Author: Jeff Park Source: X, @dgt10011 Translation: Shan Oppa, Golden Finance

Last week, two media outlets, Axios and More Perfect US (MPU), introduced to the public what prediction markets are. Dan Primack of Axios tried to build a neutral platform and launched a heated debate with the founder of Kalshi (although his stance was already obvious); while Trevor Hayes of MPU was more direct, hyping up prediction markets as a social ill.

To be honest, I partially agree with both sides. As a practitioner who has been deeply involved in the intersection of Wall Street and cryptocurrency for many years, I understand people’s growing uneasiness about excessive financialization – a trend that is creating a social atmosphere of “gambling public health crisis”. But the mistake these media people often make is that they first draw conclusions, and then work backwards to figure out "who is fueling this phenomenon." In the end, they use oversimplified narratives to distort and confuse multiple different issues. One second they were talking about “insider trading,” the next second they were talking about “online casinos,” and in the end it was all attributed to “gambling addiction.”

And this is the core misunderstanding that most people have about prediction markets: no matter how you view the disadvantages of excessive financialization (whether it is zero-expiry date options, swap-type ETFs or Internet celebrity concept stocks), prediction markets should be praised as a tool to enhance individual autonomy, dig out the truth, and practice decentralized moral rights.

I will break down this issue more rationally below.

The blurred boundary between “investment” and “gambling”

The only criterion for judging the boundary between "investment" and "gambling" is whether the behavior has positive expected returns (+EV), rather than whether the system itself is deterministic or random. In other words, it is the players who define the boundaries, not the game itself.

Let’s go into details. In MPU reports, Trevor Hayes always starts his questions with "Obviously prediction markets are gambling..." as if this is a self-evident conclusion. And this fundamental premise needs to be examined first.

The biggest trend in the financial field over the past two decades is that the clear boundaries between "investment" and "gambling" are increasingly blurred:

1. 60% of the trading volume in the U.S. stock market comes from high-frequency trading, which is monopolized by oligopolies such as Jane Street Group and Castle Investment;

2. Passive ETFs account for more than 90% of total ETF management (although active strategies are finally starting to belatedly pick up steam);

3. The average holding period for U.S. stocks has plummeted from nine years in the mid-1970s to only about six months in 2025.

At the same time, the average daily trading volume of U.S. stocks has more than tripled in the past ten years, which is also driven by algorithmic trading. A trend that cannot be ignored even more than these data is: the size of transactions by retail investors has exceeded $5 trillion in 2025, an increase of about 50% from 2023.

But you rarely see commentators charge that "stock trading is gambling." Why? Because most people assume that stock picking is not gambling, it requires skill. This is the key realization: the label “gambling” is unfair because it confuses games of skill with games of pure probability.

For example: Slot machines and poker are both called gambling, but they are essentially different - slot machines are an activity with negative expected returns that rely purely on luck, while poker is an activity that relies on real skills to achieve positive returns.

To put it bluntly, the definition of "investment" and "gambling" basically depends on whether people think the strategy has positive returns, and has nothing to do with the "game" itself, whether it is deterministic (risk-free arbitrage, slot machines) or random (stock picking, poker).

The prediction market, like poker, is a random game with a deterministic component. Whether you consider it "gamble" or "investment" depends entirely on the participant - whether you are a highly autonomous, highly skilled person, the opposite, or somewhere in between.

This leads to the second question: if we think of gambling as participant-driven “speculation,” how exactly do these types of markets work? Where does liquidity come from?

The other side of speculation is insurance

All financial innovations look like gambling when they are first born. Insider trading was rampant in early stock markets, both in futures markets (Eurodollars were the first tool for government officials to conduct political insider trading) and in modern commodity markets (insider trading is almost impossible to define in the traditional sense).

The reason is simple: the other side of speculation is insurance. The two are two sides of the same coin. The essence of this type of zero-sum game is standardized synthetic risk transfer. And not all “information” is naturally generated by the private sector.

Critics of prediction markets often raise a question: "Some markets are purely speculative and cannot create social value and should not exist in the first place."

The most typical example of this kind of view is sports betting. Many people believe that sports are entertainment and that betting for entertainment is inherently unproductive.

But this perception is wrong. Entertainment is social consumption and can even be said to be one of the core sources for human beings to obtain happiness in life. More importantly, entertainment itself is economic consumption and has two-sided market attributes. The annual revenue of the global sports industry exceeds 50 billion U.S. dollars. Taking into account the surrounding ecology such as media, equipment, clothing, sports nutrition, etc., the scale is estimated to exceed 1 trillion U.S. dollars. Take Nike as an example. It pays huge sponsorship fees for athletes and teams. Its capital allocation and risk hedging are naturally closely related to event results and player status.

Society today generally equates sports betting with "casinos" simply because the formal market is not allowed to exist at the federal level, which completely ignores the untapped potential value behind it.

The value of derivatives lies in risk transfer, which is the core principle of all insurance models and asset securitization. The existence of the insurance market inevitably requires speculators as counterparties; in a transparent and open market, this is the only feasible model without government intervention. In fact, most of the failures in the insurance system stem from government intervention that distorts the real market pricing of risk holders. Insurance and asset securitization remain one of the greatest financial innovations to improve capital efficiency.

