An Introduction To Analysis Of Financial Data With R

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An Introduction to Analysis of Financial Data with R

Author : Ruey S. Tsay
Publisher : John Wiley & Sons
Page : 341 pages
File Size : 50,6 Mb
Release : 2014-08-21
Category : Business & Economics
ISBN : 9781119013464

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An Introduction to Analysis of Financial Data with R by Ruey S. Tsay Pdf

A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including: Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques. An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.

Statistical Analysis of Financial Data

Author : James Gentle
Publisher : CRC Press
Page : 666 pages
File Size : 53,7 Mb
Release : 2020-03-12
Category : Business & Economics
ISBN : 9780429939235

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Statistical Analysis of Financial Data by James Gentle Pdf

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.

Statistical Analysis of Financial Data in R

Author : René Carmona
Publisher : Springer Science & Business Media
Page : 588 pages
File Size : 44,6 Mb
Release : 2013-12-13
Category : Business & Economics
ISBN : 9781461487883

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Statistical Analysis of Financial Data in R by René Carmona Pdf

Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns of risk management are addressed by the study of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Principal component analysis (PCA), smoothing, and regression techniques are applied to the construction of yield and forward curves. Time series analysis is applied to the study of temperature options and nonparametric estimation. Nonlinear filtering is applied to Monte Carlo simulations, option pricing and earnings prediction. This textbook is intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. It is sprinkled with practical examples using market data, and each chapter ends with exercises. Practical examples are solved in the R computing environment. They illustrate problems occurring in the commodity, energy and weather markets, as well as the fixed income, equity and credit markets. The examples, experiments and problem sets are based on the library Rsafd developed for the purpose of the text. The book should help quantitative analysts learn and implement advanced statistical concepts. Also, it will be valuable for researchers wishing to gain experience with financial data, implement and test mathematical theories, and address practical issues that are often ignored or underestimated in academic curricula. This is the new, fully-revised edition to the book Statistical Analysis of Financial Data in S-Plus. René Carmona is the Paul M. Wythes '55 Professor of Engineering and Finance at Princeton University in the department of Operations Research and Financial Engineering, and Director of Graduate Studies of the Bendheim Center for Finance. His publications include over one hundred articles and eight books in probability and statistics. He was elected Fellow of the Institute of Mathematical Statistics in 1984, and of the Society for Industrial and Applied Mathematics in 2010. He is on the editorial board of several peer-reviewed journals and book series. Professor Carmona has developed computer programs for teaching statistics and research in signal analysis and financial engineering. He has worked for many years on energy, the commodity markets and more recently in environmental economics, and he is recognized as a leading researcher and expert in these areas.

Statistics and Data Analysis for Financial Engineering

Author : David Ruppert,David S. Matteson
Publisher : Springer
Page : 719 pages
File Size : 46,9 Mb
Release : 2015-04-21
Category : Business & Economics
ISBN : 9781493926145

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Statistics and Data Analysis for Financial Engineering by David Ruppert,David S. Matteson Pdf

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.

Applied Probabilistic Calculus for Financial Engineering

Author : Bertram K. C. Chan
Publisher : John Wiley & Sons
Page : 532 pages
File Size : 40,8 Mb
Release : 2017-10-16
Category : Mathematics
ISBN : 9781119387619

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Applied Probabilistic Calculus for Financial Engineering by Bertram K. C. Chan Pdf

Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering—walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed—along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a "Random Walk" Financial Theory look like? Covers the GBM Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.

Analyzing Financial Data and Implementing Financial Models Using R

Author : Clifford S. Ang
Publisher : Springer Nature
Page : 465 pages
File Size : 40,9 Mb
Release : 2021-06-23
Category : Business & Economics
ISBN : 9783030641559

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Analyzing Financial Data and Implementing Financial Models Using R by Clifford S. Ang Pdf

This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.

Analysis of Financial Time Series

Author : Ruey S. Tsay
Publisher : John Wiley & Sons
Page : 724 pages
File Size : 44,6 Mb
Release : 2010-10-26
Category : Mathematics
ISBN : 9781118017098

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Analysis of Financial Time Series by Ruey S. Tsay Pdf

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

Computational Finance

Author : Argimiro Arratia
Publisher : Springer Science & Business Media
Page : 301 pages
File Size : 45,9 Mb
Release : 2014-05-08
Category : Computers
ISBN : 9789462390706

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Computational Finance by Argimiro Arratia Pdf

The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.

