Statistical Analysis of Financial Data in R (Springer Texts in Statistics) - Image 1

Price loading...

Springer Statistical Analysis of Financial Data in R (Springer Texts in Statistics)

Name: B0CY7WNVSB
Brand: Springer

Econometrics

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

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.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 1493938355
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 17 September 2016
Listed Since: 15 September 2016

Barcode

No barcode data available

Springer Statistical Analysis of Financial Data in R (Springer Texts in Statistics)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Statistical Analysis of Financial Data in R (Springer Texts in Statistics)

Statistics and Data Analysis for Financial Engineering: with R examples (Springer Texts in Statistics)

Statistics and Data Analysis for Financial Engineering: with R examples (Springer Texts in Statistics)

Statistical Analysis of Financial Data: With Examples In R (Chapman & Hall/CRC Texts in Statistical Science)

An Introduction to Data Analysis in R: Hands-on Coding, Data Mining, Visualization and Statistics from Scratch (Use R!)

Computational Finance: An Introductory Course with R: 1 (Atlantis Studies in Computational Finance and Financial Engineering, 1)

Mathematical and Statistical Methods for Actuarial Sciences and Finance

Financial, Macro and Micro Econometrics Using R: Volume 42 (Handbook of Statistics, Volume 42)

Statistics for Finance: Texts in Statistical Science (Chapman & Hall/CRC Texts in Statistical Science)

Monte Carlo Statistical Methods (Springer Texts in Statistics)

Probability, Random Variables, and Data Analytics with Engineering Applications

Tidy Finance with R (Chapman & Hall/CRC The R Series)

Financial Econometrics (Routledge Advanced Texts in Economics and Finance)

Large Deviations and Asymptotic Methods in Finance: 110 (Springer Proceedings in Mathematics & Statistics, 110)

Statistics and Finance: An Introduction (Springer Texts in Statistics)

Analyzing Financial Data and Implementing Financial Models Using R (Springer Texts in Business and Economics)

Analyzing Financial Data and Implementing Financial Models Using R (Springer Texts in Business and Economics)

Recent Studies on Risk Analysis and Statistical Modeling (Contributions to Statistics)

Statistical Analysis of Management Data

Engineering Risk and Finance: 188 (International Series in Operations Research & Management Science, 188)

Mathematical and Statistical Methods for Actuarial Sciences and Finance: MAF 2018

Functional Data Analysis with R (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Probability, Statistics, and Data: A Fresh Approach Using R (Chapman & Hall/CRC Texts in Statistical Science)

Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics)