Author: @MrRyanChi

In the past three months, countless discussions have taken place on Twitter about how much @Polymarket is actually worth, how far this new narrative can go, and compared to cryptocurrencies or AI, how far this narrative of the prediction market can truly reach.

Meanwhile, Wall Street attempts to price everything in the world, but those elites have forgotten to price something truly significant.

Whether you are a prediction market trader, a quantitative player, a market maker, a project party, or a yield farmer, what this article does for you is what I, as the founder of insiders.bot and an ordinary veteran in prediction markets, aim to reconstruct: the narrative of "prediction markets" and what kind of narrative aligns with the development laws of prediction markets.

The Inefficacy of Pricing for Four Hundred Years

Four hundred years.

From the issuance of the first stock by the Dutch East India Company in 1602 to today, we have spent a full four hundred years answering a question:

How much is something really worth?

Over these four hundred years, intelligent individuals have created numerous valuation models. DCF, PE, SOTP, Comps—each trying to capture the truth of value through formulas.

But what is the truth?

The truth is that these models have never truly explained value. They merely provide a rationale for a small group of people to charge another group.

Have you ever thought about it—those complex valuation frameworks taught in business schools serve two real purposes in the world:

First, they raise industry barriers. They make enough people feel that "finance is too difficult," allowing a small number of individuals to make big money.

Second, they give you a piece of paper, a number, a starting point for negotiations. You walk into a boardroom and slam down your calculated DCF model on the table—it is not the truth; it is a bargaining tool.

That's all.

When a university graduate spends 72 hours building a three-page DCF model and then grabs a seven-figure salary to "price" a company, what is he essentially doing?

He is arbitraging with degrees and information asymmetry, doing exactly what Wall Street has done for four hundred years.

When bubbles arise, these models never issue a warning. After the bubble bursts, these models always find a way to rationalize themselves.

After every crisis, financial workers do not reflect on the failure of the models themselves but instead find new variables, new assumptions, new excuses to package the mistakes as "black swans," then continue to extract water from this huge financial machine.

Valuation models do not predict the future. They only explain the past. And each time of "post-explanation" is a ticket for Wall Street to continue charging fees.

But something is happening here that most people have not yet realized.

Those parts that valuation models can never capture—such as events, expectations, the collective human judgment about the future—are now being priced by a completely new mechanism.

Prediction markets. Yes or No.

No three hundred-page pitch book, no jargon that requires an MBA to understand, no WACC assumptions that only insiders know.

Only one question, one price, a zero-sum game.

Prediction markets are turning "events" themselves into a tradeable asset.

I call it "Event as an Asset."

This is something that DCF cannot model and PE cannot measure, yet it truly affects the price of every traditional asset on Earth. Wars, elections, policies, technological breakthroughs—these "events" have always been the core variable in asset pricing, but for four hundred years no model has truly assigned them an independent price.

Until now.

The zero-sum game of prediction markets is becoming a missing piece in the traditional financial valuation system. It is not replacing Wall Street; it is accomplishing what Wall Street has never managed to do in four hundred years.

Events are the Atoms of Valuation

What is the essence of finance?

Pricing.

How are stocks priced? PE, profit growth rate, DCF. In plain language: a stock is the discounted sum of all value the company can create in the future.

But the problem is, who can predict the future?

No one decides.

So when unexpected events happen and people's faith in the future wavers, stock prices react.

This logic applies to any asset:

Gold at 7000? Because the market expects cash to become less and less valuable. Bitcoin at a million? Likewise. The subprime mortgage boom of 2008? Because everyone believed that borrowers would not default.

This is not financial nihilism. This is the fundamental operating logic of finance.

What finance binds are the values that assets can create. But the values that assets can create are strongly bound to uncertainty about the future—that is, "events."

So events themselves can not only be priced but must be priced.

Simply put:

The essence of finance is pricing. The essence of pricing is expectation. The essence of expectation is events.

From the perspective of financial history, this logic becomes clearer.

Let's break it down again from the perspective of financial history.

Initially, we only looked at tangible assets: land, machinery.

