How to do & plot simple and rolling linear regression on financial data xts object in R?

Question

Working with 30 minute data, of which I have put a sample online. It's the notional dollar value of the spread between ES and 2 contracts of NQ (ES-2*NQ). Sample is small, but should be long enough to use directly in a demo if you like. R code to grab it and use it as I am trying to: ``` demo.xts <- as.xts(read.zoo('http://dl.dropboxusercontent.com/u/31394273/demo.csv', sep=',', tz = '', header = TRUE, format = '%Y-%m-%d %H:%M:%S')) ``` head(demo.xts): ``` [,1] 2013-05-27 00:00:00 -37295.0 2013-05-27 00:30:00 -37292.5 2013-05-27 01:00:00 -37300.0 2013-05-27 01:30:00 -37280.0 2013-05-27 02:00:00 -37190.0 2013-05-27 02:30:00 -37245.0 ``` What I am mainly after is a rolling window regression (or linear regression curve, as my trading platform terms it) - save it, then plot it. And, I figured to lead up to that I should be able to also plot a single simple regression for a specified time period. After the window regression, I would add standard deviation "bands" to that, but I think I can…

Accepted Answer

You can use `predict` to compute the points on the regression line and `tail` to extract the most recent one.

```
# Sample data
library(quantmod)
getSymbols("^GSPC", from="2009-01-01")

# Rolling regression (unweighted), with prediction intervals
x <- rollapplyr( 
  as.zoo(Ad(GSPC)), 
  width=300, by.column = FALSE, 
  FUN = function(x) {
    r <- lm( x ~ index(x) )
    tail(predict(r, interval="prediction"),1)
  } 
)

# Plots
plot( index(GSPC), Ad(GSPC), type="l", lwd=3, las=1 )
lines( index(x), x$fit, col="purple", lwd=3 )
lines( index(x), x$lwr, col="purple", lwd=3, lty=3 )
lines( index(x), x$upr, col="purple", lwd=3, lty=3 )
abline( lm( Ad(GSPC) ~ index(GSPC) ), col="light blue", lwd=3 )  
```

How to do & plot simple and rolling linear regression on financial data xts object in R?

Solution

Problem