Probability

Numerical Probability PDF Author: Gilles Pagès
Publisher: Springer
ISBN: 3319902768
Category : Mathematics
Languages : en
Pages : 591

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Book Description
This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance. Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration. Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study.

Foundations of Quantization for Probability Distributions

Foundations of Quantization for Probability Distributions PDF Author: Siegfried Graf
Publisher: Springer
ISBN: 3540455779
Category : Mathematics
Languages : en
Pages : 238

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Book Description
Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first mathematically rigorous account of the fundamental theory underlying these applications. The emphasis is on the asymptotics of quantization errors for absolutely continuous and special classes of singular probabilities (surface measures, self-similar measures) presenting some new results for the first time. Written for researchers and graduate students in probability theory the monograph is of potential interest to all people working in the disciplines mentioned above.

Derivatives in Financial Markets with Stochastic Volatility

Derivatives in Financial Markets with Stochastic Volatility PDF Author: Jean-Pierre Fouque
Publisher: Cambridge University Press
ISBN: 9780521791632
Category : Business & Economics
Languages : en
Pages : 222

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Book Description
This book, first published in 2000, addresses pricing and hedging derivative securities in uncertain and changing market volatility.

Nonlinear Option Pricing

Nonlinear Option Pricing PDF Author: Julien Guyon
Publisher: CRC Press
ISBN: 1466570342
Category : Business & Economics
Languages : en
Pages : 480

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Book Description
New Tools to Solve Your Option Pricing ProblemsFor nonlinear PDEs encountered in quantitative finance, advanced probabilistic methods are needed to address dimensionality issues. Written by two leaders in quantitative research-including Risk magazine's 2013 Quant of the Year-Nonlinear Option Pricing compares various numerical methods for solving hi

Large Deviations and Asymptotic Methods in Finance

Large Deviations and Asymptotic Methods in Finance PDF Author: Peter K. Friz
Publisher: Springer
ISBN: 3319116053
Category : Mathematics
Languages : en
Pages : 590

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Book Description
Topics covered in this volume (large deviations, differential geometry, asymptotic expansions, central limit theorems) give a full picture of the current advances in the application of asymptotic methods in mathematical finance, and thereby provide rigorous solutions to important mathematical and financial issues, such as implied volatility asymptotics, local volatility extrapolation, systemic risk and volatility estimation. This volume gathers together ground-breaking results in this field by some of its leading experts. Over the past decade, asymptotic methods have played an increasingly important role in the study of the behaviour of (financial) models. These methods provide a useful alternative to numerical methods in settings where the latter may lose accuracy (in extremes such as small and large strikes, and small maturities), and lead to a clearer understanding of the behaviour of models, and of the influence of parameters on this behaviour. Graduate students, researchers and practitioners will find this book very useful, and the diversity of topics will appeal to people from mathematical finance, probability theory and differential geometry.

Financial Signal Processing and Machine Learning

Financial Signal Processing and Machine Learning PDF Author: Ali N. Akansu
Publisher: John Wiley & Sons
ISBN: 1118745639
Category : Technology & Engineering
Languages : en
Pages : 312

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Book Description
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.

Introduction to Modeling and Control of Internal Combustion Engine Systems

Introduction to Modeling and Control of Internal Combustion Engine Systems PDF Author: Lino Guzzella
Publisher: Springer Science & Business Media
ISBN: 3662080036
Category : Technology & Engineering
Languages : en
Pages : 303

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Book Description
Internal combustion engines still have a potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. These goals can be achieved with help of control systems. Modeling and Control of Internal Combustion Engines (ICE) addresses these issues by offering an introduction to cost-effective model-based control system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed in the text and selected feedforward and feedback control problems are discussed. The appendix contains a summary of the most important controller analysis and design methods, and a case study that analyzes a simplified idle-speed control problem. The book is written for students interested in the design of classical and novel ICE control systems.

FX Options and Structured Products

FX Options and Structured Products PDF Author: Uwe Wystup
Publisher: John Wiley & Sons
ISBN: 111847113X
Category : Business & Economics
Languages : en
Pages : 649

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Book Description
Advanced Guidance to Excelling in the FX Market Once you have a textbook understanding of money market and foreign exchange products, turn to FX Options and Structured Products, Second Edition, for the beyond-vanilla options strategies and traded deals proven superior in today’s post-credit crisis trading environment. With the thoroughness and balance of theory and practice only Uwe Wystup can deliver, this fully revised edition offers authoritative solutions for the real world in an easy-to-access format. See how specific products actually work through detailed case studies featuring clear examples of FX options, common structures and custom solutions. This complete resource is both a wellspring of ideas and a hands-on guide to structuring and executing your own strategies. Distinguish yourself with a valued skillset by: Working through practical and thought-provoking challenges in more than six dozen exercises, all with complete solutions in a companion volume Gaining a working knowledge of the latest, most popular products, including accumulators, kikos, target forwards and more Getting close to the everyday realities of the FX derivatives market through new, illuminating case studies for corporates, municipalities and private banking FX Options and Structured Products, Second Edition is your go-to road map to the exotic options in FX derivatives.

Mathematical Methods for Foreign Exchange

Mathematical Methods for Foreign Exchange PDF Author: Alexander Lipton
Publisher: World Scientific
ISBN: 9789810246150
Category : Business & Economics
Languages : en
Pages : 702

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Book Description
This comprehensive book presents a systematic and practically oriented approach to mathematical modeling in finance, particularly in the foreign exchange context. It describes all the relevant aspects of financial engineering, including derivative pricing, in detail. The book is self-contained, with the necessary mathematical, economic, and trading background carefully explained. In addition to the lucid treatment of the standard material, it describes many original results. The book can be used both as a text for students of financial engineering, and as a basic reference for risk managers, traders, and academics.