In a tech-finance world that has spent the last twelve months obsessed with AI and its pace of evolution, prediction markets have been one of the only other narratives to cut through the noise. Since the last US presidential election, where they called the outcomes with more accuracy and well in advance of traditional polling methods, prediction markets have emerged from from backwater academic novelty to being touted as new financial primitives.
While we might disagree about the “financial primitive” label (they’re just binary options, right?) What is undeniable is the breadth of markets being offered, the distribution power and the potential. What may seem to many like simply a gambling play is being taken very seriously by others, such as Jeff Yass and Brian Armstrong, as a potentially a fundamental way to re-wire some core components of the finance world, such as insurance markets. Others leaning into the space include the team behind the hugely successful Hyperliquid DEX, who released the HIP4 proposal recently, which would add outcome-based trading (read: prediction and option markets) to its platform.
So, the width of outcomes being offered, and the institutions involved make this a very, very interesting space at the moment - it’s clearly a rapidly evolving and being built with favourable regulatory conditions. How best then to analyse the opportunities that are being presented?
As a trading firm, LO:TECH is already providing liquidity into these nascent markets. And to be able to analyse and trade in any market, you need great, reliable data; data that is easy to work with and compare across related markets. We’ve built that pipeline as a core part of our infrastructure, and we’re proud to announce that prediction market data is now available as part of our best-in-class live and historical market data service.
Like the rest of our offering, it is built to the exacting standards trading teams like us require.
If you’re interested in access, coverage details, or a quick technical walkthrough, get in touch.
