Prediction Market revolving around the following question: Which privacy oriented token will perform better, ZCash or Monero?

In the nascent crypto space without significant understanding or regulation, companies have been launching subpar ICOs to capitalize on hype, and currency trading is extremely volatile. Tokens often serve as a means for companies to raise money quickly with users either genuinely believing in the success of a venture, or looking to make a quick profit by playing off of volatility. There aren’t many valid written sources producing actionable information on the legitimacy of such companies. In order to obtain useful information, incentives must be aligned.

With prediction markets, users stand to profit off of outcomes if they occur, and as such are incentivized to “vote” in accordance with their views. Furthermore, these markets provide insight into public opinion and help hold companies accountable, when there aren’t any other entities that do so. By pitting two competitors against each other in a prediction market, they are each automatically incentivized to take action that would satisfy consumers, aligning with user behavior versus the alignment with investor needs brought about in ICOs with app tokens. Moreover, beyond just human users, bots with access to data streams on certain performance indicators can also contribute to the market. This whole process introduces oversight and accountability by a decentralized mass versus having any sort of centralized regulation. Users are able to hold corporations accountable through the simple economic principle of competition aligning incentives.

This specific use case focuses on the privacy token space in which accountability is especially necessary as consumers inherently expect privacy from each specific service, simply based on what each service promises to provide. Without a specific measure of accountability, these companies aren’t necessarily incentivized to uphold their promises.

Looking into Monero, up until September of 2017, RingCT was not mandatory in client software, meaning that 62% of transactions made before 2017 can be deanonymized, which presents a significant consumer vulnerability. This issue has been present since the inception of the currency, however, the company did nothing to resolve the issue until MoneroLink published such results. With a prediction market, those aware of such issues can display their concerns allowing such vulnerabilities to be resolved sooner.

ZCash and Monero are the current leading tokens in this space - each one promising privacy, but tackling the issue from different perspectives. Monero takes the approach of distorting information utilizing RingCT, while ZCash makes use of zero-knowledge proofs. With ZCash working on protocol improvements to increase efficiency and reduce currently high costs, and Monero resolving some of its anonymity issues, these two cryptocurrencies are becoming more competitive in this space. Using a prediction market, we can determine which token is expected to perform better within the scope of the next year as both platforms plan to roll out significant improvements. In this manner, as they release updates and announcements, each company will be able to measure user satisfaction in relation to its competition and thus prioritize the needs of the user. This is basically a real-time indicator of feedback for each company.

The first iteration of this market is scheduled to run for one year, giving both companies time to build improvements, attend to user feedback, and respond accordingly. The market will decide on which token performed better. When we say “performed better,” we define this metric in relation to how widely used each token is. Since both ZCash and Monero are usage tokens, meaning that the token is needed to access the digital service each provides, actual usage of a token represents its value to consumers. In this case, that would be using ZCash or Monero to complete transactions which keep user data private. Thus, in measuring transaction volume of each token throughout the course of the year, we can measure token performance.

This same sort of ideology of pitting competitors against each other to benefit consumers can be applied to tokens in general beyond just the privacy space and multiple companies can be entered into such a marketplace.

This is implemented as a use case of Gnosis' prediction markets using gnosis.js and the gnosis market testing environment.

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