Note: Icobeast posted a graphic this weekend showing global Crypto Category Prediction Market share volume as reported by Artemis. Although the graphic itself had nothing to do with Kalshi’s Perpetuals offering, the ensuing X threads seemed to focus exclusively on trading activity on Kalshi’s Perpetuals platform. Outside of a criticism of how the Prediction Market Industry at large counts volume1, nothing we’ve seen has anything to do with Kalshi’s Predictions platform, so we mostly focus on addressing the Perpetuals comments in this blog post.
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This weekend, various threads took off on X accusing Kalshi of exaggerating our crypto perps volume. Rather than respond to each one individually, we figured it made sense to show in one place why the claims those threads made were misleading in some cases, and false in others.
tl;dr
The primary claim was that certain identified trades in Kalshi’s ETH Perpetual were “wash trades.” Wash trading is when trader(s) enter positions they don't actually want - usually to create a false appearance of market activity or price movement. The dumbest way to do this is to trade with yourself (this is mechanically blocked on Kalshi). A slightly smarter way to do it is by trading with a partner (this is surveilled for and banned on Kalshi).
However, all the trades that were shared on X this weekend are trades that both sides wanted to take at the time, because they disagreed on the fair price. It turns out that one side was pretty consistently right (the takers - which were hundreds of distinct traders) and one side was pretty consistently wrong (the maker). This is a sign of genuine economic activity rather than wash (where you’d expect volume to increase without either side taking a profit/loss). We'll walk through it below.
Kalshi, like most regulated exchanges, has programs where it offers market makers a flat fee across a variety of perpetual markets to maintain resting liquidity. The purpose of an exchange having resting liquidity is to quickly and efficiently fill orders when they get placed. Incentives like these are standard across regulated exchanges (See eg. CME, CBOE, Nasdaq), and done to ensure that participants are always able to enter and exit positions at fair values. These structures do not provide an incentive for traders to wash trade because they do not reward volume traded, just resting liquidity provided.
A market maker in the program has to stay in the market (that’s their commitment or obligation) - even when they're entering trades they don't want. That means a smart trader who is consistently faster than the market maker might have many opportunities to profitably trade against them. This dynamic exists in traditional exchanges as well.
With that said, we first cover a few basics.
Liquidity vs Volume
Although both Liquidity and Volume can be used to measure market health, the two metrics measure different things. Volume is backward looking: it measures trading activity that has already happened. $1 traded corresponds to $1 in volume. On the other hand, liquidity is forward looking: it measures the opportunity for trading activity in the future. Liquidity measures the answer to questions like “If I wanted to buy $1000 worth of a Bitcoin Perpetual, what price would I pay?” and “Is the price I would pay for $10,000 worth of a Bitcoin Perpetual significantly different from the price I would pay if I were only buying $10?”
In other words, liquidity helps measure execution quality. Better liquidity on the books leads to better outcomes for our users, more efficient markets, and better price discovery. It should come as no surprise that Kalshi, or any regulated exchange, really cares about liquidity in markets. Which leads us to the first point we want to make.
Kalshi Perpetuals’ market maker programs use liquidity incentives.
The Liquidity Provider incentives we have are largely of the form “Kalshi will pay you $W a month if you have bid and ask orders of size $X or above, no more than Y% apart, at least Z% of the time.” (See a similar program on e.g. NYSE) On Kalshi, these programs are available to any trader that can meet the requirements.
An example program can look like this:
Kalshi will pay Bank Street Trading $100k a month if Bank Street Trading has bid and ask orders resting on the book of size (at least) $5,000, (no more than) 0.1% apart. These orders must be resting on the book (at least) 95% of every hour.
We like knowing that, when it comes time for a user to place a trade, they will be able to do so. And thanks to Bank Street’s commitments, we can quantify and predict what sort of experience this user will get.
The second point we’d like to make is that professional trading firms like Bank Street Trading tend to trade perpetuals as “Self-Clearing Members” instead of through a broker2.
There is currently a fee holiday for Perpetuals Self-Clearing Members.
Kalshi benefits from having a wider base of Self-Clearing Members for various risk-management reasons3. In July, as an incentive to encourage more traders to become Self-Clearing perps traders, Kalshi initiated a temporary fee rebate program. Under this filing, Self-Clearing Members receive a rebate at the end of each month that matches exactly their trading fees paid on perpetual futures trades (see a comparable program at e.g. CME and CBOE or the event contract fee waiver from CME). Kalshi’s public filing is available, e.g. here and it includes language that explicitly prevents net-negative fees per-trade (i.e. get paid more to trade more)4.
