Opening Range Breakout Bot: Short Backtest Performance Compared with SPY
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Summary
This document presents a QuantStats tear sheet for an automated strategy labeled “orb-plain,” compared with SPY over January 4–9, 2026. It reports return and risk statistics, including a 0% total return for the strategy, a 0.67% maximum drawdown, a 0.55 Sharpe ratio, and 67% time in the market. The benchmark’s reported total return is 1%, with a 7.02 Sharpe ratio over the same displayed period.
The report also lists the strategy’s universe of large US stocks and records that the backtest used Alpaca data and an AI researcher and trader workflow. It does not explain the opening range rules, entry or exit logic, position sizing, or transaction-cost assumptions. The displayed sample spans only a few days, and annualized figures extrapolated from such a short period are not reliable evidence of durable performance. Treat the metrics as a limited snapshot, not a validated trading result.
Key ideas
- The report compares an opening range strategy with SPY over a few days in January 2026.
- The strategy tear sheet reports a 0% total return and a 0.67% maximum drawdown.
- The benchmark shows a higher reported total return and Sharpe ratio for this period.
- The document omits the signal rules, execution assumptions, and transaction cost details.
- Annualized statistics from this very short sample provide little evidence about long-term performance.
Tags
Full text
# opening range breakout ai trading bot
Tearsheet (generated by QuantStats)
orb-plain Compared to SPY 4 Jan, 2026 - 9 Jan, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource alpaca | Backtest time 33:25 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
9.68%
Total Return ⓘ
0%
Max Drawdown ⓘ
-0.67%
RoMaD ⓘ
14.4
Longest DD Days ⓘ
3
Sharpe ⓘ
0.55
Sortino ⓘ
0.85
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.51%3.51%
Time in Market67.0%67.0%
Total Return1%0%
CAGR% (Annual Return)93.85%9.68%
Sharpe7.020.55
RoMaD275.1114.4
Corr to Benchmark1.00.81
Prob. Sharpe Ratio82.88%51.42%
Smart Sharpe4.580.36
Sortino20.140.85
Smart Sortino13.140.55
Sortino/√214.240.6
Smart Sortino/√29.290.39
Omega3.251.11
Max Drawdown-0.34%-0.67%
Longest DD Days23
Volatility (ann.)7.4%8.16%
R^20.660.66
Information Ratio-0.52-0.52
Calmar275.1114.4
Skew0.51-0.24
Kurtosis-1.412.32
Expected Daily%0.15%0.02%
Expected Monthly%0.91%0.13%
Expected Yearly%0.91%0.13%
Daily Value-at-Risk-0.49%-0.68%
Expected Shortfall (cVaR)-0.49%-0.68%
MTD0.91%0.13%
3M0.91%0.13%
6M0.91%0.13%
YTD0.91%0.13%
1Y0.91%0.13%
3Y (ann.)93.85%9.68%
5Y (ann.)93.85%9.68%
10Y (ann.)93.85%9.68%
All-time (ann.)93.85%9.68%
Best Day0.66%0.67%
Worst Day-0.32%-0.67%
Best Month0.91%0.13%
Worst 1-Month Return0.91%0.13%
Best Year0.91%0.13%
Worst Year0.91%0.13%
Avg. Drawdown-0.34%-0.67%
Avg. Drawdown Days23
Recovery Factor2.670.19
Ulcer Index0.00.0
Serenity Index-12.34-3.37
Annualized Return on Risk Capital16,231.79%1,145.29%
Worst 3-Month Return--
Time to Recovery (Days)02
5th Percentile Tail Loss-0.25%-0.5%
Time Underwater (Days)23
Percent Positive Months100.0100.0
Avg. Up Month0.91%0.13%
Avg. Down Month--
Win Days3.04.5
Loss Days3.01.5
Win Days%50.0%75.0%
Win Month%100.0%100.0%
Win Quarter%100.0%100.0%
Win Year%100.0%100.0%
Beta-0.9
Alpha--0.42
Correlation-81.44%
Treynor Ratio--3.77%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
20260.910.130.14-
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-072026-01-09-0.673
2026-09-29T23:29:21.662882
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.703003
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.741474
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.798398
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.841380
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.883474
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.938811
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:21.988713
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:22.037814
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:22.082868
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:22.123069
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:22.175350
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:29:22.224757
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
Disclaimer: This report is for informational purposes only and
should not be considered as investment advice. Past performance
is not indicative of future results.
Parameters Used
ParameterValue
universe['SPY', 'QQQ', 'AAPL', 'MSFT', 'NVDA', 'AMZN', 'META', 'GOOGL', 'TSLA', 'AMD']
agent_max_model_calls120
agent_researcher_modelopenai/gpt-6-luna
agent_trader_modelopenai/gpt-6-luna
agent_model_calls60
agent_researcher_calls30
agent_researcher_cache_hits0
agent_researcher_tool_calls163
agent_researcher_input_tokens2390391
agent_researcher_output_tokens48234
agent_researcher_total_tokens2438625
agent_researcher_thinking_tokens24614
agent_researcher_cached_input_tokens2156959
agent_researcher_cache_write_input_tokens0
agent_researcher_uncached_input_tokens233432
agent_researcher_tool_use_input_tokens0
agent_researcher_latency_ms_total557334
agent_researcher_latency_ms_avg18577.8
agent_researcher_first_event_latency_ms_avg3250.97
agent_researcher_detail_parquetlogs/orb-plain_2026-09-29_22-55_miMr1d_agent_detail.parquet
agent_trader_calls30
agent_trader_cache_hits0
agent_trader_tool_calls429
agent_trader_input_tokens5427422
agent_trader_output_tokens105321
agent_trader_total_tokens5532743
agent_trader_thinking_tokens73160
agent_trader_cached_input_tokens5116331
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens311091
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total1435517
agent_trader_latency_ms_avg47850.57
agent_trader_first_event_latency_ms_avg3951.63
agent_trader_detail_parquetlogs/orb-plain_2026-09-29_22-55_miMr1d_agent_detail.parquet
BACKTESTING_DATA_SOURCEalpacaShown in full with attribution under the source's licence. Licence: GPL-3.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.