HFTS

High Frequency Trading Simulator

Event-driven · Network-aware · Microsecond precision

Backtest HFT strategies
with real latency

Traditional backtesting engines oversimplify. HFTS simulates every market event with real network delays and exchange processing time — so you know if your strategy actually works before you risk your money.

tick-by-tickevent replay granularity
< 1 mslatency injection precision
Pythonstrategy scripting
free tierno credit card required

Latency is not an edge case — it is the edge

Traditional OHLC-based backtests assume your order fills instantly at the candle close. In high-frequency markets, that assumption costs money.

From the author

  • Worked in the HFT department at Deutsche Bank.
  • During the crypto boom, ran my own algo HFT strategies.
  • Every platform I tested offered a simplified simulation model. Strategies that looked profitable in backtests consistently failed in live trading. HFTS exists to fix that.
⏱️

Microsecond-precise event timestamps

HFTS replays raw quote events at their original exchange timestamps — down to the microsecond. When your strategy signal fires at T+0 µs, the engine schedules the order arrival at T + RTT and matches it only against the order book state that existed at that exact moment. A 10 ms difference in round-trip latency can mean the difference between a fill and a miss.

📡

Configurable network latency injection

Set your expected round-trip time — from a co-located 0.3 ms to a retail 80 ms connection — and HFTS injects that delay deterministically into every order. Because the order enters the event stream at the correct delayed timestamp, slippage is not random noise: it is the structural cost of being late to a fast-moving queue. You see exactly how many basis points your strategy bleeds to execution lag per trade.

📊

Level-2 tick replay, not OHLC bars

OHLC candles compress thousands of individual quote updates into four numbers. HFTS feeds your strategy a raw Level-2 event stream — every bid/ask and size update in original arrival order — so passive limit orders are matched against the actual queue state at the moment of arrival. A limit posted 12 ms after a large momentum tick faces a different fill probability than one posted in a quiet period; HFTS captures that difference.

🛡️

Expose hidden assumptions before going live

Strategies that look profitable on daily bars often rely implicitly on instant fills and zero latency. HFTS forces every fill through the latency pipeline, so overfitted logic fails in the backtest — where it is safe — rather than in production. The gap between your candle-based result and your HFTS result is precisely the cost your real infrastructure will pay.

Write strategies in plain Python

No proprietary DSL. No framework lock-in. Your strategy is a Python function that receives every market event as a structured object and returns orders. HFTS handles the rest.

  • Built-in syntax highlighting with CodeMirror
  • Load community templates to get started in seconds
  • Save multiple strategy variants per account
  • Code runs in a sandboxed environment — your logic stays private
def on_calc(self, tick): if self.has_active_orders(): return self._highs.append(tick.ask) self._lows.append(tick.bid) if len(self._highs) < self.window: return chan_high = max(self._highs[-self.window:-1]) chan_low = min(self._lows[-self.window:-1]) # Breakout above channel → momentum long if tick.ask > chan_high: self.buy_limit(tick.ask - 0.01, None)

Detailed per-trade analytics

See every fill, every cancellation, and every latency measurement. The report view shows your accumulated P&L curve alongside a trade log that includes actual execution delay per order.

  • Accumulated P&L curve on an interactive Highstock chart
  • Per-trade table: price, size, fee, latency, fill status
  • Summary statistics: total P&L, win rate, average latency, drawdown
  • Cancelled and failed orders flagged inline
▶ Run complete — 825 ms
Total P&L+$142.30 Trades38 Win rate63.2 % Avg latency47 ms Max drawdown-$61.10 Fees paid$8.44
2024-03-01T09:31:22 BUY-L 42 118.50 +$18.20
2024-03-01T09:44:07 SELL-M 42 133.10 -$7.80
2024-03-01T10:02:55 BUY-L 42 128.40 +$31.60

Curated tick-level market data

You do not need to source or clean data. HFTS ships with high-quality Level-2 quote data for major crypto instruments, updated regularly, ready to replay against your strategy.

  • Multiple symbols and date ranges available
  • Raw exchange quote feed — no resampling artefacts
  • Consistent event format across all instruments
  • More datasets added with each plan tier
  • Planned:L3 order book data
# Quote event structure { "type": "Q", "time": "2024-03-01T09:31:22.481231Z", "bid_price": 42117.80, "ask_price": 42118.50, "bid_size": 0.142, "ask_size": 0.089 }

Start free, scale when you need

All plans include the full strategy editor and event-driven engine. Paid plans unlock longer date ranges, more strategies, and extended execution limits.

Free

$0

forever · no card required


  • Full Python strategy editor
  • Event-driven backtester with latency
  • 1 day of tick data per backtest
  • Up to 5 saved strategies
  • Limited run frequency (rate limited)
  • Demo strategies to explore
  • No network access
Get started free

Quant

$50

per month · billed monthly


  • Everything in Pro
  • Full history — all available data
  • 500 saved strategies
  • High run rate limits
  • Multiple instruments per run
  • API access
  • Network access — link with your own infrastructure or AI
  • Planned: full L2 and L3 & depth-of-market event processing
Coming soon

Built for people who take execution seriously

Feedback from early users testing strategies on real tick data.

"Every other backtester I used showed my scalping strategy breaking even at worst. HFTS showed me it was actually losing 40 bps per trade to execution lag alone. That was exactly the insight I needed."

Mikhail R.
Algorithmic trader, crypto markets

"The Python interface is clean and the event format is well-documented. I had my existing signal logic running in under 10 minutes. The latency injection is the feature that sets this apart from everything else."

Sara K.
Quantitative researcher

"I love that the free tier gives you real tick data for one day — enough to validate your idea quickly without paying anything. Upgraded to Pro when I needed longer history."

James T.
Independent quant developer

Get in touch

Have a question, feedback, or would like to suggest a new feature? Do not hesitate to contact us directly.

Email
support@hfts.app
Discord community
Join the HFTS server

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