16 Feb Why Wall Street Is Starting to Take Prediction Markets Seriously
For most of their existence, prediction markets sat squarely outside mainstream finance: an interesting technological and cultural phenomenon, but too small, too thinly traded and too often associated with online gambling to attract meaningful institutional interest.
That began to change in 2025, as trading volumes rose sharply, media attention intensified and regulatory clarity improved, making the sector increasingly difficult for institutions to ignore.
Prediction-market probabilities are now starting to appear in institutional data feeds and mainstream financial coverage. In January, meanwhile, Goldman Sachs CEO David Solomon disclosed that he had met with Polymarket and Kalshi to explore how the bank might engage with the space.
Together, these are early signs of a shift in sentiment at the highest levels of traditional finance.
Why 2025 Marked a Turning Point
The change in tone from institutions has largely followed a change in scale.
Industry data shows prediction market trading volume rising from roughly $15.8 billion in 2024 to more than $63 billion in 2025 — an increase of over 300 percent year-on-year.
Liquidity also became more concentrated and more durable. Rather than spiking briefly around election cycles and fading, activity began sustaining depth in contracts linked to central bank decisions, major political outcomes and crypto-related catalysts. A record $12 billion notional trading month in January 2026 suggests sustained interest beyond one-off headline moments.
That depth is important because it translates to tighter spreads, deeper order books and a probability signal stable enough for institutions to take seriously.
Regulatory posture in the United States has evolved in parallel. Kalshi’s legal dispute with the Commodity Futures Trading Commission (CFTC) in 2024 forced a clearer distinction between gambling and federally-regulated event contracts. The ruling did not eliminate uncertainty — and state-level tensions remain — but it shifted the classification debate in a direction compliance teams could analyse rather than dismiss outright.
Taken together, scale and partial regulatory clarity have altered the institutional calculus. Prediction markets have become large enough to monitor seriously and structured clearly enough to not be dismissed out of hand.
From Signal to Risk Tool
For now, the most credible institutional use case remains primarily informational.
Financial markets already operate as expectation machines. Bond yields, for example, imply forecasts of future interest rates and inflation. Options prices encode volatility expectations. Credit spreads reflect assessments of default risk. Institutions rely on these signals not because they are perfect, but because they represent capital-weighted consensus views.
Prediction markets apply the same mechanism to discrete events.
A contract paying $1 if a specified outcome occurs and $0 otherwise trades at a price that can be read as implied probability. That probability reflects money at risk and updates continuously in real-time as new information enters the market.
Reports that the likes of Oldenburg Capital are experimenting with incorporating prediction-market data into their risk models do not imply a wholesale shift away from polling or analyst research. They do, however, suggest institutions are assessing whether market-implied probabilities add something incremental — a continuously updated, capital-backed signal, that can sit alongside existing tools.
The emerging pattern is less about wholesale trading and more about integration: probabilities are beginning to sit alongside yields, volatility surfaces and credit spreads inside institutional workflows.
The risk-transfer and hedging angle remains more tentative.
Traditional derivatives hedge the market’s reaction to events — duration around a Federal Reserve meeting, volatility into an election — rather than the event itself. A tightly defined binary contract isolates the trigger. Structurally, it resembles a short-dated, cash-settled derivative with a defined expiry and payout condition.
There is still limited public evidence of banks deploying significant balance sheets directly into event contracts. What is more visible is the professionalisation of liquidity. Reports that firms such as Jump Trading are exploring stakes or liquidity provision in major venues suggest price formation is becoming more robust. Deeper books and tighter spreads are prerequisites for serious hedging; without them, probabilities remain fragile.
The longer-term institutional pathway is more likely to run through structuring rather than direct retail venue participation. Large asset managers and pension funds are unlikely to trade consumer-facing platforms at scale. But event-linked exposures can, in principle, be referenced within structured products or macro overlays that sit comfortably inside existing mandates.
In that sense, prediction markets may be more valuable as a continuously priced input embedded within others.
Parallels to the Crypto Industry
The current phase will be familiar to those who recall the evolution of crypto derivatives between 2017 and 2019.
Early growth was initially retail-heavy and uneven. Liquidity was thin. Institutional scepticism was widespread. Over time, professional market makers entered, regulatory posture clarified incrementally and derivatives became core infrastructure for the asset class.
Prediction markets appear to be in a comparable transition phase.
Outlook
While engagement today is cautious and experimental, prediction markets are already being evaluated, and in some cases, tested directly — particularly as data inputs rather than trading venues.
That alone marks a structural shift demonstrating that event probabilities are moving from the periphery into the analytical toolkit.
Full structural integration — clearing integration, systematic risk-model incorporation, routine balance-sheet deployment — has not yet arrived. Nor is it guaranteed. But it doesn’t need to be for these markets to matter.
The more credible trajectory is complementary. As liquidity deepens prediction markets may increasingly function as a continuously priced probability layer around policy and macro risk — sometimes read, occasionally hedged and selectively structured via instruments that fit existing custody, counterparty and risk-governance frameworks.
The credibility threshold, at least, has been crossed. What happens next will be determined less by narrative and more by market structure.