A team of Princeton faculty members are developing a prediction market based on bitcoin transactions.
Prediction markets are purely speculative markets created for the sole purpose of making various predictions, ranging from all sorts of business predictions to more mundane events, such as weather and various real-world events.
Prediction markets are often frowned upon by the financial community, although a number of major companies are said to be using different prediction markets and techniques to gain a competitive edge. These include software companies like Google, chipmakers like Intel and Qualcomm, along with industry heavyweights like GE, Siemens and Arcelor Mittal.
More than just gambling
The basic principle has been around for more than a century. It basically functions like a purely speculative stock market, allowing participants to trade “shares” that are tied to the outcome of certain events.
“We have this beautiful decentralized system that allows two parties to transact with each other without a central authority.”
The average probability of any given event is calculated using the number of people making different predictions. For example, if more people are willing to bet that Qualcomm will gain a few high-profile design wins for tablets, chances are Intel will lose market share.
Those who bet on Intel will lose their cash if the prediction comes true. Coincidentally, Intel is said to be using prediction markets to manage manufacturing capacity.
The biggest problem with prediction markets is that they are purely speculative and regulators in some jurisdictions view them as a form of gambling.
They are underpinned by people willing to put their money where their mouth is, betting on various outcomes in industries they are familiar with.
One prominent example is Intrade.com, which was forced to shut down after the US Commodity Futures Trading Commission concluded it was an illicit form of gambling. Intrade is currently working on a new version of its market, noting that “cold hard cash” can no longer be used as a “carrot” in its model, due to legal impediments.
How about a bitcoin carrot?
This is probably why the Princeton team, led by computer scientist Arvind Narayanan, is experimenting with bitcoin as an alternative to hard currency. Since bitcoin is neither regulated nor centralized, it can be employed in lieu of fiat money, effectively isolating prediction markets from financial oversight. Narayanan said:
“Now that we have this beautiful decentralized system that allows two parties to transact with each other without a central authority, can we make it so that arbitration of events can be decentralized in some form?”
The academic pointed out that the team is already converging on a successful model, but it is still too early to say whether it will work or not. He told the Daily Princetonian that he could not reveal more information until the team has published the research paper.
An existing bitcoin prediction market, Predictious, was founded in July last year. Although relatively unknown, reports suggest that the Irish company has already handled over $300,000 in BTC.
Decentralisation is not enough
Bitcoin developer Mike Hearn believes the idea has the ability to decentralize trading systems, saying:
“Making something decentralized can be a way to avoid these regulatory hassles in a way.”
However, Hearn warns that decentralisation is not a silver bullet, as even decentralised systems can be regulated in other ways.
Narayanan even suggested using the bitcoin exchange rate as a proxy to predict whether the currency will succeed. If a lot of investors believe it will, it could increase its chances of success. He argues that the value of bitcoin could increase twenty-fold if ever becomes a mainstream currency.
However, current investors do not think this will be the case. The value will continue to depend on the level of adoption by mainstream businesses.
Hearn warns that bitcoin will have a hard time competing against PayPal and credit cards, but it might gain a foothold in niche industries, including prediction markets.
Exchange Data Image via Shutterstock