Finding a Historical Edge in the Stock Market

I mentioned in my new blog that my forthcoming book will include skills-building lessons for identifying potential historical edges in the market by analyzing historical data in Excel. Unlike some traders, I do not rely on these historical studies for mechanical trading signals. Rather, I use them as indications of how markets tend to behave under a particular set of conditions. If I see the market open and begin to follow the historical scenario, I will then trade the pattern. If the market opens and does not follow the historical pattern, that, too, is useful information. Often, something special is going on if a market isn't following its usual script--and that something special can lead to useful trade ideas.

If I'm a physician and I know that a patient's normal pulse is 80, blood pressure is 110/75, cholesterol level is 160, and average blood sugar level is 104, that's useful information. I can take current readings and see if the patient is deviating from historical norms. Those deviations help lead to diagnoses; when there's no deviations, I can rule out certain problems.

Similarly, if I know the measurements of an average manufactured ball bearing and the variation around that average, I have useful information to tell me whether the current batch is up to standard or not. That, in turn, tells me if my equipment is faulty or operating normally. The same logic that applies to quality control applies to markets: when their outputs deviate from historical norms, something is afoot.

That is not the usual way people use historical information in markets. They would like the historical analyses to provide predictions. I use them for diagnoses.

Most markets at any point in time have some unique, distinctive feature. Maybe they've been up on strong volume; maybe they're moving lower on reduced volatility. Maybe they're moving one way, while other markets are moving differently. Each of these features can be investigated for past occurrences to see if there is a directional tendency associated.

It's when we see multiple distinctive features and a directional tendency common to all of them that we most want to take note of historical patterns. Those are strong tendencies that serve as solid bases for diagnosis.

One advantage of archiving unique market data (20-day new highs; money flows; adjusted TICK) is that you can then investigate historical patterns that few other people are looking at.

So let's say that we investigate the number of stocks closing above the volatility envelopes surrounding short- and medium-term moving averages (Demand) and the number of stocks closing below those envelopes (Supply). I think it's safe to say not too many people look at that.

What we find is that we've had more Demand than Supply for four consecutive trading sessions. That seems distinctive. So I go back in my database to 2004 (my first full year of those data; N = 1105 trading days) and examine all occasions in which we've had four consecutive sessions of Demand exceeding Supply. Five days later, the S&P 500 index (SPY) averages a loss of -.42% (34 up, 62 down), much weaker than the average gain of .16% (588 up, 421 down).

You might wonder what happens when we have four consecutive trading sessions in which Supply exceeds Demand, a situation that occurred last week. Five days later, SPY averages a healthy gain of .52% (41 up, 21 down).

When I saw the findings for this and related patterns, I took a small short position in the market to hold over the weekend. If we break the highs of the past week, I'll be stopped out with minimal risk. If I see weakness early in the week, I'll add to my short position as long as I see the historical pattern playing itself out.

I mention this, not at all necessarily to suggest that you trade similarly or that you take a similar market position. Rather, it's an illustration of one way of planning trades, managing risk, pursuing opportunity, and making sense of market uncertainty. The best trades have a proactive quality: they're the result of seeing patterns and acting upon them in a manner that maximizes the reward taken per unit of risk. The worst trades are reactive: the result of chasing markets out of the emotion of the moment.

One value of historical analyses is that they help keep me out of reactive trades.

RELEVANT POST:

Historical Patterns and Understanding Markets
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