R Programming and Its Applications in Financial Mathematics

R Programming and Its Applications in Financial Mathematics
Author: Shuichi Ohsaki
Publisher: CRC Press
Total Pages: 310
Release: 2018-01-31
Genre: Business & Economics
ISBN: 1351649868
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This book provides an introduction to R programming and a summary of financial mathematics. It is not always easy for graduate students to grasp an overview of the theory of finance in an abstract form. For newcomers to the finance industry, it is not always obvious how to apply the abstract theory to the real financial data they encounter. Introducing finance theory alongside numerical applications makes it easier to grasp the subject. Popular programming languages like C++, which are used in many financial applications are meant for general-purpose requirements. They are good for implementing large-scale distributed systems for simultaneously valuing many financial contracts, but they are not as suitable for small-scale ad-hoc analysis or exploration of financial data. The R programming language overcomes this problem. R can be used for numerical applications including statistical analysis, time series analysis, numerical methods for pricing financial contracts, etc. This book provides an overview of financial mathematics with numerous examples numerically illustrated using the R programming language.

R Programming and Its Applications in Financial Mathematics

R Programming and Its Applications in Financial Mathematics
Author: Shuichi Ohsaki
Publisher: CRC Press
Total Pages: 259
Release: 2018-01-31
Genre: Business & Economics
ISBN: 1498766102
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Download R Programming and Its Applications in Financial Mathematics Book in PDF, Epub and Kindle

This book provides an introduction to R programming and a summary of financial mathematics. It is not always easy for graduate students to grasp an overview of the theory of finance in an abstract form. For newcomers to the finance industry, it is not always obvious how to apply the abstract theory to the real financial data they encounter. Introducing finance theory alongside numerical applications makes it easier to grasp the subject. Popular programming languages like C++, which are used in many financial applications are meant for general-purpose requirements. They are good for implementing large-scale distributed systems for simultaneously valuing many financial contracts, but they are not as suitable for small-scale ad-hoc analysis or exploration of financial data. The R programming language overcomes this problem. R can be used for numerical applications including statistical analysis, time series analysis, numerical methods for pricing financial contracts, etc. This book provides an overview of financial mathematics with numerous examples numerically illustrated using the R programming language.

Introduction to Financial Mathematics

Introduction to Financial Mathematics
Author: Donald R. Chambers
Publisher: CRC Press
Total Pages: 581
Release: 2021-06-16
Genre: Computers
ISBN: 1000370127
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This book’s primary objective is to educate aspiring finance professionals about mathematics and computation in the context of financial derivatives. The authors offer a balance of traditional coverage and technology to fill the void between highly mathematical books and broad finance books. The focus of this book is twofold: To partner mathematics with corresponding intuition rather than diving so deeply into the mathematics that the material is inaccessible to many readers. To build reader intuition, understanding and confidence through three types of computer applications that help the reader understand the mathematics of the models. Unlike many books on financial derivatives requiring stochastic calculus, this book presents the fundamental theories based on only undergraduate probability knowledge. A key feature of this book is its focus on applying models in three programming languages –R, Mathematica and EXCEL. Each of the three approaches offers unique advantages. The computer applications are carefully introduced and require little prior programming background. The financial derivative models that are included in this book are virtually identical to those covered in the top financial professional certificate programs in finance. The overlap of financial models between these programs and this book is broad and deep.

R Programming for Actuarial Science

R Programming for Actuarial Science
Author: Peter McQuire
Publisher: John Wiley & Sons
Total Pages: 645
Release: 2023-10-16
Genre: Computers
ISBN: 1119754976
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R Programming for Actuarial Science Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. In R Programming for Actuarial Science, readers will find: Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth. Topics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses. More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles. An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic. Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is an essential reference for BSc/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.

Computational Finance with R

Computational Finance with R
Author: Rituparna Sen
Publisher: Springer Nature
Total Pages: 352
Release: 2023-05-16
Genre: Business & Economics
ISBN: 9811920087
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This book prepares students to execute the quantitative and computational needs of the finance industry. The quantitative methods are explained in detail with examples from real financial problems like option pricing, risk management, portfolio selection, etc. Codes are provided in R programming language to execute the methods. Tables and figures, often with real data, illustrate the codes. References to related work are intended to aid the reader to pursue areas of specific interest in further detail. The comprehensive background with economic, statistical, mathematical, and computational theory strengthens the understanding. The coverage is broad, and linkages between different sections are explained. The primary audience is graduate students, while it should also be accessible to advanced undergraduates. Practitioners working in the finance industry will also benefit.

The Book of R

The Book of R
Author: Tilman M. Davies
Publisher: No Starch Press
Total Pages: 833
Release: 2016-07-16
Genre: Computers
ISBN: 1593276516
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The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Computational Finance

Computational Finance
Author: Argimiro Arratia
Publisher: Springer Science & Business Media
Total Pages: 305
Release: 2014-05-08
Genre: Computers
ISBN: 9462390703
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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.

Mastering R for Quantitative Finance

Mastering R for Quantitative Finance
Author: Edina Berlinger
Publisher: Packt Publishing Ltd
Total Pages: 362
Release: 2015-03-10
Genre: Computers
ISBN: 1783552085
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This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.

Introduction to Financial Mathematics

Introduction to Financial Mathematics
Author: Donald Robert Chambers
Publisher: CRC Press
Total Pages: 0
Release: 2024-08-26
Genre: Biography & Autobiography
ISBN: 9780367752781
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This book's primary objective is to educate aspiring finance professionals about mathematics and computation in the context of financial derivatives. The authors offer a balance of traditional coverage and technology to fill the void between highly mathematical books and broad finance books.

Quantitative Methods in Finance using R

Quantitative Methods in Finance using R
Author: John Fry
Publisher: McGraw-Hill Education (UK)
Total Pages: 264
Release: 2022-07-04
Genre: Business & Economics
ISBN: 0335251277
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“The book will form a solid foundation to support the transition of students into the world of work or further research.” Professor Jane M Binner, Chair of Finance, Department of Finance, University of Birmingham, UK “In over 20 years of teaching quantitative methods, I have rarely come across a book such as this which meets/exceeds all the expectations of its intended audience so well” Tuan Yu, Lecturer, Kent Business School, Canterbury, UK “This is a fantastic book for anyone wanting to understand, learn and apply quantitative methods in finance using R” Professor Raphael Markellos, Professor of Finance, Norwich Business School, UK Quantitative Methods in Finance Using R draws on the extensive teaching and research expertise of John Fry and Matt Burke, covering a wide range of quantitative methods in Finance that utilise the freely downloadable R software. With software playing an increasingly important role in finance, this book is a must-have introduction for finance students who want to explore how they can undertake their own quantitative analyses in dissertation and project work. Assuming no prior knowledge, and taking a holistic approach, this brand new title guides you from first principles and help to build your confidence in tackling large data sets in R. Complete with examples and exercises with worked solutions, Fry and Burke demonstrate how to use the R freeware for regression and linear modelling, with attention given to presentation and the importance of good writing and presentation skills in project work and data analysis more generally. Through this book, you will develop your understanding of: •Descriptive statistics •Inferential statistics •Regression •Analysis of variance •Probability regression models •Mixed models •Financial and non-financial time series John Fry is a senior lecturer in Applied Mathematics at the University of Hull. Fry has a PhD in Mathematical Finance from the University of Sheffield. His main research interests span mathematical finance, econophysics, statistics and operations research. Matt Burke is a senior lecturer in Finance at Sheffield Hallam University. He holds a PhD in Finance from the University of East Anglia. Burke’s main research interests lie in asset pricing and climate finance.