tailieunhanh - Lecture Introductory econometrics for finance – Chapter 8: Modelling long-run relationship in finance

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,. | Chapter 8 Modelling long-run relationship in finance ‘Introductory Econometrics for Finance’ c Chris Brooks 2013 1 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 R 2 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’ c Chris Brooks 2013 2 Value of R 2 for 1000 Sets of Regressions of a Non-stationary Variable on another Independent Non-stationary Variable 200 frequency 160 120 80 40 0 2 ‘Introductory Econometrics for Finance’ c Chris Brooks 2013 3 Value of t-ratio on Slope Coefficient for 1000 Sets of Regressions of a Non-stationary Variable on another Independent Non-stationary Variable 120 100 frequency 80 60 40 20 0 –750 –500 –250 ‘Introductory Econometrics for Finance’ c Chris Brooks 2013 0 t-ratio 250 500 750 4 Two types of Non-Stationarity • Various definitions of non-stationarity exist • In this chapter, we are really referring to the weak form or covariance stationarity • There are two models which have been frequently used to characterise non-stationarity: the random walk model with drift: yt = µ + yt−1 + ut (1) and the deterministic trend process: yt = α + βt + ut (2) where ut is iid in both cases. ‘Introductory Econometrics for Finance’ c Chris Brooks .

• Kinh tế học
• Modelling long run relationship
• Stochastic non stationarity
• Econometrics for Finance
• Introductory Econometrics for Finance
• Financial data
• Financial modelling
• Univariate time series modelling
• Stochastic processes
• Modelling volatility
• GARCH models
• Teachers’ financial literacy
• Does it impact on financial behaviour
• Long term planning
• The Greater Jakarta
• Partial Least Square Structural Equation Modelling
• Financial literacy on financial behaviour among teachers
• Islamic banking
• Mathematical modeling
• Product musharaka Islamic financial risk
• Modelling and assessment
• Manage risks related
• Lecture Consumer finance
• Rational economic choice
• Financial decisions
• Modelling human financial behavior
• Optimal consumption
• strategic benchmark
• financial planner
• individual accounts
• modelling uncertainty
• parameter lognormal
• performance measurement
• Business Cycles
• Financial Crises
• Dynamic Economic Development
• Unfinished Research Agenda
• Cycle Modelling
• Business Cycle Theory
• Purpose of econometrics
• Econometric model
• Classical linear regression model
• Multiple linear regression
• Multivariate models
• Simultaneous equations models
• Switching models
• Switching behaviour
• Panel data
• Fixed effects models
• Limited dependent variable models
• Linear probability model
• Evolution of analytical methods
• Real world inferential insights
• Miller and Modigliani
• Firm’s financial leverage
• Corporate bankruptcy model
• Indian Construction Industry
• Structural Equation Modelling
• Financial and non financial encouragements
• Employees of construction industry
• Help of structure questionnaires
• Modelling
• Virtual Crack Closure
• Technique and Finite
• Predicting the Delamination
• Growth Initiation
• Composite Structures
• Modelling Methodology
• Business Perspective
• Conceptual Data Model
• Role Model
• Financial Instruments
• Practical Risk
• ncreasingly
• economic development
• abandoning traditional
• recruiting large
• tax breaks
• financial incentives
• Introduction to Computing
• Financial Accounting Systems
• Booking Systems
• Management Applications
• Modelling and Simulation
• Reasons for using simulations
• Journa science
• International journal of financial research
• Value at Risk modelling
• Warsaw Stock Exchange
• Realized volatility
• Straight lines
• Statistical foundations
• Regression analysis
• Statistical distributions
• Simulation methods
• Random number generation