Combining Statistics and Intermarket Analysis
In Chapter 1, we discussed many different intermarket relationships that are valuable for developing trading systems. If you actually have programmed some of the examples in Chapter 1, you have learned that these systems work very well during some periods, but do have long periods of drawdown.
Our research over the past few years has shown that analysis of intermarket relationships, based on current correlations between the intermarket and the market you are trading, is a very valuable tool in developing trading strategies.
USING CORRELATION TO FILTER INTERMARKET PATTERNS
Let's now show how Pearson's correlation can be used to improve classic intermarket relationships. In Chapter 1, we showed that you can trade crude oil using the Dollar index (see Table 1.3). You go long when the dollar is below its 40-day moving average, and you go short when it is above that average. This relationship has been steady over the years, but it did have problems during 1991 and 1992. During those years, this model lost $3,920.00 and recorded its maximum drawdown.
By using Pearson's correlation as a filter for this simple intermarket relationship, we are able to improve our model's performance. We will still enter and exit our trades using a 40-day moving average of the Dollar, but we now also require a 40-day correlation between the Dollar and crude ...