An Easy Way To Trade Volatile Markets

Over the past few weeks, I’ve received questions about the volatility indicator I reference in my weekly trading services and how it was developed.

The answer goes back to my research, which earned the 2015 Charles H. Dow Award.

Like many investors, I was intrigued by the Cboe Volatility Index, or VIX, commonly known as the market’s “Fear Index.” It has long been recognized that periods of elevated fear often occur near important market lows. The challenge is that the VIX has significant practical limitations. It is derived from options on the S&P 500, making it a measure of broad market sentiment rather than individual stocks, and its peaks can only be identified with certainty after they occur. That limits its usefulness as a real -time trading tool.

My research focused on whether the same concept could be applied more effectively. The resulting paper examined Larry Williams’ VIX Fix, an indicator designed to measure fear in any stock or ETF, and expanded on that work by developing an objective trading methodology. Rather than relying on subjective interpretation, my research established mechanical buy-and-sell rules and tested them across thousands of stocks over a 15-year period. The methodology was then evaluated in real time through an options trading strategy to determine whether the historical results could be replicated in live markets.

One of the key conclusions was that fear itself is not the signal. Instead, opportunity often develops as fears begin to recede. The research demonstrated that measuring those shifts in investor behavior could provide a repeatable framework for identifying potential trade setups.

More than a decade later, that principle remains at the core of my process. Markets have changed, technology has advanced, and artificial intelligence has become part of the investment landscape, but investor psychology has not. Fear and greed continue to drive markets, and my goal has always been to measure those emotional extremes objectively rather than react to headlines or opinions.

If you’re interested in the original research, you can read the complete Charles H. Dow Award-winning paper here.