Kirk Northington’s Volatility-Based Technical Analysis: Strategies for Trading the Invisible (Wiley, 2009) is a 450-page infomercial for his MetaStock add-on. Although he purports to offer both MetaStock and Trade Station formulas unique to his system, all but the most basic MetaStock fomulas have proprietary components and hence are useless. He seems to have been a bit more generous with his Trade Station coding. Looking at the MetaStock charts that are chosen to demonstrate the potency of his indicators, I’m not wowed. And since, despite his system building, he claims to be a discretionary trader, there are virtually no backtests, no statistics, to lend credibility to all those entry and exit symbols on his charts.
Now that I’ve vented, let me look at this book more constructively. The basic premise is sound: volatility is a critical descriptor of market movement and hence should not be ignored in constructing a trading system. Of course, volatility is not a univocal concept. Historical volatility is easily described by traditional technical analysis software; implied volatility is captured only by options software (which usually includes historical volatility indicators as well). Writing a trading system for equities that successfully incorporates both elements is not for the faint of heart or the mathematically challenged. Northington does not undertake this task, though he offers an “equalizer,” what he calls projected implied volatility. For the most part he focuses on the usual suspects in the indicator world—standard deviation, average true range, linear regression, and R squared.
One theme that runs throughout the book is the power of combining and compounding. This, I think, may have some merit. At least, it’s something I might play with a bit. Here are two examples. First, create a composite security from two related securities. The chart of the composite security is sometimes clearer than that of either of the individual securities. When your system signals an entry on the chart of the composite security, split your order equally between the two securities. Second, compound indicators to highlight extremes. This is important for Northington because, he argues, “money is to be made at the extremes.” (p. 16) For example, multiply a normalized value of the distance of price from its x-period moving average by its average true range. “When both values are at extremes, the calculated value will be truly magnified.” (p. 72) In its simplest form, using MetaStock coding, the function would be (((C – Mov(C, 40, E)) / C) * 100) * ((ATR(14) / C) * 100). Northington tweaks this function, looking at highs and lows instead of closes, overlaying standard deviation bands, and optimizing values, but the basic idea remains intact.
Another point, not original but nonetheless important enough to keep repeating, is that a critical step in system building is breaking the system. Every strategy has its blind spot, and when a developer breaks his system he discovers its vulnerability. He can then decide how to address this vulnerability—whether to hedge, whether to diversify, whether to cut back on position size, whether to keep a tighter stop, or whether simply to throw the damned thing out!
A final idea that deserves a brief paragraph occurs in the subtitle of the book: trading the invisible. In some ways, of course, it’s merely a catchy phrase, a bit too cute. But Northington’s point is that the eye tricks us into seeing patterns that aren’t there and missing patterns that are. To study a chart and then trade based solely on what we see is to trade the visible but perhaps the illusory.