Prediction Markets: A Differentiated Hedging Tool
Prediction Markets is the Alpha.
Prediction Markets are growing rapidly and have become one of the hottest narratives right now. The more I read about them, the more I came to realise that prediction markets could be a great tool to hedge against certain global and local events, depending on which side of the trade I am already exposed to. This is obviously not being utilised much at the moment, but I expect that as liquidity improves and prediction markets reach a broader audience, this use case will surge.
Vitalik also talked about it in his recent piece on Low-Risk DeFi.
That being said, the hedging against certain events is the most significant use case of such markets. Not only does it help sustain the liquidity flow, but it also creates more opportunities for the general prediction market participant.
We already know that multiple new companies have emerged to capitalise on the prediction market trend, bringing the number of projects being built in this category to 97. While these projects provide their services across a wide variety of niches and will grow in line with their respective sectors and audiences, when examining volume statistics, we see clear outperformance from a few products.
Moreover, it is also worth noting that Prediction Markets, as a niche, is currently being explored, and there will be new winners over time, alongside already established projects like Polymarket, Kalshi, and Limitless (owning a major share of the Prediction Markets Volume).
Evolution of Prediction Markets
I will keep this section brief and touch on the history (not a distant past) of prediction markets. Prediction Markets have seen mainstream adoption more recently, with Polymarket experiencing significantly higher volumes during the 2024 presidential elections, giving prediction markets the attention they required.
Since that rise, consistently high volumes have been maintained (although not at the 2024 levels), but recently, these volumes have started to grow again, as shown in the monthly volume chart above.
With this growth, other companies, such as Kalshi and Limitless, also began to gain higher volumes and evolved into strong contenders to Polymarket today.
Apart from this, various other prediction markets are growing, targeting different audiences and use cases, and catering to different niches. A good example of this is Noise (currently in testnet), which lets users leverage trade the mindshare of a specific project.
Prediction Markets as a Hedging Tool
I will start making my case here.
Prediction Markets in the future will become efficient and liquid enough to serve as a valuable hedge tool. I am not saying that it is not currently used for hedging, but there is certainly not enough scale to perform it at the larger level.
If we examine current use cases, this article from Wonder does a good job of putting it into perspective. He explained how he used the prediction market for hedging when Trump Token launched early this year. He simply bought $TRUMP tokens and also bought “Yes” shares of the market, “Was Trump Hacked?”. Now, if it were actually a hack, he could have recouped his investment from the “Yes” shares he bought; otherwise, the token would have had an enormous upside (and we know how high it eventually went).
I will try to frame the “hedge” opportunity through this other example. Suppose a certain investor has a fair share of their portfolio in a specific pharma company. The company is awaiting FDA approval for a new product. If this approval is granted, the company’s stock price is likely to surge; if it is rejected, it will likely plummet. If there is a prediction market for the same outcome, the pharma company investor can hedge their stock position by buying “No” shares.
Now, there are different arguments about this, that there are certainly better and more liquid venues to perform this hedge. The investor can simply open a short position and wait for approval, but in that case, can the investor maintain their hedge strictly based on the single fact that there might be an FDA approval? The answer you find here is negative.
To hedge specifically on a decision not known to anybody can be smoothly performed through a prediction market. Perhaps in the long run, prediction markets will become a hedge tool that can be complemented by existing hedging venues.
A prediction market, if used efficiently, can be a great hedge tool.
I can continue with other examples, such as election results, macroeconomic events, and rate cuts. There is no other way to hedge based on a specific event of your choice and importance.
What It Takes for Prediction Markets to Scale?
The evolution of prediction markets and the introduction of new liquidity from users contribute to making it a liquid venue for hedging against specific events/markets.
But are the markets liquid enough to perform hedging at scale?
A simple answer: No, it isn’t, at least for the majority of the markets.
