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Author SHA1 Message Date
Exocet92andGitHub 6cae686283 bench: add a cost workload and a multi-asset one, and go to three repetitions (#10)
Two gaps a reader could name without running anything: costs appeared on one
workload out of four, and nothing in the suite was a portfolio.

Costs could not simply be switched on across the board, and the reason is
measured. On FractionOfEquity sizing a 5 bps fee puts the engines 1.3e-4 of
capital apart and 2 bps of slippage 2.1e-5, against a 1e-9 tolerance, while the
round-trip counts stay identical: the trading agrees, the cost arithmetic does
not, because one charges the fee on top of the notional and the other reserves
it out of cash first. In fixed units both land exactly, to 1e-15. So
`sma_cross_costs` carries a fee and slippage on the headline signal, sized in
units, and the price of that is visible rather than hidden: x48.0 against x50.6
at 100k bars.

`multi_asset` runs five independent series in one shared book. It is the
workload manifoldbt does worst on, and it is here for that reason: going from
one asset to five costs it 6.1x and vectorbt 1.4x, so the ratio falls from x36.7
to x8.8 at a million bars. Broadcasting a column per asset is close to free;
walking five books is not. A portfolio is also what people actually run, and a
suite that only measures where it wins is not evidence.

Both are capped where a materialised five-column simulation would stop measuring
the engine and start measuring the swap file, and `ema_rsi_fees` keeps the
ceiling it got for going bankrupt.

Repetitions go from two to three: the floor at which a median is a median rather
than the mean of two.
2026-08-20 18:45:05 +02:00
Exocet92andGitHub d9f1862fd9 bench: run the vectorbt comparison on public runners (#5)
A speed claim a reader cannot reproduce is a screenshot. This harness
installs manifoldbt from PyPI like any user would, generates its own data,
and gates every timing behind a parity check: a workload where the two
engines disagree publishes nothing and fails the run.

It lives here rather than in the engine repository because it benchmarks the
published wheel, not the source. Anyone can fork this repository and press
"Run workflow" to get the same table on their own runner.

The workflow runs on demand, weekly, and on every published release, so a
version that gets slower says so in public.
2026-08-18 02:49:20 +02:00