Original title: Prediction Markets: They Grow Up So Fast , Author: Alex Immerman ( @aleximm )
Compiled by Odaily Odaily( @OdailyChina ); Translated by Asher ( @Asher_0210 )
Editor's Note: In late March of this year, prediction markets, once considered a fringe field, reached a pivotal moment. Kalshi Research, a research arm of Kalshi, held its inaugural research conference in New York, bringing together academics, Wall Street executives, former politicians, and frontline traders. The composition of the attendees sent a clear signal— prediction markets are moving from a niche to the mainstream .
The conference opened with a conversation between Kalshi co-founder Tarek Mansour and Luana Lopes Lara, moderated by Bloomberg reporter Katherine Doherty. This article excerpts and summarizes the key points from the conference.
Prediction markets are not limited to elections and sports.
For a long time, prediction markets have been defined by certain "highlight moments"—the US presidential election, the Super Bowl, and March Madness. These events dominate the news cycle and naturally consume most of the trading volume, leading outsiders to mistakenly believe that the value of prediction markets is limited to these events.
But this impression is being shattered. Just as the conference was being held, weekly trading volume for sports-related projects approached $3 billion, accounting for approximately 80% of Kalshi's total trading volume. While seemingly a standout performer, this masks a more crucial trend: the proportion of sports-related transactions is actually at an all-time low.
In other words, all other categories are growing faster . Entertainment, crypto, politics, and culture are among the sectors experiencing stronger user growth and more stable retention. Sports is more like an entry point product—it's intuitive, emotionally driven, and has a clear rhythm, making it suitable for attracting mass participation. Meanwhile, the long-tail market, accounting for over 20% of total trading volume, is growing rapidly, and these markets will play a significant role in institutional hedging and information pricing in the future.
This view is also corroborated by institutional investors. Cyril Goddeeris, co-head of Goldman Sachs' global equities business, stated that forecasts related to macroeconomic events and CPI are currently the most closely watched categories on Wall Street. Sally Shin, head of CNBC's growth platform, mentioned that she is already using forecasts of the Federal Reserve Chairman's market and non-farm payroll data as narrative tools. Troy Dixon, co-head of global markets at Tradeweb, envisioned a future where large investment banks will establish dedicated forecast market trading departments, with financial contracts as their core products.
Prediction markets are shifting from "entertainment trading" to "information and risk tools".
Why did Kalshi attract Wall Street's attention?
The efficient operation of traditional financial markets largely relies on the existence of universally accepted benchmarks for various assets. The S&P 500 represents the average performance of 500 stocks, while crude oil has the ICE benchmark price. However, for political and economic events (such as who will win an election, whether a tariff will be passed, or the outcome of a Supreme Court case), there have been almost no widely accepted and dynamically updated "benchmarks" in the past.
Prediction markets have changed this. Today, the future of almost any event can have a real-time, liquid price benchmark . When the market can provide a credible price for the probability of a 30% tariff passing, institutions can trade around that price or hedge other risks in their portfolios. This makes the event itself a directly tradable object.
As Tradeweb's Troy Dixon put it: "If we go back to when Trump was first elected, many people were hedging in the stock market, for example, short the S&P 500, because they thought his election would cause the market to fall. But that was a bad trade. The question is, how should these events be priced in? Where is the benchmark?"
Tarek also mentioned that one of his motivations for founding Kalshi stemmed from his previous work at Goldman Sachs advising on trades surrounding the 2024 general election and Brexit. Without market prediction, when institutions hedge political or macroeconomic events with related assets, they actually need to simultaneously make two judgments—one on the outcome of the event itself, and another on the relationship between the event and the traded assets, the latter of which carries the risk of failing on its own.
When an event itself has a direct price benchmark, the previously separate risks are merged into a single judgment. As Tarek stated, the market has begun to price in various events.
Three stages towards institutional adoption
It is too early to conclude that Wall Street institutions have engaged in large-scale Kalshi trading. Currently, most institutions still primarily use it as a data reference rather than actual trading .
However, Luana points out that the path adopted by the institution is already very clear and can be divided into three stages:
- The first phase is data integration : incorporating market price predictions into the daily workflows of institutions, such as allowing Goldman Sachs investment managers to view Kalshi's odds like they would the VIX index. This phase has already been achieved to some extent. Johns Hopkins University professor and former Federal Reserve official Jonathan Wright stated that Kalshi is almost the sole source of reference for Federal Reserve decisions, unemployment rates, and GDP.
- The second phase is system integration : including compliance approval, legal confirmation, technology access, and internal training, which involves incorporating the forecasting market into a system of usable financial instruments;
- The third stage is actual trading : institutions begin to hedge risks on the platform, and trading volume and liquidity gradually accumulate, forming a positive feedback loop. More hedgers attract more speculators, tighter spreads attract more hedgers, and the benchmark price is continuously strengthened.
Currently, most institutions are still in the first phase, some have entered the second phase, and only a few have entered the third phase.
A major obstacle preventing institutions from entering Phase 3 is that current market prediction trading requires full margin; a $100 position requires a corresponding $100 deposit. This is acceptable for retail investors, but a significant limitation for hedge funds or banks that rely on leverage and capital efficiency. As Tarek stated, if you want to hedge $100, you must deposit $100, which is too costly for institutions; institutions like Citadel or Millennium would not adopt this approach. Kalshi has already obtained a license from the National Futures Association and is working with the Commodity Futures Trading Commission to introduce a margin trading mechanism.
What will happen next?
Michael McDonough, head of market innovation at Bloomberg, offers a straightforward assessment: the hallmark of success is that these things become boring . He compares the forecasting market to the options market of the 1970s, when it also faced controversies over manipulation and regulatory uncertainty, but these issues were eventually digested and evolved into an infrastructure that requires almost no thought.
AQR partner Toby Moskowitz said he's willing to bet on the future of the prediction market. Within five years, or even less, it will become a viable tool at the institutional level.
Garrett Herren of Vote Hub describes the final form where the question is no longer whether to use prediction markets, but how to use them. Once the discussion shifts to this level, it means they have become indispensable. Indeed, while prediction markets are still relatively small, the hedging market itself is enormous.
The normalization of market prediction is already underway.
In discussions on political issues, former Congressman Mondaire Jones noted that top figures from both parties, including Trump, House Minority Leader Jeffries, and Senate Minority Leader Schumer, have begun publicly citing Kalshi's odds . DDHQ's Scott Tranter also confirmed that forecasting market data has now become a crucial input for party decision-making. Meanwhile, Vote Hub announced that it has directly integrated Kalshi data into its midterm election forecasting model.
These things were almost nonexistent two years ago. Back then, the most successful traders on Kalshi were still considered amateurs. But now, things have changed, and it's difficult to define them with that term anymore.
At the roundtable, four traders shared their journeys. One spent eleven years studying the Billboard charts, while another had been involved in prediction markets since 2006—back when it was just a niche hobby with limited funding and a slightly geeky vibe. They didn't come from the financial industry, but from diverse backgrounds including music, politics, and poker. However, they all agreed that what this platform truly rewards is deep knowledge of the field, not a resume.
summary
Prediction markets have come a long way. They were once considered academic experiments, later became a brief hot topic during election cycles, and were also seen as an extension of sports betting.
The message conveyed by this conference is quite clear: prediction markets are gradually evolving into an infrastructure for pricing uncertainty, serving a wide range of participants from retail investors to large institutions and diverse application scenarios.
