2028 Presidential Election: Putting Your Money Where Your Mouth Is

A ccording to political prediction markets, Marco Rubio is the most likely next president (17 percent probability). JD Vance (16 percent) is the second choice of those risking real dollars. Third choice is a tie between two Democrats, Gavin Newsom and Jon Ossoff (both 11 percent). No one else is in double digits. That likely says less about overall Republican advantage than about how fragmented and uncertain the Democratic field currently appears.

Prediction markets are not without their controversy. Their proximity to sports gambling, regulatory turf battles, Trump family connections, and insider-trading accusations connected to the apprehension of former Venezuelan leader Nicolás Maduro, and even the Super Bowl halftime show, have seen to that.

But they also provide a valuable service. Investors do not need to love politics to care about election outcomes. Taxes, antitrust policy, tariffs, subsidies, and approvals for drugs and drilling all affect asset prices, so professional investors closely monitor politics and policy. Since Washington’s machinations are outside the bailiwick of the stock picker, insight has been sought from pundits and polls, with mixed success. These peer-to-peer exchanges offer a market-based alternative.

In the past, skeptics have pointed to the lack of liquidity in election markets. Historically, U.S.-accessible election markets capped individual contracts at less than $1,000 per trader. Others have pointed to market manipulation. Famously, there was a “Romney Whale” in 2012 who, through his prediction-market positions, was able to inflate Mitt Romney’s apparent odds to as high as 1 in 3 early on Election Day despite strong evidence that Barack Obama would win.

These markets are now deeper and more liquid than ever before. To date, the Kalshi market for the 2028 Democratic presidential nominee has traded $153.4 million of volume. That level of depth makes prediction markets increasingly useful not simply as gambling vehicles but as tools for aggregating probabilistic information.

The advantage of prediction markets is that there is accountability. The anonymous Romney Whale is thought to have lost several million dollars as the market collapsed. Markets impose a level of accountability often missing from the conversation. Disagree with the pundits? Fine, put up some money. Think the polls are off? Great, buy a contract.

With most of the current punditry and polling focusing on the 2026 midterms, prediction markets can offer a glimpse of what’s to come shortly after the midterms.

The first question to be answered is who will run. Traders have prices for each of the top candidates. On the Democratic side, Gavin Newsom and Andy Beshear are viewed as the Democrats most likely to enter the race (86 percent chance each) while Kamala Harris is given a 68 percent likelihood, and Alexandria Ocasio-Cortez only 63 percent.

For Republicans, JD Vance (78 percent) is seen as most likely to run, followed closely by Ted Cruz (67 percent) and then Marco Rubio (63 percent).

The market to win the Democratic nomination has Newsom first, at 20 percent, seemingly low for a front-runner. Ocasio-Cortez (16 percent) and Ossoff (15 percent) are second and third, respectively. This implies that the ultimate nominee has a high chance (49 percent) of being someone else.

To win the GOP nomination, the market sees two clear front-runners in Vance (40 percent) and Rubio (29 percent). This implies that the remaining field has a collective chance of 31 percent.

There are several interesting inferences that can be drawn from comparing the different markets mentioned above. For example, despite apparent interest and enthusiasm from Democrats, Alexandria Ocasio-Cortez is seen as not especially likely to enter the presidential race, perhaps because she may run for a New York Senate seat, the likelihood of which is 55 percent according to a separately traded market on that question. For Republicans, it’s interesting to note that Vance is seen as more likely to be the nominee, but Rubio is viewed as more likely to become president. This apparent contradiction is reconciled by the insight that the market believes that Rubio would be a strong general election candidate, with a 59 percent chance of winning the presidency if he becomes the nominee. Vance, by contrast, is seen to have only a 40 percent chance if he’s the GOP’s choice.

Prediction markets force traders to think probabilistically rather than tribally. While a partisan voter may insist that his preferred candidate is “obviously” strong, markets wrestle with a more nuanced set of questions. Will the potential candidate even run? Can that person consolidate a coalition? Can he survive a primary? How would he perform in the general election? Each contract embeds not one prediction but a whole chain of interlocking probabilities. That structure can reveal subtleties otherwise missed. Rubio’s stronger general election pricing relative to Vance, for example, suggests that traders believe he appeals to a broader coalition even while Vance may currently be better positioned within the Republican primary electorate.

The two leading prediction markets are Polymarket and Kalshi. Historically, Polymarket operated as an offshore, on-chain market that was not available to those in the U.S. In July 2025, Polymarket acquired QCX, a CFTC-regulated entity. Polymarket’s U.S. offering is still evolving from a beta trial and lengthy wait list. Kalshi, by contrast, has operated as a CFTC-designated contract market since November 2020.

Historically, long-dated election markets faced a practical challenge: Many traders were reluctant to tie up capital for years on low-probability outcomes. Kalshi partially addresses this problem by paying interest on cash collateral and allowing offsetting positions in multi-candidate markets to be netted against one another. These mechanics improve capital efficiency and help explain why modern prediction markets are becoming deeper and more liquid than their predecessors. For these reasons, this article uses Kalshi prices when quoting market-implied probabilities. Probabilities are as of 2:45 PM (EDT) on July 16, 2026, and, for brevity, figures have been rounded off to the nearest percentage point.