Many people have stated that bitcoin is akin to tulip mania. It’s not. It is true that cryptocurrencies may be in a mania phase where price is decoupled from productivity, but that does not tell the full story. Blockchain technology, and by extension cryptocurrency, is a technological revolution and it follows the cycle of other technological revolutions like the Industrial Age and the Information Age. At times, I’ll use blockchain and crypto interchangeably. For blockchain technology to change the world, it must be implemented as cryptocurrency. The two are inextricably linked. This article aims to explain the difference between bitcoin (and the entire crypto-asset class) and tulip mania. I intend to show that cryptocurrency, as a technology in concert with other technologies, is driving the next long wave economic cycle. Technological revolutions transform the world and I will illustrate how, when and where cryptoassets fit within that picture.
A prediction market is a collection of people speculating on future events or outcomes. These events include (but are not limited to) elections, sales of a company, price fluctuations of commodities, even changes in the weather and just about any event or outcome that can be objectively verified ex post.
…fill the oracle role when the event has occurred and pay out the profits to the correct predictors. In decentralized prediction markets, oracles are needed to submit and verify information on real-world events & outcomes to the blockchain for the smart contracts to initiate the right payouts. Oracles can come in different forms such as software, hardware, or humans and can be centralized (trusted parties) or decentralized. We recommend this article for more information about the different kinds of oracles. Oracles are a …
So similarly to how stocks represent the aggregated investors’ prediction on a company’s future performance, these outcome tokens will be priced according to supply and demand and represent the aggregated probabilistic predictions of the respective event.
After the market is set up, participants can invest for example $100 and receive 1 “A-token” and 1 “B-token” in return. Both types of tokens automatically pay out $100 each in the event that the respective outcome happens. If the outcome does not happen, $0 will be paid out for this type of token. So if no action is taken, $100 (the initial investment) will be paid out with a 100% certainty. However, these tokens can also be sold freely with other participants.
Does this sound too abstract? Imagine this: In your typical corporate meeting on the next year’s sales forecasts, there are people from different corners of the company, each having their very own insights on the topic. However, these people are usually adversely incentivized to share their knowledge. This might affect the marketing lead to make estimate the sales too high in order to secure a larger marketing budget or the sales lead forecasting too low in order to set the bar low (“underpromise and overdeliver” being a known mantra with these folks).
The classic example often used to explain the value of prediction markets are political elections. Prediction market platforms allow to create a poll-like market where the participants can trade the outcomes of an election similar to sports-bets. So if a business owner thinks that a certain politician being elected would negatively affect the revenue of his business, he could bet on the event of a successful election and thus hedge against the disadvantageous outcome.
The main purpose of prediction markets is the aggregation of beliefs over an unknown future outcome. Because they incorporate a wide variety of thoughts and opinions, prediction markets have proven to be quite effective as a prognostic tool. Thus, these markets can directly advise important policy decisions, by giving more accurate estimat…