Author: Payment 201
In this episode of "Unchained," Markus, the founder of 10x Research, deeply analyzes the core of competition in prediction markets. He also discusses: **Will more platforms follow Polymarket and launch their own tokens? He elaborates on a nearly certain trading opportunity hidden within Polymarket and shares *10 strategies for participating in prediction market trading without holding opinions on the events themselves*. One key insight is: "What is truly valuable is not the wisdom of the crowd, but the wisdom among the crowd."
Takeaways:
The essence of prediction markets is probability pricing markets, structurally closer to one-touch barrier options rather than traditional gambling.
Each prediction market trade has a clear expiration date and certainty of win or loss, unlike crypto assets that can be held long-term.
The current prediction market is still in its early stages, but trading volume and user scale are rapidly approaching mainstream financial platforms.
The real moat is not product functionality, but the concentration effect of liquidity and trading volume.
Professional traders do not "predict outcomes," but look for structural pricing errors.
The most stable returns come from event contracts where time is approaching but probabilities have not fully converged.
Low probability "moonshot" trades contribute to most losses and should be systematically avoided.
Endgame sweeps and time decay capture are the most cost-effective strategy sources in prediction markets.
The truly valuable signals in the market come from a few high-quality participants among the crowd, not the average opinion of the crowd.
Prediction markets are evolving from entertainment betting to professional probability trading and risk management tools.
Laura Shin:
Hello everyone, welcome to Unchained, a show that does not hype and focuses on the real situation in the crypto industry. I am your host, Laura Shin, and thank you for joining this live broadcast. Before we begin, a quick reminder: nothing you hear on Unchained constitutes investment advice. This show is for informational and entertainment purposes only, and my guests and I may hold assets discussed in the program. For more disclosure information, please visit unchainedcrypto.com.
Laura Shin:
Today's guest is Markus Thielen, CEO of 10x Research. Welcome, Markus.
Markus Thielen:
Hi, Laura, thanks for the invitation.
Laura Shin:
I’m looking forward to discussing this topic with you. The prediction market space is really hot right now. The two biggest players are Polymarket and Kalshi, both of which have very high valuations and are in fierce competition with each other, which I think most people on X can feel.
And with Polymarket now entering the U.S. market, this competition will only escalate. Meanwhile, Gemini, Robinhood, and some other platforms are also starting to enter this field. At the same time, this space is facing some regulatory hurdles. Nevertheless, none of this has stopped the trading volume in prediction markets from continuing to grow, almost every month. The trading volume in November alone was close to $2 billion, at least for Polymarket and Kalshi.
What do you think about the current stage of prediction markets? Where do you think they are on the adoption curve?
Markus Thielen:
Yes, of course. One very interesting point is that the trading volume has indeed come up, and it is now basically at a relatively stable high level. I think we are currently seeing weekly trading volumes close to $1 billion, which is quite high. It’s somewhat similar to the situation when Bitcoin dropped from around $100,000 to about $25,000; it was at that stage that the trading volume and activity in prediction markets began to rise significantly. The number of weekly users has actually grown from about 70,000 to nearly 250,000. These numbers are quite large, indicating that many people are participating.
Of course, this is also related to the fact that Kalshi and Polymarket have collectively raised about $3 billion in the past few weeks. This means they have very strong market promotion capabilities.
I believe that as we look towards 2026, we will see many things gradually unfold. I think more investors and traders will start using these platforms to hedge some economic risks, macro risks, and of course, also for speculation.
However, currently, about 90% of the trading volume still comes from sports betting. On the crypto-related prediction market side, it is still a relatively small niche, but it is growing.
From multiple perspectives, this market is very interesting. So if I had to judge, I would say prediction markets are still in a very early stage. Because these platforms hardly existed a year or two ago, the trading volume really began to grow significantly after the Trump election; that was the first real push.
If we look at the activity from last month, for example, how many users visited these platforms, as a comparison: about 40 million users visited Robinhood, about 30 to 32 million users visited Coinbase, while Polymarket had nearly 20 million.
So from a user perspective, these prediction markets are becoming increasingly attractive, starting to attract a large trading volume on various types of events. I think we are currently at a starting point, and as we enter 2026, many things will accelerate further. As you mentioned earlier, Gemini has just obtained a license related to prediction markets. So competition is heating up, and many people want to enter this field and get a piece of the pie.
Laura Shin:
I want to follow up on a connection you just mentioned. You said that when Bitcoin prices started to fall, trading in prediction markets began to rise. Are you suggesting that some of the people who were originally trading Bitcoin have now turned to trading in prediction markets? How do you assess this?
