Example
This example demonstrates a simple RSI-based strategy on QQQ data.
import oequant as oq
import pandas_ta as ta
from bokeh.io import output_notebook
# Required for Bokeh plots in notebooks
output_notebook()
# 1. Get Data
ticker = "QQQ"
start_date = "2010-01-01"
end_date = "2025-05-01"
data = oq.get_data(ticker, start=start_date, end=end_date)
# 2. Add Indicator & Signals
# Calculate RSI_3
data.ta.rsi(length=3, append=True, col_names=('rsi_3',))
# Calculate exit signal: close > high.shift()
data['exit_signal'] = data['close'] > data['high'].shift(1)
# Entry signal: rsi_3 < 20 (will be passed as an expression)
entry_expression = "rsi_3 < 20"
data.dropna(inplace=True) # Drop NaNs from indicator calculation
# 3. Run Backtest
results = oq.backtest(
data=data,
entry_column=entry_expression,
exit_column='exit_signal',
fee_frac=0.001,
capital=100_000
)
# 4. Show Report and Plot
results.report(show_plot=True, plot_args={
'indicators_other': ['rsi_3'],
'per_indicator_plot_height': 160,
'plot_theme': 'dark'
})
Sample Output
--- Backtest Report ---
Start Date: 2010-01-04
End Date: 2025-04-30
Duration: 5595 days 00:00:00
Initial Capital: 100,000.00
Final Equity: 211,555.28
Benchmark Final Equity: 1,174,411.72
--- Performance Metrics ---
| | Strategy | Benchmark |
|====================|============|=============|
| CAGR (%) | 5.02% | 17.47% |
| Avg Trade (%) | 0.47% | 1,074.41% |
| Sharpe Ratio | 0.5031 | 0.8771 |
| Sortino Ratio | 0.3253 | 1.1264 |
| Time in Market (%) | 15.93% | 99.97% |
| Max Drawdown (%) | -16.14% | -35.12% |
| CAGR / Max DD | 0.3111 | 0.4975 |
| Serenity Ratio | 4.3518 | 3.1370 |
| Total Trades | 169.0000 | 1.0000 |
| Win Rate (%) | 69.23% | 100.00% |
| Loss Rate (%) | 30.77% | 0.00% |
| Avg Win Trade (%) | 1.52% | 1,074.41% |
| Avg Loss Trade (%) | -1.90% | 0.00% |
| Profit Factor | 1.7373 | inf |
| Avg Bars Held | 3.6331 | 3,854.0000 |
An interactive plot showing the price, trades, equity curve, benchmark, and RSI indicator would also be displayed:
