The Black–Scholes–Merton Model as an Idealization of Discrete-Time Economies
The Black–Scholes–Merton Model as an Idealization of Discrete-Time Economies

Author: David M. Kreps

Publisher: Cambridge University Press

Published: 2019-09-19

Total Pages: 218

ISBN-13: 1108775500

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This book examines whether continuous-time models in frictionless financial economies can be well approximated by discrete-time models. It specifically looks to answer the question: in what sense and to what extent does the famous Black-Scholes-Merton (BSM) continuous-time model of financial markets idealize more realistic discrete-time models of those markets? While it is well known that the BSM model is an idealization of discrete-time economies where the stock price process is driven by a binomial random walk, it is less known that the BSM model idealizes discrete-time economies whose stock price process is driven by more general random walks. Starting with the basic foundations of discrete-time and continuous-time models, David M. Kreps takes the reader through to this important insight with the goal of lowering the entry barrier for many mainstream financial economists, thus bringing less-technical readers to a better understanding of the connections between BSM and nearby discrete-economies.

Analysis of Panel Data
Analysis of Panel Data

Author: Cheng Hsiao

Publisher: Cambridge University Press

Published: 2022-07-07

Total Pages: 539

ISBN-13: 131651210X

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A comprehensive introduction of fundamental panel data methodologies.

Stochastic Finance
Stochastic Finance

Author: Amanda Turner

Publisher: Cambridge University Press

Published: 2023-01-31

Total Pages: 264

ISBN-13: 1009059270

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Stochastic Finance provides an introduction to mathematical finance that is unparalleled in its accessibility. Through classroom testing, the authors have identified common pain points for students, and their approach takes great care to help the reader to overcome these difficulties and to foster understanding where comparable texts often do not. Written for advanced undergraduate students, and making use of numerous detailed examples to illustrate key concepts, this text provides all the mathematical foundations necessary to model transactions in the world of finance. A first course in probability is the only necessary background. The book begins with the discrete binomial model and the finite market model, followed by the continuous Black–Scholes model. It studies the pricing of European options by combining financial concepts such as arbitrage and self-financing trading strategies with probabilistic tools such as sigma algebras, martingales and stochastic integration. All these concepts are introduced in a relaxed and user-friendly fashion.

The Theory of General Economic Equilibrium
The Theory of General Economic Equilibrium

Author: Andreu Mas-Colell

Publisher: Cambridge University Press

Published: 1985

Total Pages: 396

ISBN-13: 9780521388702

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This book brings together the author's pioneering work, written over the last twenty years, on the use of differential methods in general equilibrium theory.

Revealed Preference Theory
Revealed Preference Theory

Author: Christopher P. Chambers

Publisher: Cambridge University Press

Published: 2016-01-05

Total Pages: 241

ISBN-13: 1107087805

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The theory of revealed preference has a long, distinguished tradition in economics but lacked a systematic presentation of the theory until now. This book deals with basic questions in economic theory and studies situations in which empirical observations are consistent or inconsistent with some of the best known economic theories.

The Black-Scholes Model
The Black-Scholes Model

Author: Marek Capiński

Publisher: Cambridge University Press

Published: 2012-09-13

Total Pages: 179

ISBN-13: 1107001692

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Master the essential mathematical tools required for option pricing within the context of a specific, yet fundamental, pricing model.

Energy and Power Risk Management
Energy and Power Risk Management

Author: Alexander Eydeland

Publisher: John Wiley & Sons

Published: 2003-02-03

Total Pages: 506

ISBN-13: 0471455873

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Praise for Energy and Power Risk Management "Energy and Power Risk Management identifies and addresses the key issues in the development of the turbulent energy industry and the challenges it poses to market players. An insightful and far-reaching book written by two renowned professionals." -Helyette Geman, Professor of Finance University Paris Dauphine and ESSEC "The most up-to-date and comprehensive book on managing energy price risk in the natural gas and power markets. An absolute imperative for energy traders and energy risk management professionals." -Vincent Kaminski, Managing Director Citadel Investment Group LLC "Eydeland and Wolyniec's work does an excellent job of outlining the methods needed to measure and manage risk in the volatile energy market." -Gerald G. Fleming, Vice President, Head of East Power Trading, TXU Energy Trading "This book combines academic rigor with real-world practicality. It is a must-read for anyone in energy risk management or asset valuation." -Ron Erd, Senior Vice President American Electric Power

An Introduction to Hybrid Dynamical Systems
An Introduction to Hybrid Dynamical Systems

Author: Arjan J. van der Schaft

Publisher: Springer

Published: 2007-10-03

Total Pages: 189

ISBN-13: 1846285429

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This book is about dynamical systems that are "hybrid" in the sense that they contain both continuous and discrete state variables. Recently there has been increased research interest in the study of the interaction between discrete and continuous dynamics. The present volume provides a first attempt in book form to bring together concepts and methods dealing with hybrid systems from various areas, and to look at these from a unified perspective. The authors have chosen a mode of exposition that is largely based on illustrative examples rather than on the abstract theorem-proof format because the systematic study of hybrid systems is still in its infancy. The examples are taken from many different application areas, ranging from power converters to communication protocols and from chaos to mathematical finance. Subjects covered include the following: definition of hybrid systems; description formats; existence and uniqueness of solutions; special subclasses (variable-structure systems, complementarity systems); reachability and verification; stability and stabilizability; control design methods. The book will be of interest to scientists from a wide range of disciplines including: computer science, control theory, dynamical system theory, systems modeling and simulation, and operations research.

A Non-Random Walk Down Wall Street
A Non-Random Walk Down Wall Street

Author: Andrew W. Lo

Publisher: Princeton University Press

Published: 2011-11-14

Total Pages: 449

ISBN-13: 1400829097

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For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future. The articles track the exciting course of Lo and MacKinlay's research on the predictability of stock prices from their early work on rejecting random walks in short-horizon returns to their analysis of long-term memory in stock market prices. A particular highlight is their now-famous inquiry into the pitfalls of "data-snooping biases" that have arisen from the widespread use of the same historical databases for discovering anomalies and developing seemingly profitable investment strategies. This book invites scholars to reconsider the Random Walk Hypothesis, and, by carefully documenting the presence of predictable components in the stock market, also directs investment professionals toward superior long-term investment returns through disciplined active investment management.

Financial Signal Processing and Machine Learning
Financial Signal Processing and Machine Learning

Author: Ali N. Akansu

Publisher: John Wiley & Sons

Published: 2016-04-21

Total Pages: 312

ISBN-13: 1118745639

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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.