Markus Thielen:
I think it’s more of a coincidence. If a large number of people suddenly abandoned crypto exchanges to rush into prediction market trading, I think that would be a bit of a stretch.
This is one of the questions we are trying to study and clarify, but so far, that doesn’t seem to be the case. For example, when we ask our subscribers, not many of them are actually participating in prediction market trading. Many are interested in it, but the actual trading volume is not that large. Many contracts and many bets are actually quite small in scale; they do not have the liquidity scale we are used to seeing in the crypto market. In the crypto market, you often see $100 billion, $200 billion, or even $300 billion in trading volume, while prediction markets are still a very niche market. Nevertheless, I do think there are some interesting opportunities here.
From another perspective, this is also a continuation of the "gamification" of financial markets. People want to be attracted to entertaining financial products; it’s just a matter of whether you are participating in the market from an entertainment perspective or from a probability perspective. But in any case, this market is expanding; it has become a new tool.
If we look at how people historically arbitraged between different price differences and products, it is actually similar to what we are studying in prediction markets: are there certain structural arbitrage opportunities?
Laura Shin:
It sounds like you are trading in both the crypto market and the prediction market. How would you describe the differences between these two types of markets in terms of trading?
Markus Thielen:
Of course. One thing that many people may not truly realize is that prediction markets are essentially a form of exotic options trading. It is fundamentally about probability, about understanding probabilities, and it heavily relies on the speed of reaction to news. These are all contracts with deterministic outcomes. It’s basically "yes" or "no," with no middle ground. In the end, one side must win, and the other must lose. In crypto exchanges, for example, when trading an asset, the situation is completely different. As long as you hold the asset, if the price goes up, all holders can potentially make money. So this is a completely different narrative structure.
I would say that prediction markets and crypto markets are structurally very different. But they also have some similarities, especially for mature traders. If we use more "hardcore" options terminology, prediction markets are very much like one-touch barrier options. You need to understand how to price these contracts and understand the factors that affect probabilities. In the crypto market, many times people are buying a narrative, a theme, a story. I think that is the biggest difference between the two.
However, for mature traders, whether in prediction markets or crypto markets, their way of thinking is actually very similar. Of course, everyone knows that many crypto exchanges have their own internal trading teams, fund management teams, or liquidity provision teams. These teams may be proprietary to the exchange or affiliated.
In the past two to three years, many things have been revealed, showing how these exchanges have "engineered" liquidity in the early stages. Because without liquidity, retail users cannot match with each other directly. Without liquidity, there are no trades; without trades, there are no users. We saw this situation in the early days of BitMEX. I remember when Arthur Hayes was doing a presentation in Hong Kong in 2015, he mentioned that there were a lot of Korean retail investors trading high-leverage futures, with implied volatility and funding rates being very high, and he hoped to attract institutional traders to stand on the other side to arbitrage.
In prediction markets, the situation is actually similar. Many people may not know that there are also very mature professional trading teams on Polymarket and Kalshi. Some are owned by the platform, and some are teams that the platform hopes to establish. These teams are trading 24/7 and are very professional.
The similarity here is that there are a lot of unique contracts and unique betting targets in prediction markets, but you still need market makers willing to stand on the opposite side; otherwise, you cannot attract trading flow. So the structure remains: patient market makers vs. impatient takers. This is very similar to the crypto market. But the overall structure is still different. However, this structural similarity does allow mature traders to look for arbitrage opportunities across different platforms.
Laura Shin:
Let's talk specifically about the two biggest players right now. We mentioned earlier that there are other platforms entering the space, but let's focus on the current main competitors, which are Polymarket and Kalshi. They will soon be competing head-to-head in the U.S. market. Polymarket's application is now gradually launching in the U.S., currently in a beta phase. Polymarket has raised $2 billion, with a valuation of $12 billion; Kalshi has raised $1 billion, with a valuation of $11 billion. How would you assess the strengths and weaknesses of these two companies?
Markus Thielen:
The key difference is that Polymarket is a crypto-native platform.
Its on-ramp is very fast, and the account opening process is extremely simple. For non-U.S. users, I've received screenshots showing that someone was 240,000th on the waiting list, indicating very strong demand. If you are not a U.S. user, opening an account takes basically two minutes, and you can deposit directly using cryptocurrency. This process is similar to many early crypto exchanges: you just need an email, receive a verification code, and then your account is set up. After that, you will have a wallet address where you can deposit different cryptocurrencies or stablecoins, and then you can start betting. The whole process takes less than two minutes. If you are a regulated platform in the U.S., the process will be much slower due to long backlogs. This is one of the differences.
