Introduction to Statistical Methods for Financial Models

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A01=Thomas A Severini
advanced portfolio analysis
asset pricing
asset pricing theory
Asset Returns
Author_Thomas A Severini
Box Ljung Test
Category=KCH
Category=PBW
Conditional Expectation
econometrics applications
Efficient Frontier
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
EWMA Estimator
Excess Returns
factor model
Factor SMB
financial risk modeling
French Data Library
IBM Stock
Large Sharpe Ratio
market model
Market Portfolio
Minimum Variance Portfolio
Monthly Excess Returns
Monthly Log Returns
multivariate statistics
Nonmarket Component
portfolio theory
Portfolio Weights
quantitative finance
Random Walk Hypothesis
Return Standard Deviation
returns
Risk Averse Portfolio
Risk Free Asset
Sample Autocorrelation Function
Sharpe Ratio
Single Index Model
statistical modeling for finance students
Tangency Portfolio
Thomas A. Severini
Wal Mart Stock

Product details

  • ISBN 9781138198371
  • Weight: 870g
  • Dimensions: 156 x 234mm
  • Publication Date: 12 Jul 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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.

Thomas A. Severini is a professor of statistics at Northwestern University. He is a fellow of the American Statistical Association and the author of Likelihood Methods in Statistics and Elements of Distribution Theory. He received his PhD in statistics from the University of Chicago. His research areas include likelihood inference, nonparametric and semiparametric methods, and applications to econometrics.

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