> ## Documentation Index
> Fetch the complete documentation index at: https://docs.notional.xyz/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

## The Everything Exchange Era

There has been a cambrian explosion in exchanges. Crypto market structure now spans perp exchanges
(e.g. Hyperliquid and Lighter), prediction markets (e.g. Kalshi and Polymarket), RFQ venues (e.g.
Variational), AMMs, spot venues, options venues, and more. Each venue gives traders access
to a specific liquidity profile, market structure, fee schedule, and risk model.

That specialization creates better ways to trade, but leaves margin and risk separated across
accounts. If a trader wants to fund a Polymarket position but only has BTC on Hyperliquid,
they must reduce exposure, move funds, wait for settlement, and pay transfer and execution
costs. In periods of stress, when trading opportunities are most time-sensitive, high gas costs,
chain congestion, and slower settlement make those delays especially costly.

Most exchanges recognize this fragmentation problem. Their response is to expand toward the
everything exchange model: one account where a trader can access the instruments, markets, and
collateral workflows they need without leaving the venue. The goal is to make margin portable inside
the exchange, even if it remains isolated from the rest of the market.

## Exchange Expansion Tradeoffs

The exchanges trying to do this mostly fall into two categories.

The first category is venues with their own liquidity, such as CLOBs. Hyperliquid is the clearest
example. These venues can provide deep orderbooks, native limit orders, strong price discovery, and
transparent market structure. The tradeoff is that every new market needs liquidity to be rebuilt
from scratch.

The second category is RFQ or synthetic-exposure venues. These can list new markets quickly because
they do not need to bootstrap a full public orderbook for each instrument. The tradeoff is that users
accept a different set of risks: spreads can be wider than the underlying venue, limit-order behavior
is less native, and PnL can depend on the solvency and behavior of the market maker.

Both models are powerful and have clear advantages. The optimal system gives traders access to both.
This is what Notional enables.

## Notional's Model

Notional is an application-specific blockchain that lives directly on top of exchanges. It connects margin and risk across
venues through an onchain ledger, a built-in risk engine, and exchange accounts operated through an
omnibus model.

The omnibus model means Notional traders deposit to and trade through shared protocol accounts on
underlying exchanges. On Hyperliquid, for example, Notional operates through a single protocol account,
while its ledger internally credits each trader with the right collateral, positions, debt,
funding, fees, and PnL.

If trader A and trader B both deposit to Notional on Hyperliquid, both deposits are held in the
same underlying Hypercore account, but the ledger credits each trader separately. If trader A goes
long \$10 of BTC-USDC perp and trader B goes short \$10 of BTC-USDC perp, the Notional Hyperliquid account has zero net
exposure. The Notional ledger still records trader A's long and trader B's short, and the risk engine
evaluates each account independently.

Each block is therefore mostly made up of financial actions across connected exchanges: deposits,
orders, cancels, fills, withdrawals, funding, fees, and risk updates. Exchanges still provide
execution. Notional provides the shared account, ledger, and risk engine above them.

The model creates three core advantages.

1. Higher capital efficiency through cross-exchange margining. For example, positive unrealized PnL
   on one exchange can fund a trade on another.
2. Lower operational risk. Traders no longer need to bridge funds, pre-fund every venue, or manually
   move collateral before they can trade.
3. Greater access and liquidity. Traders can access more markets and choose where to route orders by
   price, liquidity, fees, latency, risk, payoff function, and market structure.

Users can pay fees similar to, or equal to, what they would pay on the underlying exchange directly.
Notional makes money from the spread between those user-facing fees and the lower effective exchange
fees the protocol can achieve through volume fee tiers and exchange-specific discounts, such as
staking HYPE.