Another difference is liquidity. From an institutional perspective, most bets are still concentrated in the sports betting sector, accounting for about 90%. Other areas, such as event contracts and crypto-related predictions, are still relatively small.
Of course, the situation will be different during election periods. For example, during the U.S. elections, about $3.7 billion in funds participated. The products on these two platforms are highly overlapping in sports betting and political events. Future differentiation will become less and less. I believe they will ultimately converge wherever there is trading volume.
Additionally, users can initiate new bets themselves; as long as the proposal is approved, you can bet on both platforms simultaneously, and if the odds differ, you can even arbitrage. Currently, they differ in style and regulation, but they will ultimately converge, especially since the U.S. market is the largest market.
Laura Shin:
Now let's talk about these new competitors. For example, Gemini has launched Gemini Titan, and Robinhood has a partnership announcement with Susquehanna. A few months ago, Limitless also conducted a controversial token issuance. Of course, there are definitely other players. What do you think about these new entrants? Which ones do you think could become truly competitive rivals?
Markus Thielen:
In my personal view, the two big platforms are still the most important. They dominate almost all trading activity. Because ultimately, everything in this market depends on liquidity and trading volume, and whether you can attract trading volume very quickly. We have seen this many times in the crypto exchange space: trading volume is key. Unless there is some major regulatory event, like the incidents that impacted some exchanges over the past few years, from Mt. Gox to BitMEX, the market tends to concentrate where the trading volume is highest. You can see how Binance grew. It attracted more users because of its trading volume and ultimately established its leadership position. Other platforms that want to get a piece of the pie must come up with very smart strategies to attract trading volume.
The situation is similar in prediction markets. If you are a smaller prediction market platform, you also need trading volume. And to gain trading volume, you need some professional traders.
You mentioned Susquehanna; they are very active in the professional market-making space. I believe they are collaborating with multiple platforms, which is exactly their role as market makers. So the key question remains: How do you "engineer" trading volume? This has always been a challenge for crypto exchanges, and the same issue applies to prediction markets.
Laura Shin:
Among the current competitors, who do you think is leading in trading volume?
Markus Thielen:
That certainly depends on the specific contracts, but overall, Polymarket is slightly ahead. If you look at last month's traffic data, Kalshi had about 5 million monthly visitors, while Polymarket had about 19 million. This is related to Kalshi being more U.S.-focused, while Polymarket is a global platform with a simpler account opening process. Additionally, Polymarket has frequently appeared at crypto conferences and various events over the past one to two years, which has increased its market exposure, making it one of the reasons for its lead.
However, in terms of valuation, the two are very close. Kalshi may have a better revenue model because it charges relatively higher trading fees, while Polymarket's fees are currently lower. But because Polymarket is a crypto exchange, it does not have to bear as many traditional regulatory costs and has not prioritized the U.S. market early on, so the compliance pressure is relatively small. However, this situation is changing now as they are entering the U.S. market.
So I believe some of the differences between them will ultimately converge. The ultimate question is: who can attract more users and establish partnerships with larger market makers? Because it all comes back to liquidity: no liquidity → no retail → no institutions → no market. This logic has been repeatedly validated in crypto exchanges and applies equally to prediction markets.
Laura Shin:
This might also relate to the recent debates on Twitter. I saw some charts on The Block showing that in recent months, especially in the past two months, Kalshi's trading volume seems to have surpassed Polymarket. However, I'm not quite sure how this data is calculated, as there are some differences in calculation methods. I won't go into details. But I want to ask, there are actually some structural differences between the platforms in the market. You also wrote about this in your blog. Some use traditional limit order books, while others have different structures. Can you talk about these differences and how they might affect users' trading behaviors?
Markus Thielen:
From the end-user perspective, I don't think there is much difference. They are basically all using limit order book structures, which essentially still involve patient market makers vs. impatient takers. Market makers will place a large number of orders in the market, waiting for retail traders to hit their buy or sell prices. When market liquidity is insufficient, the spreads will become large. This is very similar to crypto exchanges.
So from the user's perspective, as long as there is enough trading volume, the structure itself is not important. The key is: without trading volume, the spreads will be too wide, and trading costs will be very high. Every time you cross the bid-ask spread, you are essentially losing money. This is why prediction market platforms must place a strong emphasis on building liquidity.
We have already seen that some platforms have started to establish partnerships with professional market makers. I also believe Kalshi has its own internal trading team acting as market makers behind the scenes. Polymarket is also trying to establish a similar system. Because, again, trading volume is key. From the user's perspective, whether it is a limit order book is not important as long as the liquidity is sufficient. Of course, this also brings to mind Robinhood's model of generating revenue through payment for order flow in the stock market, which has some similarities.
Currently, prediction markets have about $1 billion in weekly trading volume, which is still not large, but it can grow. We can also use data tools like Token Terminal to compare the trading volume changes between Kalshi and Polymarket. It is possible that Kalshi's recent increase in trading volume is related to the start of the NFL season, as they are stronger in sports betting, while Polymarket's users are more global and may not be as interested in American sports.
But ultimately, both have raised $3 billion, which is a huge amount of funding, and they are both preparing for expansion into the U.S. market. I believe a lot will happen in the next year.
Laura Shin:
Okay, let's shift our perspective slightly to next year. We have set the stage, with these two main competitors and many new entrants. One event we haven't discussed yet, but I think is very important, is that Polymarket will issue its own token, POLY. Interestingly, they have chosen to do this through an airdrop, which is not the most popular method at the moment. I would love to hear your thoughts: how do you think Polymarket should ensure the success of this airdrop and use it to solidify its leading position?
Markus Thielen:
Yes, I think based on past experiences, airdrops have indeed become very common. Of course, some airdrops are very successful, while others are not as successful. But here, a very interesting point is that Polymarket itself is a crypto-native platform, and everything is on-chain. Therefore, this data can be well analyzed. For example, betting behaviors can be analyzed, and we can see how funds are flowing.
This is also one of the important reasons we write related research reports—an airdrop is coming. This information has been confirmed by the CEO and the head of growth. The airdrop will definitely happen. And because anyone can easily open an account, you will have a wallet address, so the airdrop can be smoothly distributed directly to your account. I do believe this airdrop could be very successful. Because people are looking for airdrops, that is a fact.
This is also why, for example, investing in the BNB token itself is a strategy, because if you sell on the first day of the airdrop, you could earn about 10% more this year. So I think people are actively looking for these "free yield" opportunities.
From a crypto perspective, this is also why people prefer the Polymarket platform. Because if you trade there, you automatically qualify for the airdrop. Moreover, the trading volume is actually concentrated among a few large players. We have studied this and seen some other research: if your cumulative trading volume on Polymarket reaches $50,000, you are already in the top 1% of users.
So from this perspective, at least at this stage, becoming a "big player" is not difficult, making it easy to qualify for the airdrop. I believe the potential value of this airdrop could be quite substantial. Because competition is clearly heating up, and you want to reward your core users. Historically, rewarding users has always been a very effective strategy.
We have seen similar situations on Hyperliquid. About a year ago, it conducted a token issuance, and since then, trading volume has started to rise in sync. A similar thing could happen here. Because anyone holding the token will, to some extent, become a "marketer" for this protocol.
So I think this airdrop is very interesting, and its value logic is sound. I am confident it will happen, and it will occur sooner than many people expect. If I had to guess, I would say it might happen at the end of Q1 next year. I believe Polymarket wants to gain a first-mover advantage in the competition. Moreover, being crypto-native, it doesn't need to spend much time preparing. Therefore, we think now is the best time to participate and observe these opportunities.
Laura Shin:
Do you think we should expect other platforms to take similar actions and issue their own tokens?
Markus Thielen:
Personally, I don't think so. Because truly becoming a crypto-native platform is very difficult, and that is Polymarket's huge advantage. If Kalshi suddenly issues a token but is not a crypto-native platform, it would be very hard to define what that token is actually useful for. For example: will there be buybacks? Will there be trading fee discounts? Will there be other incentive mechanisms? In contrast, these things are much easier on a crypto-native platform.
We have seen many such cases in the past: crypto exchanges issuing tokens to provide fee rebates, special tier benefits, and so on. Of course, if you exclude the failed case of FTT, overall, the performance of crypto exchange tokens has been quite good. This is also why I am willing to draw comparisons. If you look at history, you will find that many exchange tokens have performed quite well. So if you can obtain these tokens through an airdrop, it is not a bad thing in itself.
Laura Shin:
I can't think of many right now; the first one that comes to mind is BNB. What are some other successful exchange tokens?
Markus Thielen:
You can look at Bitget; it has its own token, which has performed quite well. OKX also has a token. In fact, you can list many crypto exchange tokens. Their performance this year has been surprisingly good.
