Original author: Jeff Park, Bitwise

Original translation: Saoirse, Foresight News

Last week, two media organizations Axios and MorePerfectUS (MPU) respectively educated the public about what predictive markets are. Dan Primack from Axios attempted to create a neutral dialogue space for the multiple discussions by the founder of the Kalshi platform, even though his own position was not hard to discern; meanwhile, another media outlet’s Trevor Hayes took a clear stance, deliberately exaggerating contradictions and viewing predictive markets as a type of social hazard.

To be frank, I partially agree with both perspectives. I have long navigated the intersecting fields of Wall Street and the crypto industry, and I fully understand the current public unease about the increasing financialization, which has already given rise to a gambling culture that is seen as a public health crisis. However, these reporters generally fall into a misconception: they rashly jump to conclusions, tracing back to find culprits and lumping insider trading, online casinos, and gambling addiction into an overly simplistic and one-sided narrative.

Yet, this is precisely the greatest misunderstanding that the public has about predictive markets: regardless of the various financialization issues caused by 0DTE options, swap ETFs, and meme stocks, predictive markets themselves should be recognized. They empower individuals with a high degree of autonomy and seek to uncover truths; their decentralized nature itself holds legitimate value.

In the following, I will delve into this issue layer by layer.

The blurred boundary between investment and gambling depends only on whether the participants' strategies have a positive expected return (+EV) and is irrelevant to whether the market itself operates on deterministic or stochastic mechanisms. In other words, it is the people that define the two, not the games themselves.

Let’s break this down in detail. I noticed that in MPU's reporting, Trevor Hayes often begins his argument with a presupposed premise: "Since predictive markets obviously belong to gambling…" as if this is an established fact that requires no proof. This foundational assumption needs to be reexamined.

The most significant trend in the financial sector over the past two decades is the continuous blurring of the lines between investment and gambling. There is data to support this:

• 60% of the trading volume in US stocks comes from high-frequency trading, and this sector is monopolized by Jane Street and Citadel;
• Passive ETFs account for over 90% of total assets under management in ETFs (active investment strategies have only recently begun to warm up);
• The average holding period for US stocks has shortened from 9 years in the mid-1970s to about 6 months in 2025.

At the same time, the daily trading volume in US stocks has more than tripled in the past decade, driven largely by algorithmic trading. There is also an irreversible trend: retail trading volume is expected to exceed $5 trillion by 2025, approximately a 50% increase from 2023.

However, very few financial commentators accuse stock trading itself of being gambling. Why is that? The public generally defaults to the notion that stock picking investments do not constitute gambling because people subconsciously believe it requires professional skills. This is crucial: people unfairly lump skill-based games and purely probability-based games together as gambling. For instance, both slot machines and poker are termed gambling, but they are completely different: slot machines rely purely on luck and have negative expected returns; while poker depends on technical strategy, which can fully achieve positive expected returns.

To put it bluntly, the criterion for distinguishing investment and gambling only looks at whether the strategy can achieve positive returns, and is unrelated to the game itself—regardless of whether the game is deterministic arbitrage, a fixed-result model like a slot machine, or a random fluctuation model like stock picking or poker.

Predictive markets are similar to poker, belonging to a random game that contains inherent deterministic logic. Whether it is considered investment or gambling is entirely determined by the participants themselves: it depends on whether you are a highly autonomous, highly skilled person, or a low-autonomy, low-cognitive-level person, or somewhere in between. This leads us to the second question: if we understand gambling as a speculation-driven behavior led by individuals, how does such a market operate, and where does its liquidity come from?

Speculation has another side, which is risk hedging (insurance).

All financial innovations are viewed as gambling at their inception. The early stock markets were rife with rampant insider trading, and the futures market for Eurodollars almost became a tool for politicians to engage in insider trading; even today’s commodity trading is hard to define using traditional definitions of insider trading—this is the case. The root cause is that speculation and hedging are two sides of the same coin. This is a zero-sum game, with the core being risk transfer; and not all information is inherently generated by private entities.

This brings us to the most common criticism of predictive markets: some markets have purely speculative attributes and cannot create value for society, and thus should not exist. The most common example they cite is sports betting. In the public’s ingrained perception, sports are entertainment, and betting for entertainment has no social value.

However, this viewpoint is fundamentally flawed. Entertainment itself is a form of social consumption for humanity, and it can even be argued that entertainment is one of the core sources of life satisfaction. More importantly, entertainment is itself an economic activity, possessing bilateral market characteristics. The global sports industry generates annual revenues exceeding $50 billion, and when combined with surrounding industries such as media, equipment, apparel, and sports nutrition, the total scale is estimated to exceed $1 trillion. Take Nike as an example; it invests significant sponsorship funds into teams and athletes, which itself must be based on the allocation of capital and risk hedging according to event outcomes and athlete performances. Just because the U.S. has not opened an official compliant market, the public equates sports betting with casinos, completely ignoring its potential financial value.

The core value of derivatives lies in achieving risk transfer. This is the underlying logic of all insurance products and asset securitization. To achieve risk hedging, there must be speculators on the other side of the market; in an open, transparent market with no government intervention, this structure is irreplaceable. In fact, most issues that arise in insurance systems are due to government intervention distorting true market pricing. Insurance and securitization are among the greatest financial innovations in human history that enhance capital efficiency.

Yet, we still cannot escape a core question: how do we define whether something is a social hazard or possesses practical value as a financial service? How do we establish a system for categorizing events? Next, I will elaborate on the core argument of this article.

Predictive markets differ from other derivatives in two core characteristics: precision and a finite expiry date.

