Statistical Models and Methods for Financial Markets

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Publisher : Springer Science & Business Media
ISBN 13 : 0387778276
Total Pages : 363 pages
Book Rating : 4.73/5 ( download)

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Book Synopsis Statistical Models and Methods for Financial Markets by : Tze Leung Lai

Download or read book Statistical Models and Methods for Financial Markets written by Tze Leung Lai and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Statistical Methods for Financial Models

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Publisher : CRC Press
ISBN 13 : 1351981900
Total Pages : 303 pages
Book Rating : 4.03/5 ( download)

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Book Synopsis Introduction to Statistical Methods for Financial Models by : Thomas A Severini

Download or read book Introduction to Statistical Methods for Financial Models written by Thomas A Severini and published by CRC Press. This book was released on 2017-07-06 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.

Statistical Methods in Finance

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Publisher :
ISBN 13 :
Total Pages : 760 pages
Book Rating : 4.50/5 ( download)

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Book Synopsis Statistical Methods in Finance by : G. S. Maddala

Download or read book Statistical Methods in Finance written by G. S. Maddala and published by . This book was released on 1996-12-11 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive reference work for teaching at graduate level and research in empirical finance. The chapters cover a wide range of statistical and probabilistic methods applied to a variety of financial methods and are written by internationally renowned experts.

Statistical Methods for Financial Engineering

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Publisher : CRC Press
ISBN 13 : 1439856958
Total Pages : 490 pages
Book Rating : 4.56/5 ( download)

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Book Synopsis Statistical Methods for Financial Engineering by : Bruno Remillard

Download or read book Statistical Methods for Financial Engineering written by Bruno Remillard and published by CRC Press. This book was released on 2016-04-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: While many financial engineering books are available, the statistical aspects behind the implementation of stochastic models used in the field are often overlooked or restricted to a few well-known cases. Statistical Methods for Financial Engineering guides current and future practitioners on implementing the most useful stochastic models used in f

A Course on Statistics for Finance

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Publisher : CRC Press
ISBN 13 : 1439892547
Total Pages : 281 pages
Book Rating : 4.41/5 ( download)

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Book Synopsis A Course on Statistics for Finance by : Stanley L. Sclove

Download or read book A Course on Statistics for Finance written by Stanley L. Sclove and published by CRC Press. This book was released on 2012-12-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taking a data-driven approach, A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introduces regression analysis, time series analysis, and multivariate analysis step by step using models and methods from finance. The book begins with a review of basic statistics, including descriptive statistics, kinds of variables, and types of data sets. It then discusses regression analysis in general terms and in terms of financial investment models, such as the capital asset pricing model and the Fama/French model. It also describes mean-variance portfolio analysis and concludes with a focus on time series analysis. Providing the connection between elementary statistics courses and quantitative finance courses, this text helps both existing and future quants improve their data analysis skills and better understand the modeling process.

Statistical Analysis of Financial Data in S-Plus

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Publisher : Springer Science & Business Media
ISBN 13 : 0387218246
Total Pages : 456 pages
Book Rating : 4.43/5 ( download)

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Book Synopsis Statistical Analysis of Financial Data in S-Plus by : René Carmona

Download or read book Statistical Analysis of Financial Data in S-Plus written by René Carmona and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book at the graduate textbook level to discuss analyzing financial data with S-PLUS. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. The book is aimed at undergraduate students in financial engineering; master students in finance and MBA's, and to practitioners with financial data analysis concerns.

Statistical Analysis of Financial Data

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Publisher : CRC Press
ISBN 13 : 042993923X
Total Pages : 666 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Statistical Analysis of Financial Data by : James Gentle

Download or read book Statistical Analysis of Financial Data written by James Gentle and published by CRC Press. This book was released on 2020-03-12 with total page 666 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets, describing the market operations and using exploratory data analysis to illustrate the nature of financial data. The software used to obtain the data for the examples in the first chapter and for all computations and to produce the graphs is R. However discussion of R is deferred to an appendix to the first chapter, where the basics of R, especially those most relevant in financial applications, are presented and illustrated. The appendix also describes how to use R to obtain current financial data from the internet. Chapter 2 describes the methods of exploratory data analysis, especially graphical methods, and illustrates them on real financial data. Chapter 3 covers probability distributions useful in financial analysis, especially heavy-tailed distributions, and describes methods of computer simulation of financial data. Chapter 4 covers basic methods of statistical inference, especially the use of linear models in analysis, and Chapter 5 describes methods of time series with special emphasis on models and methods applicable to analysis of financial data. Features * Covers statistical methods for analyzing models appropriate for financial data, especially models with outliers or heavy-tailed distributions. * Describes both the basics of R and advanced techniques useful in financial data analysis. * Driven by real, current financial data, not just stale data deposited on some static website. * Includes a large number of exercises, many requiring the use of open-source software to acquire real financial data from the internet and to analyze it.

Statistics and Data Analysis for Financial Engineering

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Publisher : Springer
ISBN 13 : 1493926144
Total Pages : 736 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Statistics and Data Analysis for Financial Engineering by : David Ruppert

Download or read book Statistics and Data Analysis for Financial Engineering written by David Ruppert and published by Springer. This book was released on 2015-04-21 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Financial Statistics and Mathematical Finance

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Publisher : John Wiley & Sons
ISBN 13 : 1118316568
Total Pages : 355 pages
Book Rating : 4.66/5 ( download)

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Book Synopsis Financial Statistics and Mathematical Finance by : Ansgar Steland

Download or read book Financial Statistics and Mathematical Finance written by Ansgar Steland and published by John Wiley & Sons. This book was released on 2012-06-21 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical finance has grown into a huge area of research which requires a lot of care and a large number of sophisticated mathematical tools. Mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, it considers various aspects of the application of statistical methods in finance and illustrates some of the many ways that statistical tools are used in financial applications. Financial Statistics and Mathematical Finance: Provides an introduction to the basics of financial statistics and mathematical finance. Explains the use and importance of statistical methods in econometrics and financial engineering. Illustrates the importance of derivatives and calculus to aid understanding in methods and results. Looks at advanced topics such as martingale theory, stochastic processes and stochastic integration. Features examples throughout to illustrate applications in mathematical and statistical finance. Is supported by an accompanying website featuring R code and data sets. Financial Statistics and Mathematical Finance introduces the financial methodology and the relevant mathematical tools in a style that is both mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, both graduate students and researchers in statistics, finance, econometrics and business administration will benefit from this book.

Statistics for Finance

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Publisher : CRC Press
ISBN 13 : 1315362554
Total Pages : 384 pages
Book Rating : 4.57/5 ( download)

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Book Synopsis Statistics for Finance by : Erik Lindström

Download or read book Statistics for Finance written by Erik Lindström and published by CRC Press. This book was released on 2018-09-03 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Itō’s formula, the Black–Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives, identify interest rate models, value bonds, estimate parameters, and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues. In addition, end-of-chapter exercises develop students’ financial reasoning skills.