Continuing our example from above, let’s say that both Bank Street Trading and one of their competitors, Thames River Securities, are Self-Clearing Members.
In this fictional world, Thames River Securities has made significant investments into its low-latency communications network and its predictive models. As a result, Thames River Securities has great technology set up to tell it the very latest price for products it trades. Bank Street Trading has made investments as well, but for whatever reason, Thames River Securities is slightly faster.
What would you expect to see in the orderbook? Bank Street would, in order to get paid 100k/month, place resting bids and offers of $5000. Thames River might then watch the price of Bitcoin elsewhere. Whenever the price of Bitcoin deviates slightly from the prices Bank Street has quoted, Thames River would trade against Bank Street5.
Because Thames River Securities isn’t paying fees, making even a small profit over and over again would cause them to trade. And because Bank Street is required to meet their liquidity conditions, they’ll keep on quoting. In the meantime, they’ll try to minimize how much money Thames River Securities, and other takers, can make off of them.
With this in mind, let’s now take a look at some of the analysis we’ve seen over the last few days. We’ll start with this “Kalshi Wash Trading” analysis6 because it neatly helps make our points for us.
We start reading the analysis at the back.
One of the first things you notice is that the aggressor has an edge. These so-called “wash trades” are profitable for the taker! Recall: Thames River Securities isn’t paying any fees. If Thames River Securities were making these trades against Bank Street Trading, they would have walked away with about $98,000 in profit.
The rest of the study is largely focused on the fact that trades of the same size keep reappearing in the trade log. For example, we can take a look at Section 6.2.
Thames River Securities, as well as any other faster traders, would love to trade higher volumes7, but they can’t, because the current volumes are all that Bank Street Trading is willing to trade. The fixed size trades are entirely consistent with a single maker putting up resting orders of a fixed size and getting traded against by many takers.
Conclusion
This past weekend, a few threads took off that accused Kalshi of causing wash trading. Putting aside the natural explanation for the trading patterns explained above, it is worth re-iterating that wash trading is explicitly banned in our rulebook. We are regulated. We know who is trading. We mechanically block self-trades, and have surveillance watching for pre-arranged trades with a partner. We’ve seen no evidence of collusion or wash trades.
Ultimately, it is worth taking a step back to look at what is happening. Kalshi cares about market liquidity so that we can provide a good user experience to traders on our platform. Because perps markets are new, we’re willing to pay for this market liquidity. This is very common for new product offerings on any regulated exchange. But because we’re an open platform, this liquidity we’re paying for isn’t limited to retail traders; anybody can take advantage of it. And while these analyses show that some professional traders are benefiting from these incentives, the benefits are also reaching regular users in the form of liquid markets. In the last few months, we’ve amassed over 350,000 lifetime perpetual traders, adding thousands of new traders per day since June who benefited from liquid markets. Open Interest, primarily held by discretionary traders rather than HFT market makers, has grown consistently week over week, doubling in the last 30 days. We’re excited to continue growing the first perps market in the U.S., deepening liquidity and improving the trading experience over time.
Footnotes
1 The gist of the complaint is that Kalshi counts volume using notional value, so for example, a trade where someone pays 3c trade is counted as $1 of volume. But this is standard in the prediction market industry, and it's how every relevant industry player reports their volume, because a 3c trade on YES necessarily has a 97c trade on NO on the other side. So the total value transacted is a dollar. In any case, Taker Volume is also publicly available as a metric on Dune (and elsewhere) for those who prefer it over Total Volume.
2 Anybody can trade as a Self-Clearing Member if they meet the regulatory requirements. Most Kalshi users trade on the Predictions platform as Self-Clearing Members.
3 In order to become a Self-Clearing Member for margined products, one must contribute capital to the Guaranty Fund that stands in place to socialize losses should an exchange member default on margin obligations. Kalshi has contributed $40m of its own capital to backstop liquidity in the Guaranty Fund supporting the Perpetuals exchange. More members with 'skin in the game' softens the blow should any member default and losses need to be socialized.
4 A separate filing referencing +0.3 bps Taker/-0.3 bps Maker fees has also been going around. This program is not live, and in any case would require a public exchange notice were it to take effect.
5 Kalshi doesn't have any speed bumps. Because of this, even a small latency advantage that Thames River Securities has over Bank Street Trading is enough to win them the trade as their taker order reaches the matching engine faster than Bank Street's order cancel.
7 As the study points out, the aggressor does not have a fixed order size!
