Research and Markets: Probability and Statistics for Finance

DUBLIN--(BUSINESS WIRE)--Research and Markets (http://www.researchandmarkets.com/research/273f64/probability_and_st) has announced the addition of John Wiley and Sons Ltd's new book "Probability and Statistics for Finance" to their offering.

A comprehensive look at how probability and statistics is applied to the investment process

Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before. In order to keep up, you need a firm understanding of this discipline.

Probability and Statistics for Finance addresses this issue by showing you how to apply quantitative methods to portfolios, and in all matter of your practices, in a clear, concise manner. Informative and accessible, this guide starts off with the basics and builds to an intermediate level of mastery.

• Outlines an array of topics in probability and statistics and how to apply them in the world of finance
• Includes detailed discussions of descriptive statistics, basic probability theory, inductive statistics, and multivariate analysis
• Offers real-world illustrations of the issues addressed throughout the text

The authors cover a wide range of topics in this book, which can be used by all finance professionals as well as students aspiring to enter the field of finance.

Key Topics Covered:

PART ONE Descriptive Statistics.

• Basic Data Analysis.
• Measures of Location and Spread.
• Graphical Representation of Data.
• Multivariate Variables and Distributions.
• Introduction to Regression Analysis.
• Introduction to Time Series Analysis.

PART TWO Basic Probability Theory.

• Concepts of Probability Theory.
• Discrete Probability Distributions.
• Continuous Probability Distributions.
• Continuous Probability Distributions with Appealing Statistical Properties.
• Continuous Probability Distributions Dealing with Extreme Events.
• Parameters of Location and Scale of Random Variables.
• Joint Probability Distributions.
• Conditional Probability and Bayes' Rule.
• Copula and Dependence Measures.

PART THREE Inductive Statistics.

• Point Estimators.
• Confidence Intervals.
• Hypothesis Testing.

PART FOUR Multivariate Linear Regression Analysis.

• Estimates and Diagnostics for Multivariate Linear Regression Analysis.
• Designing and Building a Multivariate Linear Regression Model.
• Testing the Assumptions of the Multivariate Linear Regression Model.

APPENDICES:

• Important Functions and Their Features.
• Fundamentals of Matrix Operations and Concepts.
• Binomial and Multinomial Coefficients.
• Application of the Log-Normal Distribution to the Pricing of Call Options.

Author:

SVETLOZAR T. RACHEV, PhD, DSC, is Chair Professor at the University of Karlsruhe in the School of Economics and Business Engineering, and Professor Emeritus at the University of California, Santa Barbara, in the Department of Statistics and Applied Probability. He was cofounder of Bravo Risk Management Group, acquired by FinAnalytica, where he currently serves as Chief Scientist.

MARKUS HCHSTTTER, PhD, is an Assistant Professor in the Department of Econometrics and Statistics, University of Karlsruhe.

FRANK J. FABOZZI, PhD, CFA, CPA, is Professor in the Practice of Finance and Becton Fellow at the Yale School of Management and Editor of the Journal of Portfolio Management. He is an Affiliated Professor at the University of Karlsruhe's Institute of Statistics, Econometrics and Mathematical Finance, and is on the Advisory Council for the Department of Operations Research and Financial Engineering at Princeton University.

SERGIO M. FOCARDI, PhD, is a Professor of Finance at EDHEC Business School and founding partner of the Paris-based consulting firm Intertek Group plc.

For more information visit http://www.researchandmarkets.com/research/273f64/probability_and_st