Later, we started looking at inventory and processes.

With the arrival of the internet age, we began to look at expected earnings, brands, intangible assets, goodwill.

To encapsulate all variables affecting valuation, we invented the simplest method: the discounted sum of expected profits to determine asset prices.

To summarize these increasingly abstract factors in one go, finance chose a simple and crude approach—using the total of future profit expectations to decide today's value.

Thus, the entire financial world has become a game about "expectations." The movement of K-lines essentially reflects expectations.

For example.

When Wall Street investment bankers go all-in on Nvidia, they will give you a bunch of "rational" reasons:

1. How high Nvidia can achieve CAGR during the AI wave

2. How large a market value Nvidia can occupy in the future AI world

3. How to calculate "reasonable" valuations using revenue multiples and asset ratios

Then they pile up a bunch of hypothetical numbers and use DCF to tell you:

"The current stock price is still far below our model-calculated target price."

But have you ever thought about what those assumptions really are?

They are nothing more than a collection of events.

Will Nvidia's next-generation chip outperform its competitors?—Event.

Will OpenAI continue using Nvidia's chips?—Event.

Will TSMC's production capacity remain stable?—Event.

All assumptions, when deconstructed, are events.

But this most fundamental variable of "events" has never been priced separately in traditional finance.

A single hurricane can close down a factory.

An injury to a player can result in a club's market value plummeting.

A government shutdown can force a rapidly growing company to lay off a significant number of employees.

These events continuously and dramatically rewrite asset values every day. Yet, in Wall Street's valuation models, they are just a vague footnote under "risk factors."

I studied the top business curriculum at Chinese University of Hong Kong and also studied finance at Wharton. But to be honest, I’ve always felt a deep-rooted hypocrisy in traditional finance.

Professors tell you that valuation rationalization is sufficient.

Seniors tell you that logic on the PPT is all that matters.

Investment bank reports bounce back and forth, and auditing annual reports are produced by interns on HK$50 hourly wages; the market is far from being as "efficient" as they say.

These elites overlook the core variable of "events," yet comfortably earn millions in salaries based on the "reasonable" valuations built on assumptions.

Event assets are the missing piece of contemporary finance.

Looking back at history, every significant leap in financial valuation has occurred when we learned to price new dimensions.

The first valuation revolution happened at the turn of the millennium—when the market finally learned to include profit growth rates in valuation, the network effects of internet products were first rationalized. A whole generation of tech giants was thus born.

When we learn to price "events" themselves, the second valuation revolution will begin.

And that is exactly what prediction markets are doing today.

The Zero-Sum Game Dressed in a Suit

"The essence of finance is the monetization of cognition."

This saying comes from a childhood friend of mine. He just received a return offer from JP Morgan IBD, and he regards this statement as a guiding principle.

In his worldview, buying stocks means buying "future income streams." When prices meet expectations, he elegantly hands off the chips to the next retail investor—he calls this "the reward for value discovery."

We maintain a tacit agreement that sometimes feels competitive and sometimes feels friendly. But to be honest, I have always harbored a stern and difficult-to-dissolve skepticism about the business school logic he prides himself on.

Because when you deconstruct this narrative down to its core, you’ll find—

The decorum of traditional finance is merely packaging the plundering of liquidity and asset redistribution as a "reward for correct valuation."

This layer of facade must be torn down today.

The underlying belief of Wall Street elites, when opened up, is built on three extremely fragile assumptions.

The first layer: The illusion of valuation.

They believe that assets are the sum of future earnings. Buying low and selling high is rooted in the notion that "I saw the truth before the market." But the previous section made it very clear—the so-called "truth" is just a set of guesses about future events. No one has truly seen the truth; everyone is just betting on events yet to happen.

The second layer: The rationalization of trading.

Selling high is called "fair trading" on Wall Street. The logic is: so long as I believe the current valuation is reasonable, selling to a buyer is the right thing to do. Whether the buyer is losing money due to cognitive bias? That’s their problem, not my responsibility.

This narrative is polished and self-consistent, lacking only one thing: honesty.

