Production-ready examples from simple strategies to institutional-grade systems. All code is taken from our real test suite.
Simple moving average crossover strategy. Perfect starting point for understanding the SDK.
XGBoost ensemble with volatility regime detection. Multi-model voting classifier.
PPO agent training with Stable Baselines3. Custom exit rules and dashboard generation.
Complete hedge fund workflow with portfolio management, risk controls, and optimization.
Production-ready strategies: Falcon ATR with intrabar analysis, multi-indicator systems.
Web dashboard generation, charting, and trade visualization with export capabilities.
from rlxbt import Backtester, Strategy, load_data
class MyStrategy(Strategy):
def generate_signals(self, data):
df = data.copy()
df["signal"] = 0
# Your logic here
return df[["signal"]]
data = load_data("data.csv")
bt = Backtester(initial_capital=100_000)
result = bt.run(MyStrategy(), data)
print(result)from rlxbt import rlx
# After running backtest...
dashboard = rlx.DashboardGenerator(
initial_capital=100_000,
commission=0.001,
use_intrabar_resolution=True
)
result = dashboard.generate_dashboard(
backtest_result, data
)
# Launch web UI
dashboard.plot(result, port=8000)