This edition of the newsletter dives into the ins and outs of prediction markets as a "wisdom of crowd" concept and our thoughts about the space and its challenges. We'll also share some interesting articles, portfolio updates and market highlights.
1. Research Articles
a) The Second $100B AI Company
• The potential for AI companies to reach a market cap of $100 billion or more is very possible. The writer argues that while there have been several successful tech companies that have achieved this milestone, there are relatively few AI companies that have done so.
• The writer predicts that the first AI company to reach this valuation will likely be a consumer-focused company, rather than an enterprise-focused one. They also highlight the potential for significant growth in the AI application layer, and the opportunities for startups in this space.
b) A New Era of DeFi with App-Specific Sequencing
• The article discusses Application-Specific Sequencing (ASS), a method that allows individual dApps on Ethereum to control the order in which their transactions are executed. This is a departure from the current system, where transactions are collected and sequenced by builders who compete in a block auction.
• ASS can help protect dApps and their users from the harmful effects of MEV, while also allowing applications to capture value that would otherwise be lost to Ethereum validators. The article also discusses the challenges and potential solutions for implementing ASS, such as the need for trust assumptions, liveness guarantees, and censorship resistance.
c) Onchain Reality Maximalism
• The article argues that the virtual world is inherently flawed due to its reliance on falsehood and inconsistency, while the real world offers a sense of permanence and peace. However, the boundary between the two is often blurred, leading to confusion about what is real and what is virtual.
• "Onchain Reality Maximalism" can provide a foundation for building new, meaningful realities that are free from the limitations of the physical world. By constructing large-scale decentralized applications, individuals can become masters of their own destinies and create a future that is more hopeful and fulfilling.
2. Portfolio Updates
a) Solv Protocol
• Solv Protocol has raised $11m in a strategic funding round ($200m valuation), bringing its total funding to $25m. This new capital will be used to advance the company's mission of revolutionizing Bitcoin staking through the Staking Abstraction Layer (SAL).
• Solv Protocol is best known for its flagship product SolvBTC, a "Bitcoin Reserve for Everyone," which has staked more than 20,000 BTC since launch. The company's launch of the Staking Abstraction Layer (SAL) marks a new era for Bitcoin staking, as it simplifies Bitcoin staking across multiple blockchains.
b) zkPass
• zkPass has successfully secured $12.5m in a Series A funding round which brings their total funding to $15m and will accelerate zkTLS development across Web3 ecosystems.
• They are the go-to for leveraging web private data to build solutions such as proof of humanity, anonymous voting and parametric insurance.
Shipping matters more than storytelling.
1/10
524
c) Artela
• Artela is looking for its second round of "Artela Stars" - community members who actively contribute and show potential. These Stars will receive benefits like early access to features and rewards programs. This is the last selection round before the mainnet launch on November 4th, so anyone interested should apply now.
3. Prediction Markets - Wisdom of the Crowds
Introduction
Prediction markets are platforms where participants can speculate on the outcome of future events by buying or selling contracts. These contracts pay out a fixed amount if the predicted event occurs and nothing if it does not.
Based on the "wisdom of crowds" principle, prediction markets can generate accurate forecasts by aggregating the collective knowledge and opinions of many individuals. Over the past decade, they have been used to predict various outcomes, including elections, sports results, economic indicators, corporate decisions, and even niche markets like scientific developments.
The history of prediction markets dates back approximately 500 years, with a primary focus on political outcomes. This article will explore the diverse applications of prediction markets in the past decade and how blockchain technology has contributed to their evolution and accessibility.
History of prediction markets
In the early 2010s, prediction markets like Intrade and Betfair gained prominence, especially in political forecasting, particularly for U.S. presidential elections. However, their growing popularity attracted increased regulatory scrutiny. This led to legal uncertainties in the U.S., causing prediction markets to face challenges. Intrade, for example, was forced to shut down in 2013, just a year after the 2012 election. Despite this, some academic and internal corporate prediction markets, like those at Google and Microsoft, continued to operate, forecasting project deadlines and other business outcomes.
In 2015, blockchain technology emerged as a new venue for prediction markets. The decentralized nature of blockchains allowed these markets to operate outside of a single regulatory framework, avoiding legal and political obstacles.
Augur, the first decentralized prediction market, capitalized on blockchain technology by launching on the Ethereum network. Users could create markets on any question or event. However, during a period of inconsistent user engagement in the blockchain space, Augur faced challenges.
Other platforms, like Polymarket, emerged with unique approaches to market creation and settlement. Polymarket gained popularity due to its user-friendly interface and focus on timely, controversial topics, such as COVID-19 outcomes.
Types of prediction markets
a) Event-based markets
• Focus on specific events with outcomes tied to real-world occurrences.
• Examples: Political markets (predicting election results), sports markets (betting on sporting event outcomes), economic markets (forecasting economic indicators).
b) Binary vs. multi-outcome markets
• Binary markets: Have two possible outcomes (e.g., "YES" or "NO"). Contracts pay out if the predicted event occurs and are worthless otherwise.
• Multi-outcome markets: Offer more than two possible outcomes (e.g., predicting which candidate will win a multi-candidate race or which team will win a tournament).
c) Continuous vs. categorical Markets
• Continuous Markets: Predict outcomes that vary across a range of values (e.g., stock prices, weather temperatures, percentage of votes).
