Heating Up
Less than a week out from the US election things are really heating up.
While it is a cliche, it really does feel like the stakes have never been higher and the whole world is holding its breath.
It’s a topic everyone has an opinion on, and decentralised prediction markets have reflected this with a surge of activity and well over a million dollars of volume.
Decentralised prediction markets offer huge improvements over their centralised counterparts, they’re non-custodial and accessible by anyone anywhere in the world.
Catnip
One platform in particular has caught my attention with rapid growth this week.
A few days ago Catnip was celebrating a record breaking $125,000 of volume.
But just 24 hours later it had nearly doubled that, breaching $222k.
What is it?
Catnip is a decentralised prediction exchange from AugurDAO built on Augur and Balancer. It provides a simple Uniswap-style interface, with a focus on simplifying prediction markets for new users.
Currently the US election is the only market with more on the way soon.
DAI is converted into YTRUMP and NTRUMP, and the winning outcome is settled back into DAI.
Right now NTRUMP is trading at $0.38 and YTRUMP at $0.62.
Users can either trade the exchange or mint the markets tokens with Augur Foundry, full guide here.
You can tell Catnip have put a lot of thought into the design, with a smooth UX, use of the internet’s favourite furry friend for branding, and the option to choose dark or light mode.
But it’s the numbers that really make this project stand out.
Catnip promises up to 10x lower transaction fees than Augur’s native UI, and 50% lower transaction fees than Balancer’s. There are also zero settlement fees, so users can put their money where their meow is without losing out.
AugurDAO
Catnip is created by AugurDAO, and I’m looking forward to seeing how governance evolves in the coming months.
I’d recommend anyone interested in learning more head over to the community Discord channel, and you can read Catnip’s full announcement post here.
And if you’re interested in learning how we use Balancer pools for our indices at PieDAO, come say hi.