Strange! Wall Street giants Citadel and Charles Schwab are quietly making moves, so why are mainstream media collectively afraid of this "truth market"?

Recently, two media organizations coincidentally explained to the public what prediction markets are. One tried to remain neutral, while the other took a clear stance, depicting them as a social hazard. Frankly, I understand some of their concerns. Having spent a long time at the intersection of Wall Street and the crypto industry, I am well aware of the public’s wariness of the over-financialization trend, which has indeed fostered a gambling culture seen as a public health crisis.

But journalists often make a mistake: they jump to conclusions first, then backtrack to find reasons, crudely fitting issues like insider trading, online casinos, and gambling addiction into a simplified narrative. This is the biggest misconception the public has about prediction markets. Leaving aside the problems caused by expiry options, swap-based ETFs, and Meme stocks, prediction markets themselves, because of their decentralization—empowering individual choice and uncovering truths—should be properly recognized.

The boundary between investment and gambling is actually quite blurry. This line does not depend on whether the market mechanism is deterministic or random, but solely on whether participants’ strategies have a positive expected return. In other words, it’s humans who define the game, not the game itself.

Some analyses point out that their argument often begins with “since prediction markets obviously belong to gambling,” as if this is an self-evident axiom. This fundamental assumption is precisely what needs to be re-examined. Over the past twenty years, the boundary between investment and gambling has been continuously dissolving. Data proves this: about 60% of US stock trading volume comes from high-frequency trading, monopolized by a few giants; passive ETFs account for over 90% of all ETFs; and the average holding period of US stocks has shrunk from nine years in the mid-1970s to about half a year today.

Meanwhile, over the past decade, the daily trading volume of US stocks has more than doubled, driven still by algorithms. Another irreversible trend is the rapid expansion of retail trading volume. Yet few commentators accuse stock trading itself of being gambling. Why? Because the public assumes stock picking requires professional skills.

This point is crucial: people unfairly conflate skill-based games with pure probability games. Slot machines and poker are both called gambling, but they are vastly different. Slot machines rely purely on luck and are negative expected value games; poker depends on skill and can achieve positive expected returns. Simply put, the dividing line depends on whether the strategy can make money, not on the game format.

Prediction markets are similar to poker—a form of stochastic game with an embedded deterministic logic. Whether it is investment or gambling depends entirely on the participant: whether you are someone with high autonomy and professional ability, or the opposite.

This leads to a second question: if gambling is understood as human-led speculation, how do these markets operate? Where does liquidity come from? The other side of speculation is risk hedging, which is insurance. Almost all financial innovations at their inception were viewed as gambling.

In the early days, insider trading in the stock market was rampant, and futures markets were used as tools for politicians; today’s commodity trading also cannot be strictly defined by traditional insider information, because the root lies in the fact that speculation and hedging are two sides of the same coin. It’s a zero-sum game, centered on risk transfer, and not all information originates solely from the private sector.

Critics most often question: some markets are purely speculative and cannot create social value, such as sports betting. They believe sports are entertainment, and betting for entertainment has no value. But this view is itself mistaken. Entertainment is a core source of social consumption and happiness for humans, and it is also an economic activity with a bilateral market nature.

The global sports industry generates over 8B USD annually, and with related industries, the total scale is estimated to surpass one trillion USD. Take Nike as an example: its huge sponsorship investments require allocating capital and hedging risks based on event outcomes. Simply because some regions do not have open, compliant markets, equating this with casinos completely ignores its potential financial value.

The core value of derivatives is risk transfer, which is the underlying logic of all insurance and asset securitization. To achieve risk hedging, there must be speculators on the other side of the market. In open and transparent markets, this structure is irreplaceable. In fact, problems with the insurance system are often caused by government intervention distorting true pricing.

So, how do we define whether an event is a social hazard or a valuable financial service? How to establish an event classification system? Prediction markets differ from other derivatives in two major ways: precision and limited expiration.

