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Analysis of financial data
Koop, Gary.
Hoboken, NJ : John Wiley & Sons Inc., c2006.
Bibliographic Information
| Format: | Book |
|---|---|
| Author: | Koop, Gary. |
| Subject: |
Finance Econometrics |
| Publication Year: | 2006 |
| Language: | English |
| Published: | Hoboken, NJ : John Wiley & Sons Inc., c2006. |
| ISBN: | 9780470013212 0470013214 0470013214 (pbk. : alk. paper) |
| Notes: | Includes bibliographical references and index. Introduction -- Organization of the book -- Useful background -- Appendix 1.1: Concepts in mathematics used in this book -- Basic data handling -- Types of financial data -- Obtaining data -- Working with data: graphical methods -- Working with data: descriptive statistics -- Expected values and variances -- Chapter summary -- Appendix 2.1: Index numbers -- Appendix 2.2: Advanced descriptive statistics -- Correlation -- Understanding correlation -- Understanding why variables are correlated -- Understanding correlation through xy-plots -- Correlation between several variables -- Covariances and population correlations -- Chapter summary -- Appendix 3.1: Mathematical details -- An introduction to simple regression -- Regression as a best fitting line -- Interpreting OLS estimates -- Fitted values and r2: Measuring the fit of a regression model -- Nonlinearity in regression -- Chapter summary -- Appendix 4.1: Mathematical details -- Statistical aspects of regression -- Which factors affect the accuracy of the estimate ?? -- Calculating a confidence interval for ? -- Testing whether ????? -- Hypothesis testing involving r2: The f-statistic -- Chapter summary -- Appendix 5.1: Using statistical tables for testing whether ????? -- Multiple regression -- Regression as a best fitting line -- Ordinary least squares estimation of the multiple regression model -- Statistical aspects of multiple regression -- Interpreting OLS estimates -- Pitfalls of using simple regression in a multiple regression context -- Omitted variables bias -- Multicollinearity -- Chapter summary -- Appendix 6.1: Mathematical interpretation of regression coefficients -- Regression with dummy variables -- Simple regression with a dummy variable -- Multiple regression with dummy variables -- Multiple regression with both dummy and non-dummy explanatory variables -- Interacting dummy and non-dummy variables -- What if the dependent variable is a dummy? -- Chapter summary -- Regression with lagged explanatory variables -- Aside on lagged variables -- Aside on notation -- Selection of lag order -- Chapter summary -- Univariate time series analysis -- The autocorrelation function -- The autoregressive model for univariate time series -- Nonstationary versus stationary time series -- Extensions of the AR(1) model -- Testing in the AR(p) with deterministic trend model -- Chapter summary -- Appendix 9.1: Mathematical intuition for the AR(1) model -- Regression with time series variables -- Time series regression when x and y are stationary -- Time series regression when y and x have unit roots: spurious regression -- Time series regression when y and x have unit roots: cointegration -- Time series regression when y and x are cointegrated: the error correction model -- Time series regression when y and x have unit roots but are not cointegrated -- Chapter summary -- Regression with times series variables with several equations -- Granger causality -- Vector autoregressions -- Chapter summary -- Appendix 11.1: Hypothesis tests involving more than one coefficient -- Appendix 11.2: Variance decompositions -- Financial volatility -- Volatility in asset prices: Introduction -- Autoregressive conditional heteroskedasticity (arch) -- Chapter summary -- Appendix A Writing an empirical project -- Description of a typical empirical project -- General considerations. |
| Course: |
FIN410 |
Availability at HKSYU Library
| Location | Call number | Status |
|---|---|---|
| English Book (4/F) | 332.015195 KOO 2006 | Available |
| English Book (4/F) | 332.015195 KOO 2006 | Available |