TAILIEUCHUNG - Lecture Introductory Econometrics for Finance: Chapter 8 - Chris Brooks

In this chapter, students will be able to understand: Highlight the problems that may occur if non-stationary data are used in their levels form, test for unit roots, examine whether systems of variables are cointegrated, estimate error correction and vector error correction models, explain the intuition behind Johansen’s test for cointegration,. | ‘Introductory Econometrics for Finance’ © Chris Brooks 2013 Chapter 8 Modelling long-run relationship in finance Introductory Econometrics for Finance Copyright 2013, Chris Brooks ‘Introductory Econometrics for Finance’ © Chris Brooks 2013 Stationarity and Unit Root Testing Why do we need to test for Non-Stationarity? The stationarity or otherwise of a series can strongly influence its behaviour and properties - . persistence of shocks will be infinite for nonstationary series Spurious regressions. If two variables are trending over time, a regression of one on the other could have a high R2 even if the two are totally unrelated If the variables in the regression model are not stationary, then it can be proved that the standard assumptions for asymptotic analysis will not be valid. In other words, the usual “t-ratios” will not follow a t-distribution, so we cannot validly undertake hypothesis tests about the regression parameters. Introductory Econometrics for Finance

• Kinh tế học
• Econometrics for Finance
• Introductory Econometrics for Finance
• Regression model
• Purpose of econometrics
• Modelling long run relationship
• Stochastic non stationarity
• Econometric model
• Financial modelling
• Straight lines
• Statistical foundations
• Classical linear regression model
• Regression analysis
• Multiple linear regression
• Statistical distributions
• Univariate time series modelling
• Stochastic processes
• Multivariate models
• Simultaneous equations models
• Modelling volatility
• GARCH models
• Switching models
• Switching behaviour
• Panel data
• Fixed effects models
• Limited dependent variable models
• Linear probability model
• Simulation methods
• Random number generation
• Empirical research project
• Research project
• Financial data