One of the major concerns regarding investment market analysis is the acceptance of presuppositional fallacies as actionable insights. While mentioning a decline in share price or a financial valuation ratio may be a statement in fact, the fallacy occurs when the analyst assumes that the metric at hand carries predictive value without first validating the assumption.
For example, in the financial publication space, you’ll often hear phrases like such-and-such stock may bounce off support or that a company’s modest price-to-earnings ratio represents good value. However, these claims are merely assertions unanchored to an empirical basis. The claims could turn out to be accurate or they might not — they’re educated guesses at best.
To avoid falling into the presuppositional fallacy trap, I prefer to utilize conditional probabilities — using past analogs to determine forward probabilities. However, financial metrics such as share price or valuation ratios are continuous signals, which prevent easy categorization. To remedy this dilemma, I convert past historical data into market breadth — or sequences of accumulative and distributive sessions.
By default, demand profiles based on binary market breadth data, lend themselves to categorization and quantification. Because each profile is a distinct, discrete behavioral state, it’s possible to monitor the probability of transition from one state to another. Such an analysis would simply not be possible when using continuous signals such as raw share prices.
The other critical advantage of converting price data into market breadth is that all publicly traded securities now speak the same language. This data can then be thrown into a spreadsheet, where it can be sorted based on probability of upside.
That’s exactly what we’re doing here with the Saturday Spread. We’re focusing on the most actively traded stocks which statistically offer higher-than-average odds for bullish speculators. Using math doesn’t guarantee success but what it does is provide a rational justification for betting.
Let’s get right into it with biopharmaceutical giant Gilead Sciences (GILD). In the past two months, the price action of GILD stock can be converted as a 4-6-U sequence: four up weeks, six down weeks, with a positive trajectory across the 10-week period. Admittedly, this process compresses GILD’s magnitude dynamism into a simple binary code. However, the benefit is that this code can now form the basis of past analogs for the purpose of calculating probabilistic analysis.
