backtesting
metrics
sharpe
data-quality
quant
It's easy to compute a Sharpe ratio. It's harder to compute one that won't embarrass you in front of an allocator. Our metrics derive elapsed time from the calendar span (not the bar count), use textbook downside deviation, and ship a data-quality re...
Jonny Bravo -
data-engineering
data-catalog
architecture
crypto
quant
Crypto data is a mess of inconsistent column names, symbol formats, and venue quirks. The dataset catalog maps a clean logical name — 'ohlcv', 'funding' — to a physical table plus a column map and point-in-time semantics, so a strategy says what it n...
Jonny Bravo -
ai
llm
code-generation
quant
developer-experience
An LLM that writes trading code from a one-line description is a parlor trick — unless it's grounded in the exact authoring API, the live dataset catalog, and real sample rows, and its output is validated against the same sandbox the engine uses, wit...
Jonny Bravo -
developer-experience
editor
monaco
tooling
quant
A strategy editor whose autocomplete drifts from the engine is worse than no autocomplete — it confidently suggests methods that don't exist. Ours introspects the real source on every request, so the surface you're offered is exactly the surface that...
Jonny Bravo -
security
sandbox
platform
python
infrastructure
A platform that lets users write Python and run it on your infrastructure has a hard problem: that Python could try to escape. Here's the layered sandbox — save-time AST validation, restricted builtins, an allowlisted importer — that lets quants writ...
Jonny Bravo -
fund-operations
nav
investor-accounting
fees
compliance
A profitable strategy is half a fund. The other half is investor accounting that doesn't drift: unitized NAV-per-unit, pro-rata P&L, management and performance fees with a high-water mark, and a compliance-grade execution audit trail. Here's the acco...
Jonny Bravo -
backtesting
optimization
parameter-sweep
performance
quant
Research velocity is a competitive edge. A grid of five parameters across five values is 3,125 backtests — and on our engine the data for all of them is pulled once, cached as parquet, and reused. Here's how the sweep harness and the cache turn a cof...
Jonny Bravo -
backtesting
live-trading
execution
quant
infrastructure
The deadliest gap in systematic trading is between the code you backtested and the code that trades live. We close it by running the exact same engine in both — preflight in milliseconds, backtest in minutes, then schedule the identical strategy as a...
Jonny Bravo -
backtesting
funding
perpetuals
basis-trading
crypto
quant
If your backtester ignores funding, every carry, basis, and delta-neutral strategy you test is a fiction. Our engine accrues funding per bar on live mark notional, prorated by each venue's own funding interval — so a Binance 8h feed and a Hyperliquid...
Jonny Bravo -
backtesting
quant
data-engineering
point-in-time
crypto
Most backtests quietly leak the future into the past. Here's how our engine makes look-ahead bias structurally impossible — as-of joins on the bar clock, per-instrument freshness TTLs, and a leak-check attestation on every preview....
Jonny Bravo -