Now that the “why” has been covered, let’s move on to the “how” part of the equation.
Forcerank is organized as a weekly competition in which participants enter thematic contests and rank a list of 10 names in order of which they think will perform best to worst that week (by percent change), with a focus on equities or macroeconomics. Equity competitions cover the Technology sector (Enterprise tech, Hardware, Social Media, Semiconductors), Consumer Discretionary (Apparel, Ecommerce, Restaurants, Media), Energy (Exploration and production), Industrials (Airlines), Health Care (Biotech) and Financials (Investment Banks), while macro contests include topics such as forex and commodities (see “Pick a contest,” below). The goal is to correctly match up your rankings with the actual results at the end of the week.
Forcerank introduces new competitions each week, adding to its suite of equity coverage. Contests are comprised within an industry group and within a specific market capitalization range. Selections are based on the most popular sectors and the noteworthy stocks within those sectors, as judged by investor attention and partially derived from activity seen on the Estimize site using a popularity algorithm. As we see certain games are performing well, we add additional industry games under that sector umbrella. Currently the most popular sectors are Consumer Discretionary and Information Technology. The objective is to eventually have every single stock in the Russell 3000 represented, starting with Russell 1000.
How are points calculated?
Points are awarded within each game at the end of the week based on how accurate a player’s rankings were compared to the percent change in the price of those stocks. The Forcerank points system awards accuracy based on the distance in positions between your ranking and where that stock actually fell. The higher or lower you go in the rankings, the greater your potential to score, and the larger number of points you can accumulate for being accurate (see “Forcerank scoring).
The reason behind this is the fact that the further a stock is ranked from the middle (5th or 6th position), the more difficult it is to be correct. We want the community to focus on getting the #1 and #10 stock correct, as the 5th and 6th positions are more or less irrelevant.
For each position, the user earns a score of 0 to 100. A score of zero implies you ranked a stock the furthest position from where it placed at the end of the week; for example you ranked Amazon #10 in the Ecommerce contest and it came in at #1. One-hundred points are rewarded when a ranking is spot on.
Each score has a multiplier based on how far the ranking was from a middle position. The extreme slots get higher multipliers because we want to reward people for taking the risk, all the way down to a 1 multiplier for the 5th and 6th positions.
Who: Unlike the analyst surveys that polled only the sell-side, Forcerank is free and open to participants of all biographical backgrounds and currently is composed of both professionals and non-professionals alike. Many of the most avid Estimize contributors also participate in weekly Forcerank competitions.
Although the Forcerank app is open to all, it is very self-selecting in that only those interested in the stock market are likely to participate. Consensus rankings are disseminated to all competitors at the same time every Monday morning. These rankings can help inform trades for that week.
Where: Forcerank is set up as a free to play app for iOS through the Apple app store.
When: Contests currently run from market open on Monday to the close on Friday.
Consensus Rankings: Once the data is ingested each Monday morning, it is aggregated in order to come up with the consensus ranking for each name within its particular contest (see “Box score”). A history of each ranking is kept to show how stock positions change.
The goal of this data is to provide a better sense of where the broader market believes stocks will trade during the week. The importance of having a more representative dataset is that it means better data for everyone, ultimately resulting in more efficient markets.