For example, there is an exchange in Europe called WhiteBIT. I hadn't really heard of it until May of this year, but its token has risen about 100% since May, while the entire crypto market has not performed well during the same period. Bitget's token also performed quite well at the beginning of this year. So interestingly, even in a year when altcoins overall performed poorly, some exchange tokens outperformed the market. Of course, Hyperliquid has also had good performance since it issued its token a year ago, although it has recently pulled back a bit. But overall, holding these tokens is, in a way, an exposure to the entire ecosystem. This is why I think it is meaningful.
As you mentioned, BNB's performance has certainly been outstanding. Moreover, users can still earn benefits through some ongoing airdrop mechanisms. In the future, we may see some "permanent airdrop" structures that continuously create value for these token holders. If the token economics are designed well, they can indeed help these platforms establish a foothold in the crypto space. Of course, it should be emphasized that most trading in prediction markets is still concentrated in sports betting, which is a different market. However, the crypto niche within prediction markets is still a market that can be continuously built.
Laura Shin:
Before we dive into how you specifically trade in prediction markets, I would like you to explain: what are the different risks of trading in prediction markets compared to regular crypto trading?
Markus Thielen:
Of course. Prediction markets trade in event contracts, and these contracts have a clear end time. This is similar to options and somewhat like early crypto futures—back then, there were expiration dates, unlike the perpetual contracts that everyone trades now. Options also have expiration dates; whereas crypto assets, like altcoins, can be seen as a kind of open-ended option. As long as you continue to hold, you always have the chance to make money, even to achieve excess returns.
But in prediction markets, it is not like that. The contracts in prediction markets have a clear end time. Some contracts have long durations, while others are short. They fundamentally operate based on probabilities, essentially a form of barrier options. You need to truly understand what probabilities you are implying and at what price level you are buying in.
Generally speaking, the prices of these contracts range from 1 cent to 100 cents, or $0.01 to $1. If you buy a contract at 60 cents, it means you are betting that the probability of this event occurring is 60%. Moreover, most contracts are structured as binary events of "yes/no." Therefore, timing is crucial.
For example, if you bet that Bitcoin will reach $100,000 before the end of the year, then this contract ends on December 31. If you just bought Bitcoin itself, even if it reaches $100,000 on January 1, you would still make money. But in the prediction market, you would lose because the contract has expired. So, these contracts are essentially probability-based options contracts, not the kind that can be held long-term while waiting for a narrative to play out.
Additionally, probabilities can change. We have seen this happen, for example, when Trump suddenly started interviewing new candidates for the Federal Reserve chair; the market's probabilities for certain candidates changed. I remember the Financial Times reported that Trump was interviewing more candidates this week, and as a result, the probability of Kevin Hassett becoming the Federal Reserve chair dropped from 80% to 70% in just a few minutes.
Professional traders see the news headlines immediately, quickly adjust their positions, and reprice to profit from it. If you are just a non-professional trader, you might not notice until a day or two later, and you might even wonder why your P&L has changed. This is precisely the advantage of professional traders: they are at the center of the news flow, trading volume flow, and liquidity flow, which creates a huge difference.
Laura Shin:
Okay, let's talk specifically about an article you wrote titled "A Nearly Certain Bitcoin Trade on Polymarket with an Annualized Return of 63%." Can you explain what this trade is about? How are these numbers calculated? Why can it achieve a 63% annualized return under nearly certain conditions?
Markus Thielen:
Yes. The 60%+ annualized return we are talking about actually corresponds to about 4% absolute return from now until the end of the year. For many crypto traders, 4% might not seem high; it is a very small return. But if you look at it over a period of just a few weeks, the annualized return is actually quite substantial. Especially when your capital can continuously roll between different trades, this return gets amplified. I think the key is to find these high-certainty trades.
In our report, we listed 10 different strategies for people to reference and use. The specific trade you mentioned revolves around the Bitcoin ETF. The question is: will the inflow into Bitcoin ETFs in 2025 exceed that of 2024? If you aggregate the data: last year, Bitcoin ETFs attracted a total of $33.6 billion in inflows; this year, so far, it is about $22 billion. There is a $11 billion gap. So the question arises: is it possible for Bitcoin ETFs to attract another $11 billion in inflows from now until the end of the year?
We can analyze this problem mathematically. We can calculate probabilities and run Monte Carlo simulations, just like we do in option pricing. We ran 200,000 simulation paths, and the results showed that the probability of this happening is almost zero, to be precise, it is in the seventh decimal place. But even so, you can still achieve about 4% return from this trade.
So if you believe that the inflow into Bitcoin ETFs in 2025 cannot exceed that of 2024, because that would require an additional $11 billion inflow in a very short time, then you can make this trade.
