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A letter to Prediction Markets & Nick Tomaino
Since I started Onchain Letters two months ago, I've written 22 deep dives on different topics in crypto. And as I've been going through this process, I started to notice that there were many things I thought I understood only to realize that most of my insights were surface level. I couldn't back up my opinions with sound reasoning. A lot of what I knew before I started writing was just regurgitated crap from doomscrolling on Farcaster and crypto twitter.
Okay so what's my point?
Well, if you had asked me to put money down on a thesis in crypto, I don't think I would have felt comfortable doing so. Maybe for some basic viewpoints such as "I'm bullish on Farcaster". But for the most part, I wouldn't be able to put my money where my mouth is.
Or as Nick Tomaino puts it, I wouldn't have high enough conviction to have skin in the game.
Now, why is that important? Because talk is cheap. Talk is everywhere and social media has made it simple stupid to just follow the herd. Everyone these days is surrounded by so many opinions on a variety of topics that it's becoming nearly impossible to think for yourself. And that's not to say you need to have flushed out reasoning for everything. If anything, that's also counterproductive as you would be spreading yourself too thin.
Rather, what's important is being intellectually honest about what you do and don't know. And a good way to check is to see if you'd be willing to bet your own money on a given position.
As Alex Tabarrok bluntly puts it...
"A bet is a tax on bullshit"
And with that, let's get started on today's topic: prediction markets.
In January, Polymarket, one of the hottest prediction markets out there right now, started to gain a ton of traction. Additionally, Nick Tomaino has been quite vocal about his excitement on this vertical which piqued my interest even further. So, I decided to dive deeper and form my own opinion on all things prediction markets.
For my letters, I typically have three long sections. But for today's post, there were a variety of things I wanted to touch on so I'm doing 7 mini sections to make sure I cover all grounds.
Sections below:
Our desire to predict
Papal succession & the totality of knowledge
Iowa's win & DARPA's blunder
Uniswap for beliefs
Fact checking media
Letting AI in on the fun
Hanson's search for gold
Let's dive in 🚀
1. Our desire to predict
Before we even get into the financial aspect of this topic, let's discuss why humans make predictions in the first place.
Many people look down on prediction markets and compare it to the lottery or Vegas casinos. But the truth is, everyone is predicting all the time. Wall street investors have to predict interest rate changes. Parents have to predict which schools will provide the best environment for their kids. College students have to predict which topics will be covered on their next final. And so on.
Some decisions are large and have a much bigger impact. And others are micro decisions which we don't even think about because they're just part of our daily routine.
Predicting is a core part of human nature that is deeply rooted in evolutionary biology and psychology.
Our ancestors had to anticipate threats, changes in weather, availability of resources, etc. in order to survive. Those who could better predict these things increased their odds of successfully reproducing.
Predicting outcomes forces us to think strategically about how we should allocate our time and capital. No one likes to lose. And in order to win, you have to predict how to best navigate a situation.
And lastly, predicting is really fun! It's what lets us bond with others who have common interests and connect with them on a deeper level. There's a sense of community that comes with predicting what's going to happen and it fulfills our intrinsic need to better understand the world.
Okay, so if the desire to predict is a core evolutionary behavior, what are some early examples?
2. Papal succession & the totality of knowledge
One of the earliest recorded instances of prediction betting was on the outcome of papal successions in the Vatican.
Betting on who would become the next Pope was one of the biggest events in the 1500s 😂
In fact, the betting culture grew so much that "in 1591, Pope Gregory XIV forbade Catholics from betting on the election of a pope or the length of a pope’s term in office" (Micah Cohen).
Additionally, there is evidence of early versions of prediction markets on European monarchies and even literary/theater success (i.e. how well will a play do)!
Though it may seem that there has been a sudden rise in popularity of prediction markets, it's important to remember that the concept has been around for hundreds of generations.
Okay, now let's fast forward a few centuries and discuss the modern era of prediction markets.
Two economists, Friedrich Hayek and Ludwig von Mises, are known to have provided the framework for how we think about this vertical today.
Hayek authored "The use of Knowledge in society" in 1945 and Mises authored "Economic calculation in the socialist commonwealth" in 1920.
Together, their research provides a constructive argument of the importance of prediction markets in society. h/t chatGPT for helping me better understand the papers.
There's 3 main points:
Decentralized information processing - centralized decision making is inefficient due to the dispersed nature of knowledge. Society is better off harnessing collective intelligence as that leads to more accurate predictions compared to expert opinions.
Dynamic adaptation - prediction markets offer a platform for dynamic adaptation to new information. Participants can quickly adjust their positions in response to changing information leading a to a proactive forecasting process.
Efficient allocation & pricing mechanism - prediction markets efficiently allocate speculative capital by incentivizing participants to invest their money based on their knowledge and informational advantage. These betting odds aggregate diverse opinions from the crowd and reflect collective wisdom.
tl;dr is in this paragraph of Hayek's paper...
"The economic problem of society...is a problem of the utilization of knowledge which is not given to anyone in totality"
Cool, now that we covered the theory side of things, let's discuss some early examples of prediction markets in the U.S.
3. DARPA's blunder & Hollywood stock exchange
There are some fun examples of applied prediction markets in the last few decades that I wanted to quickly touch on.
The point of this section is to underscore that economists & technologists have been thinking about this field for quite a while now and it's been a never ending argument of what should and shouldn't be allowed.
Let's cover three examples before the 2000s hit.
Iowa Electronic Markets (IEM)
The IEM was set up in 1988 by the University of Iowa for research purposes primarily analyzing election forecasting.
What's interesting is that unlike many of the early prediction market applications, IEM actually did use real money but capped the bets to $500 in order to focus on the educational aspect and less on the financial outcome.
The IEM is famous because it's historically proven to have a high level of accuracy in predicting U.S. presidential outcomes. More often than not, these markets would do better than traditional polls or expert analysis.
Here's the current IEM results for the 2024 presidential election:
Defense Advanced Research Projects Agency (DARPA) & Policy Analysis Market (PAM)
PAM was a project designed by DARPA in 2001 to predict geopolitical events, including political coups, terrorist attacks, etc. by aggregating the wisdom of the crowd.
The project was canceled in 2003 because of public and political backlash. The main argument was that it was unethical to bet on tragedies such as terrorist attacks.
PAM's ending led to widespread discussion on the potential and limitations of prediction markets. Most researchers were unsure as to how to think about PMs in terms of more nuanced and ethics based topics. Predicting weather is easy to approve, but regime changes is a whole other thing.
Hollywood Stock Exchange (HSX)
HSX is a virtual prediction market that launched in 1996 where participants were able to shares trades of movies, actors, directors, etc. The primary goal is to predict box office success and of course how well celebrities will do in the coming years.
Anyone who uses HSX uses a virtual currency known as Hollywood Dollars to make their trades. This is primarily to avoid any regulation issues as it's more of game than a market. And using HSX also makes it accessible to a wider audience without the higher stakes financial risk of traditional prediction markets.
The market accuracy is actually beyond impressive. This stat below blew my mind...
"In 2007, players in the Hollywood Stock Exchange correctly predicted 32 of the 39 major-category Oscar nominees and seven out of eight top-category winners."
You can even bet on movies that are coming out years from now. For example, here's the market on Avengers 5 starring Chris Hemsworth which is coming out in 2026.
It's also worth noting that Intrade was a huge success in it's time as well but was shut down in 2013 due to regulation issues.
Alright, now that we've covered some of the OG examples from the late 90s, let's dive into what the current ecosystem looks like today.
4. Uniswap for beliefs
The purpose of this section is to give a birds eye view of prediction markets and discuss the benefits of prediction markets that use automated market making solutions.
At a high level, we can split this ecosystem in half: traditional prediction markets and decentralized, blockchain based solutions.
Note: I'm sure there's a ton of companies out there, I'm listing a few that are popular.
Traditional PMs
Iowa Electronic Market (IEM) - used for academic purposes as discussed above in section 3
PredictIt - operates under a no-action letter from CFTC allowing it to function legally in the U.S. There are strict rules on investment amounts and participant numbers in each market.
Manifold Markets - use virtual currencies that allow them to make a market on pretty much anything
Kalshi - a hot new PM that has been working diligently to get through legal barriers. They're the first CFTC regulated exchange.
Decentralized PMs
Before I list some examples, let's discuss what I mean by the title of this section, Uniswap for beliefs.
The analogy here is how Uniswap is a decentralized exchange and a novel mechanism for exchanges. It's a zero to one innovation on the way banks operate. Uniswap and similar exchanges are AMMs (automated market makers) that use algorithms to determine the price of assets and provide liquidity to the market automatically, without the need for traditional order books or market makers.
The price of assets in these pools is determined by a formula (x∗y=k), which adjusts automatically based on the supply and demand dynamics of the pool's assets as trades are executed. This model allows for 24/7 trading, reduced slippage, and lower entry barriers for liquidity providers.
Similarly, decentralized prediction markets use a version of AMM known as FPMM (fixed product market making) in order to create dynamic, transparent markets on any kind of prediction. We won't get into details here but the core point is that decentralized prediction markets adjust prices based on the ratio of bets in liquidity pools very similar to how products like Uniswap set prices for swapping assets.
In fact, when Vitalik first brought up the idea of AMMs on r/Ethereum, he explains it using prediction markets.
Here's a few examples:
Augur - first prediction market on Ethereum. It was one of the first projects to raise money through an ICO in 2015. After a few years of development, it went live in 2018 and $1.53 million of value was staked across more than 800 outcome bets within the first month.
Omen - Built on the Gnosis protocol by Martin Koppelmann
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Polymarket - launched by Shayne Coplan and team in 2020 right in time for the U.S. presidential election. The platform had a virality moment as things were getting crazy between Biden and Trump in Q4 '20. In the bear market, it slowed down as expected but recently has seen a resurgence in activity.
Note: people in the US are not allowed to bet on Polymarket due to regulation constraints but can make a market on the platform. I know it's weird but that's D.C. for you.
Polymarket's advantage according to most active bettors is that the UX is simple and the product does a great job of making it easy to understand and place bets.
It'll be interesting to see if prediction markets do in fact have a "escape velocity" moment even within the crypto/tech space like NFTs did in the last bull market.
And on that note, let's discuss some of the use cases for prediction markets and how they might be able to find mainstream adoption.
From all my research for this post, I was able to group the prediction market vertical into three main categories that I'll discuss in the next few sections.
5. Fact checking media
Takeaways from this section:
Right now, most people only care about general events because that's where all the money and hype is.
As prediction markets enter the mainstream by demonstrating forecasting accuracy for major upcoming events such as the 2024 elections, there will be more capital to incentivize liquidity for the long tail of local markets.
People naturally care more about events and outcomes directly related to them than general ones. Prediction markets will need better marketing and UX (i.e. polymarket) in order for there to be increased participation in markets past national politics and culture.
Tyler Cowen has a post where he says,
For a prediction market to take off, it probably has to satisfy a few criteria: general enough to attract widespread interest; important enough to matter; and unusual enough not to be replicable by trading in existing assets. The outcomes also need to be sufficiently well-defined that contract settlement is not in dispute.
From my understanding, other than regulation constraints, prediction markets haven't really taken off because professional traders have not found the motives to provide liquidity to the long tail of markets.
What does that mean?
Well, right now, prediction market platforms are typically focused on general topics such as elections, celebrity drama (will Travis Kelce propose to Taylor Swift at the superbowl), and business events (Reddit valuation on IPO day). People are ready to bet on these markets without much convincing - similar to sports. However, for local events and communities, there's no incentive for traders to participate as there's no one betting!
To me, there's a chicken and egg problem present here. It seems as though most events that are important to people are in fact the local ones but they're tough to gain initial interest. For example, I'd be much more interested to see outcomes of events related directly to my life such as local real estate prices, crypto community events, etc. rather than who will win the senate position in Montana.
How is this fixed? As Nick mentioned, there has to be a "escape velocity" moment where prediction markets really enter the mainstream media. Once this is reached, I believe more people will realize there is an arbitrage opportunity to be the ambassadors of their own communities they're involved with. How can I be the "market making guy" for x thing I'm already passionate about.
And that brings me to my next point. How do prediction markets enter the mainstream? Well, it seems as though the answer is to actually counter the media and use prediction markets as a fact checker.
Media outlets were notoriously bad in the 2016 & 2020 elections in terms of biased reporting and sampling. For example, in the 2016 election, mainstream media had made it seem as though Hillary Clinton was the obvious choice and was going to win. But eventually, the silent majority spoke up at the polls which led to a Trump victory and shocked most people around the world. The media did a poor job of reflecting what the hivemind actually was thinking.
If prediction markets were popular then, would we have had a more accurate estimate of what all Americans felt in terms of the upcoming vote? Additionally, Covid was another wakeup call for people around the world in terms of how much they can trust media outlets. In general, there's been a bit of shake up with how people view mainstream news in the past 4 years.
2024 is an election year for many large countries around the world. This might be the golden chance for prediction market enthusiasts to speak up and have people participate in decentralized polling rather than relying on the old, biased methods. Remember, the Iowa Electronic Market is a great case study because it regularly outperforms media polls. It's really a matter of marketing push and getting people excited to participate.
To sum this section up, it really comes down to whether there is enough of a push to bring applications such as Polymarket to the "mainstream" at least in the tech, business, and finance worlds. In my head, it's like convincing anyone who is already active in the stock market to start participating in prediction markets - that sell seems pretty doable at a birds eye view.
And once there is this moment of consistent growth in prediction market volume, then naturally people will be looking to make the next niche of markets which will gear towards more local and personalized events.
6) Letting AI in on the fun
This next section is completely based off Vitalik's recent post on Crypto & AI. I'm going to copy over the relevant section for you all to read as he does a fantastic job explaining it.
The key takeaway is that prediction markets can come in macro & micro forms. Macro being elections, fed rates, and other topics humans are excited to participate in. And micro being checking for spam, Twitter community notes, and things like data labeling that most people don't care about and are not efficient at doing.
His point is that humans won't be doing the menial tasks for micro prediction markets and that's where AI will come in. AI models will compete with each other to win out the micro prediction markets.
From Vitalik's post:
AIs are willing to work for less than $1 per hour, and have the knowledge of an encyclopedia - and if that's not enough, they can even be integrated with real-time web search capability. If you make a market, and put up a liquidity subsidy of $50, humans will not care enough to bid, but thousands of AIs will easily swarm all over the question and make the best guess they can. The incentive to do a good job on any one question may be tiny, but the incentive to make an AI that makes good predictions in general may be in the millions. Note that potentially, you don't even need the humans to adjudicate most questions: you can use a multi-round dispute system similar to Augur or Kleros, where AIs would also be the ones participating in earlier rounds. Humans would only need to respond in those few cases where a series of escalations have taken place and large amounts of money have been committed by both sides.
This is a powerful primitive, because once a "prediction market" can be made to work on such a microscopic scale, you can reuse the "prediction market" primitive for many other kinds of questions:
Is this social media post acceptable under [terms of use]?
What will happen to the price of stock X (eg. see Numerai)
Is this account that is currently messaging me actually Elon Musk?
Is this work submission on an online task marketplace acceptable?
Is the dapp at https://examplefinance.network a scam?
Is
0x1b54....98c3actually the address of the "Casinu Inu" ERC20 token?
You may notice that a lot of these ideas go in the direction of what I called "info defense" in my writings on "d/acc". Broadly defined, the question is: how do we help users tell apart true and false information and detect scams, without empowering a centralized authority to decide right and wrong who might then abuse that position? At a micro level, the answer can be "AI". But at a macro level, the question is: who builds the AI? AI is a reflection of the process that created it, and so cannot avoid having biases. Hence, there is a need for a higher-level game which adjudicates how well the different AIs are doing, where AIs can participate as players in the game.
7) Robin Hanson's search for gold
And for the third category of prediction markets, I'd like to share this video of Robin Hanson called "Search for Gold".
For those of you that don't know, Hanson is a pioneer of modern day prediction markets and has been one of the biggest advocates and researchers of the field for the last 30 years.
The key point Hanson makes in his speech is that most people are caught up in the basic functionality of prediction markets which is betting on politics, culture, etc.
He believes that in order for this space to really go mainstream, it will come at the application level. He mentions how folks who are trying to build in this vertical should not make the next platform for general betting but rather try implementing the prediction market model in business use cases such as employee hiring, project deadlines, etc.
There have been implementations of this at companies such as Google way back in 2005 but were quickly discontinued as it led to internal conflicts and corporate politics. But he mentions that there hasn't been robust experimentation here and there's a huge untapped market for better decision making.
Hanson's point is that at the end of the day, everything comes down to better decision making for organizations. So how can we build applications where this is possible through prediction markets? This doesn't need to feel like betting but rather a more effective "skin in the game" process at organizations that may feel weird at first, but if successful can catch on very quickly.
As I was prepping for this post, one of my friends Kevin mentioned how this idea is focused on turning prediction markets into action markets.
I know this letter was reallllly long, so thanks for sticking with me if you made it this far.
I'll probably do a follow up post sometime later this year as I continue to track Polymarket's growth and we get closer to elections.
I hope you have a great weekend!
- YB