• Categorical Markets: Center around discrete options (e.g., predicting which film will win the Best Picture award).
d) AMM vs. Order Book-Based Markets
i. AMM-based markets (algorithms to adjust prices based on supply and demand)
• Examples: Logarithmic liquidity, market rebalancing (Logarithmic Market Scoring Rule)
• Ensure liquidity and continuous pricing.
• Prices are adjusted based on trade volume.
• The market remains liquid as prices are always available for buyers and sellers.
ii. Order Book-Based Markets (uses an order book system similar to stock markets)
• Participants submit buy and sell orders.
• Prices are determined by matching these orders.
• Bid and ask prices are determined by the highest and lowest prices someone is willing to pay.
• Trades are made when both sides agree on a price.
Landscape
The landscape of companies developing new prediction markets or integrating this feature into their existing product suites is continuously evolving. This expansion reflects a growing interest in using market-based forecasting across various sectors, including finance, sports, politics, and technology. As more organizations recognize the potential of prediction markets to provide valuable insights, enhance user engagement, and diversify revenue streams, the ecosystem is becoming increasingly dynamic and competitive.
As shown in the chart below, Polymarket has consistently maintained the highest trading volume among all prediction market categories, despite a modest daily active user (DAU) count of approximately 40,000 wallets. This surge in trading volume and user engagement can be attributed to several political events, including high-profile debates, Joe Biden's withdrawal from the 2024 presidential race, and other significant occurrences. These events not only drive participation but also demonstrate the unique ability of prediction markets to reflect and capitalize on real-time public sentiment.
The future - can crypto prediction markets stand the test of time?
a) Betting on prediction markets as an uninformed retail participant often leads to a net negative outcome
• It's pure speculation with limited long-term upside, especially compared to the broader opportunities in the crypto space, which offers more attractive alternatives.
• Returns from on-chain yield, staking, or direct investments in liquid assets provide better risk-adjusted returns and hedging strategies for market volatility.
b) The primary motivation for participating in prediction markets is often not financial gain but social and emotional factors
• People place bets that align with their personal beliefs, values, and interests, often choosing outcomes or candidates that resonate with them deeply. This explains certain patterns in prediction market behavior, such as why some candidates may perform better despite questionable odds. Thus, prediction markets are not just about estimating the probability of events but also about capturing the intensity of sentiment and engagement among participants.
• This distinction highlights a broader trend within the crypto space, where speculation is not only about financial returns but also about participating in a community, experiencing excitement, and making a statement.
c) Furthermore, this element of engagement and bias opens up opportunities for new crypto-native prediction markets
• Participants can speculate on a range of niche areas, such as narratives, market sentiment, content popularity, asset listing probabilities, and other specialized topics unique to the crypto landscape.
Challenges
a) Truth or fiction: which will you bet on?
Earlier, we compared prediction markets to traditional financial stock markets. However, the negative effects are more significant here than in traditional markets because the core purpose of prediction markets is to generate accurate information. While profit maximization is the primary motivation in traditional financial markets, participants in prediction markets are often driven by personal beliefs, political biases, or vested interests in particular outcomes. Consequently, they may be more willing to accept financial losses within the market if their bets align with their values or if they anticipate benefits outside the market itself. This creates a significant divide between delivering accurate information and information driven by personal or financial incentives. When participants prioritize their beliefs over objective analysis, the market's ability to serve as a reliable forecasting tool is undermined, leading to a misalignment between the market's outcomes and the true probabilities of events.
Market Inefficiencies
For prediction markets to be efficient, they must continuously integrate new public information and adjust prices accordingly. However, if participants rely on entirely different streams of information—essentially inhabiting separate realities—it becomes impossible for the markets to effectively incorporate public data. When traders cannot agree on basic facts, these disagreements manifest as noticeable and exploitable anomalies in market prices. The efficient market hypothesis assumes that information is uniformly interpreted by rational traders; yet, humans often disagree on how to distinguish fact from fiction and determine relevance. While one might argue that such issues do not apply to traditional financial markets, prediction markets face unique constraints, such as trade size caps that limit participation from large institutions, allowing these inefficiencies and anomalies to persist without correction.
Manipulation
Manipulation in crypto-based prediction markets presents considerable challenges and risks due to the relatively unregulated environment in which they operate. Unlike traditional financial markets, which benefit from established regulations and oversight mechanisms, blockchain based prediction markets are more vulnerable to a range of manipulative practices. These actions can distort market prices and undermine the integrity of the information being conveyed. The efficient market hypothesis above, relies on the assumption that market prices reflect all available information, but manipulation disrupts this equilibrium, as malicious actors can create artificial market conditions that mislead participants. Furthermore, the decentralized nature of these markets complicates accountability, making it difficult to identify and penalize those responsible for manipulation. As discussed in previous sections, this lack of oversight not only invites exploitation but also contributes to the persistence of anomalies, ultimately eroding trust among participants and detracting from the potential value of prediction markets as tools for informed speculation.
Conclusion
In summary, prediction markets are inherently shaped by human passions and interests. While they experience significant spikes in activity during major events, such as U.S. presidential elections, the challenge lies in maintaining long-term engagement and ensuring a qualitative, truthful source of information. To sustain momentum, it is crucial to diversify into smaller, niche markets that enable communities and individuals to participate actively, thereby preserving excitement beyond high-profile events. This diversification not only fosters ongoing interest but also enhances the potential for meaningful engagement within the crypto ecosystem. By adapting to these dynamics, prediction markets can continue to attract attention and remain relevant as valuable tools for speculation and community interaction in an ever-evolving landscape.
Not an investment advice, please DYOR.
