Original Author: Jeff Park, Bitwise
Original Compilation: Saoirse, Foresight News
Last week, two media outlets, Axios and MorePerfectUS (MPU), took turns educating the public about prediction markets. Dan Primack of Axios attempted to create a neutral dialogue space for the founders of the Kalshi platform, although his own stance was not hard to discern; while Trevor Hayes of the other outlet took a clear and sharp position, deliberately exaggerating conflicts and portraying prediction markets as a type of social hazard.
Frankly, I agree with parts of both perspectives. Having long worked at the intersection of Wall Street and the crypto industry, I deeply understand the growing public unease with excessive financialization, a trend that has already fostered a gambling culture viewed as a public health crisis. However, these journalists commonly fall into a misconception: they hastily draw conclusions, then trace back to find a scapegoat, lumping issues like insider trading, online casinos, and gambling addiction into an overly simplistic and one-sided narrative.
But this is precisely the biggest misunderstanding about prediction markets: setting aside the various ills of excessive financialization brought by 0DTE options, swap-based ETFs, and meme stocks, prediction markets themselves deserve recognition. They empower individuals with high autonomy, uncover truth, and their decentralized nature inherently holds legitimate value.
Below, I will deconstruct this issue layer by layer.
The blurred line between investing and gambling depends solely on whether the participant's strategy has a positive expected value (+EV), and has nothing to do with whether the market mechanism itself is deterministic or random. In other words, the distinction is made by people, not by the game itself.
Let's break it down in detail. I noticed that in MPU's report, Trevor Hayes often begins his arguments with a presupposition: "Since prediction markets are obviously gambling...", as if it were an indisputable fact. Yet this foundational assumption is precisely what needs to be re-examined.
The most significant trend in finance over the past two decades has been the continuous erosion of the boundary between investing and gambling. The data proves it:
- 60% of US stock trading volume comes from high-frequency trading, and this field is oligopolized by Jane Street and Citadel;
- Passive ETFs account for over 90% of total ETF assets under management (active investment strategies are only now making a belated comeback);
- The average holding period for US stocks has shortened from about 9 years in the mid-1970s to just about 6 months in 2025.
Meanwhile, the average daily trading volume in US stocks has more than tripled over the past decade, driven again by algorithmic trading. There's also an irreversible trend: retail trading volume surpassed $5 trillion in 2025, an increase of about 50% compared to 2023.
But very few financial commentators accuse stock trading itself of being gambling. Why? The public generally assumes that stock picking isn't gambling because they subconsciously believe it requires professional skill. This is crucial: people unfairly lump skill-based games and pure chance games together under the label of gambling. For example, both slot machines and poker are called gambling, but they are worlds apart: slot machines are pure luck with negative expected value; while poker relies on skill and strategy and can achieve positive expected value.
Put bluntly, the dividing line between investing and gambling depends solely on whether the strategy can achieve positive returns, not on the game itself—whether it's a deterministic arbitrage, a fixed-outcome mode like slot machines, or a random fluctuation mode like stock picking or poker.
Prediction markets, like poker, are random games with deterministic logic. Whether they count as investing or gambling is entirely up to the participant: it depends on whether you are a highly autonomous, highly skilled person, or a person with low autonomy and low cognitive level, or somewhere in between. This leads to the second question: if gambling is understood as speculation driven by people, then how do such markets actually operate, and where does liquidity come from?
The other side of speculation is risk hedging (insurance).
All financial innovations are initially viewed as gambling. The early stock market was rife with rampant insider trading; in the futures market, even the Eurodollar became a tool for politicians' insider trading; and today's commodity trading also struggles to define insider trading in traditional terms—it's always been this way. The root cause is that speculation and hedging are two sides of the same coin. It's a zero-sum game, the core of which is the transfer of risk; and not all information is naturally born within private entities.
This touches on the most common criticism skeptics level against prediction markets: some markets are purely speculative and create no social value, and thus shouldn't exist. Their most frequent example is sports betting. In the public's固有认知 (inherent understanding), sports are entertainment, and betting on entertainment has no social value.
But this view is itself wrong. Entertainment is itself a form of social consumption for humans; one could even say that entertainment is one of the core sources of life happiness. More importantly, entertainment itself is an economic activity with a two-sided market属性 (attribute). The global sports industry generates over $50 billion in annual revenue, and including peripheral industries like media, equipment, apparel, and sports nutrition, the total size is estimated to exceed $1 trillion. Taking Nike as an example, it invests huge sponsorship funds in teams and athletes, and itself needs to allocate capital and hedge risks based on game outcomes and athlete performance. Simply because the US hasn't opened official compliant markets, the public equates sports betting with casinos, completely ignoring its potential financial value.
The core value of derivatives is to achieve risk transfer. This is the underlying logic of all insurance products and asset securitization. And to achieve risk hedging, there must be speculators on the other end of the market; in an open, transparent market without administrative intervention, this structure is irreplaceable. In fact, problems in the insurance system mostly arise when government intervention distorts true market pricing. Insurance and securitization are also among the greatest financial innovations in human history for improving capital efficiency.
But a core question remains unavoidable: how do we define whether something is a social harm or a financial service with practical value? How should we establish a system for categorizing events? This leads to the final core argument of this article.
Prediction markets are distinguished from other derivatives by two core characteristics: precision and finite expiration.
Let's return to market-making basics to understand this. Ordinary financial markets rely on central limit order books to provide liquidity, and the underlying assets have perpetual value. But prediction markets are completely different: once the corresponding event is settled, market liquidity drops directly to zero, and both buyers and sellers close their positions and exit. The binary 0/1 payout outcome makes conventional dynamic hedging strategies completely ineffective, posing enormous challenges for professional market makers.
