Beyond Prediction Markets: How to Determine Whether Bitcoin Will Rise or Fall?

Conditional markets not only predict whether an event will occur but also assess how the event will impact asset prices.

Written by: Vaidik Mandloi
Compiled by: Chopper, Foresight News

Currently, all prediction markets, whether Polymarket or Kalshi, output only one type of result: probability. Probability is a number that represents the collective judgment of the market on the likelihood of an event occurring.

Over the past two years, this underlying tool has proven that the market can aggregate scattered information from various sources, predicting future events with greater accuracy than polls, expert reviews, and all previous human prediction methods.

However, the information of "probability" is not complete when applied to finance. If you hold Bitcoin and see that the market predicts a 65% chance that the Federal Reserve will cut interest rates by 75 basis points next month, you know that this event is likely to happen, but you have no idea how it will affect your holdings. You only know that the likelihood of a rate cut is high, but you do not know how Bitcoin's price will move. If the rate cut happens, will Bitcoin rise to $110,000? Or $95,000, or $140,000? Ordinary prediction markets cannot answer this question.

The event itself and the impact it will have on businesses and assets are two completely different matters. For a long time, financial markets have mixed these two issues together. Distinguishing between them is the direction for the development of the next generation of financial products.

The industry is now creating two distinctly different types of products. The first type arises from the insights provided by prediction markets: since the market's ability to aggregate information is so strong, why should organizational governance still rely on voting? This type of product is called a Decision Market. The second type is a brand new concept: it can directly tell you what the price of Bitcoin will be if the Federal Reserve cuts rates by 75 basis points. It does not just predict whether the rate cut will happen, but calculates the corresponding dollar price of Bitcoin in this hypothetical scenario. This type of market is called an Impact Market, and its value is currently vastly underestimated. Both types are classified as Conditional Markets.

Later, we will discuss Impact Markets in detail. To quickly understand why they are important, one can first look at the shortcomings of Decision Markets.

What Happens When Governance Becomes a Market?

Decision Markets were initially used in governance scenarios because DAOs and token voting have inherent flaws: the person with the most tokens may have the least information; those who hold key information may have too few tokens to change the voting outcome. Decision Markets reverse this: anyone who invests funds can express their opinions, regardless of whether they hold tokens. The market can price information in real-time.

Robin Hanson proposed the concept of "Prediction Governance" back in 2000, and the core idea is quite simple. Suppose a protocol needs to decide whether to reduce staking rewards, instead of voting with tokens, traders would price the protocol's tokens in two futures contracts: one corresponding to "reward reduction" and the other to "maintaining existing rewards." The scenario with the higher token price will be executed. If you blindly trade without understanding the economic logic of the protocol, knowledgeable individuals will profit from your losses; your losses will also directly reduce the voting weight of all your future governance proposals.

This system becomes smarter with use; uninformed funds continuously lose money and exit, while knowledgeable funds accumulate. Token voting is exactly the opposite— even if you make incorrect choices on all proposals for a year, your voting weight does not decrease at all. Prediction Governance will make ignorance pay a real price, something no governance system has achieved before.

MetaDAO is the first team to implement this mechanism. By the end of 2023, it will launch on Solana, adopting a binary model: each proposal will have only two outcomes, either approval or disapproval, determined by the conditional market, eliminating token voting, with the market's conclusions having binding authority.

However, this binary model brings new problems. The market can only answer "yes" or "no," and all parameters of the proposal, such as budget, timeline, and technical changes, must be negotiated in advance on forums before the market opens. This contradicts the original goal of Decision Markets; proposal details still rely on the original informal consensus discussions, with large holders still dominating the entire discussion. You are merely handing the final binary choice to the market, which is an improvement, but the proposal design phase remains within the old system you want to replace.

In September of this year, Umia upgraded MetaDAO's system to a multi-outcome version. There are no longer just simple approval/rejection; multiple parameter schemes of the same proposal can compete simultaneously. The market automatically eliminates unreasonable parameters through trading. The optimal proposal scheme emerges directly from market competition, rather than being finalized in forums beforehand. If the original intention of this mechanism is to rely on price discovery, it should be this way.

Currently, 22 DAOs are using this mechanism, and 96 proposals have been approved through market governance. The total treasury managed by the market amounts to $50.5 million, of which MetaDAO accounts for $39.3 million. This model shows potential for significant growth. However, even if the treasury scales up a hundredfold, Decision Markets still face a ceiling, and this bottleneck is unrelated to funding, user scale, or development team capability.

In economics, there is Goodhart's Law: once a certain indicator is treated as a target, it ceases to be a reliable measure. Credit ratings were originally used to assess default risk; once banks began relying on ratings to select mortgage products, investment banks deliberately designed securities to meet rating standards rather than filtering for quality loans. The underlying mortgage assets continuously deteriorated, yet the securities still received the highest AAA rating.

Decision Markets inherently have this flaw. After a proposal is approved, the token price rises for two reasons: one is that the proposal itself creates value, and the other is that approval represents strong confidence from the team. Even if a quality project proposes to use treasury funds to mint a bronze bull statue, the token price will still rise upon approval; traders are betting on governance-level confidence rather than the statue itself. When Apple announces a buyback at a high valuation, the stock price also exhibits similar behavior.

