About Backtick
Real order-flow practice, without a subscription.
Why it exists
Most chart-replay tools show you a candle moving forward. That's useful, but a candle hides the thing that actually moved price: the order flow inside it — who was the aggressor, where size traded, where bids or offers got absorbed. The tools that surface that are usually locked behind a premium tier, and your data lives on someone else's servers.
Backtick was built for discretionary backtesting: stepping through history the way you'd actually trade it, reading the tape and the footprint, and placing the trades you'd really take — to see how they'd have resolved against how price actually printed.
What makes it different
- True time & sales. Every print is tagged buy or sell from Binance aggTrades' real
is_buyer_makerflag — not inferred from the candle. Aggressive buys at the ask show green; sells at the bid show orange. - Tick-by-tick replay with a synced tape. Step or auto-play individual trades while the forming candle rebuilds and the tape streams in lockstep, from 1× to 200×.
- Footprint. Per-candle buy/sell volume by price level, so absorption and imbalance are visible inside the bar.
- Local-first & open source. It runs on your machine, reads straight from Binance, and your hypothetical trades stay in your own session. The whole thing is MIT-licensed — read it, fork it, self-host it.
An honest note on style
Backtick is opinionated toward a specific discretionary approach — wide stops, smaller targets, a high hit-rate game. It places exactly the orders you ask for and resolves them faithfully against real price action. It won't redesign your risk model or nag you about reward-to-risk; that's a deliberate choice, not an oversight.
How it's built
A small, legible stack: a FastAPI backend that fetches and caches Binance klines and aggTrades, the replay/trade engine in plain Python, and a vanilla-JS front end on TradingView's lightweight-charts — no framework, installable as a PWA. It deploys as a single service and runs just as happily on localhost.