Analysis of financial data
By: by Gary Koop.
Publisher: John Wiley & Sons Inc.
Published: 2006
Place of publication: Hoboken, NJ
Language: eng
Number of pages: 252
Subjects: Finance -- Mathematical models.; Econometrics.
Notes: Includes bibliographical references and index.
Table of contents: title: Introduction; title: Organization of the book; title: Useful background; title: Appendix 1.1: Concepts in mathematics used in this book; title: Basic data handling; title: Types of financial data; title: Obtaining data; title: Working with data: graphical methods; title: Working with data: descriptive statistics; title: Expected values and variances; title: Chapter summary; title: Appendix 2.1: Index numbers; title: Appendix 2.2: Advanced descriptive statistics; title: Correlation; title: Understanding correlation; title: Understanding why variables are correlated; title: Understanding correlation through xy-plots; title: Correlation between several variables; title: Covariances and population correlations; title: Chapter summary; title: Appendix 3.1: Mathematical details; title: An introduction to simple regression; title: Regression as a best fitting line; title: Interpreting OLS estimates; title: Fitted values and r2: Measuring the fit of a regression model; title: Nonlinearity in regression; title: Chapter summary; title: Appendix 4.1: Mathematical details; title: Statistical aspects of regression; title: Which factors affect the accuracy of the estimate ??; title: Calculating a confidence interval for ?; title: Testing whether ?????; title: Hypothesis testing involving r2: The f-statistic; title: Chapter summary; title: Appendix 5.1: Using statistical tables for testing whether ?????; title: Multiple regression; title: Regression as a best fitting line; title: Ordinary least squares estimation of the multiple regression model; title: Statistical aspects of multiple regression; title: Interpreting OLS estimates; title: Pitfalls of using simple regression in a multiple regression context; title: Omitted variables bias; title: Multicollinearity; title: Chapter summary; title: Appendix 6.1: Mathematical interpretation of regression coefficients; title: Regression with dummy variables; title: Simple regression with a dummy variable; title: Multiple regression with dummy variables; title: Multiple regression with both dummy and non-dummy explanatory variables; title: Interacting dummy and non-dummy variables; title: What if the dependent variable is a dummy?; title: Chapter summary; title: Regression with lagged explanatory variables; title: Aside on lagged variables; title: Aside on notation; title: Selection of lag order; title: Chapter summary; title: Univariate time series analysis; title: The autocorrelation function; title: The autoregressive model for univariate time series; title: Nonstationary versus stationary time series; title: Extensions of the AR(1) model; title: Testing in the AR(p) with deterministic trend model; title: Chapter summary; title: Appendix 9.1: Mathematical intuition for the AR(1) model; title: Regression with time series variables; title: Time series regression when x and y are stationary; title: Time series regression when y and x have unit roots: spurious regression; title: Time series regression when y and x have unit roots: cointegration; title: Time series regression when y and x are cointegrated: the error correction model; title: Time series regression when y and x have unit roots but are not cointegrated; title: Chapter summary; title: Regression with times series variables with several equations; title: Granger causality; title: Vector autoregressions; title: Chapter summary; title: Appendix 11.1: Hypothesis tests involving more than one coefficient; title: Appendix 11.2: Variance decompositions; title: Financial volatility; title: Volatility in asset prices: Introduction; title: Autoregressive conditional heteroskedasticity (arch); title: Chapter summary; title: Appendix A Writing an empirical project; title: Description of a typical empirical project; title: General considerations.