Let’s return to the fundamental principles of market making to understand this. Ordinary financial markets rely on central limit order books to provide liquidity, and the underlying assets have perpetual value. But predictive markets are entirely different: once the corresponding event is settled, market liquidity will drop to zero, with both buyers and sellers completely exiting the market. The binary 0/1 payout result renders conventional dynamic hedging strategies completely ineffective, posing significant challenges for professional market makers.

More importantly, predictive markets are odds-based markets, not price-based markets. This means that slight fluctuations within a 50% probability range have far greater liquidity than fluctuations in a 98% extreme probability range — the latter's payout cost will increase exponentially with each point of odds change. Therefore, liquidity cannot simply rely on spread supply continuously, a fact that fixed-income derivatives traders are well aware of (for example, a 10-basis-point fluctuation at a benchmark interest rate of 4% and a 10-basis-point fluctuation at 0.5% have drastically different meanings).

In summary, in event markets where there is a significant information gap and participants have absolute information advantages, professional market makers will almost never enter to provide liquidity. This also means that the scenario where "insiders profit by relying on informational advantages" envisioned by critics has extremely limited profit potential in the vast majority of cases. The market itself will spontaneously filter out the events that the public truly cares about.

For instance, I know very well whether my next podcast episode will feature Bitwise-branded apparel, but the corresponding predictive market is unlikely to generate any liquidity. One major concern of the public against insider trading is that insiders will earn exorbitant profits, yet the reality is not so: obscure, unvaluable events inherently lack liquidity, and the market liquidity itself has already priced in the value of information. A reasonable event grading system will thus naturally form.

So, what is the value of predictive markets that is sufficient to cover their potential risks?

The precision mentioned earlier is its most precious characteristic. Currently, the global financial situation is engulfed by excessive financialization, with asset prices increasingly influenced by capital flows and technical trends, detaching from fundamental realities; predictive markets are one of the few tools that allow prices to anchor directly to facts and filter out unnecessary disturbances.

In the future, if you have a fundamental assessment that Tesla's revenue will exceed expectations, instead of directly buying and selling Tesla stock (whose price may also be influenced by irrelevant macro factors, market trends, and capital), it is better to place bets in predictive markets; if you want to predict non-farm payroll data, you need not trade Eurodollar futures or stock index futures, but can directly participate in the corresponding predictive market. This precise attribute will genuinely reward in-depth research, professional judgment, and real informational advantages.

There is a significant amount of critical voice from the outside claiming that predictive markets exploit financially uninformed ordinary people, and that participants generally incur losses, characterizing it as a social hazard. However, the reality is quite the opposite: predictive markets operate with the fairest mechanism that rewards professional investors possessing informational advantages. Moreover, there are no house cuts like casino platforms, making predictive markets completely different from Las Vegas casinos — casinos will expel consistently profitable players, while predictive markets welcome all participants who have informational advantages.

Citadel Securities and Charles Schwab have both announced their entry into the predictive market business. Are these giants exploiting vulnerable groups? Clearly not. They understand more profoundly than the public: speculation and hedging are interdependent, and one party's risk exposure is precisely the profit space for the other party.

Why do authoritative media fear this truth market?

(Note: "Gray Lady" refers to The New York Times. In earlier years, the print version of The New York Times used gray uncoated paper, black-and-white typesetting, and very few colored images, giving it a solemn and dark appearance; coupled with a rigorous and conservative writing style, solemn wording, and the traditional authoritative media temperament, it is referred to by readers and industry as the Gray Lady. This term generally refers to traditional authoritative media, mainstream American opinion leaders, the mouthpiece of American elites, and the traditional large media that hold discourse power.)

By this point, you should understand that under reasonable regulation, predictive markets hold significant potential. As long as the returns outweigh the risks, issues such as gambling addiction and social negative effects can find resolution pathways. However, we still have a key question remaining: will insider trading concerning major public events lead to unfair private monopolistic profits?

This question is quite complex, and I will write separately to answer it in detail. Here, I would like to share a line of thought and a book I recently read — Ashley Rindsberg’s "The New York Times's Ambiguous Complicity."

This book outlines the systematic dereliction of duty by this authoritative media over decades, and it is not due to accidental errors: concealing the Stalin-era famine, whitewashing the rise of Castro, generating hype around the rumors of Weapons of Mass Destruction in Iraq, downplaying the risks of the rise of Nazis. The New York Times has consistently relied on information channels, ideology, and institutional self-preservation needs to distort truth dissemination.

Understanding this book will make it clear that media bias is not a simple matter of left or right, but a deeper structural issue: top authoritative institutions actively create social consensus and then whitewash their reporting errors afterward.

Returning to the initial topic: Axios and MorePerfectUS are not neutral parties in the industry. This is also the reason why more and more media will criticize predictive markets in the future. But you must be clear: the reasons they reject predictive markets are precisely the reasons you should support them.

Information inherently has a price; this is a point that does not require debate. I have always believed: the opposite of false information is never absolute truth; the opposite of false information is information under official control.

The real debate has never been about the pricing of information itself, but rather about who has the right to define information, who can profit from information, and whether information has already been monopolized and utilized before the public is aware of it.

When insiders hoard asymmetrical information, profit is secondary; the core issue is power contention. Relying on the public’s informational disadvantage to reap benefits, information may be used to manipulate public opinion, create false narratives, and the entire truth dissemination system can be trapped by monopolization.

Therefore, the core of opposing insider trading has never been about economic efficiency, but rather about the equality of information access rights: some people trade based on exclusive information, while ordinary people can only access filtered and allowed information.

After understanding this layer, you will not hold a pessimistic view of predictive markets but will instead look at the world with a more precise and rational perspective. This is also the reason I firmly believe: being optimistic about predictive markets is itself a deeply democratic value concept.

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