Kasa.ComT: Common Trend(s) according to Kasa(1992)
In Fan-Yang-Econ/CommonTrend: Extract and plot common trends from a cointegration system. Calculate P-value for Johansen Statistics.

Description Usage Arguments Details Value Author(s) References See Also Examples

Extract Common Trend(s) from a cointegration system according to Kasa(1992). Loading Matrix and Othogonal Complement of alpha and beta are also reported.

1	Kasa.ComT(data, rank, k)

`data`	Data used to construct the cointegration system
`rank`	Number of cointegration vectors specified
`k`	Lag order in VECM

Common trends extracted using Kasa's method does not necessarily correspond to the Permanent part in the original series. But the advantage of this method is that it only uses β to construct common trends, and β has a nice propery which α does not have: Super Consistent.

Though this method does not involve α, α is also reported for your convenience.

Currently this function assumes that no determinstic parts, such as the constant and the trend, are in the Error-Correction Terms (ECT). But it does allow the existence of constant term in the VECM (just outside ECT).

An object of class ComT.

Fan Yang

Kasa, K., 1992. Common stochastic trends in international stock markets, Journal of Monetary Economics 29, 95-124.

Gonzalo, J., and C. Granger, 1995. Estimation of Common Long-Memory Components in Cointegrated Systems, Journal of Business & Economic Statistics 13, 27-35.

ComT-class,plotComT

 
 data(benchmark)
 x=seq(1,6689,by=23) ## monthly data
 global=data.frame(benchmark[x,2:4])
 
 Kasa.ComT (global,2,4)
 
 ## Plot the Common Trend

 K=GG.ComT (global,2,4)

 Date=benchmark[x,1]
 plotComT(K,1,x.axis=Date,approx.ticks=12,
         legend=c("S&P 500 Price index", "Common Trend"),
         main="Extract Common Trend(s) from Benchmark Markets",
         ylab="Price", xlab="Time"  )