Financial Analytics with R

Author : Mark J. Bennett,Dirk L. Hugen
Publisher : Cambridge University Press
Page : 397 pages
File Size : 47,7 Mb
Release : 2016-10-06
Category : Business & Economics
ISBN : 9781107150751

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Financial Analytics with R by Mark J. Bennett,Dirk L. Hugen Pdf

Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

Introduction to R for Quantitative Finance

Author : Gergely Daróczi,Michael Puhle,Edina Berlinger,Péter Csóka,Daniel Havran,Márton Michaletzky,Zsolt Tulassay,Kata Váradi,Agnes Vidovics-Dancs
Publisher : Packt Publishing Ltd
Page : 253 pages
File Size : 55,8 Mb
Release : 2013-11-22
Category : Computers
ISBN : 9781783280940

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Introduction to R for Quantitative Finance by Gergely Daróczi,Michael Puhle,Edina Berlinger,Péter Csóka,Daniel Havran,Márton Michaletzky,Zsolt Tulassay,Kata Váradi,Agnes Vidovics-Dancs Pdf

This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.

Multivariate Time Series Analysis

Author : Ruey S. Tsay
Publisher : John Wiley & Sons
Page : 414 pages
File Size : 40,7 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9781118617755

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Multivariate Time Series Analysis by Ruey S. Tsay Pdf

An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.

Computational Finance and Financial Econometrics

Author : Eric Zivot
Publisher : CRC Press
Page : 500 pages
File Size : 43,7 Mb
Release : 2017-01-15
Category : Electronic
ISBN : 1498775772

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Computational Finance and Financial Econometrics by Eric Zivot Pdf

This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. The author explains how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios.

Financial Statement Analysis

Author : Martin S. Fridson,Fernando Alvarez
Publisher : John Wiley & Sons
Page : 414 pages
File Size : 47,8 Mb
Release : 2002-10-01
Category : Business & Economics
ISBN : 9780471264606

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Financial Statement Analysis by Martin S. Fridson,Fernando Alvarez Pdf

Praise for Financial Statement Analysis A Practitioner's Guide Third Edition "This is an illuminating and insightful tour of financial statements, how they can be used to inform, how they can be used to mislead, and how they can be used to analyze the financial health of a company." -Professor Jay O. Light Harvard Business School "Financial Statement Analysis should be required reading for anyone who puts a dime to work in the securities markets or recommends that others do the same." -Jack L. Rivkin Executive Vice President (retired) Citigroup Investments "Fridson and Alvarez provide a valuable practical guide for understanding, interpreting, and critically assessing financial reports put out by firms. Their discussion of profits-'quality of earnings'-is particularly insightful given the recent spate of reporting problems encountered by firms. I highly recommend their book to anyone interested in getting behind the numbers as a means of predicting future profits and stock prices." -Paul Brown Chair-Department of Accounting Leonard N. Stern School of Business, NYU "Let this book assist in financial awareness and transparency and higher standards of reporting, and accountability to all stakeholders." -Patricia A. Small Treasurer Emeritus, University of California Partner, KCM Investment Advisors "This book is a polished gem covering the analysis of financial statements. It is thorough, skeptical and extremely practical in its review." -Daniel J. Fuss Vice Chairman Loomis, Sayles & Company, LP

The R Book

Author : Michael J. Crawley
Publisher : John Wiley & Sons
Page : 953 pages
File Size : 51,6 Mb
Release : 2007-06-13
Category : Mathematics
ISBN : 0470515066

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The R Book by Michael J. Crawley Pdf

The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.

Statistics of Financial Markets

Author : Szymon Borak,Wolfgang Karl Härdle,Brenda López-Cabrera
Publisher : Springer Science & Business Media
Page : 246 pages
File Size : 41,6 Mb
Release : 2013-01-11
Category : Business & Economics
ISBN : 9783642339295

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Statistics of Financial Markets by Szymon Borak,Wolfgang Karl Härdle,Brenda López-Cabrera Pdf

Practice makes perfect. Therefore the best method of mastering models is working with them. This book contains a large collection of exercises and solutions which will help explain the statistics of financial markets. These practical examples are carefully presented and provide computational solutions to specific problems, all of which are calculated using R and Matlab. This study additionally looks at the concept of corresponding Quantlets, the name given to these program codes and which follow the name scheme SFSxyz123. The book is divided into three main parts, in which option pricing, time series analysis and advanced quantitative statistical techniques in finance is thoroughly discussed. The authors have overall successfully created the ideal balance between theoretical presentation and practical challenges.