XXSim 0.17.3

Exchange Execution Simulator - stock exchange single bar execution simulator

XXSim

Exchange Execution Simulator — simulates order execution against OHLCV candlebar data.

Disclaimer

Own risk warning — Execution prices are best estimations based on worst-case scenarios and statistics. There will be price differences between simulations and real-world execution. By using this package the user acknowledges consent and takes full responsibility for any implications caused by errors or misinterpretation of results.

The challenge

The golden standard of market data comes in OHLCV candlebars (1-min, 5-min, daily, etc.). Within each bar, the intra-bar price path is unknown. Fill prices depend on rules and order formations that are hard to simulate exactly.

The solution

XXSim reconstructs a plausible intra-bar price path from OHLC data and evaluates orders against it, producing realistic fill prices within statistical uncertainty.

Supported order types

• MarketOrder
• LimitOrder
• StopOrder
• StopLimitOrder
• TrailingStopMarket
• TrailingStopLimit
• MarketOnCloseOrder (MOC) — fills at bar.close only on bars where BarData.is_close_bar=True

Not supported

• Limit-on-Close (LOC)
• Market-if-Touched (MIT)

Order modifiers

Fields that modify order behavior without changing the order type:

Field	Description
tif	Time-in-force: GTC (default), DAY (expires on date change), GTD (expires after goodTillDate)
goodTillDate	Expiry datetime for GTD orders — format '%Y%m%d %H:%M:%S <timezone>'
goodAfterTime	Order inactive until this datetime — format '%Y%m%d %H:%M:%S <timezone>', timezone is mandatory
ocaGroup	One-Cancels-All group name — when one order in the group fills, the rest are cancelled

Execution algorithm assumptions

• No partial fills — orders fill entirely or not at all
• Aggressive approach — order fills if there is any plausible price path through the bar that would trigger it
• Intra-bar price path for trailing stops:
  • Bullish bar (close > open): open → low → high → close
  • Bearish bar (close ≤ open): open → high → low → close
• Optional fill drift — volatility-based normal distribution drift, configurable via SimulatorConfig:
  • fill_drift_model="none" (default): deterministic fills at exact price
  • fill_drift_model="normal": drift drawn from N(0, bar_range / std_divider)
  • Result always clamped to [bar.low, bar.high]
  • Use random_seed for reproducible backtests

Installation

pip install XXSim

Usage

Single-Bar Execution

from XXSim import ExecutionEngine
from xtrading_models import MarketOrder, BarData
from datetime import datetime

engine = ExecutionEngine()
bar = BarData(
    date=datetime(2025, 1, 1, 9, 30),
    open=100.00, high=105.00, low=95.00, close=102.00, volume=1000000,
)
order = MarketOrder(action='BUY', totalQuantity=100)
fills = engine.execute(order, bar)
print(fills)

Multi-Bar Simulation

from XXSim import Simulator, SimulatorConfig
from xtrading_models import MarketOrder, LimitOrder

sim = Simulator()

# Register callbacks
sim.on_fill(lambda trade, fill: print(f"Filled: {fill.execution.price}"))
sim.on_cancel(lambda trade: print(f"Cancelled: {trade.log[-1].message}"))

# Submit orders
sim.submit_order(MarketOrder(action='BUY', totalQuantity=100))
sim.submit_order(LimitOrder(action='SELL', totalQuantity=100, price=110.0))

# Process bars
for bar in historical_bars:
    fills = sim.process_bar(bar)

Bracket Orders

from xtrading_models import MarketOrder, StopOrder, LimitOrder

entry = MarketOrder(action='BUY', totalQuantity=100)
stop_loss = StopOrder(action='SELL', totalQuantity=100, price=95.0)
take_profit = LimitOrder(action='SELL', totalQuantity=100, price=110.0)

entry.add_child(stop_loss)
entry.add_child(take_profit)

trade = sim.submit_order(entry)

The Simulator supports:

• Bracket orders: child orders activate when parent fills
• Callbacks: on_fill, on_cancel, on_status, on_bar
• SimulatorEvent: enum of all event names (fill, cancel, status, bar) — use instead of raw strings when subscribing via EventEmitter directly

Development

Running Tests

pytest tests/ -v

Visualizations

Stop-limit and trailing test cases can be visualized:

python docs/stop-limit-chart-generator.py test-data/stop-limit/<filename.csv>
python docs/trailing-stop-chart-generator.py test-data/trailing-stop/<filename.csv>

Contributing

Contributions are welcome! Please see the documentation in the docs folder for algorithm details and test specifications.