There are only 14 to 15 trading days left, and there is also the Christmas holiday in between. We know that since October, the inflow into ETFs has significantly slowed down. On average, this year, the daily inflow has been less than $100 million. But to achieve this goal, the inflow needs to be $700 million per day going forward, which seems extremely unlikely. Especially if the Fed meeting shows Powell being more hawkish, which is what the market has generally expected, this would further suppress institutional investor participation. So, to make a long story short, from a mathematical perspective, this outcome is almost impossible.
But the market still leaves you with an opportunity to earn a 4% return; you just need to stand on the opposite side of this trade. We have observed many similar trades—they are mathematically almost impossible, yet the market still provides a pricing premium. This is how we view prediction markets.
Laura Shin:
Next, in another blog post you wrote, you listed many different strategies for making money in prediction markets, and you don't even need to have any opinions or judgments about the events themselves. I find this very interesting. Let's go through them one by one. The first strategy you call cross-market arbitrage. Can you explain what this means and how you use this strategy?
Markus Thielen:
Of course. If Kalshi and Polymarket provide different probabilities for the same event, that in itself constitutes an arbitrage opportunity.
For example, contracts related to the U.S. elections, or future midterm elections, or contracts like "Who will be the next Federal Reserve chair?" The probabilities on one platform may adjust faster than on another, depending on which professional market makers and participants are on the platform. These types of trades are often quite systematic and require very fast execution capabilities and sufficient capital.
Because unlike crypto exchanges, in prediction markets, you cannot quickly move stablecoins back and forth between two platforms at any time like you can in the crypto market. But it is indeed a strategy.
If two platforms provide very different odds for the same event, you can go long on one platform and short on the other to hedge your risk. This is one of the lowest-risk strategies we have listed. In our report, we will rank these strategies from lowest risk to highest risk. We tend to participate in those lowest-risk strategies because historically, these strategies have the highest probability of making money. On the other hand, those "moonshot" trades, which bet on extreme outcomes, often do not succeed. Smart traders and market makers typically place their funds on high-probability trades rather than low-probability bets.
So in practice, does that mean you are betting the same amount in both markets? Then regardless of which outcome occurs, your profit is the difference between what you earn on the winning side and what you lose on the losing side?
Markus Thielen:
Yes, that's basically it. Of course, you also need to consider transaction costs. For example, Kalshi has some fees, while Polymarket may not, or the fee structures may differ. There are indeed some small differences between the two platforms, and they haven't designed arbitrage to be that easy. It's a bit like the early days of the crypto market: in the initial stages, arbitraging between different exchanges wasn't easy. But arbitrage opportunities do exist.
Especially during last year's election, these opportunities were very obvious. Because at that time, the demographic structure of the people trading on these platforms was different, and as Polymarket entered the U.S. market, these differences may gradually disappear.
Laura Shin:
I want to confirm, when you say the platforms haven't made arbitrage easy, do you mean they are deliberately designed that way?
Markus Thielen:
No, that's not what I mean. What I mean is that on Polymarket, you can transfer crypto assets very quickly, and the funds are almost instantly available. But on Kalshi, you need to transfer the funds in advance, and the funds are "stuck" there. This is different from the arbitrage environment in modern crypto exchanges, where you can move USDC or USDT between different exchanges at any time.
Laura Shin:
Got it. The next strategy you refer to as endgame sweep or late-stage arbitrage. How does this work specifically?
Markus Thielen:
Yes, this strategy is somewhat similar to the time decay we just discussed. I already explained this with the example of the Bitcoin ETF. When we are very close to the contract's expiration, some probabilities are mathematically almost certain, but the market spreads have not fully converged. A day or even a few hours before the contract expires, the outcome is basically already decided. For example, it is almost impossible for the Bitcoin ETF to suddenly see an inflow of $11 billion now. Mathematically, that cannot happen. So we are willing to bet at this time because we can earn a 4% return. And a 4% return, when annualized, is actually quite a good return.
Laura Shin:
Right, I felt something similar when reading these strategies. It's like a day trader's mindset; as long as you do enough, the profits will keep accumulating. The next strategy you mentioned, time decay capture, is actually in the same category as this one, right?
Markus Thielen:
Yes, they are indeed somewhat similar. Generally speaking, time decay capture corresponds to a situation where the market is still overpricing volatility. For example, do you think Bitcoin will outperform gold this year? So far, Bitcoin has basically been flat this year, while gold has risen about 60%. There are only three weeks left. If you bet that "Bitcoin will not outperform gold this year," you can still earn about 4% return. This is the time decay capture strategy. From the perspective of option pricing, we find that the implied volatility of these trades is priced too high.
