Sector Correlations as a Decision Support Tool for Active Traders

I've spoken with a number of intraday traders who have difficulty judging the daily market environment in which they're operating. Is this a busy, volatile day, or a slow, non-volatile one? Is this a range day, or a trending one? Of course, none of us can know the future with certainty and, at any point in the day, markets can shift gears. Still, making as accurate an assessment of market conditions as possible is extremely helpful in knowing where to place profit targets (nearer in slow, range markets) and stops (wider in volatile markets). Understanding the character of a market day is also very helpful in the decision of whether to let profits run vs. book them in a more opportunistic fashion.

Above is one of my analytical tools that helps me identify market conditions as they're evolving. The blue line is the S&P 500 Index (SPY) at 15-minute intervals. As we can see, over the two day period charted, we have been quite rangebound.

The pink line represents the correlation among four key S&P 500 sectors: financials (XLF), energy (XLE), consumer discretionaries (XLY) and consumer staples (XLP). I calculate the correlation of each sector with every other sector over a moving one-day period (26 15-minute periods) and then plot the average of those correlations. Historically, this average correlation among sectors is .53. When we see the correlation significantly higher than .53, it suggests that the different sectors are moving very much in tandem intraday. When we see the correlation significantly lower than .53, it suggests that the different sectors are not moving in unison.

Why is this important? In a trending market, the sectors tend to move in harmony. Strong uptrends or downtrends tend to move all sectors. Conversely, as markets become transitional and rangebound, sectors tend to move their separate ways, with stronger ones showing relative strength and weaker ones lagging. So, as a rule, when I see a correlation among sectors that is high and rising, I view the current environment as trending. When I see a correlation among sectors that is low and falling, I view the trading environment as rangebound. When the correlation is low and rising, I entertain the possibility that a trending move is in the making. When the correlation is high and falling, I consider the possibility that a trending market may turn transitional and rangebound.

As you can see from the chart above, the low, falling correlation has been an excellent tell over the past two days for the market's range behavior. This was very helpful in terms of avoiding bad trades (not buying range highs or selling lows) and considering some good ones (fading moves to range extremes). The low correlation has also been useful in suggesting that market moves are unlikely to extend, making it particularly important to book profits when they're available.

The above chart was created in a matter of minutes in Excel using data from a real-time data feed. No special software or programming expertise was needed. I have found such decision support tools invaluable in my own trading. They do not take the trader away from the screen for lengthy periods of time and very much help in preparing the trader for the coming day.

RELATED POST:

Anticipating Market Volatility (see also the links at the end of that post)
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