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Prediction markets have exploded into the mainstream over the last two years, drawing attention from investors, traders, institutions, and policymakers who increasingly view them as an alternative way to measure probabilities and future outcomes. But according to Evercore ISI strategists, not every prediction market delivers useful insight.

In a new analysis led by strategist Julian Emanuel, the firm outlined a framework for identifying when these markets become genuinely valuable forecasting tools and when they become little more than a reflection of speculation and public sentiment.

Their conclusion was straightforward: prediction markets tend to work best when they have high trading volume, shorter time horizons, and simple contracts with clearly defined outcomes.

However, the analysts stopped far short of calling prediction markets a perfect crystal ball for investors.

Instead, they argued that these platforms are better understood as a measurement of collective expectations rather than a machine capable of discovering the future.

The Formula Evercore Says Improves Forecast Accuracy

Prediction markets operate by allowing participants to trade contracts tied to future events. The price of those contracts effectively translates into a probability estimate for an outcome.

For example, if a contract implying a presidential candidate's victory trades at 70 cents, the market is effectively suggesting a 70% chance of success.

Evercore's research found that certain conditions consistently increased reliability.

High-volume contracts generally produced stronger probability signals because they included more participants, larger amounts of capital, and a broader range of opinions.

Shorter-term contracts also performed better than long-dated markets because they involve fewer unknown variables and less room for changing circumstances.

Simple contracts with objective rules were another critical factor.

Questions such as:

"Will interest rates rise this quarter?"

or

"Will inflation exceed a specific percentage by a certain date?"

can generally be resolved with straightforward data.

The clearer the outcome, the stronger the usefulness of the prediction.

Most Markets Suffer From a Major Liquidity Problem

One of the most significant weaknesses identified by Evercore involves trading activity itself.

While prediction markets have grown rapidly in visibility and popularity, the overwhelming majority of contracts still attract limited participation.

Research showed that only around 8% of events listed on major prediction platforms such as Kalshi and Polymarket generate more than $1 million in trading volume.

The situation becomes even more noticeable when looking exclusively at active markets.

As of recent measurements:

• Nearly 60% of live markets carried less than $1,000 in trading volume

• Only around 5.3% of active contracts exceeded $100,000 in trading volume

This imbalance creates a major challenge because low liquidity can distort market signals.

When only a small number of participants are trading, a single investor with significant capital can substantially move prices, creating the appearance of changing probabilities even if broader market opinion remains unchanged.

Thin markets can therefore create misleading conclusions.

Why Prediction Markets Perform Well During Uncertain Economic Events

Despite their limitations, Evercore highlighted areas where prediction markets may outperform traditional forecasting methods.

Periods of macroeconomic uncertainty and rapidly changing global events appear to be environments where prediction markets become especially useful.

Unlike traditional forecasting systems that depend on surveys, polls, analyst opinions, or economic models, prediction markets react almost immediately to real-world developments.

When major headlines emerge, prices can adjust within seconds.

Traditional forecasting tools can sometimes suffer from:

• Polling inaccuracies

• Expert bias

• Delayed information

• Subjective assumptions

Prediction markets, meanwhile, continuously incorporate fresh information into prices through buying and selling activity.

Analysts noted that the diversity of participants often strengthens this process.

These markets can include:

• Macro traders

• Financial institutions

• Industry experts

• Regional specialists

• Retail investors

• Political observers

The combined participation creates a dynamic environment where multiple perspectives are reflected simultaneously.

According to Evercore, market pricing may not deliver a perfect forecast, but it often becomes a useful representation of real-time consensus expectations.

Diversity Can Strengthen Markets But Also Distort Them

The same diversity that improves market depth can also create unexpected complications.

Not every participant enters a market for the same reason.

Some traders are seeking profit opportunities.

Others may be hedging exposure.

Some participate for entertainment purposes, while others may simply want to express personal opinions.

Evercore warned that these varying motivations can contaminate price signals.

For example, in geopolitical prediction markets, trades may sometimes reflect emotional reactions, political beliefs, or fears rather than objective analysis.

Instead of predicting what is likely to happen, market prices may occasionally reflect what participants want to happen or fear could happen.

This creates additional noise within the system.

Ambiguous Questions Can Weaken Forecast Quality

Another major issue involves contract design itself.

Prediction markets appear strongest when outcomes are objective and measurable.

However, many real-world events are not easily reduced to a simple yes-or-no answer.

For example, a contract asking:

"Will a ceasefire hold?"

sounds straightforward but can create interpretation problems.

Questions immediately emerge:

How long must it hold?

What qualifies as a violation?

Who determines the final outcome?

Ambiguous wording creates uncertainty that can shift attention away from the real event and toward technical interpretations of contract language.

Analysts suggested that poorly defined contracts can weaken the quality of prediction signals.

Simple Questions Solve Problems But Leave Gaps

Although straightforward contracts generally work better, simplicity has limitations as well.

Real-world events are often complex and involve multiple layers of uncertainty.

Reducing those events to a binary outcome can sometimes hide important information.

A simple yes-or-no contract might capture only a narrow piece of a much larger story.

For investors making major decisions, that missing context can matter significantly.

A single market price may suggest one probability while overlooking economic, political, or strategic factors that influence broader outcomes.

Why Prediction Markets Have Experienced Massive Growth

Prediction markets have moved from niche financial tools to mainstream discussion topics at remarkable speed.

Several developments have accelerated this expansion:

• Increased institutional participation

• Improved trading infrastructure

• Wider contract offerings

• Growth in retail investor activity

• Regulatory developments

A major turning point came with the approval of election-related contracts on Kalshi following decisions involving the U.S. regulatory environment during the 2024 election cycle.

Major platforms including Kalshi and Polymarket saw substantial volume increases during the presidential election period.

However, analysts noted that trading activity accelerated even more dramatically during late 2025 as broader adoption increased.

The Bottom Line for Investors

Evercore's message is relatively clear: prediction markets can be valuable, but context matters.

High-volume markets with short timelines and clearly defined outcomes appear to provide the most useful information.

Low-volume contracts, ambiguous wording, and emotionally driven participation can reduce reliability.

Prediction markets may not predict the future with precision, but they can offer a real-time window into what large groups of people collectively believe is likely to happen.

For investors, that distinction could make the difference between using prediction markets as a decision-making tool and mistaking crowd sentiment for certainty.