You might have seen some good volume stats at the start of this piece. Polymarket closed the last month with nearly $1 billion in volume, which is excellent for a binary market setup that doesn’t offer any leverage and is working within a relatively new narrative. However, this volume is diversified across different markets and topics; this isn’t about a single event, but rather the net volume across the platform. However, a small number of events will indeed be responsible for the majority of this volume.
Now, keeping volume aside, let’s talk about the main issue here, which is Liquidity, as volume follows deeper liquidity.
Deeper liquidity ensures that price manipulation is not easy and that no single trade significantly affects the entire market while also facilitating trading with minimal slippage.
Currently, prediction markets source this liquidity in two different ways:
Automated Market Makers (AMMs): The vanilla AMM structure, where users trade against the liquidity pool. They are suitable for the markets in the initial phases, but not ideal for scaling. Orderbooks win there.
Orderbooks: Orderbooks require active traders or market makers (MMs) to maintain liquidity. They are great for scaling.
I would recommend this piece from Baheet to understand the mechanics of Prediction Markets in detail:
Now, since we are focusing on the scale here, I will keep my focus on orderbooks. In orderbooks, liquidity can either be achieved through active limit orders by traders, MMs or the combination of both. The structure that involves market makers will be more efficient.
However, market making is more challenging to perform in binary markets like Polymarket or Kalshi due to the varying characteristics between traditional markets and event contracts (prediction markets).
These are some of the reasons why MMs might not want to be involved:
High Inventory Risk: Prediction Markets move significantly in response to certain news. A market which is going well in one direction can go in the opposite direction at a fast pace, and at that moment, MMs, if priced in the opposite direction, can lose big. It can be mitigated through hedging, but often these instruments do not have such an option easily available.
Insufficient Traders and Liquidity: Markets lack sufficient liquidity. Now, it might sound like the “chicken and egg” problem, but the market needs frequent traders or takers who can keep making MMs money on bid-ask spreads. But there is simply not enough volume and trades on specific markets, which doesn’t incentivise MMs to perform their operations.
Some products are actively working on solving this problem, like Kalshi, which utilises third-party market makers and also has an internal trading arm to maintain liquidity. On the other hand, Polymarket is dependent on the natural supply and demand in the order book.
At the end, to gain these volumes and users, it is necessary to build the market everyone is looking for and wants to be a part of, a market which encompasses three characteristics:
High Leverage: This is not easily achievable in binary markets with a Yes/No question because users can’t utilise leverage to target a bigger payout. There are platforms like Flipr which provide leverage trading on prediction markets, but they often witness lower volumes. Additionally, Limitless provides markets with daily and weekly strikes, which could potentially increase users’ payouts as they can be involved in markets that settle faster.
High-Frequency Markets: The more options users have, the more they tend to use the same platform. Having more markets drives more volume.
High Market Outcome Value: If the market’s impact is substantial, it will drive significant volumes. It is particularly true for markets around elections and drug approvals, whose outcomes have a high impact on how the broader market reacts.
Closing Thoughts
Prediction markets have certainly left their mark on the industry. Just this week, they exceeded the trading volumes of memecoins, indicating their clear growth and adoption.
I would also like to point out that the prediction market definitely contributes to the state of Hyperfinancialization. And honestly, there is no problem with this state until people lose a ton of money. I even wrote a piece on how we are moving towards a state where everything has become a market, and why this is both beneficial and detrimental.
If you want to give it a read, you can find it here:
As a final thought, I truly believe that prediction markets are a great way to onboard new users to crypto, as these markets often cater to a general audience outside of the CT bubble. There are markets for everything and everyone, including pop culture, celebrity drama, new Apple product releases, and almost anything else you can think of. This allowance for anyone to trade upon anything they have an interest in can be a hugely powerful force, and one I am excited to observe and participate in.
So, yeah, Prediction Markets is the alpha.
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Great piece @Noveleader. I enjoyed the part where you mentioned about hyperfinancialisation. I see the unique proposition where prediction markets could offer a hedge on any specific outcomes. I guess the idea is to cap the downside + having the unlimited upside.
nice POV.