|Item type||Location||Collection||Call number||Copy number||Status||Date due|
|Text||Reserve Section||Non Fiction||332.015118 BOF 2016 (Browse shelf)||C-1||Not For Loan|
|Text||Circulation Section||Non Fiction||332.015118 BOF 2016 (Browse shelf)||C-2||Checked out||18/04/2019|
Includes bibliographical references (pages 261-265) and indexes.
Table of contents ntroduction to financial time series The object of interestApproaching the datasetNormality Stationarity Autocorrelation HeteroskedasticityLinear time seriesModel selection How to import data ARMA models Autoregressive (AR) processesMoving-average (MA) processes Autoregressive moving-average (ARMA) processes Application of ARMA models Modeling volatilities, ARCH models, and GARCH models Introduction ARCH models ARCH(p) GARCH models Asymmetric GARCH models Alternative GARCH models Multivariate GARCH modelsIntroduction Multivariate GARCH Direct generalizations of the univariate GARCH model of Bollerslev Nonlinear combination of univariate GARCH-common features Final remarksRisk management Introduction Loss Risk measures VaR Backtesting procedures Contagion analysis Introduction Contagion measurement
Financial Econometrics Using Stata is an essential reference for graduate students, researchers, and practitioners who use Stata to perform intermediate or advanced methods. After discussing the characteristics of financial time series, the authors provide introductions to ARMA models, univariate GARCH models, multivariate GARCH models, and applications of these models to financial time series. The last two chapters cover risk management and contagion measures. After a rigorous but intuitive overview, the authors illustrate each method by interpreting easily replicable Stata examples.