Author: Publisher:
ISBN: 9814464988
Category :
Languages : en
Pages :
Book Description
Stochastic Filtering with Applications in Finance
Author: Stochastic Filtering with Applications in Finance
Author: Ramaprasad BharPublisher: World Scientific
ISBN: 9814304859
Category : Business & Economics
Languages : en
Pages : 354
Book Description
This book provides a comprehensive account of stochastic filtering as a modeling tool in finance and economics. It aims to present this very important tool with a view to making it more popular among researchers in the disciplines of finance and economics. It is not intended to give a complete mathematical treatment of different stochastic filtering approaches, but rather to describe them in simple terms and illustrate their application with real historical data for problems normally encountered in these disciplines. Beyond laying out the steps to be implemented, the steps are demonstrated in the context of different market segments. Although no prior knowledge in this area is required, the reader is expected to have knowledge of probability theory as well as a general mathematical aptitude. Its simple presentation of complex algorithms required to solve modeling problems in increasingly sophisticated financial markets makes this book particularly valuable as a reference for graduate students and researchers interested in the field. Furthermore, it analyses the model estimation results in the context of the market and contrasts these with contemporary research publications. It is also suitable for use as a text for graduate level courses on stochastic modeling.
Stochastic Analysis, Stochastic Systems, and Applications to Finance
Author: Allanus Hak-Man TsoiPublisher: World Scientific
ISBN: 9814355712
Category : Business & Economics
Languages : en
Pages : 274
Book Description
Pt. I. Stochastic analysis and systems. 1. Multidimensional Wick-Ito formula for Gaussian processes / D. Nualart and S. Ortiz-Latorre. 2. Fractional white noise multiplication / A.H. Tsoi. 3. Invariance principle of regime-switching diffusions / C. Zhu and G. Yin -- pt. II. Finance and stochastics. 4. Real options and competition / A. Bensoussan, J.D. Diltz and S.R. Hoe. 5. Finding expectations of monotone functions of binary random variables by simulation, with applications to reliability, finance, and round robin tournaments / M. Brown, E.A. Pekoz and S.M. Ross. 6. Filtering with counting process observations and other factors : applications to bond price tick data / X. Hu, D.R. Kuipers and Y. Zeng. 7. Jump bond markets some steps towards general models in applications to hedging and utility problems / M. Kohlmann and D. Xiong. 8. Recombining tree for regime-switching model : algorithm and weak convergence / R.H. Liu. 9. Optimal reinsurance under a jump diffusion model / S. Luo. 10. Applications of counting processes and martingales in survival analysis / J. Sun. 11. Stochastic algorithms and numerics for mean-reverting asset trading / Q. Zhang, C. Zhuang and G. Yin
Stochastic Processes, Finance and Control
Author: Samuel N CohenPublisher: World Scientific
ISBN: 9814483915
Category : Mathematics
Languages : en
Pages : 604
Book Description
This book consists of a series of new, peer-reviewed papers in stochastic processes, analysis, filtering and control, with particular emphasis on mathematical finance, actuarial science and engineering. Paper contributors include colleagues, collaborators and former students of Robert Elliott, many of whom are world-leading experts and have made fundamental and significant contributions to these areas. This book provides new important insights and results by eminent researchers in the considered areas, which will be of interest to researchers and practitioners. The topics considered will be diverse in applications, and will provide contemporary approaches to the problems considered. The areas considered are rapidly evolving. This volume will contribute to their development, and present the current state-of-the-art stochastic processes, analysis, filtering and control. Contributing authors include: H Albrecher, T Bielecki, F Dufour, M Jeanblanc, I Karatzas, H-H Kuo, A Melnikov, E Platen, G Yin, Q Zhang, C Chiarella, W Fleming, D Madan, R Mamon, J Yan, V Krishnamurthy. Contents:Stochastic Analysis:On the Connection Between Discrete and Continuous Wick Calculus with an Application to the Fractional Black-Scholes Model (C Bender and P Parczewski)Malliavin Differentiability of a Class of Feller-Diffusions with Relevance in Finance (C-O Ewald, Y Xiao, Y Zou and T K Siu)A Stochastic Integral for Adapted and Instantly Independent Stochastic Processes (H-H Kuo, A Sae-Tang and B Szozda)Independence of Some Multiple Poisson Stochastic Integrals with Variable-Sign Kernels (N Privault)Differential and Stochastic Games:Strategies for Differential Games (W H Fleming and D Hernández-Hernández)BSDE Approach to Non-Zero-Sum Stochastic Differential Games of Control and Stopping (I Karatzas and Q Li)Mathematical Finance:On Optimal Dividend Strategies in Insurance with a Random Time