Kalshi’s new liquidity incentives could be the dawn of the garage-band market maker
The exchange takes a note from rival Polymarket to make markets tighter, faster, and fairer
Kalshi has submitted a filing with the CFTC1 that could transform prediction markets: direct payments for maintaining tight quotes. For traders willing to consistently post bids and offers near market prices, this means a new income stream. If the exchange is generous enough, it could be the beginning of a whole new class of trader: the garage-band market maker.
The core issue in prediction markets has always been liquidity – having enough standing orders to trade efficiently. But providing that liquidity is risky business. You run the risk of being adversely selected due to information asymmetry. That’s just a fancy way of saying “if there’s price-moving news and you aren’t quick to move your bids, you’ll get picked off by someone faster and smarter than you.” No surprise that few want to do it for free.
The industry has tried three approaches: automated market makers (AMMs), paying liquidity providers, or hiring professional firms. Kalshi initially went the professional route, building an in-house team2 and later partnering with SIG. Meanwhile, Polymarket tried AMMs, found them wanting, and switched to paying providers to quote. Now Kalshi is adding that weapon to its arsenal.
How Kalshi’s Liquidity Incentives Actually Work
Let’s just say that it isn’t the friendliest document to people who aren’t “MIT math nerds”:
So, in my capacity as a former professional liquidity provider, I’m happy to try and explain to you how this program actually works, in terms that even a state school alumnus could understand.
For each eligible market Kalshi sets:
Target Size (how much size they want displayed)
Discount Factor (penalty for quoting away from the best price)
Time‑Period Reward (pool paid out over each period)
Example (one second snapshot):
Target size: 1,000 contracts
Discount factor: 0.9
Reward: $100
Resting orders:
A: 500 contracts at best bid ($0.65)
B: 300 at one tick away ($0.64)
C: 400 at two ticks ($0.63)
Score = size × (discount^distance)
A: 500 × 0.9^0 = 500
B: 300 × 0.9^1 = 270
C: 400 × 0.9^2 = 324
Total = 1,094 points
Payout (that second):
A: 500/1,094 ≈ 45.7% → $45.70
B: 270/1,094 ≈ 24.7% → $24.70
C: 324/1,094 ≈ 29.6% → $29.60
Kalshi averages these second‑by‑second snapshots over each time period. The design explicitly rewards:
Bigger displayed size
Tighter (closer‑to‑best) quotes
Consistent quoting over time
Two‑sided quotes (yes and no both score)3
It’s actually straightforward math that biases incentives toward deeper, tighter, and persistent order books.
Why this works well for exchanges
Instead of hiring an all-purpose market maker, this decentralizes incentives and lets the long tail of the community step in. With markets from tennis to weather to Rotten Tomatoes, one shop can’t cover everything well4.
Put a pot of money out and the best vertical specialists show up. The film buff can trade Rotten Tomatoes and the hobby meterologist quotes temperature markets.
The exchange doesn’t have to do the work of finding and hiring a trader who is good at both. They can also just pick and choose which markets need more liquidity at will. Polymarket has enjoyed the perks of this system for years now.
The downside of this system is that you don’t get the upside when market making is actually profitable. All of the profits (or losses) will accrue to the individuals, and those profits can be substantial.
A new dawn for the garage-band market maker
This program may serve as a boon to the fledgling class of semi-professional liquidity providers. Polymarket’s extremely generous liquidity program has already spawned anonymous teams who quote full‑time.
Polymarket is currently handing out $~300,0005 a month in incentives. That’s enough for a solid group of people to make a great living (although the distribution is probably not uniform).
With thick new coffers and the onset of a sports trading boom that will net Kalshi a ton of free cash flow, I could imagine the exchange being even more generous… Maybe even by an order of magnitude.
Say Kalshi starts pouring $5 million a month into incentives to bootstrap liquidity across the exchange. There would be a veritable gold rush to grab a piece of that pie by quoting broadly and deeply where needed. There will definitely be small scrappy teams making six figures a month by being the first through the wall in a new asset class.
The ideal trader profile? Traders who6:
Have deep subject matter expertise in specific market categories
Can maintain consistent quote presence during market hours
Understand how to manage risk and avoid adverse selection
Have the technical capability to automate quote updates
Don’t try to game it
The obvious exploit is “snapshot farming”: post orders for milliseconds to catch reward snapshots without trading risk. Kalshi’s countermeasures make that unprofitable:
Snapshots occur at a random time within each second and require orders to be live for the whole second.
Brief quotes (~0.1s) catch only ~10% of snapshots, so you’d earn ≈10% of steady makers' rewards.
Constant posting/canceling adds costs and draws compliance scrutiny.
The CRO can revoke participation for behavior “inconsistent with the purpose” of the program.
In short, while it's a clever idea, the randomization and monitoring aspects make snapshot farming unlikely to be profitable compared to genuine market making.
The bigger picture
Beyond market makers getting paid, this is about building better prediction markets. When multiple traders compete for incentives, everyone wins: regular traders get tighter spreads and deeper liquidity, while forecasters get cleaner signals from more efficient markets. The exchange ponies up for sure, but they are pouring gas into a flywheel that will build for the long term.
Yes, there are caveats. Benefits will be uneven across markets7, and Kalshi will need to stay vigilant for exploitation. But the potential upside is massive: a new class of specialized traders making markets in their areas of expertise, funded by exchange incentives rather than their own capital.
Net-net: this means better prediction markets, sharper forecasts, and maybe even a new career path for subject matter experts willing to put in the work.
The document itself purports a start date of August 22 or later. It appears that this is not live at the moment but should be soon. Stay tuned…!
Disclosure: I was a trader for Kalshi Trading, Kalshi’s internal market maker.
This is particularly interesting if Kalshi decides to provide liquidity for “unders” on player props? Who is bold enough to quote the NO side with the injury risk?
Ask me how I know…
An earlier version of this article misstated the number as $600k, not $300k. Apologies - here is a data source.
I asked Kalshi about two things that I haven’t heard back about yet:
How do they plan to disperse and communicate the size and location of the incentives? Will there be an API field for this?
The filing states that Designated Market Makers and Affiliated Market Makers (SIG and Kalshi Trading, respectively) will not be eligible for the rewards. But does that mean their shares get excluded from the calculation or not? Meaning, does competing with SIG cut into the incentive pie despite them not being paid for it? This significantly changes the calculus of where I would decide to compete for incentive payouts.
If I get an answer to these questions I will edit this blog post and post about it on X.