FastMM

FastMM is a low-latency market-making engine.

If you are running FastMM on Binance, try bndesk, a real-time dashboard for your accounts.

Features

• Strategies in C++ or Python. Python hooks marked @fastmm.hot compile to machine code with Numba.
• One strategy file for backtest and live. Replays are deterministic, and the simulated exchange models queue position.
• Account pools. Several sub-accounts trade behind one venue, and orders spread across them.
• Gateway. One fastmm-gateway holds the exchange connections; several strategy processes attach to it and can stop or restart without dropping them.
• Live control. fastmm-ctl changes a running session's parameters without a restart.
• Low-latency tuning. Host and network tuning built in, such as core pinning and kernel bypass.

Quickstart

pip install "fastmm-engine[hot]"
fastmm init my-mm && cd my-mm
python backtest.py

This runs a strategy on a simulated market, with no account and no API keys (Linux x86-64, Python 3.10+).

A strategy

import fastmm
from fastmm import Param


class TouchMM(fastmm.Strategy):
    half_spread_bps = Param(0.01, min=0.0, doc="half spread, bps")
    quote_qty = Param(0.002, min=0.0, doc="size per side")

    @fastmm.hot  # compiled to machine code with Numba
    def on_book(self, ctx, book):
        if not book.valid:
            ctx.pull()
            return
        half = book.mid * self.half_spread_bps * 1e-4
        ctx.clear()
        ctx.bid(book.mid - half, self.quote_qty)
        ctx.ask(book.mid + half, self.quote_qty)
        ctx.keep_passive()

Exchanges

Binance, OKX, Bybit, Gate, Deribit, Gemini and Coinbase. Nasdaq over TotalView-ITCH and OUCH 5.0.

Documentation

• Quickstart
• Quote on one exchange, hedge on another
• Account pools
• Low-latency TCP
• Run on a testnet or demo account
• Run in production
• How FastMM works
• How fast it is
• Benchmarks

Full documentation: https://ziy.bio/FastMM/

License

MIT