FINANCIAL TIME-SERIES ECONOMETRICS.ppt
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1、FINANCIAL TIME-SERIES ECONOMETRICSINTRODUCTIONContents 1. Models,Data and Process The nature of the econometric approach The Process of an econometric analysis 2. Applications of Financial Econometrics Dynamic effects of various shocks Empirical finance Refining data 3. Key Features of Financial Tim
2、e Series The regression model Time series models Dynamic model 4. Contents of Time Series Modeling Stationary stochastic time series model Nonstationary stochastic process Multiple time series modeling Time series models of heteroskedasticity State space model 5. Text and Software Text Software 6. S
3、ome Basic Tools Difference equations and their solutions Solution methodology Stability conditions Impulse response function The basics of time series analysis software 7. Summary and Conclusions Appendix: TSP Program to Accompany Chapter 1 Box: Empirical Research on Exchange Rate Bibliography1. MOD
4、ELS, DATA AND PROCESS The Nature of The Econometric Approach structural analysis evaluation forecasting The Process of An Empirical Analysis model specification structural equations and reduced forms parameters conditions sampling and refining data Identification and estimation statistical test econ
5、omic interpretationTheoryFactsModelDataStatistical TheoryEconometric TheoryRefined DataEconometric TechniquesEstimation of Econometric Model with the Refined Data Using Econometric TechniquesEvaluationForecastingStructural AnalysisEconometric Approach Structural Analysis Econometric Model Linear mod
6、el Greene (2000) Nonlinear model* Davidson Mackinnon (1993) Static model Time series model Enders (1995) Dynamic model Christian Gourieroux (1997) Structure Change (Maddala and Kim,1998) Chow test Time-varying parametersEvaluation The Simulation Approach Identification Limited-information estimation
7、 Full-information estimation Monte Carlo studies Other Approaches The Instruments-targets approach The Social-welfare-function approachForecasting Forecasting Methods Sample information Economic theory Introduction to Forecasting Techniques Time series model (ARIMA,GARCH,KALMAN-filter) Statistical m
8、odel (Monte Carlo techniques,MSFE) Data and Refining Type Quantitative versus qualitative data Time-series versus cross-section data (Panel Data) Non-experimental versus experimental data Micro versus macro data Nature Degrees of freedom Multicollinearity Serial correlation Structural change Errors
9、in measurement Non-stationary Source IMF international financial statistics (CD-ROM) 2. APPLICATIONS OF FINANCIAL ECONOMETRICS Dynamic Effects of Various Shocks Transmission mechanism of financial crisis Credit channel of policy Empirical Finance Forecasting(price of capital assets, risk premium,etc
10、.) Predictability of asset returns Market microstructure Term structure Financial integration Refining Data Missing data Base changes (GDP,M1,etc.) Nonstationary (EX,IR,etc.)3. KEY FEASURES OF FINANCIAL TIME SERIES The Regression Model The Method of ordinary least squares Assumption (disturbance ter
11、m;observations, independent variables) The Gauss-Markov theorem (BLUE,consistency) Other methods of estimation Maximum likelihood Moments Bayesian approach The Probability distribution for OLS estimator Parameters and disturbance term t,F,P tests and significance (confidence intervals) Applications
12、(structural break,prediction,model selection) Extensions Diagnosis and treatment)(tttuxy Time Series Models Differences between LRM and TSM Exogenous variables,sequence,theory Components Trends Seasonality Cycle Irregularity (convergence) Conditional heteroskedasticity (volatility) Non-linearity (st
13、ate dependency) Determinants Function structure: Lag order: Dynamic Model Transfer process (impulse response function),.,(21tpttttuxxxfxfp),.,(21tptttttuyyyxfy4. CONTENTS OF TIME SERIES MODELING Stationary Stochastic Time Series Model ARMA ARIMA Nonstationary Stochastic Process Unit root test Cointe
14、gration and error correction model Multiple Time Series Modeling VAR Granger test Structural VAR Time Series Models of Heteroskedasticity ARCH GARCH State Space Model KALMAN filter Regime switching modelOther Useful Financial Econometric Models Methods of Instrumental Variables GMM Discrete and Limi
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