advanced-algorithmic-trading

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We can replicate the above steps for RDS-A and RDS-B as we did for EWA and EWC. The
full code to carry this out is given below. The only minor difference is that we need to utilise
the get("...") R function, since quantmod pulls in RDS-A as the variable "RDS-A". R does
not like hyphens in variable names as the minus operator takes precedence. Hence we need to
use get as a workaround:
> getSymbols("RDS-A", from="2006-01-01", to="2015-12-31")
> getSymbols("RDS-B", from="2006-01-01", to="2015-12-31")
> RDSA <- get("RDS-A")
> RDSB <- get("RDS-B")
> rdsaAdj = unclass(RDSA$"RDS-A.Adjusted")
> rdsbAdj = unclass(RDSB$"RDS-B.Adjusted")
We can plot both share classes on the same chart. Clearly they are tightly cointegrated:
> plot(rdsaAdj, type="l", xlim=c(0, 2517), ylim=c(25.0, 80.0),
xlab="January 1st 2006 to December 31st 2015",
ylab="RDS-A and RDS-B Backward-Adjusted Closing Price in GBP", col="blue")
> par(new=T)
> plot(rdsbAdj, type="l", xlim=c(0, 2517), ylim=c(25.0, 80.0), axes=F,
xlab="", ylab="", col="red")
> par(new=F)
Figure 12.9: Backward-adjusted closing prices of RDS-A and RDS-B
We can also plot a scatter graph of the two price series. It is apparent how tight the linear
relationship between them is. This is no surprise given that they track the same underlying
equity: