I haven’t posted in a while, mainly busy with a number of things, including the f(o)unding of @aori_io. Now that the market’s resolved (way overdue), I thought I’d do an introspective writeup on the US presidential election prediction markets and detail some of the stuff I learnt and some of the strategies that I ran. I had to do a lot of learning as a non-US-citizen very new to US politics, so here details a lot of that research, combined with some knowledge. Of course, this is not financial advice.

A Primer on US Elections

The US Presidential Elections typically runs every 4 years, of which members of each state will vote for various representatives at the federal-level (e.g president, vice, senator rep) and state-level.

For the presidential election, the winner is not the person with the most votes by person across the country but by the number of “electoral college” votes given to each state based on population. Some states have a strong tendency to vote in favour for specific parties each election, having converged to a bipartisan system involving the “Republican” and the “Democratic” political parties. The last time that a third-party presidential candidate has won a state was back in 1968, relating to the support of states to police racial segregation at the state-level by the presidential candidate George Wallace of the American Independent Party.

Many states vote in favour of the same party for their presidential candidate again and again in consecutive elections, but with the gap between each election, votership and party alignment changes, sometimes “swinging” from Republican to Democrat or vice-versa. Many interested observers tend to bring greater attention to these “swing states” as battlegrounds that presidential candidates will dedicate more effort such as rallies and media events, to help swing votership their way. This is done to elect a sole “nominee” of the political party, or ultimately the presidential candidate that wins; for the former, “primaries” and “caucuses” are held by political parties to choose the presidential candidate that the party puts forward for their campaign.

Tailwinds from On-Chain Capital

Undoubtedly, this year has seen on-chain prediction markets grow substantially from the many accessible markets and venues to take directional exposure in the 2024 US Presidential Elections that aim to be as efficient as possible.

In prior years, many would use macro instruments (Bitcoin, Ethereum) to get indirect exposure to political decisions and elections due to the lack of liquidity in prediction markets at the time - indirect as it often didn’t lead to complete correlated risk / reward of the impact on the market. Investors for certain asset companies or companies would benefit or suffer depending on certain policies or trends, but it wasn’t the end-all-be-all.

The isolation of outcomes has lead to more distinct markets, allowing for greater risk tailoring that help to either increase directionality to a certain future that a trader is believing to occur or to hedge against it.

Though Polymarket wasn’t one of the first (many years ago were Augur and Gnosis / Azuro, and then Omen, Manifold), it happens to be a matter of right time, right place for them to capitalise on the considerable amount of on-chain capital that has been eager to play in the upcoming elections.

It was even the case in which larger players like Robinhood released market products to trade the election results throughout the run-up, where events throughout the campaign helped to drum up volume.

Most prediction markets work by allowing users to buy YES or NO binary futures on any of the possible candidates relating to the outcome of the result. A pair of YES and NO binary futures on a candidate can be minted for $1, where specifically one of the futures will payout $1 and the other $0 based on the resolved outcome of the election. These futures can then be sold on the same platform to others, allowing people to have directional exposure of betting YES on Kamala or NO on Trump etc. This could be held until the time of expiry (when the election results are officially released) or sold before then for a return.

Putting ethics aside for the example, a bet YES on Trump winning the presidential election before his Pennslyvania rally on July 13th could then be sold a day after for a positive ROI to trade around the event, effectively allowing for people to be paid for their skin-in-the-game interest even in the run-up to the elections.

Arbitrage in Prediction Markets

One of my favourite posts comes from a couple years ago from Dan Robinson:

A nice thought experiment, it puts into perspective that there is no definitive price for each token individually but that there are mechanisms that can be used to deduce their prices in relation to each other in an efficient market. Token A can be trading at 0.75 USDC and token B can be trading at 0.25 USDC and some traders may consider it a ‘fair price’ whereas others may consider it ‘mispriced’ and participate. Information asymmetry and beliefs leads to divergences in perceived fair value of each token for which that comes together to form a ‘market price’ as there are more participants.

A previous tagline used years ago for prediction markets was that they helped to pool together the “wisdom of crowds” but with varying barriers to entry and types of audiences led to extreme skew in the types of entrants involved. The failure comes where experts are not themselves the representative trading participants in these markets, being overshadowed by speculative traders that add noise.

Different CEX and DEX prediction market venues e.g Polymarket, Drift, PredictIt, Kalshi, will vary in odds on the same equivalent prediction due to a number of factors such as market access, membership, and behaviour of traders that can greatly affect how representative the prediction market is.

The sample that trades on a specific venue’s prediction market may not be representative to e.g the votership of an election, or the production team involved in the making of a documentary on who Satoshi could be. There are some cases were one can be more informed than others, but there always exist a risk, especially on such a scale, that the lack of information ends up becoming a tail risk you can’t accurately account for.

Polymarket allows a vastly larger number of people to participate compared to traditional polls, offering broader insights. More importantly, it aggregates collective predictions about who will win, rather than simply reflecting who individuals plan to vote for. This distinction makes it a unique and valuable indicator of perceived outcomes rather than direct voter intent.

With this, there was much variance to be had between venues. Ignoring exchange or gas costs, if 1 USDC can be minted for 1 YES and 1 NO token for a choice where one eventually resolves to 1 USDC and the other to 0 USDC and equivalently on other venues, then there is that certainty that can be used to find arbitrages.

Many venues gave different odds throughout. A YES for Trump on one venue could be $0.60 but a NO bet for Trump could be valued at $0.30 on another, effectively cancelling each other out in terms of sentiment and netting a total $1 risk-free when both markets resolve as expected (often termed the expected value) - a form of cross-venue arbitrage when this expected value is common with others. By purchasing it for “cheap” ($1 of value at $0.90), it can then be sold for something more closer to a $1.

Pricing In or Out Tail Risk

Tail risks such as the potential for a third party candidate to win or the chance of no outcomes to be correct are possible, but incredibly unlikely, so it is up to one to decide how they price this in terms of expected value.

A YES for Trump and a NO for Trump will have a total expected value of $1 at the time of expiry but there are things that can make that not be the case e.g if the venue somehow chooses not to go ahead with paying out i.e counterparty risk. For most venues, it is expected that they will pay out and thus one can assume a total expected value prior to the expiry of $1 (by considering this to be priced at $0 to happen), but one can assume otherwise.

It is possible to consider a YES for Trump as a NO for Kamala (the lead candidates representing each political party) but that is not exactly equivalent. Rather, a YES for Trump is a NO for Kamala, a NO for Jill Stein (Green Party nominee), a NO for Chase Oliver (Libertarian Party nominee) and a NO for every other candidate, but one can choose to price third party candidates at $0 and consider arbitrage opportunities conditional on this.

As mentioned before, the last time that a third-party presidential candidate has won a state was back in 1968, but was related to a controversial policy at the time that won a third party candidate, George Wallace, the winning candidate in a number of states.

Arbitrage opportunities lie in also buying a portfolio of positions of YES for one candidate and YES for the others that ultimately cancel out to $1 but for other candidates / successful outcomes, they may not be as liquid.

Frontrunning the News

One of the interesting points to mention in regards to decentralised nature of the prediction market is that you can always sell your positions at any time before the closing of the market, contrasting the experience normally with centralised bookmakers e.g Fanduel, Draftkings where a bet is held by the sole bettor until expiry. A common notion that many highlight for decentralised prediction markets is that if the prediction market resolves in your favour, then you’ll make money, but that is one part of the story of how to win.

Prediction markets are a very pure form of market, you make money if you’re right, and lose it if you’re wrong. And that’s why they work.

Purchasing a YES binary option at $1 that resolves as YES will payout $1 but it doesn’t offer anything additional. Purchasing a YES binary future at $0.90 that then resolves to $1 makes money, but so is purchasing a YES binary future at $0.80 that you then sell for $0.90 a week later.

The better mental model here is that if you make money if the ‘market’ believes that your prediction is ‘more right’ at the time of expiry or when you come to sell the future. Trading before and after a note-worthy event that the market deems positive in your favour can prove to be profitable so finding venues to offload inventory was part of the upkeep.

One feature of prediction markets that I think gets understated (and often gets misconstrued) is the fast rate of convergence to the correct outcome in the presence of definitive evidence to rule the outcome correct, operating faster than the oracle to resolve towards the right answer. The value that can be captured from the definitive $1 payoff is a known premium that can be earned when certain of a specific result thus exists an arbitrage.

A strategy I commonly observed were using bots or live sources to pick up official information as quickly as possible to trade on as a form of latency arbitrage, similar to the story of the Blanc Brothers, finding indicative information faster (please don’t) and trading upon that:

Their methods involved tapping into the telegraph wires outside of stations with their own magnets to intercept communications. The brothers then decoded messages related to financial transactions and stock prices by translating the Morse code. This gave them a sneak peek at breaking financial news up to a day before it reached Paris and moved markets there.

You just have to be the first to pick up asymmetric information, automatic or manual much like the French trader.

Akin to this is insider trading, but I digress; bots would trade on market events related to election news sure to spike some change and frontrun market news to enter a position prior to any updates and sell shortly after by taking on short-term inventory risk gambling on the direction of the price movement.

Preempting important price-moving events by following campaign calendars from each party and candidate, particularly events in “battleground” states, helped in monitoring risk tolerance and catch any bugs live in the code under stress - primaries, conventions and some caucuses with set dates were good for this, before eventually volume picked up with the mimetic nature of things e.g the attempted assassination of Trump, “Kamala is brat”, the euthanisation of Peanut the Squirrel and Fred the Raccoon and how news outlets have a tendency to bring such things back to the presidential race.

Post-Election Outlook for Prediction Markets

Arbitrage trading, whether it be via delta neutral market making (market making and then taking back the position or equivalent on another venue to close out the arbitrage) or simple take-takes, naturally benefits from more volume, variance and changes in prices happening for more arbitrage opportunities to exist.

For a future that eventually will expire and close out, this undoubtedly sets a cap on the time that the market can really exist for, so demand needs to be sustained for the next cohort of markets for prediction markets to be successful. The volatility of the US elections market each occasion is becoming more and more events-driven, being greatly emotion and speculative in nature where logic goes out the window (both in price and on CT threads) to potentially take opportunities on, though it’s hard to say whether other prediction markets will receive the same level of attention, much like the shiny-object-syndrome volumes seen on DeFi Kingdoms, Friendtech and LooksRare.

Lamenting on specific venues for those interested, CEXs (think prediction market platforms like PredictIt, Kalshi, Robinhood, as well as more retail-focused betting platforms such as Betfair, Bet365 and Shuffle) were relatively easy to integrate and utilise after KYC, whereas on-chain prediction market DEXs (Polymarket, Drift BET, etc.), especially ones that spun up specifically to capture election-specific volume, were less popular routes for some strategies due to their liquidity / taker volume.

Polymarket was our predominant on-chain venue to make and arbitrage against, but the infrequency of bets, many taking single naked positions and holding until expiry, and limits on users (no US users), sometimes didn’t make arbitrages sensible unless facilitating some of this flow OTC for friends.

There is also the incoming regulatory air by other commissions to crack down on some of these venues as gambling and limit users further.

Personally, I believe that other real-world prediction markets won’t come close in terms of popularity, speculation and action as the US elections. I instead point towards more targeted use cases of prediction markets that I think will prove to be more useful in localised markets (i.e applications) such as that of futarchy (e.g MetaDAO) or more customised trading experiences (@euphoria_fi).

Overall, it was pretty fun.

Feel free to DM me (@0xTaker) and reach out about anything trading, MEV or whatnot - always happy to chat. I would also like to thank Nate (@0xPerp) for a lot of insightful feedback - this guy is the real person to look at for news-based trading and prediction markets.

Do follow @98two as well.