advanced-algorithmic-trading

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Figure 12.6: Backward-adjusted closing prices of EWA and EWC
You will notice that it differs slightly from the chart given in Ernie’s work as we are plotting
the adjusted prices here, rather than the unadjusted closing prices. We can also create a scatter
plot of their prices:
> plot(ewaAdj, ewcAdj, xlab="EWA Backward-Adjusted Prices",
ylab="EWC Backward-Adjusted Prices")
At this stage we need to perform the linear regressions between the two price series. However,
we have previously mentioned that it is unclear as to which series is the dependent variable and
which is the independent variable for the regression. Thus we will try both and make a choice
based on the negativity of the ADF test statistic. We will use the R linear model (lm) function
for the regression:
> comb1 = lm(ewcAdj~ewaAdj)
> comb2 = lm(ewaAdj~ewcAdj)
This will provide us with the intercept and regression coefficient for these pairs. We can plot
the residuals and visually assess the stationarity of the series:
> plot(comb1$residuals, type="l",
xlab="April 26th 2006 to April 9th 2012",
ylab="Residuals of EWA and EWC regression")
We can also view the regression coefficients starting with EWA as the independent variable:
> comb1
Call: