We do a lot of handicapping, but we acknowledge that won’t make us better traders. The value of handicapping ends with stock picking. Once stocks are picked and opinions are formed, one must gauge whether or not one should place an actual bet.
We are primarily value bettors. This is not to suggest we only place value bets. Rather, the better part of investment capital is allocated to those issues where a clear discrepancy between benchmark and implied probability is evident, while the remainder is allocated to long shots. In our portfolio, the ratio of value bets to long-shots is roughly 70/30.
For every issue we study, odds are calculated for 12 discrete price points; from the odds, an implied probability for each price point is generated. The implied probabilities are then weighed against benchmark implied probabilities for the sector to which the issue belongs.
Whether a bet is placed on the long or short side is determined by whether or not its cycle — as we calculate it — is up or down.
We maintain benchmark probabilities for the following sectors: gold, silver, platinum, uranium, oil services, and agriculture.
Over the course of the next week, we will be publishing herein a visual representation of the math with which our betting forms (totes) are produced. As odds are read differently depending upon the part of the world in which you live, output will be in decimal, fractional and American forms. We are Americans, but we think in European fractional terms, so when discussing odds, it will be primarily in the terms of fractions (e.g. 13/1 against…).
In addition, it’s important to note that we also compute conditional probability sets, but for simplicity’s sake, these won’t be included on our published totes.
Is this really how we place our bets?
It is. It’s also how we quantify our exits. However, the totes that we will be publishing will be those wherein value is present a high percentage of the time relative to a benchmark, though this isn’t necessarily the price point at which we will choose to exit. Our own tolerances allow us to exit at price points that have a fair confidence interval with a preset margin for error.
Stay tuned for Part II.
