February 16th Why Wall Street is starting to take prediction markets seriously
Posted on February 16, 2026 in Education
For most of their existence, prediction markets have sat outside of mainstream finance. Although an interesting technological and cultural phenomenon, it has been too small, too few transactions, and too often associated with online gambling to attract meaningful institutional attention.
Things will begin to change from 2025 onwards, with rapidly increasing trading volumes, heightened media attention and improved regulatory clarity, making it increasingly difficult for institutions to ignore the sector.
Predictive market odds are now starting to appear in institutional data feeds and mainstream financial reporting. Meanwhile, in January, Goldman Sachs CEO David Solomon said he had met with Polymarket and Kalshi to see how the bank could participate in the space.
These are all early signs of a change in sentiment at the highest levels of traditional finance.
Why 2025 is a turning point
Changes in institutional climate largely followed changes in scale.
Industry data shows that prediction market trading volume will increase from approximately $15.8 billion in 2024 to over $63 billion in 2025, an increase of more than 300% year-on-year.
Liquidity has become more concentrated and durability has increased. Rather than temporarily surging and fading around election cycles, it has begun to maintain a depth of contracts related to central bank decisions, major political outcomes, and cryptocurrency-related catalysts. The record monthly notional volume of $12 billion in January 2026 suggests ongoing interest beyond a one-off headline moment.
That depth is important because it translates into tighter spreads, deeper order books, and stochastic signals that are stable enough for institutions to take seriously.
The U.S. regulatory stance has also developed in parallel. Kalshi’s legal dispute with the Commodity Futures Trading Commission (CFTC) in 2024 led to a clearer distinction between gambling and federally regulated event contracts. The ruling does not resolve uncertainty, and tensions at the national level remain. However, the classification discussion has shifted to something that compliance teams can analyze rather than ignore entirely.
The combination of scale and partial regulatory clarity has changed the institutional calculus. Prediction markets have become large enough to be seriously monitored and clearly structured to be impossible to ignore.
From Signals to Risk Tools
Currently, the most trusted institutional use cases are primarily informational.
Financial markets already operate as expectations machines. For example, bond yields imply predictions about future interest rates and inflation. Option prices capture volatility expectations. Credit spreads reflect an assessment of default risk. Institutions rely on these signals not because they are perfect, but because they represent a capital-weighted consensus view.
Prediction markets apply the same mechanism to individual events.
A contract that pays $1 if a certain outcome occurs and $0 otherwise is traded at a price that can be read as an implied probability. The odds reflect the money at risk and are continuously updated in real time as new information enters the market.
Reports that companies like Oldenburg Capital are experimenting with incorporating predictive market data into their risk models do not signal a wholesale shift in opinion polls or analyst research. But they do suggest that the agency is evaluating whether market-implied probabilities add something incremental, a continuously updated, capital-backed signal that can be used alongside existing tools.
The new pattern is closer to consolidation than wholesale trading. Probability is beginning to find its place within institutional workflows alongside yields, volatility surfaces and credit spreads.
Risk transfer and hedging angles are still tentative.
Traditional derivatives hedge the market’s reaction to events (Fed meeting period, election volatility) rather than the events themselves. Strictly defined binary contracts isolate triggers. Structurally, it is similar to a short-term cash-settled derivative with defined expiration and payment terms.
Public evidence of banks deploying significant balance sheets directly into event contracts remains limited. What is more striking is the specialization of liquidity. Reports that companies such as Jump Trading are seeking to provide equity or liquidity in key venues suggest that price formation is becoming more robust. Deeper books and tighter spreads are prerequisites for serious hedging. Without them, the odds are still fragile.
Long-term institutional pathways are more likely to proceed through structuring rather than direct retail involvement. Large asset managers and pension funds are unlikely to trade on consumer-facing platforms at scale. However, event-related exposures can in principle be referenced within structured products or macro overlays that can be used comfortably within existing regulations.
In that sense, prediction markets may be more valuable as continuously priced inputs embedded in other markets.
Similarities to the Cryptocurrency Industry
The current phase will be familiar to those who remember the evolution of cryptocurrency derivatives between 2017 and 2019.
Early growth was initially retail-driven and uneven. Liquidity was lacking. Institutional skepticism was widespread. Over time, professional market makers came on board, the regulatory status gradually clarified, and derivatives became a core infrastructure for the asset class.
Prediction markets appear to be in a similar transition phase.
field of vision
Today, participation is cautious and experimental, but prediction markets are already being evaluated and, in some cases, directly tested. This is especially true as a data entry rather than a trading venue.
This alone represents a structural change that shows that event probabilities are moving from the periphery to the analytical toolkit.
Full structural integration (clearing integration, systematic risk model integration, routine balance sheet deployment) is not yet complete. It is not guaranteed. But these markets don’t have to be important.
More reliable trajectories are complementary. As liquidity deepens, prediction markets can increasingly function as a continuously priced probability layer for policy and macro risks. Sometimes read, sometimes hedged, selectively structured with tools that fit your existing custody, counterparty, and risk governance framework.
At least the reliability threshold has been surpassed. What happens next will be determined more by market structure than narrative.