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Analysis of Integrated and Cointegrated Time Series with R (Use R) Bernhard Pfaff
Publisher: Springer

As we saw in the definitions near the start of this post, this model would be of the general form: ΔCt = α1 + α2ΔYt + α3Rt-1 + ut , where Rt is the OLS residuals series from the "cointegrating regression" discussed in point 1 just above. GRASP is a combination of advanced S Plus functions and GIS (Geographical Information System) Many of these applications can be run through the software “R” (www.r-project.org). Error-correction model: Spell-checker. When I use the ADF, do I need to test the series for all 3 specifications or there is any way to decide the specification for the series? The expression "long run" means in this case the "statistical" long run, as used by Engle and Granger in their analysis of integrated and cointegrated time series variables. As for the time series script: I use the Sweave package and therefore any single number, any table or figure in my script is reproducible. The long term coefficients are statistically significant, while the . A regression model that explains the short-term dynamics of the relationship between two or more non-stationary, but cointegrated, time-series variables. If you use time series data in regression analysis, autocorrelation of residuals will be a problem area, since it will lead to an upward bias in the statistical significance of coefficient estimates. Many thanks to Bernhard Pfaff for his R package ;vars ; as well as the companion book Analysis of Integrated and Cointegrated Time Series with R, and Joel Hasbrouck for his book Empirical Market Microstructure . A Durbin Watson test can be used to .. The specification fits fairly well, with an adjusted R-squared of 0.34, and a Breusch-Godfrey Serial Correlation LM Test (2 lags) failing to reject the null at conventional levels. In theory cointegration provides a useful filter against spurious correlations. Download data source("/home/robo/Desktop/PairTrading/downloadV2.R") # Find co-integrated pairs source("/home/robo/Desktop/PairTrading/cointegrationV2.R") # Analyze data and export output file source("/home/robo/Desktop/PairTrading/ analysisV2.R") I learned at school that I should use cointegration in situations where I investigate long lasting relationship between two time series.