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

# Market value

> What you'd actually get swapping the asset. Jupiter routed quote, USDC numeraire, repriced via Pyth.

Market value is what the secondary market is willing to pay right now. We read it from
**Jupiter's routing engine** — the same way an actual swap would execute.

## The query

```text theme={"theme":"github-dark"}
market_quote = jupiter.quote(
  input_mint  = asset.mint,
  output_mint = USDC.mint,
  amount      = asset.market_probe_size,   # per-asset, ~$10k notional
  slippage_bps = 50,
)
market_usdc(asset) = market_quote.out_amount / asset.market_probe_size
market_usd(asset)  = market_usdc(asset) × pyth.USDC/USD
```

The probe size is configured per asset to be large enough that we sample real
depth, but small enough that we don't move the market. For deep assets like USDC
↔ USDT it's higher; for thinner assets like Hylo's `hyloSOL+` it's smaller.

We always swap *to* USDC and then convert USDC → USD via Pyth. This keeps the
numeraire consistent: every asset's `market_usd` is denominated the same way, and
USDC's own market price (a depeg signal) doesn't contaminate other assets'
spreads.

## Why Jupiter and not a single DEX

Jupiter's router aggregates depth across Orca, Raydium, Phoenix, Meteora and the
LST-specialized AMMs. Reading a single DEX gives you that DEX's idiosyncratic
liquidity profile. Reading Jupiter's route gives you the price an actual user
would receive — which is what matters for the alert.

The [mSOL/Pyth case study](/docs/case-studies/msol-pyth-may-2022) is the canonical
counter-example: a single thin pool (Mango) was the entire oracle input. The
resulting flash crash liquidated \$21M of healthy collateral. If the oracle had
read a routed quote, the thin pool would have weighted accordingly and the print
would not have happened.

## Polling cadence

* **Jupiter market quote**: a single round-robin loop ticks every `jupiter_tick_ms`
  (≈2.5s) and fires a small batch of quotes per tick. Across the \~19 Jupiter-backed
  slots this works out to **≈50s per asset** — the cadence stays under the keyless
  `lite-api` RPS budget.
* **Sanctum LST intrinsic**: a single batch call for all LSTs at once every **15s**
  (`sanctum_poll_ms`).

We do not query Jupiter on every Pyth tick — that would melt the API quota and
generate noise on micro-prints. The round-robin pacing keeps the market poll
time-aligned with the intrinsic feeds the engine's recompute consumes.

The Pyth intrinsic stream reconnects on transport errors with exponential backoff
(500ms → 30s) plus ±50% jitter — that jitter applies to the **stream reconnect**, not
to the Jupiter market poll.

## What we don't model

**Slippage at size.** Pegana's probe is fixed; if you intend to swap \$5M of an
asset, your effective market price will be worse than what we publish. The signal
is calibrated for small-to-medium trades and for state monitoring. For large
trades, use Jupiter's quote API directly with your real size.

**Routing instability.** A route may exist this second and not the next. We accept
that as long as Jupiter returns *some* quote. If routing fails entirely (no path
to USDC), the engine **skips the recompute and holds the last published state** until a
route returns — it does not flip the asset to `UNKNOWN`.

**MEV-extracted user price.** Our quote is what the route returns. A real swap
may receive a slightly worse price because of MEV between submission and inclusion.
We do not adjust for this — the gap is typically small enough not to matter for
peg state, though it matters a lot for actual execution.

## Caching and freshness

* The router's quote is cached for the polling interval (no double-call inside 15s)
* The engine refuses to consume a quote older than 30s (staleness gate)
* On a stale quote the engine **skips the recompute and holds the last published state**
  rather than emitting a fresh verdict on degraded input (it does not flip to `UNKNOWN`)

## Next

<Card title="The spread" icon="equals" href="/docs/methodology/spread">
  The formula, EWMA smoothing, per-asset thresholds, the 5-state FSM.
</Card>