I’ve spent more than a decade building analytical tools for options traders. Over the past year, I’ve turned that same lens on prediction markets. What I see is an asset class with extraordinary potential that’s moving fast but still has meaningful gaps to close before it can serve the full range of strategies that options markets support.
The good news: the exchanges are aware of most of these gaps, and there’s clear evidence that solutions are in development. The prediction market ecosystem is evolving at a pace that few new financial markets have matched, driven by strong institutional interest, growing regulatory clarity, and billions of dollars in investment.
Here’s what the market needs, and where I think it’s headed.
For background on prediction market mechanics: What Are Prediction Markets? A Guide for Investors. For how they compare to options: Binary Contracts vs. Puts and Calls. For why they’re not gambling: Are Prediction Markets Gambling? Why the Framing Is Backwards
Term Structures
If you trade options, term structures are part of your daily workflow. You can trade weekly, monthly, and quarterly expirations on the same underlying. The term structure itself contains information: the relationship between short-term and long-term implied volatility tells you something about market expectations for upcoming catalysts, seasonal patterns, and structural risk.
Prediction markets have some early term structure for recurring events. You can trade Fed rate contracts across multiple upcoming FOMC meetings simultaneously. But the depth and continuity lag far behind options. There’s no equivalent of the weekly/monthly/quarterly expiration series that options traders use for calendar spreads and term structure analysis. You get a handful of discrete event dates, not a rich multi-expiration curve to analyze.
Where it’s headed
This is a natural next step for exchanges competing for institutional volume. Kalshi and Polymarket are both expanding their contract offerings rapidly. Recurring economic events like monthly inflation readings, quarterly GDP reports, and regular Fed meetings are obvious candidates for rolling contract series. Some early versions of this are already visible in how both platforms handle sequential economic data releases. As the volume of available contracts grows, the ingredients for meaningful term structures will fall into place.
Scalar Markets: Beyond Binary
Today’s prediction markets are almost exclusively binary: will this happen, yes or no? This is powerful for directional views on specific events, but it limits the expressiveness of the instrument compared to options, where the payoff varies with the magnitude of the underlying’s move.
This will change. Both Kalshi and Polymarket have built support for scalar markets into their exchange architecture. Scalar markets ask “what will the value be?” rather than “will this happen?” and allow contracts across a continuous range of outcomes. A scalar prediction market on the S&P 500’s year-end level would create a probability distribution across outcome ranges. It would look remarkably like an options chain, but with direct, transparent probability pricing instead of implied volatility calculations.
Scalar market types already appear in exchange APIs, signaling clear directional intent even if the timeline for full deployment remains uncertain. Given the pace of development at both major exchanges and the clear demand from institutional participants, scalar markets are a “when” not an “if.” And when they arrive, they fundamentally expand what’s possible—bringing prediction markets much closer to the expressiveness that options traders need.
For how binary payoffs currently compare to options payoffs: Binary Contracts vs. Puts and Calls
Rolling and Continuous Strategies
Many popular options strategies depend on continuous execution across multiple expirations. The “wheel” strategy, income-focused premium selling, and systematic rolling programs all require a continuous flow of expirations with adequate liquidity.
Prediction markets can’t fully support this today. The contract lifecycle is typically a single event with a single resolution.
Where it’s headed
As term structures develop, rolling mechanics should follow naturally. If monthly contracts exist on the same theme, the basic ingredients for rolling strategies are in place. Exchanges could even build explicit roll functionality that automatically transitions a position from one contract to the next, similar to how futures platforms handle contract rolling today.
For more on what works today for income-focused investors and what’s coming: Income Strategies in Prediction Markets: What Works Today and What’s Coming
Contract Granularity and Event Types
An options trader on a major stock can choose from hundreds or thousands of strike-expiration combinations. Prediction markets currently offer a fraction of this granularity.
The market has evolved beyond simple yes/no propositions into several structural varieties: single-outcome, multiple-outcome, categorical, range, cumulative, and spread events. Each type creates different analytical opportunities.
Cumulative Thresholds as a Bridge to Scalar
Cumulative markets deserve special attention because they’re the closest thing to an options strike chain available today. Contracts like “Fed funds rate above 3%”, “above 4%”, and “above 5%” on the same event create a de facto strike chain. You can build vertical spreads, sell the tails for iron condor-like structures, and construct defined-risk positions that feel familiar to options income traders. When these cumulative thresholds exist across multiple settlement dates, you get something approaching an expiration cycle.