But controversy remains: To what extent does an incident turn from a normal financial service into a social ill? How to establish “event classification standards”? This brings me to my final point.

Two major characteristics that distinguish prediction markets from other derivatives

The prediction market is different from other derivatives in two core points:

1. Accurate results

2. Has a clear expiration date

A brief review of basic market-making logic: In most financial markets, a central limit order book (CLOB) is used to measure and provide liquidity because assets typically have perpetual value. But the prediction market is different: once the event results come true, the liquidity will instantly return to zero, and there will no longer be any buying and selling orders. This is extremely unfriendly to liquidity providers - a binary return outcome of 0 or 1, completely defeating the assumption of continuous dynamic hedging.

More importantly, the prediction market is a market based on probability, not a market based on price. A contract with odds around the 50% midline is much more liquid than a contract with a 98% probability, because the cost of compensation increases exponentially for every percentage point change in the latter. In other words, liquidity cannot be continuously provided solely by price differences, which fixed-income derivatives traders understand far better than stock traders (for example, when interest rates are at 4% and 0.5%, the same 10 basis point fluctuation has completely different meanings).

This means that in markets where information asymmetry is severe and the results can be accurately predicted, professional market makers are less willing to provide large amounts of liquidity. This also shows that the so-called assumption that insiders use information to "make huge profits" can only obtain minimal benefits in most scenarios. The market will ultimately reflect what people really care about. Even if I knew for sure “whether Jeff Parker will be wearing a Bitwise sweater on his next podcast,” the liquidity in this market would be essentially zero.

Most arguments against insider trading assume that insiders can make huge profits, but this is not the case. A valueless market will not have natural liquidity, and liquidity itself will accurately price the true value of information - and event classification standards will naturally form from this.

Why is the value of prediction markets far greater than the potential risks?

As mentioned earlier, one of the major advantages of prediction markets is accuracy, which is also its most valuable highlight.

In the current era of excessive financialization, asset prices are determined more by technical aspects and capital flows, rather than fundamental analysis and true value. Prediction markets are unique in that they return the purest “basis risk” to the facts themselves.

In the future, if you judge that Tesla’s revenue will exceed expectations, instead of buying stocks whose fluctuations are affected by external factors, it is better to place bets in the prediction market; if you have a unique judgment on non-agricultural data, you do not need to trade Eurodollars or mini-S&P futures, just bet directly on the data itself. In short, accuracy truly rewards excess returns, deep research, and real ability.

Many people accuse the prediction market of harvesting people who lack financial knowledge and assume that "gamblers" will definitely lose money, so it is a social ill. But in fact, the prediction market has the fairest mechanism and can provide positive returns to investors with independent judgment. More importantly, there are no “bookmakers” in prediction markets – unlike Las Vegas casinos that drive away high-yield players, prediction markets welcome truly capable people.

Castle Securities and Charles Schwab have both announced plans to enter the prediction market. Are they “harvesting the economically disadvantaged”? Apparently not. They understand better than most people: the other side of speculation is insurance. The concavity of your risk is exactly the convexity of my return.

Why authoritative media are afraid of the truth market

One last thing to add. After reading the above, you will at least agree: As long as it is properly regulated, prediction markets have great value. We can solve "gambling problems" and "social ills" on the premise that the benefits outweigh the costs. But there is another key question that we have ignored: "What should we do if insider trading occurs in a market that is related to major public interests? Will this become a tool for private profit-making?"

This question is very complex and I will answer it in detail in another article.

I would like to share a book I read recently - "The Gray Lady Winked" by Ashley Lindsberg. The book records the systemic failures of the New York Times that are no accident over the decades: covering up the Great Famine during the Stalin period, reporting abnormally on the rise of Castro, building momentum for weapons of mass destruction in Iraq, and downplaying the danger of Hitler coming to power... This authoritative media has always relied on information channels, ideology, and institutional self-preservation instincts to cover up the truth, create consensus, and whitewash its own mistakes afterwards.

This book allows us to re-understand "media bias": it is not a simple dispute between left and right positions, but a structural problem in which authoritative institutions create consensus and whitewash mistakes.

Back to the beginning: Axios and MPU are also not neutral in this discussion. In the future you will see more and more media criticizing prediction markets, and the reasons they oppose are exactly the reasons why you should support it.

There is no doubt that information has a price. I also often say: The opposite of false information is not necessarily the truth, but information controlled by the state.

The real dispute is: Who has the authority to price information? Who can profit from this? And did this all happen before the public knew about it?

When insiders hoard asymmetric information, financial motives are far less important than power games. Taking advantage of the public's ignorance, information will be weaponized to manipulate public opinion and spread false information, ultimately allowing the market for truth to be controlled. Therefore, the core of opposing insider trading is not economic efficiency, but the right to obtain information - some people trade based on the information they know, while most people can only trade based on the information they are allowed to know.

If you think about this, you will not be pessimistic about the prediction market, but will only look at the world more clearly and accurately. This is why I always believe that being optimistic about prediction markets is one of the most democratic values.