More importantly, prediction markets are odds-based markets, not price-based markets. This means that small fluctuations within the 50% probability range have far higher liquidity than fluctuations in the extreme 98% probability range—where each point change in odds corresponds to an exponentially increasing payout cost. Therefore, liquidity cannot be supplied simply through continuous spreads, something fixed-income derivatives traders understand deeply (for example, a 10 basis point move when the base rate is 4% means something completely different than a 10 basis point move when it's 0.5%).
In summary, in event markets with huge information asymmetry, where participants have absolute information advantages, professional market makers almost never enter to provide liquidity. This means that the skeptics' scenario of "insiders making huge profits by harvesting others using information advantages" has extremely limited profit potential in most scenarios. The market itself will spontaneously筛选 (screen) for events that the public truly cares about.
For example, I know perfectly well whether I will wear a Bitwise branded sweatshirt in my next podcast, but the corresponding prediction market would basically generate no liquidity. A major public concern opposing insider trading is that insiders will make huge profits, but reality is not like that: obscure, valueless events naturally have no liquidity; market liquidity itself has already priced the information value. A reasonable event grading system will naturally form from this.
So, where exactly does the value of prediction markets lie, enough to outweigh their potential risks?
The precision mentioned earlier is their most precious trait. Currently, global finance is caught in excessive financialization, where asset prices are more influenced by fund flows and technical trends, detached from fundamentals and facts themselves; prediction markets are one of the few tools that can directly anchor prices to facts,剔除 (removing) extraneous interference.
In the future, if you have a fundamental view that Tesla's revenue will exceed expectations, instead of directly buying or selling Tesla stock (whose price is also affected by macro, market trends, funds, and other unrelated factors), you could place a bet in a prediction market; if you want to predict non-farm payroll data, you also don't need to trade Eurodollar futures or stock index futures, you can directly participate in the corresponding prediction market. This precision attribute truly rewards deep research, professional judgment, and real information advantages.
Many external critics believe that prediction markets harvest ordinary people with weak financial literacy, that participants generally lose money, and that they are a social hazard. The truth is恰恰相反 (precisely the opposite): prediction markets have the fairest mechanism, rewarding professional investors with information advantages. Moreover, they have no house edge or platform抽水 (rake), completely different from Las Vegas casinos—casos驱逐 (expel) consistently profitable positive expected value players, while prediction markets welcome all participants with information advantages.
Citadel Securities and Charles Schwab have both announced plans to enter the prediction market business. Are these giants harvesting vulnerable groups? Obviously not. They understand more透彻地 (thoroughly) than the public: speculation and hedging are interconnected; one party's risk exposure is the other party's profit opportunity.
Why the Gray Lady Fears This Truth Market
(Note: Gray Lady refers to The New York Times. In its early years, The New York Times used plain gray paper, black-and-white排版 (layout), and very few color images, giving it a solemn, dull appearance; coupled with its rigorous and conservative writing style, dignified wording, and the沉稳 (steady)气质 (temperament) of an old-school authoritative media, it was respectfully called the Gray Lady by readers and the industry. Here it泛指 (generally refers to) old-school authorities, mainstream American舆论标杆 (public opinion benchmarks), elite American information喉舌 (mouthpieces), and traditional major media holding discourse power.)
By now you should understand that, under reasonable regulation, prediction markets have huge potential. As long as the benefits outweigh the risks, problems like gambling addiction and negative social effects can find solutions. But we are left with one key question: could insider trading on major public events create unfairness through private monopoly profiteering?
This question is very complex, and I will address it in a separate article. Here I want to share a thought, and a book I recently read—Ashley Rindsberg's "The Gray Lady Winks: How the New York Times's Misreporting, Distortions and Fabrications Radically Alter History".
The book chronicles decades of systemic failures by this authoritative media outlet, and these were not偶然失误 (accidental mistakes): concealing Stalin's famine, beautifying Castro's rise, promoting the rumor of Iraqi weapons of mass destruction, downplaying the risks of the Nazi rise. The New York Times has consistently relied on information channels, ideology, and institutional self-preservation needs to distort the传播 (dissemination) of truth.
Understanding this book makes it clear that media bias is not simply a left-right立场之争 (stance debate), but a deeper structural problem: top authoritative institutions actively manufacture social consensus and later whitewash their own reporting errors.
Returning to the initial topic: neither Axios nor MorePerfectUS are neutral parties in the industry. This is also why more and more media will criticize prediction markets in the future. But you should be clear: their reasons for排斥 (rejecting) prediction markets are precisely the reasons you should support them.
Information has a price,这一点无需争论 (this point is indisputable). I have always believed: the opposite of false information is never absolute truth; the opposite of false information is officially controlled information.
The real debate is never about pricing information itself, but about who has the right to define information, who can profit from information, and whether information is monopolized and utilized before the public knows it.
When insiders hoard asymmetric information, profiteering is secondary; more core is the power博弈 (gameplay). Relying on the public's information disadvantage to harvest benefits, information can be used to manipulate public opinion, create false narratives, and the entire truth dissemination system can be held hostage by monopolies.
Therefore, the core of opposing insider trading has never been about economic efficiency, but about equality in access to information: a portion of people trade using exclusive information, while ordinary people can only access information that has been筛选 (screened) and allowed to be disseminated.
After understanding this layer, you won't hold a pessimistic view of prediction markets; you will only view the world with a more precise and rational perspective. This is also the reason I始终坚信 (always firmly believe): being optimistic about prediction markets is itself an idea with immense democratic value.
