It’s beta, Jim, but not as we know it.

A common question for us is ‘why do betas in ArbMaker differ from those on financial websites?’

The typical beta calculation on, say Google Finance, uses the S&P500 as a reference point and is calculated via a regression of the returns data of both time series. This approach is at the heart of correlation.

The regressions in the Engle-Granger model of cointegration inside ArbMaker are calculated using price data – not returns. That emphasis points to a key difference between correaltion and cointegration; and means the resulting betas cannot be compared on a like-for-like basis.

The focus under cointegration on price data has distinct advantages over the returns-only approach for spread analysis. That is because there is comparatively limited information in returns data whereas cointegration extracts information from price data at several levels. Price data, for example, is highly autocorrelated and yields precious information about spread trends, direction and persistence that is lost to returns-based data alone.

Yet both betas have relevance – it is the key ratio defining the amount per side when configuring a pairs trade. In our next release, due out in July, we allow users to tweak this ratio. All the more reason to grasp the important differences between the two betas!