While the broader crypto market is facing one of its toughest crypto winters to date, erasing over $1 trillion since early October, prediction markets are moving in the opposite direction. According to data shared by The Block, November was by far the most profitable month for both Kalshi and Polymarket, with the platforms posting $5.81 billion and $3.74 billion in monthly trading volumes, respectively.
The surge, however, is not happening in isolation. Galaxy Digital, a global crypto-focused services firm, is reportedly in discussions with both platforms to act as their liquidity provider, effectively bringing Wall Street-style institutional infrastructure into a developing market.
More liquidity in prediction markets would mean “tighter spreads and deeper order books,” which could become the “tipping point for prediction markets to be taken seriously,” crypto analyst and investor Connor Kenny said on X.
Analysts say this move could signal the start of a broader institutionalization of prediction markets, raising questions about how liquidity provision, competitive market-making, and professional involvement might reshape the sector.
The earlier, the better for institutional liquidity providers
Galaxy Digital’s bid to bring more liquidity to prediction markets reflects a broader structural shift in the industry’s inner workings.
Speaking with Prediction News, Annabelle Huang, CEO of Altius and former managing partner of Amber Group, explained that prediction markets are “increasingly more interesting” for institutional-style liquidity provision, despite their early stage, due to the trading volumes they produce on markets around big events, such as elections, sports, and macro predictions.
She explained that institutional market makers often look for markets with consistent flow, which will allow for capital and risk to be recycled. Solid APIs, clear rulebooks, transparent dispute resolutions, and predictable fees are also aspects market makers look for.
From a data perspective, the industry’s shift toward higher institutional involvement is being accompanied by structural upgrades to how market information is aggregated and processed. Yu Hu, founder and CEO of Kaito, said his firm’s collaboration with Polymarket has introduced the first “verifiable mindshare markets” where social sentiment, popularity, and community engagement data are auditable on-chain.
Very excited to have the first verifiable mindshare markets go live on @polymarket!
This is the start of a new category – where anyone, anywhere can predict mindshare, sentiment, and popularity for anything.
Transforming AI from opaque to a verifiable system is a challenging… https://t.co/eRD5Vucl33 pic.twitter.com/vPAxsV0Spg
— Kaito AI 🌊 (@KaitoAI) November 21, 2025
“Unlike early crypto/DeFi [decentralized finance] when markets were often built on hype, unverified sentiment or purely speculative flows, the new generation is anchored in verifiable data,” Hu said. “This brings us closer to how traditional financial markets matured: quoting and pricing informed by credible data, not just social-media buzz or retail momentum.”
Winners, losers and the future of liquidity in prediction markets
Competitive market-making exists in every single liquid market, and prediction markets are no exception, Altius’ Huang said. Professional market makers with strong quantitative research, domain expertise in elections, macro, or sports modeling, cheap capital, and investments in infrastructure are best positioned to win. Those lacking these advantages, including smaller or retail-focused participants, risk being displaced as liquidity provision becomes more professionalized.
At the same time, the risks also remain considerable.
“The main risks for professional market makers involve regulatory compliance, resolution around ambiguous betting outcomes, and managing market risk through proper hedging,” Huang said.
However, the evolution of liquidity also has implications far beyond trading mechanics. Kaito’s Hu explained that institutional involvement often tends to enhance market efficiency and forecast accuracy.
“Mispricings close faster, markets react more quickly to new data, and forecast quality improves because noise trading is diluted by systematic quoting.”
Ultimately, the entrance of market makers and the emergence of competitive liquidity dynamics signal that prediction markets are evolving into a more structured, professional, and globally relevant financial sector. The next wave of growth may hinge on which platforms can balance accessibility, regulatory compliance, and sophisticated liquidity provision to dominate both US and global markets.
Note: Galaxy Digital did not respond to our requests for comment.