Laura Shin:
Next, there is a strategy you call maker spread harvesting. Can you explain what this means and how you use this strategy?
Markus Thielen:
Of course. Maker spread harvesting is more of a strategy aimed at professional traders. This strategy typically presents opportunities when the market is very volatile but liquidity is relatively low. In such cases, some traders will buy directly with market orders instead of using limit orders. The market price will then move rapidly. We have seen this happen: retail traders buy at market prices, and at that time, the bid-ask spread has widened due to significant market volatility. This creates arbitrage opportunities for market makers.
However, this type of strategy is more suitable for professional traders with mature trading systems. It is similar to the strategies used by market makers in crypto exchanges and traditional financial institutions. This strategy only truly works in a high-volatility, low-liquidity environment, when the trading volume is too large relative to the liquidity.
Laura Shin:
It sounds like this strategy somewhat relies on news events triggering emotional responses from market participants. As a market maker, how do you prepare for such situations in advance? Do you set limit orders in advance and wait for market fluctuations to occur?
Markus Thielen:
Generally speaking, market makers will continuously have limit orders in the market. When prices start to move, the trading system can automatically withdraw these orders from the market. We often see this in the crypto market. For example, if there are a lot of liquidation stop-loss orders above a certain key price level, those orders may suddenly disappear as the price approaches those levels.
Professional traders also do similar things. So it ultimately depends on how your trading engine is set up. The key is whether you are trading against the orders that are already in the market or against those market orders that "must be executed immediately." Many times, some traders will place a very low limit buy order in the market and then step away from their computer or phone. When the market suddenly fluctuates violently, those orders may get filled. These strategies are not unfamiliar to professional traders, but not everyone can execute them.
Laura Shin:
The next strategy you refer to as probability compression play. What does this specifically refer to?
Markus Thielen:
A good example is after the October FOMC meeting. At that time, the market saw a huge change in the probability of a rate cut in December. Before that, the market almost considered a rate cut in December a done deal, with probabilities around 80% to 90%. But after the October FOMC meeting, that probability suddenly dropped to 30%. Then, New York Fed President Williams came out and stated that a rate cut was still the baseline scenario, and the probability jumped back from 30% to 80%.
So you can see that probabilities can fluctuate dramatically in a very short time. This strategy is not completely risk-free because you need to make a judgment to some extent. But if the probability has been compressed to a very low level, like 30%, and you believe the Fed at least wants the market to maintain a 50/50 pricing structure before making a decision, then buying into that probability makes sense.
The same logic applies to the question of who the next Fed chair will be. Everyone knows that Trump usually leaves decisions until the last minute. If a candidate's probability is priced in at 80% or even higher, then you can choose to trade in the opposite direction, waiting for the probability to fall back. This is probability trading conducted when there is still a considerable amount of time left, but the market pricing has not yet reflected the true uncertainty.
Laura Shin:
You also mentioned before that you deliberately avoid so-called "long shots," which are extremely low-probability trades. Can you explain in more detail why?
Markus Thielen:
Yes. Low-probability trades typically refer to contracts priced below 10 cents, meaning the market believes the probability of the event occurring is less than 10%. Research shows that 60% of lost funds occur in these low-probability trades. The psychology behind these trades is very similar to buying a lottery ticket: you spend 5 cents to buy a contract, and if the event occurs, you can get $1, which seems like a very enticing return.
But in the long run, this strategy is almost destined to lose money. Just like studies on U.S. lottery purchases show: if you analyze lottery buying behavior by postal code, you will find it is highly correlated with income levels. This psychology is the same in prediction markets. Many people are attracted by the possibility of "excess returns," but the true probabilities of these trades are extremely low.
Professional traders do not operate this way. They place their funds in high-probability trades that gradually converge to certainty. That is where the real money is made.
Laura Shin:
This naturally leads us to the next category of strategies. I find this category quite interesting because from my perspective, it resembles "copy trading." One of them you refer to as liquidity imbalance trading or following whale flow. Can you explain what this means and how ordinary people can utilize this strategy?
Markus Thielen:
Of course. These platforms often claim to provide what is called "the wisdom of the crowd," which aggregates information through crowdsourcing. But in my view, a more accurate description would be: "wisdom within the crowd." Because among this group of participants, there are certainly some large players. They may have better information and can place larger positions. If they are very confident about a certain outcome, they will place a large order. This is indeed somewhat like copy trading, but the premise is that you need to find truly excellent traders.
