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[dc]T[/dc]he market is not a math problem. It is easy to get confused, though, because the market often looks like a math problem. The market generates a tremendous amount of information, and most of that information comes to us as numbers. It is tempting to blindly apply analytical tools, statistics, and other data processing techniques to market data, and, in fact, we can do that. However, this a mistake that risks missing the essential nature of the market—the market is a study in human behavior and psychology, first and foremost.

Prices are moved by the buying and selling decisions people make. New information comes into the market, it is processed, and traders make decisions to buy or sell. Even in this day of algorithmic trading, nothing truly essential has changed. Yes, the human scalper’s edge against the silicon brains is completely obliterated, but, at even slightly longer timeframes, prices are moved by the decisions human traders make. (Remember, much algorithmic trading is done by order filling algorithms, which are simply an extension of a human trader’s will.) There are recurring patterns in prices because people make, and have made, the same decisions and mistakes in response to risk and opportunity in financial markets for all of recorded history. Furthermore, they probably will as long as we have markets. Behavioral and psychological forces ultimately have the greatest power to set prices.

This does not mean that math is unimportant in markets and trading. Quite the contrary—many developing traders fail because they don’t have a good understanding of math. I have seen even experienced traders (some with quantitative backgrounds like engineering degrees) show a poor understanding of randomness in markets. Many struggling traders fail because they do not understand how counterintuitive probability can be. The correct mathematical tools can help us find edges and probabilities in the market (again, back to flipping the slightly weighted coin), but those tools must be put in context of human behavior.

One last thought: the markets are noisy, messy places. The mathematical tools that work best in this environment are simple and robust. You do not need fancy, higher math for most trading applications; you need simple, basic math, but you must understand your tools completely. Many times, all that is needed is simple counting, and a way to compare two sets of data. Over the next few weeks, I will be sharing some specific techniques and tools that I have found useful, along with some insights into how the markets move and where there are actual trading edges. I hope you will find this interesting and useful.