Boros Market

demeter.boros_v4 provides experimental Boros support for fixed-float swap backtests.

The current focus is cross-market rate research rather than full protocol or centralized-exchange replay.

What is supported

• Two Boros markets loaded from raw orderbook and liquidity event files

• Recovery of Boros settlement state from FIndexUpdated-style events

• Taker-only replay with TX_REPLAY_BEST_EXEC

• Two-leg Boros implied-rate spread strategies

• Four-leg style experiments where Boros legs are combined with synthetic perp funding cashflows

Protocol alignment

The current Boros engine already aligns several protocol-critical details:

• latestFTime is the basis for time-to-maturity in trade recovery and settlement

• floating_index and fee_index are recovered from Boros FIndexUpdated events

• fixed-float directions are aligned with Boros side semantics

  • PAY_FIXED -> LONG

  • RECEIVE_FIXED -> SHORT

• Boros-side protocol primitives are exposed in Python:

  • Side

  • TimeInForce

  • Trade

  • Fill

Important remaining gap:

• the current mark_rate used by the backtests is a decoded traded-rate proxy, not the full protocol markRateView implementation from an orderbook observation window

That means settlement is materially closer to protocol behavior than before, but execution and mark-rate estimation are still experimental.

What is not supported yet

• A standalone perp market inside Demeter

• Full maker queue simulation

• Protocol-perfect settlement fee oracle replay

• Full liquidation and margin simulation for centralized exchange perps

Two recommended samples

Two-leg Boros spread sample

Run:

PYTHONPATH=/path/to/demeter .venv/bin/python samples/strategy-example/72_boros_funding_convergence.py

This sample:

• loads Binance and Hyperliquid Boros markets

• trades the Boros implied-rate spread

• uses Boros settlement and replay only

Use it when you want to validate:

• event parsing

• settlement behavior

• Boros-only spread trading logic

Four-leg experimental sample

Run:

PYTHONPATH=/path/to/demeter .venv/bin/python samples/strategy-example/77_boros_convergence_with_perp_funding.py

This sample:

• runs the same two Boros legs

• fetches Binance and Hyperliquid funding histories

• mounts funding cashflows into the existing Boros engine

This is still experimental. The external perp side is modeled as cashflow only, not as a separate market with order fills, margin, or liquidation.

Strategy structure

Two-leg sample

The two-leg sample trades:

• one Boros PAY_FIXED leg

• one Boros RECEIVE_FIXED leg

It is a spread mean-reversion strategy over two Boros implied-rate markets.

Four-leg experimental sample

The funding-mounted sample is conceptually closer to the Boros article’s cross-exchange funding arbitrage:

• Boros leg on venue A

• Boros leg on venue B

• synthetic perp funding cashflow on venue A

• synthetic perp funding cashflow on venue B

The current implementation only simulates the Boros legs as full markets. The perp side is attached as external funding cashflow series.

Output files

The Boros convergence exporter writes:

• trade_ledger.csv

• position_ledger.csv

• settlement_ledger.csv

• spread_timeseries.csv

• summary.json

• report.md

When synthetic funding is enabled it also writes:

• perp_funding_ledger.csv

Current recommendation

If your goal is parser and settlement validation, start with the two-leg sample.

If your goal is research on Boros plus external funding carry, use the four-leg experimental sample and treat it as a costed research prototype, not a production-grade perp replay.

For execution mode selection and current benchmark guidance, see:

• market_boros_modes