Tag Archives: trading

Cointegration typically uses the price information for two related securities, and provides relative value signals. As with traditional technical trading strategies, changes to the fundamentals create a risk of bad relative value signals. With 2-security cointegration, this risk is doubled because changes to the fundamentals of either company can skew the relative value signal. However, this problem can be cut in half by creating baskets (portfolios) of securities and running the cointegration analysis with each security against the basket. This effectively generates signals which are skewed only by changes to the fundamentals of the individual security. Additionally, the required correlation matrix for the permuted set of security combinations can be replaced by a single vector of correlations – greatly improving calculation efficiency and extending the analysis processing potential.

To improve upon normalizing data to % changes, factors typically associated with beta may also provide better signalling data. For example, as the size of a company grows over the course of a few years, its price volitility may fall. Similarly, as market cap grows, the price change correlations may increase relative to larger cap baskets and decrease relative to smaller cap baskets.

By backtesting, optimal trigger strengths and bet sizes can be measured, however, given the correlation coefficients, volitilities, number of positions, and risk preferences, probabalistically optimal bet sizes may provide better results.