Ordinary financial markets rely on a central limit order book, with underlying assets having perpetual value. Prediction markets are different: once the event is settled, market liquidity drops to zero, and participants close positions and exit. The binary payout results make traditional dynamic hedging strategies ineffective, posing huge challenges for market makers.

More importantly, they are odds-based markets, not price-based markets. This means that in the 50% probability fluctuation zone, liquidity is much higher than in the 98% extreme probability zone—where each percentage point change in odds exponentially increases the payout cost. Therefore, liquidity cannot be sustained solely through bid-ask spreads.

In events with significant information asymmetry and where participants have absolute informational advantages, professional market makers rarely enter. This means the scenario envisioned by critics—insiders profiting from informational advantages—is actually very limited in most cases. The market itself will naturally filter out events that the public truly cares about.

Obscure, valueless events inherently lack liquidity, and market liquidity itself has already priced in the value of information. A reasonable event classification system will naturally form from this.

So, what is the value of prediction markets that can sufficiently cover their potential risks? The aforementioned precision is their most valuable trait. Currently, the global financial system is overly financialized, with asset prices often influenced by capital flows and technical factors, diverging from fundamentals. Prediction markets are among the few tools that can directly anchor prices to facts and eliminate noise.

In the future, if you have an opinion on Tesla’s revenue, instead of buying or selling its stock (which is affected by macro and market factors), you can bet in a prediction market; if you want to forecast non-farm payroll data, you don’t need to trade Eurodollar futures, just participate in the relevant market. This precision will truly reward in-depth research, professional judgment, and genuine information advantages.

Many critics argue that prediction markets exploit cognitively weak ordinary people, with participants generally losing money. But the reality is quite the opposite: they have the fairest mechanism, rewarding professional investors with informational advantages. Unlike Las Vegas casinos that drain the profits of consistent winners, prediction markets welcome all participants with informational edges.

Citadel Securities and Charles Schwab have announced their involvement in prediction markets. Are these giants exploiting vulnerable groups? Clearly not. They understand more thoroughly than the public: speculation and hedging are two sides of the same coin, and one party’s risk exposure is another’s profit opportunity.

Why does the authoritative narrative always reject this “truth market”? By now, you should understand that under proper regulation, prediction markets have enormous potential. As long as the expected returns outweigh the risks, issues like gambling addiction can be addressed. But a key question remains: could insider trading on public events lead to private monopolistic profits and unfairness?

This question is complex and deserves a separate discussion. Here, I want to share some thoughts and a book I recently read. The book details decades of systemic negligence by a certain authoritative media—no accident: concealing historical tragedies, glorifying dictators’ rise, fueling war rumors, and downplaying extremism risks.

This media always relies on information channels, ideology, and institutional self-preservation, distorting the truth. Understanding this reveals that media bias is not simply a matter of left or right stance, but a deeper structural issue: top-tier authorities actively create social consensus and later whitewash their reporting errors.

Returning to the beginning, neither of those two media outlets are truly neutral. This is also why more and more media will criticize prediction markets in the future. But you must understand: their reasons for opposing prediction markets are precisely the reasons you should support them.

Information inherently has a price, and this is beyond dispute. I have always believed: the opposite of false information is not absolute truth, but information under official control. The real debate is never about the pricing of information itself, but about who has the authority to define it, who can profit from it, and whether it has been monopolized before the public can access it.

When insiders accumulate asymmetric information, profit is secondary; the core issue is a power struggle. Exploiting the public’s informational disadvantage to harvest benefits involves manipulating public opinion, creating false narratives, and monopolizing the entire truth dissemination system. Therefore, the core of opposing insider trading has never been about economic efficiency, but about equal access to information.

Once you understand this layer, you will not be pessimistic about prediction markets, but will view the world with a more precise and rational perspective. That is also why I firmly believe: supporting prediction markets is fundamentally a highly democratic idea.

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