Horizon (H Albrecher and S Thonhauser)Counterparty Risk and the Impact of Collateralization in CDS Contracts (T R Bielecki, I Cialenco and I Iyigunler)A Modern View on Merton's Jump-Diffusion Model (G H L Cheang and C Chiarella)Hedging Portfolio Loss Derivatives with CDS's (A Cousin and M Jeanblanc)New Analytic Approximations for Pricing Spread Options (J van der Hoek and M W Korolkiewicz)On the Polynomial–Normal Model and Option Pricing (H Li and A Melnikov)A Functional Transformation Approach to Interest Rate Modelling(S Luo, J Yan and Q Zhang)S&P 500 Index Option Surface Drivers and Their Risk Neutral and Real World Quadratic Covariations (D B Madan)A Dynamic Portfolio Approach to Asset Markets and Monetary Policy (E Platen and W Semmler)Mean-Variance Portfolio Selection Under Regime-Switching Diffusion Asset Models: A Two-Time-Scale Limit (G Yin and Y Talafha)Filtering and Control:Existence and Uniqueness of Solutions for a Partially Observed Stochastic Control Problem (A Bensoussan, M Çakanyildirim, M Li and S P Sethi)Continuous Control of Piecewise Deterministic Markov Processes with Long Run Average Cost (O L V Costa and F Dufour)Stochastic Linear-Quadratic Control Revisited (T E Duncan)Optimization of Stochastic Uncertain Systems: Entropy Rate Functionals, Minimax Games and Robustness (F Rezaei, C D Charalambous and N U Ahmed)Gradient Based Policy Optimization of Constrained Markov Decision Processes (V Krishnamurthy and F J Vázquez Abad)Parameter Estimation of a Regime-Switching Model Using an Inverse Stieltjes Moment Approach (X Xi, M R Rodrigo and R S Mamon)An Optimal Inventory-Price Coordination Policy (H Zhang and Q Zhang) Readership: Researchers and professionals in stochastic processes, analysis, filtering and control. Keywords:Stochastic Processes;Filtering;Stochastic Control;Stochastic Analysis;Mathematical Finance;Actuarial Sciences;EngineeringKey Features:This is a festschrift of Professor Robert J Elliott, who is a world leader in the areas of stochastic processes, filtering, control as well as their applicationsIncludes contributions of many world-leading scholars in the fieldsContain many original and fundamental results in the fields rare in competing titles
Stochastic Analysis, Stochastic Systems, and Applications to Finance
Author: Allanus TsoiPublisher: World Scientific
ISBN: 9814458481
Category : Mathematics
Languages : en
Pages : 272
Book Description
This book introduces some advanced topics in probability theories — both pure and applied — is divided into two parts. The first part deals with the analysis of stochastic dynamical systems, in terms of Gaussian processes, white noise theory, and diffusion processes. The second part of the book discusses some up-to-date applications of optimization theories, martingale measure theories, reliability theories, stochastic filtering theories and stochastic algorithms towards mathematical finance issues such as option pricing and hedging, bond market analysis, volatility studies and asset trading modeling. Contents:Stochastic Analysis and Systems:Multidimensional Wick–Itô Formula for Gaussian Processes (D Nualart & S Ortiz–Latorre)Fractional White Noise Multiplication (A H Tsoi)Invariance Principle of Regime–Switching Diffusions (C Zhu & G Yin)Finance and Stochastics:Real Options and Competition (A Bensoussan, J D Diltz & S R Hoe)Finding Expectations of Monotone Functions of Binary Random Variables by Simulation, with Applications to Reliability, Finance, and Round Robin Tournaments (M Brown, E A Peköz & S M Ross)Filtering with Counting Process Observations and Other Factors: Applications to Bond Price Tick Data (X Hu, D R Kuipers & Y Zeng)Jump Bond Markets Some Steps towards General Models in Applications to Hedging and Utility Problems (M Kohlmann & D Xiong)Recombining Tree for Regime–Switching Model: Algorithm and Weak Convergence (R H Liu)Optimal Reinsurance under a Jump Diffusion Model (S Luo)Applications of Counting Processes and Martingales in Survival Analysis (J Sun)Stochastic Algorithms and Numeries for Mean-Revertig Asset Trading (Q Zhang, C Zhuang & G Yin) Readership: Financial mathematicians; applied stochastic analysts, graduate students. Keywords:Stochastic Analysis;Stochastic System;Mathematical FinanceKey Features:This book discusses some frontiers of Gaussian processes analysis and their associated Wick–Ito formula. For the first time, the studies of fractional Brownian motion is put into the framework of fractional white noise multiplication operatorsSome up-to-date treatment is of the invariance principle of regime-switching diffusion are given in detail
Machine Learning in Finance
Author: Matthew F. DixonPublisher: Springer Nature
ISBN: 3030410684
Category : Business & Economics
Languages : en
Pages : 565
Book Description
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
Stochastic Calculus and Applications
Author: Samuel N. CohenPublisher: Birkhäuser
ISBN: 1493928678
Category : Mathematics
Languages : en
Pages : 666
Book Description
Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance. Building upon the original release of this title, this text will be of great interest to research mathematicians and graduate students working in those fields, as well as quants in the finance industry. New features of this edition include: End of chapter exercises; New chapters on basic measure theory and Backward SDEs; Reworked proofs, examples and explanatory material; Increased focus on motivating the mathematics; Extensive topical index. "Such a self-contained and complete exposition of stochastic calculus and applications fills an existing gap in the literature. The book can be recommended for first-year graduate studies. It will be useful for all who intend to work with stochastic calculus as well as with its applications."–Zentralblatt (from review of the First Edition)
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics
Author: Ramazan GençayPublisher: Elsevier
ISBN: 0080509223
Category : Business & Economics
Languages : en
Pages : 383
Book Description
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method. The first book to present a unified view of filtering techniques Concentrates on exactly what wavelets analysis and filtering methods in general can reveal about a time series Provides easy access to a wide spectrum of parametric and non-parametric filtering methods
Optional Processes
Author: Mohamed AbdelghaniPublisher: CRC Press
ISBN: 0429809247
Category : Business & Economics
Languages : en
Pages : 400
Book Description
It is well-known that modern stochastic calculus has been exhaustively developed under usual conditions. Despite such a well-developed theory, there is evidence to suggest that these very convenient technical conditions cannot necessarily be fulfilled in real-world applications. Optional Processes: Theory and Applications seeks to delve into the existing theory, new developments and applications of optional processes on "unusual" probability spaces. The development of stochastic calculus of optional processes marks the beginning of a new and more general form of stochastic analysis. This book aims to provide an accessible, comprehensive and up-to-date exposition of optional processes and their numerous properties. Furthermore, the book presents not only current theory of optional processes, but it also contains a spectrum of applications to stochastic differential equations, filtering theory and mathematical finance. Features Suitable for graduate students and researchers in mathematical finance, actuarial science, applied mathematics and related areas Compiles almost all essential results on the calculus of optional processes in unusual probability spaces Contains many advanced analytical results for stochastic differential equations and statistics pertaining to the calculus of optional processes Develops new methods in finance based on optional processes such as a new portfolio theory, defaultable claim pricing mechanism, etc. Authors Mohamed Abdelghani completed his PhD in mathematical finance from the University of Alberta, Edmonton, Canada. He is currently working as a vice president in quantitative finance and machine learning at Morgan Stanley, New York, USA. Alexander Melnikov is a professor in mathematical finance at the University of Alberta. His research interests belong to the area of contemporary stochastic analysis and its numerous applications in mathematical finance, statistics and actuarial science. He has written six books as well as over 100 research papers in leading academic journals.
Applications of Stochastic Optimal Control to Economics and Finance
Author: Salvatore FedericoPublisher:
ISBN: 9783039360581
Category :
Languages : en
Pages : 206
Book Description
In a world dominated by uncertainty, modeling and understanding the optimal behavior of agents is of the utmost importance. Many problems in economics, finance, and actuarial science naturally require decision makers to undertake choices in stochastic environments. Examples include optimal individual consumption and retirement choices, optimal management of portfolios and risk, hedging, optimal timing issues in pricing American options, and investment decisions. Stochastic control theory provides the methods and results to tackle all such problems. This book is a collection of the papers published in the Special Issue "Applications of Stochastic Optimal Control to Economics and Finance", which appeared in the open access journal Risks in 2019. It contains seven peer-reviewed papers dealing with stochastic control models motivated by important questions in economics and finance. Each model is rigorously mathematically funded and treated, and the numerical methods are employed to derive the optimal solution. The topics of the book's chapters range from optimal public debt management to optimal reinsurance, real options in energy markets, and optimal portfolio choice in partial and complete information settings. From a mathematical point of view, techniques and arguments of dynamic programming theory, filtering theory, optimal stopping, one-dimensional diffusions and multi-dimensional jump processes are used.