Statistics of Financial Markets

An Introduction

Author: Jürgen Franke,Wolfgang Härdle,Christian Hafner

Publisher: Springer Science & Business Media

ISBN: 9783540216759

Category: Business & Economics

Page: 424

View: 8861

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1Statistics of Financial Markets presents in a vivid yet concise style the necessary statistical and mathematical background for Financial Engineers and introduces to the main ideas in mathematical finance and financial statistics. Topics covered are, among others, option valuation, financial time series analysis, value-at-risk, copulas, and statistics of the extremes.The underlying structure of the book, i.e. basic tools in mathematical finance, financial time series analysis and applications to given problems of financial markets, allows the book to be used as a basis for lectures, seminars and even crash courses on the topic.A full set of transparencies can be downloaded using the registration card at the back of the book. The registration card also allows the use of the e-book version with links to world wide computing servers.
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Statistics of Financial Markets

Exercises and Solutions

Author: Szymon Borak,Wolfgang Karl Härdle,Brenda López-Cabrera

Publisher: Springer Science & Business Media

ISBN: 9783642111341

Category: Mathematics

Page: 229

View: 7241

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Practice makes perfect. Therefore the best method of mastering models is working with them. In this book we present a collection of exercises and solutions which can be helpful in the comprehension of Statistics of Financial Markets. The exercises illustrate the theory by discussing practical examples in detail. We provide computational solutions for the problems, which are all calculated using R and Matlab. The corresponding Quantlets - a name we give to these program codes - are provided in this book. They follow the name scheme SFSxyz123 and can be downloaded from the Springer homepage. We have sought to strike a balance between theoretical presentation and practical challenges. The book is divided into three main parts, in which we discuss option pricing, time series analysis and advanced quantitative statistical techniques in finance.
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Statistics and Data Analysis for Financial Engineering

Author: David Ruppert

Publisher: Springer Science & Business Media

ISBN: 9781441977878

Category: Business & Economics

Page: 638

View: 475

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Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnosing modeling errors. Despite some overlap with the author's undergraduate textbook Statistics and Finance: An Introduction, this book differs from that earlier volume in several important aspects: it is graduate-level; computations and graphics are done in R; and many advanced topics are covered, for example, multivariate distributions, copulas, Bayesian computations, VaR and expected shortfall, and cointegration. The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus. Some exposure to finance is helpful.
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The Statistical Mechanics of Financial Markets

Author: Johannes Voit

Publisher: Springer Science & Business Media

ISBN: 9783540262855

Category: Business & Economics

Page: 378

View: 4006

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This highly praised introductory treatment describes the parallels between statistical physics and finance - both those established in the 100-year long interaction between these disciplines, as well as new research results on financial markets. The random-walk technique, well known in physics, is also the basic model in finance, upon which are built, for example, the Black-Scholes theory of option pricing and hedging, plus methods of portfolio optimization. Here the underlying assumptions are assessed critically. Using empirical financial data and analogies to physical models such as fluid flows, turbulence, or superdiffusion, the book develops a more accurate description of financial markets based on random walks. With this approach, novel methods for derivative pricing and risk management can be formulated. Computer simulations of interacting-agent models provide insight into the mechanisms underlying unconventional price dynamics. It is shown that stock exchange crashes can be modelled in ways analogous to phase transitions and earthquakes, and sometimes have even been predicted successfully. This third edition of The Statistical Mechanics of Financial Markets especially stands apart from other treatments because it offers new chapters containing a practitioner's treatment of two important current topics in banking: the basic notions and tools of risk management and capital requirements for financial institutions, including an overview of the new Basel II capital framework which may well set the risk management standards in scores of countries for years to come.
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Business Information Sources

Author: Lorna M. Daniells

Publisher: Univ of California Press

ISBN: 9780520081802

Category: Business & Economics

Page: 725

View: 3153

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Lists and describes the various types of general business reference sources and sources having to do with specific management functions and fields
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Statistical Models and Methods for Financial Markets

Author: Tze Leung Lai,Haipeng Xing

Publisher: Springer Science & Business Media

ISBN: 0387778268

Category: Business & Economics

Page: 356

View: 2719

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The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.
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Path Integrals in Quantum Mechanics, Statistics, Polymer Physics, and Financial Markets

Author: Hagen Kleinert

Publisher: World Scientific

ISBN: 9814273570

Category: Business & Economics

Page: 1626

View: 7856

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Topological restrictions. These are relevant to the understanding of the statistical properties of elementary particles and the entanglement phenomena in polymer physics and biophysics. The Chern-Simons theory of particles with fractional statistics (anyons) is introduced and applied to explain the fractional quantum Hall effect." "The relevance of path integrals to financial markets is discussed, and improvements of the famous Black-Scholes formula for option prices are developed which account for the fact that large market fluctuations occur much more frequently than in Gaussian distributions." --Book Jacket.
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Option Pricing and Estimation of Financial Models with R

Author: Stefano M. Iacus

Publisher: John Wiley & Sons

ISBN: 9781119990208

Category: Business & Economics

Page: 472

View: 9247

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Presents inference and simulation of stochastic process in the field of model calibration for financial times series modelled by continuous time processes and numerical option pricing. Introduces the bases of probability theory and goes on to explain how to model financial times series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets based on these models. Analysis and implementation of models goes beyond the standard Black and Scholes framework and includes Markov switching models, Lévy models and other models with jumps (e.g. the telegraph process); Topics other than option pricing include: volatility and covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book features problems with solutions and examples. All the examples and R code are available as an additional R package, therefore all the examples can be reproduced.
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Statistics for Business and Financial Economics

Author: Cheng F. Lee,John C. Lee,Alice C. Lee

Publisher: World Scientific

ISBN: 9789810234850

Category: Business & Economics

Page: 1077

View: 5305

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This text integrates various statistical techniques with concepts from business, economics and finance, and demonstrates the power of statistical methods in the real world of business. This edition places more emphasis on finance, economics and accounting concepts with updated sample data.
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The Econometrics of Financial Markets

Author: John Y. Campbell,Andrew W. Lo,A. Craig MacKinlay

Publisher: Princeton University Press

ISBN: 1400830214

Category: Business & Economics

Page: 632

View: 5659

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The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
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