Cumulative markets are a meaningful bridge between today’s binary landscape and the full scalar market future. They’re tradeable now, and they reward the kind of spread analysis that options traders already do.
For specific strategies using cumulative thresholds: Income Strategies in Prediction Markets: What Works Today and What’s Coming
Spread Events and Pair Trading
Spread markets, currently most common in sports, compare two outcomes directly: “Will Team A beat Team B by more than 7?” Conceptually, this is pair trading—a direct relative-value bet without needing to construct a long/short position in separate instruments.
The interesting possibility is extending spread markets beyond sports. A contract like “Will Stock X outperform Stock Y by more than 500bps this quarter?” would offer direct, transparent relative value without the complexity of constructing a long/short equity position. This is speculative, but the structural framework already exists and the extension to financial markets is natural.
Where it’s headed
Scalar markets will be the biggest driver of improved granularity. But even within the current framework, both Kalshi and Polymarket are steadily increasing the number of contracts and thresholds available per event. Each quarter brings noticeably more markets with finer-grained outcome ranges. The trajectory is toward the kind of contract richness that supports nuanced multi-leg positions.
Cross-Event Portfolio Analytics
Most prediction market platforms treat each market as an island. There’s no built-in framework for understanding how your positions relate to each other or whether you’re inadvertently concentrated in correlated outcomes.
For why portfolio-level thinking matters so much: The Case for Prediction Market Portfolio Theory
Where it’s headed
This is an area where third-party tools are leading the way. With Qwidgets for Prediction Markets, you can already model relative likelihoods of outcomes within an event and generate optimized position sizing using approaches like Kelly criterion. Cross-event portfolio analytics, including understanding correlation and constructing diversified portfolios across multiple events, is the natural next frontier and part of the Qwidgets roadmap. We envision the platform evolving into the single place investors go to analyze, monitor, and trade predictions, equities, options, crypto, and more with robust support for cross-portfolio and cross-asset metrics and analytics.
The Underlying Asset Question
Options derive their value from an underlying asset you can separately own and trade. Prediction market contracts have no separately tradeable underlying. This is structural rather than a maturity issue.
But this isn’t necessarily a limitation. It’s a different design. Prediction markets give you direct exposure to the event itself, without the noise of a proxy instrument. The strategic framework is different: it centers on relative value between correlated contracts, portfolio construction across independent events, and position sizing based on estimated edge.
Market Making and Liquidity
Liquid options markets depend on dedicated market makers who continuously post bids and offers. Prediction market market-making infrastructure is still developing.
Where it’s headed
This is one of the gaps closing fastest. Major trading firms including Susquehanna and DRW are building dedicated prediction market desks. Kalshi’s FIX protocol connectivity and margin trading are explicitly designed to attract institutional market makers. ICE invested $1.6 billion in Polymarket. The economic incentives are strong, and the infrastructure is being built at speed. As these participants enter, spreads will tighten, depth will increase, and execution quality will improve across the board.
The Big Picture
What strikes me most about prediction markets in 2026 is how much the trajectory resembles options markets fifteen years ago. The instruments are sound. The regulatory framework is solidifying. The exchange infrastructure is being built. And critically, the major exchanges and their institutional backers are investing heavily in exactly the features that sophisticated traders need.
A dedicated $35 million VC fund backed by both the Kalshi and Polymarket CEOs launched specifically to fund prediction market tools and infrastructure. The regulatory environment has shifted meaningfully, with the CFTC moving away from its earlier adversarial posture and federal policy appearing broadly supportive of prediction market development, even as state-level regulatory questions remain. Every week brings new contract types, new platform features, and new institutional entrants.
The gaps I’ve outlined here are real today, but most of them have visible paths to resolution. Scalar market types already appear in exchange APIs, signaling clear directional intent. Term structures will emerge as contract offerings expand. Institutional market making is arriving now. Portfolio analytics are being built by both exchange platforms and third-party tools.
The trajectory suggests prediction markets are heading toward becoming a serious, full-featured asset class—the open questions are about pace and form, not direction. And the investors who start building expertise now, understanding both the current capabilities and the near-term roadmap, will have a significant advantage when the rest of the market catches up.
Start exploring prediction markets with analytical tools built for serious investors. Qwidgets for Prediction Markets is free at predictions.qwidgets.com.