We have seen similar situations in the crypto market, where some high-performing wallets are tracked and analyzed by various tools. In prediction markets, similar things can be done. For example: who has a high historical win rate? Who consistently places large bets in a specific area and performs steadily? Who seems to have some kind of advantage? Following the capital flows of these individuals is a viable strategy. This is not blindly copying a single trade but rather identifying those participants who have a long-term advantage in a certain category.
Laura Shin:
Is it equally difficult to identify these accounts across different platforms? For example, is it easier on Polymarket because it is more crypto-oriented?
Markus Thielen:
Yes, that's absolutely correct. It can be done on Polymarket. But on Kalshi, I think it is currently not possible.
Laura Shin:
Okay, the next strategy you refer to as price sensitivity screening. Can you explain what this means and how you utilize it?
Markus Thielen:
Here we return to the concept of one-touch barrier options. Taking Bitcoin as an example, suppose there is a contract: will Bitcoin touch $100,000 before December this year? This is essentially a one-touch barrier option. We can compare this probability with the implied volatility in traditional options markets like Deribit or IBIT. On Deribit, whether an option touches a certain price on the expiration date is different from "winning as long as it touches once" in the prediction market. Therefore, the implied volatility in prediction markets is naturally higher.
But the question is: how much higher is reasonable?
We can compare the option surfaces of different markets to see if the probabilities given by the prediction market are significantly higher than those in the institutional options market. When we published this trading idea, the implied probability on Polymarket was about 60%, indicating that Bitcoin would touch $100,000. However, in the traditional options market, the implied probability was only 10%–15%. Even considering that the one-touch structure requires higher volatility, the gap between the two remains very large.
This indicates that the pricing in prediction markets clearly reflects retail optimism. In this case, you can sell this probability in the prediction market while hedging in the options market. This is a form of cross-market probability arbitrage. So far, this strategy seems to be performing quite well.
Laura Shin:
The next few strategies seem somewhat similar. One of them you refer to as conditional hedging. Can you explain how this works?
Markus Thielen:
Yes, this is more related to macro event risk. This is actually one of the core arguments for Kalshi when it received CFTC approval in 2024: prediction markets can be used to hedge real-world outcomes. For example, if you want to hedge whether oil prices will fall below a certain level, it is not easy to do so in traditional futures markets due to complex settlement rules and high delivery risks. In prediction markets, such questions can be simplified into a "yes/no" event. This is very similar to the structure of certain insurance contracts.
Laura Shin:
The last strategy is event calendar positioning. How is this different from the conditional hedging we just discussed?
Markus Thielen:
Event calendar positioning revolves more around known time points. For example: Federal Reserve meetings, major political events. Conditional hedging usually means you are already exposed to some risk in the real economy, and the prediction market serves as a hedging tool. The event calendar strategy, on the other hand, is more like trading around the events themselves. However, I don't want to complicate things too much. In terms of results, the strategies that truly make big money still focus on endgame sweep and time decay capture, rather than those "moonshot" extreme bets.
Laura Shin:
Thank you very much for explaining all these strategies. I think this really shows how detailed prediction markets can be analyzed. Many people's first reaction to prediction markets is, "You're guessing what will happen in the future." But in reality, you don't need to have any information about the event itself; you just need to assess whether the probabilities of different outcomes are reasonably priced.
Laura Shin:
Before we wrap up, is there anything important about prediction markets that I haven't asked but you think the audience should know?
Markus Thielen:
I think we've covered a lot. The key is whether you view prediction markets as a form of entertainment or as a probability market. If you're just in it for entertainment, then like any entertainment expense, you're paying an entry fee and shouldn't complain about the final outcome. But if you look at it from a probability perspective, you'll find that more and more professional traders are entering this market, pricing these events using probability models.
This is also the core message we want to convey to our subscribers: prediction markets are a probability market, not an opinion market. Making money does not come from 100% certain outcomes, but from the side with a higher probability. Ultimately, the core remains that saying: it's not the wisdom of the crowd, but the wisdom within the crowd. This is a theme that will continue to grow until 2026.
Airdrops could be a very interesting catalyst, and as trading activity increases, prediction markets will become increasingly important. This is also why we see companies like Robinhood starting to enter this space—everyone wants a piece of the pie. We hope to get ahead of this trend, which is why we study these trades and explain how to make money in prediction markets.
Laura Shin:
Markus, it has been a pleasure chatting with you today. Thank you very much for joining Unchained.
Markus Thielen:
Thank you for having me.
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