Bug futures: business models
10 July 2018
Recent question about futures markets on software bugs: what's the business model?
As far as I can tell, there are several available models, just as there are multiple kinds of companies that can participate in any securities or commodities market.
Oracle operator: Read bug tracker state, write futures contract state, profit. This business would take an agreed-upon share of any contract in exchange for acting as a referee. The market won't work without the oracle operator, which is needed in order to assign the correct resolution to each contract, but it's possible that a single market could trade contracts resolved by multiple oracles.
Actively managed fund: Invest in many bug futures in order to incentivize a high-level outcome, such as support for a particular use case, platform, or performance target.
Bot fund: An actively managed fund that trades automatically, using open source metrics and other metadata.
Analytics provider: Report to clients on the quality of software projects, and the market-predicted likelihood that the projects will meet the client's maintenance and improvement requirements in the future.
Stake provider: A developer participant in a bug futures market must invest to acquire a position on the fixed side of a contract. The stake provider enables low-budget developers to profit from larger contracts, by lending or by investing alongside them.
Arbitrageur: Helps to re-focus development efforts by buying the fixed side of one contract and the unfixed side of another. For example, an arbitrageur might buy the fixed side of several user-facing contracts and the unfixed side of the contract on a deeper issue whose resolution will result in a fix for them.
Arbitrageurs could also connect bug futures to other kinds of markets, such as subscriptions, token systems, or bug bounties.
Previous items in the bug futures series:
Paper from WEIS
Corporate Prediction Markets: Evidence from Google, Ford, and Firm X (PDF) by Bo Cowgill and Eric Zitzewitz.
Despite theoretically adverse conditions, we find these markets are relatively efficient, and improve upon the forecasts of experts at all three firms by as much as a 25% reduction in mean squared error.
(This paper covers a related market type, not bug futures. However some of the material about interactions of market data and corporate management could also turn out to be relevant to bug futures markets.)
Pipeline monument in Cushing, Oklahoma: photo by Roy Luck for Wikimedia Commons. This file is licensed under the Creative Commons Attribution 2.0 Generic license.