Peter Pham has written an engaging book. The Big Trade: Simple Strategies for Maximum Market Returns (Wiley, 2013) is not only an introduction to Excel-based, probabilistic trading strategies but a “blue jeans to BMW and back again” autobiography. (The BMW came from trading, the “back again” from a failed financial media business venture in Vietnam.)
Part of what makes Pham’s book a worthwhile read rests with his belief that markets demand humility on the part of the trader. He is not touting strategies that will consistently deliver huge returns. On the contrary, the big trade is, in Pham’s opinion, “the one you make that allows you the opportunity to make the next one.” (p. 143) The trader’s job is to read the state of the market, react decisively based on the probabilities, and keep repeating this cycle. Becoming a great trader requires, in addition to desire and dedication, “practice and repetition; reading, reacting, and ’rithmetic.” (p. 126)
The strategies that Pham describes are indeed simple, but they’re a great place for the beginning trader to start and perhaps even a decent fallback for the more experienced trader who may be overcomplicating his systems. Moreover, he shows how to build a spreadsheet to analyze a stock, starting with open, high, low, close, and volume data from a public source such as Yahoo and then adding such calculated columns as “Up or Down Day,” “Consecutive Up Days,” “Consecutive Down Days,” “High Break,” “Low Break,” “Total Breaks,” “Inside Day,” “High + Low Break,” “Range,” “High – Low,” “Open-to-High Move,” “Open = High,” “Open-to-Low Move,” “Open = Low,” and some averages or percentage probabilities: “Avg. High/Low Move,” “Break Prev High/Low,” “Total Breaks,” “Inside Day,” “High + Low Break,” and “Open is High/Low.” No higher-level math or advanced statistics required here, just a couple of basic Excel functions that Pham illustrates.
For those traders whose platforms include consolidated bid/ask volume statistics, Pham offers tips on using volume delta. For those focused on the opening range, he provides a handy cheat sheet to answer the question: “If this stock goes up X dollars, what is the probability that it will go up Y dollars?” (p. 64)
Pham urges traders to formulate falsifiable hypotheses. This approach, he argues, stands in stark contrast to traditional technical analysis. Technical analysis falls short because the “descriptive data sets (i.e., price and time charts) and the inductive statistics one builds from them are simply observations without any grounding in a hypothesis. … Data can tell you nothing in and of itself.” (pp. 15-16) “Wouldn’t you rather work from a set of numbers that you can verify and test than a set of rules and scribbles that are completely subjective?” (p. 28)
If you’d like to be a quant but have no quant skills, Pham offers a simple (but, as always, not easy) path. As a bonus, you get to know someone who sounds like a pretty nice guy.