It is human nature to make predictions about the future. I think it’s going to rain today, I predict gold will increase in value, I believe demand for oil is going to exceed supply. Every day we make educated guesses, from the minutiae of the weather to long term economic trends.
Prediction markets offer a platform for people to trade on the outcomes of these events. Today’s prediction markets allow you to generate events and make an educated prediction on almost anything, from political campaigns, and sports games to the price of commodities for a financial reward.
While there are a number of prediction markets out there, we wanted to take a look at two of the better-known examples, namely Augur and Gnosis, to figure out how they compare.
How do prediction markets work?
Using the knowledge of crowds, discerning more accurate predictions is made easier. Prediction markets take advantage of non-public insights. This inside scoop gives them the upper hand in forecasting outcomes. Without this proprietary information, people are reliant on forecasts, surveys and polls. As such, the higher the participation, the stronger the likelihood that the prediction market will be accurate.
The blockchain effect
Prediction markets are one of the industries to irrefutably benefit from blockchain technology. Public blockchains remove the need for a trusted third party, making the platform inherently censorship-resistant, borderless and permissionless. Borderless prediction markets help to democratize trading and open up markets to everyone, irrespective of geographical barriers. Permissionless platforms advance this further, as no centralized owner can control who partakes. Moreover, the censorship-resistant nature of blockchain technology prevents any one player from fixing or gaming the market in malicious pursuit.
Blockchain powered prediction markets like Augur and Gnosis work in a similar way to traditional platforms but remove information silos so that traders are privy to all predictions made.
An additional benefit of embracing multi-party participation is that participants can see what other parties to the trade are predicting, in real-time. All of this information is anonymous and aggregated but provides traders with a significant advantage when compared to the systemic opaqueness of traditional models, which favours the centralized parties controlling the trades. The ability to view and assess predictions from multiple individuals provides an invaluable insight into market sentiment, and with CloseCross, this information is finally available to all participants.
To maximize accuracy, CloseCross, like Augur and Gnosis, financially incentivizes participants to make accurate predictions to the best of their knowledge, as those who are successful will receive tokenized rewards, thus encouraging further engagement.
Are you liable?
One key differentiator between prediction markets is the onus of compliance. Are you liable for the actions you make on a platform? Considering the regulatory and ethical approach of a platform is of paramount importance.
Unlike other platforms, we don’t expect our users to be answerable for the activity facilitated by CloseCross and believe it is our duty as service providers to be entirely culpable. For scalability and endurance, achieving both local and general compliance is a must. It is unfair to expect participants in prediction markets to ensure that they are in compliance with all local and jurisdictional laws, rules and regulations on behalf of the platform.
Another characteristic where Augur and Gnosis overlap, is one-on-one trading mechanics. In the current system of trading financial assets, each party to the trade assumes the same level of risk and reward. In this setup, if you want to earn an extraordinary return, you have to accept equal risk. The fear of losing more than they possess is what discourages the vast majority of people from engaging in financial trading.
While the distinct processes differ marginally, they both require market makers. The need for counterparty interference in specific transactions is a limiting factor for decentralized scalability. The reliance on such market makers also gives rise to the bot issue and is a barrier for full trustlessness, by needing such centralized players. It can often be difficult to discern whether market makers are genuine or bots.
CloseCross eliminates unquantified risk by enabling users to participate in trades with multiple counterparties, rather than just one. This is facilitated through CloseCross’ development of Virtual Prediction Floors (VPF), which allow all market participants to enter a single multi-party contract that drives a common settlement mechanism for all participants in an autonomous manner.
Counterparties to the trade simultaneously take different positions, predicting different prices ranges for the asset in question. This results in the potential for a much higher return, while risk remains fixed to the initial stake. Users cannot lose more than they put in. In this way, CloseCross is a regulated platform that shields its users from the potentially significant risks of the financial markets in a way that traditional platforms don’t.
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