The third layer, the largest fig leaf—The lie of a positive-sum game.

This is the core belief of traditional finance: The company is growing, the cake is getting bigger, so we are all winning.

But what’s the reality?

Cash flows in the market are governed by macro liquidity, not by the growth of individual companies. When you buy low and sell high, you are literally redistributing others' assets into your own pockets. Even if a company does generate more profit in a certain quarter, under DCF algorithms, the vast majority of stock prices are still supported by "expectations" rather than "reality."

Every penny you earn fundamentally comes from someone else's misjudgment of the future.

This is not pessimism. This is the underlying code of a zero-sum game.

At this point, many might want to argue: "Isn't the prediction market just gambling? Isn't that even more zero-sum?"

Exactly. Prediction markets are zero-sum games. But that is precisely where their superiority lies.

What traditional finance does is to wrap zero-sum games into positive-sum games, allowing participants to ream each other under the illusion of "value investing," while thinking they are creating value.

What prediction markets do is to expose the essence of zero-sum games, then operate it with a more pure and efficient mechanism.

When you strip away the hypocritical "value investing" facade of traditional finance, you’ll find that the underlying logic of prediction markets and asset pricing is not only homogenous but also cleaner.

Why?

Because prediction markets perfectly replicate and optimize three things that the stock market genuinely does—

Cognition is alpha. When you discover discrepancies between the reality probability and market odds, you have found mispricing. This is logically no different from discovering an undervalued stock. The only difference is that prediction markets do not require you to pretend you are "investing in the future."

Trading is hedging. In prediction markets, when you buy a position in an event, you could be speculating or hedging real-world risks—like going long on oil volatility to protect your equity position. The logic of covering is entirely consistent with the stock market.

And the most critical point is instant valuation anchoring.

For example. When an AI company releases a groundbreaking model, competitor valuations in the same field drop sharply. In traditional finance, this value transfer could take until the next earnings season or even the next annual report to be fully reflected. Analysts must rebuild models, investment banks must update reports, and the market must gradually digest.

But in prediction markets?

It directly trades the "AI breakthrough" event itself. Value transfers happen in real time.

No delays, no intermediaries, no one using a PPT to tell you "our model indicates..."

Prediction markets are a zero-sum game, stripped of hypocrisy and entirely aligned with the logic of asset pricing.

By now, the logic chain is complete.

Traditional finance anchors valuation to "future cash flows." But what are future cash flows made of?

They consist of numerous concrete, definable, and verifiable events.

Can a SaaS product renew its contract with a major client next year?—Event.

Will a brand experience a trust crisis?—Event.

Will a regulatory policy be implemented?—Event.

In traditional finance, these events reflect on stock prices through extremely complex transmission mechanisms, albeit belatedly and distortedly. Analysts guess with models, traders gamble with intuition, and retail investors chase based on emotions. Every layer adds noise; every layer distorts.

What prediction markets have achieved, however, is something that has never been done before—they price events themselves.

Without relying on models. Without narratives. Without any intermediate layers.

When events are seen as a tradeable asset, the traditional finance chain of "valuation → assumptions → events" has been thoroughly compressed. We no longer need to make a huge detour to guess how events will affect cash flows, how that will affect valuations, and how that affects prices. We directly trade the events themselves.

This is why I say—

Events as assets are the missing piece of contemporary finance.

The essence of the zero-sum game does not undermine this judgment. On the contrary—the acknowledgment of the zero-sum game allows us to discard the hypocritical packaging and touch the true core of pricing.

In an ideal future, companies could precisely hedge the impact of specific events on valuations through prediction markets. Investors could directly trade the events themselves rather than staking indirectly through stocks. Individuals could build positions in events they care about on-chain and participate in a pricing process that is transparent and permissionless.

This is not gambling. It is the deepest correction of traditional financial models.

Prediction markets represent the truthfully honest financial world that faces the future.

Eight Billion Dollars, Died from Granularity

Let us pull the lens back to my childhood friend.

In a debate about the zero-sum nature of traditional finance, he interrupted me and said一句让我至今记忆犹新的话—

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