Librarian View

a| 2005017245

a| 0470013214 (pbk. : alk. paper)

a| (HKSYU)b11693794-852hksyu_inst

a| DLC c| DLC d| DLC d| HKSYC

a| pcc

a| HG106 b| .K67 2006

a| HG106 b| .K667 2006 9| wsl

a| 332/.01/5195 2| 22

a| 332.015195 b| KOO 2006

a| Koop, Gary.

a| Analysis of financial data / c| by Gary Koop.

a| Hoboken, NJ : b| John Wiley & Sons Inc., c| c2006.

a| x, 240 p. : b| ill. ; c| 25 cm.

a| Includes bibliographical references and index.

a| 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.

a| Finance x| Mathematical models.

a| Econometrics.

a| b11693794 b| 24-03-22 c| 17-11-05

a| wpc b| ksc

a| (HKSYC)500599275 9| ExL

a| book b| 20-12-05 c| m d| a e| - f| eng g| nju h| 0 i| 0

h| Principal l| location i| barcode y| id f| bookplate a| callnoa b| callnob n| FIN410

h| Principal l| location i| barcode y| id f| bookplate a| callnoa b| callnob n| FIN410