The more I read about @TermMax , the less I think “fixed rate” is the sleeper feature.
I’d argue the quieter innovation is the range-order pricing curve.
TermMax’s February 6, 2025 AMM paper describes a model inspired by Uniswap V3 concentrated liquidity, but applied to fixed-income tokens: FT and XT.
The important part is the cut points.
Instead of LPs accepting one static rate, they can define multiple cut points that create a piecewise FT/XT exchange-rate curve.
One example in the paper:
▶ $1,000 USDC to lend
▶ 80% allocated to a 10%–15% APR range
▶ 20% allocated to a 15%–40% APR range
▶ 3 cut points create 2 separate ranges
So the rate can change as more of the order gets filled.
That’s a pretty different mental model from:
“Here is the market rate. Take it or leave it.”
Most people looking at @TermMax are probably tracking the headline:
fixed-rate lending
But underneath that is another question:
How precisely can liquidity express its preferred rate?
That matters because fixed-income markets aren't really one price.
They’re a curve across risk, size and term.
TermMax’s range-order design tries to encode some of that directly into liquidity.
And this isn't just a marketing diagram. The paper specifies how each range stores its liquidity and reserve parameters, and how adjacent ranges are aligned at their cut points.
There’s also a time component.
The paper notes that as maturity approaches, FT and XT prices change even at the same APR, so the pricing curve is recalculated when transactions execute.
I think that’s the interesting part.
The “fixed” in fixed-rate lending doesn't mean the entire market has one fixed price.
It means each position can have a defined rate, while the market around those positions can still have a structured curve.
That’s genuinely clever.
What data would convince you that TermMax’s range-order curve is actually improving rate discovery?
@TermMax #TermMax $TMX $BTW
I’d argue the quieter innovation is the range-order pricing curve.
TermMax’s February 6, 2025 AMM paper describes a model inspired by Uniswap V3 concentrated liquidity, but applied to fixed-income tokens: FT and XT.
The important part is the cut points.
Instead of LPs accepting one static rate, they can define multiple cut points that create a piecewise FT/XT exchange-rate curve.
One example in the paper:
▶ $1,000 USDC to lend
▶ 80% allocated to a 10%–15% APR range
▶ 20% allocated to a 15%–40% APR range
▶ 3 cut points create 2 separate ranges
So the rate can change as more of the order gets filled.
That’s a pretty different mental model from:
“Here is the market rate. Take it or leave it.”
Most people looking at @TermMax are probably tracking the headline:
fixed-rate lending
But underneath that is another question:
How precisely can liquidity express its preferred rate?
That matters because fixed-income markets aren't really one price.
They’re a curve across risk, size and term.
TermMax’s range-order design tries to encode some of that directly into liquidity.
And this isn't just a marketing diagram. The paper specifies how each range stores its liquidity and reserve parameters, and how adjacent ranges are aligned at their cut points.
There’s also a time component.
The paper notes that as maturity approaches, FT and XT prices change even at the same APR, so the pricing curve is recalculated when transactions execute.
I think that’s the interesting part.
The “fixed” in fixed-rate lending doesn't mean the entire market has one fixed price.
It means each position can have a defined rate, while the market around those positions can still have a structured curve.
That’s genuinely clever.
What data would convince you that TermMax’s range-order curve is actually improving rate discovery?
@TermMax #TermMax $TMX $BTW