The entire mechanism can fail, as the market's results can influence the very targets it aims to evaluate. To fix this issue, traders lose their incentive to participate. However, if the governance aspect is removed and this conditional mechanism is used to analyze external events— that is, external events whose trading outcomes cannot be altered— this interfering cycle disappears, and prices become difficult to manipulate. This is the Impact Market.

What Can Impact Markets Do?

Currently, the hedging tools in the crypto industry are very crude. If you hold Bitcoin and are concerned that a certain regulatory decision will affect your holdings, you have only two choices: either sell directly, forfeiting all potential gains in other favorable scenarios, or buy volatility products, but these products track the overall market volatility and are unrelated to the specific issue you are worried about. Previously, there were no financial products that could isolate a single event to trade how much price impact it would have on a specific asset. Impact Markets can achieve this.

For example, the U.S. SEC is about to determine whether a certain type of DeFi protocol counts as a security, and you hold a large amount of ETH. You believe that if the ruling is negative for DeFi, ETH will drop to $1,800. In this "SEC negative ruling scenario for ETH Impact Market," the current market price is $2,300, representing a collective expectation that once the ruling is made, the price of ETH will reach $2,300.

You sell this contract at $2,300. Subsequently, the negative ruling is made, and ETH drops to $1,800. Because your judgment is more accurate than the market, you earn $500 for each token. Even if you are wrong and ETH only drops to $2,200, you still make $100. Before the birth of Impact Markets, such trades did not exist. There was no product that could trade the price volatility caused by a specific event on a particular asset, with real-time market pricing allowing everyone to compete for the price.

The principle is that the current price of an asset is essentially a number compressing all possible future outcomes into one. Impact Markets allow us to penetrate this surface and trade one specific future scenario.

Now, when people want to avoid specific risks, they generally diversify their holdings across multiple assets, which is essentially just a rough guess at the correlation between the price movements of those assets. Impact Markets completely change this thinking: you can hold a large amount of Bitcoin and purchase risk protection specifically against the regulatory or macro events you are worried about, without selling your holdings or buying volatility insurance for thousands of unrelated scenarios.

Instead of relying on asset diversification and betting on the correlation of price movements for hedging, you directly hedge against the risk of specific scenarios. This is a brand new risk management approach, with the premise that the product provides conditional prices rather than probabilities of events occurring.

I believe the impact of Impact Markets will far exceed that of prediction markets. Prediction markets only settle two outcomes: "occurs / does not occur" at expiration, which, while useful, has limited application space. Probability itself cannot be directly traded and cannot be used to build complex financial instruments.

In contrast, Impact Markets output the dollar price of an asset under specific hypothetical scenarios. You can use it to hedge risks and continue to develop derivatives. Before the emergence of conditional prices, such tools could not be created at all. Various derivative products built on reliable conditional prices will ultimately scale far beyond the conditional markets themselves, just like the options and derivatives markets, which are much larger than the underlying stock market.

The market space for the question of whether an event will occur is not small, but it has a natural ceiling; there are limited things that can be done relying solely on probabilities. However, the question of "how much will this event change the asset price" corresponds to an endless array of scenarios, with market depth equivalent to the entire financial industry.

The first batch of products has already launched, and the expansion speed is increasing. Protocols like Branchpoint have even developed Branchmap, a universal naming standard across projects that standardizes the definitions of various conditional scenarios. Standardization is crucial: only when the meaning of "ETH in the SEC negative ruling scenario" is completely the same across all trading platforms can Impact Markets become a true financial foundation. Without a unified standard, liquidity will be fragmented, and conditional prices across different platforms cannot be compared.

Branchpoint calls this system Multiverse Finance. Each conditional market is like a window, corresponding to a future and a branch of reality, representing the world after a certain event occurs or does not occur. As Impact Markets mature and liquidity increases, the market will not only provide conditional prices for single events but will comprehensively display the valuations of an asset across countless parallel futures and different scenarios.

For decades, the financial industry has sought to dissect the driving factors behind asset prices. The entire discipline of event studies relies on historical data to estimate the extent to which a specific event drives price changes, with the remainder categorized as noise. However, in the past, people could only make rough estimates after events concluded.

Impact Markets can accomplish this dissection in advance and in real-time. Once such data can be obtained, the underlying logic of risk pricing will be rewritten.

In the next stage, conditional prices will be integrated into risk models and asset portfolio systems, which currently can only operate based on spot prices and implied volatility. Once this integration occurs, the capital hedging and risk exposure management framework in the crypto space will be completely restructured.

This mechanism is not limited to the crypto industry. Once this price is established, the way funds are allocated will undergo a chain reaction. Insurance companies can transfer niche risks that their underwriting capacity cannot handle to conditional markets, thereby accepting policies they previously had to decline. Venture capital funds can separate hedging industry risks from individual company risks, allowing them to invest heavily in promising founders rather than diversifying into 30 projects to compensate for lack of confidence. When governments plan to raise the minimum wage, they can use conditional markets to see the real-time price of employment impacts derived from market competition, rather than arguing among a pile of contradictory economic models.

In the 1970s, options brought similar transformations to the stock market, giving rise to many previously unimaginable new industries. Conditional markets, like options, are among the most fundamental tools in finance. The difference is that they dissect risk based on various events rather than the assets themselves; the number of potential events in the world is limitless.

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