Short Backtest of an AI-Run SPY Iron Condor Strategy
Document Lumibot
Summary
This QuantStats tear sheet reports a backtest of an AI-operated iron condor strategy against SPY over a short period in January 2026. The report names Alpaca as its data source and provides a broad set of performance and risk measures, including returns, drawdown, Sharpe and Sortino ratios, volatility, and benchmark correlation. It does not describe the option selection rules, entry and exit logic, or position sizing, so the trading method cannot be reproduced from the report alone.
The strategy shows a slightly negative total return and an annualized return of -0.5%, with a Sharpe ratio of -3.02; its reported maximum drawdown is -0.12%. These figures come from a brief sample and should not be treated as evidence of durable performance. The report also includes model-call and data-use metadata, but offers no discussion of transaction costs, slippage, or out-of-sample results. Past performance does not establish future results.
Key ideas
- The tear sheet compares an AI-run iron condor strategy with SPY over a short January 2026 period.
- The reported strategy return is slightly negative, with a negative Sharpe ratio.
- The report supplies risk metrics but omits enough trading rules to reproduce the strategy.
- The short sample limits what can be inferred about future performance.
Tags
Full text
# iron condor ai trading bot
Tearsheet (generated by QuantStats)
iron-condor-2agent Compared to SPY 4 Jan, 2026 - 15 Jan, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource alpaca | Backtest time 13:31 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
-0.5%
Total Return ⓘ
-0%
Max Drawdown ⓘ
-0.12%
RoMaD ⓘ
-3.97
Longest DD Days ⓘ
6
Sharpe ⓘ
-3.02
Sortino ⓘ
-3.65
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.56%3.56%
Time in Market59.0%59.0%
Total Return0%-0%
CAGR% (Annual Return)2.08%-0.5%
Sharpe-0.27-3.02
RoMaD3.02-3.97
Corr to Benchmark1.00.4
Prob. Sharpe Ratio47.82%42.9%
Smart Sharpe-0.15-1.75
Sortino-0.42-3.65
Smart Sortino-0.24-2.11
Sortino/√2-0.29-2.58
Smart Sortino/√2-0.17-1.5
Omega0.960.65
Max Drawdown-0.69%-0.12%
Longest DD Days36
Volatility (ann.)5.53%1.3%
R^20.160.16
Information Ratio-0.03-0.03
Calmar3.02-3.97
Skew0.62-0.76
Kurtosis1.92-0.1
Expected Daily%0.01%-0.0%
Expected Monthly%0.06%-0.01%
Expected Yearly%0.06%-0.01%
Daily Value-at-Risk-0.47%-0.11%
Expected Shortfall (cVaR)-0.49%-0.12%
MTD0.06%-0.01%
3M0.06%-0.01%
6M0.06%-0.01%
YTD0.06%-0.01%
1Y0.06%-0.01%
3Y (ann.)2.08%-0.5%
5Y (ann.)2.08%-0.5%
10Y (ann.)2.08%-0.5%
All-time (ann.)2.08%-0.5%
Best Day0.66%0.08%
Worst Day-0.49%-0.12%
Best Month0.06%-0.01%
Worst 1-Month Return0.06%-0.01%
Best Year0.06%-0.01%
Worst Year0.06%-0.01%
Avg. Drawdown-0.51%-0.12%
Avg. Drawdown Days24
Recovery Factor0.10.12
Ulcer Index0.00.0
Serenity Index-5.09-25.1
Annualized Return on Risk Capital273.8%-365.0%
Worst 3-Month Return--
Time to Recovery (Days)15
5th Percentile Tail Loss-0.4%-0.12%
Time Underwater (Days)58
Percent Positive Months100.00.0
Avg. Up Month--
Avg. Down Month--
Win Days5.146.86
Loss Days6.865.14
Win Days%42.86%57.14%
Win Month%100.0%0.0%
Win Quarter%100.0%0.0%
Win Year%100.0%0.0%
Beta-0.09
Alpha--0.01
Correlation-39.85%
Treynor Ratio--37.99%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
20260.06-0.01-0.24-
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-072026-01-12-0.126
2026-01-142026-01-15-0.122
2026-09-29T21:23:48.804647
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:48.860791
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:48.911606
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:48.988494
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.043099
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.104884
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.173995
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.240280
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.303064
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.360533
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.409929
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.475058
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:23:49.540654
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
symbolSPY
agent_max_model_calls120
agent_researcher_modelopenai/gpt-6-luna
agent_trader_modelopenai/gpt-6-luna
agent_model_calls18
agent_researcher_calls9
agent_researcher_cache_hits0
agent_researcher_tool_calls336
agent_researcher_input_tokens2082424
agent_researcher_output_tokens41770
agent_researcher_total_tokens2124194
agent_researcher_thinking_tokens21046
agent_researcher_cached_input_tokens1873245
agent_researcher_cache_write_input_tokens0
agent_researcher_uncached_input_tokens209179
agent_researcher_tool_use_input_tokens0
agent_researcher_latency_ms_total543688
agent_researcher_latency_ms_avg60409.78
agent_researcher_first_event_latency_ms_avg3067.56
agent_researcher_detail_parquetlogs/iron-condor-2agent_2026-09-29_21-10_66ic34_agent_detail.parquet
agent_trader_calls9
agent_trader_cache_hits0
agent_trader_tool_calls158
agent_trader_input_tokens1429014
agent_trader_output_tokens15504
agent_trader_total_tokens1444518
agent_trader_thinking_tokens5964
agent_trader_cached_input_tokens1286807
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens142207
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total265130
agent_trader_latency_ms_avg29458.89
agent_trader_first_event_latency_ms_avg3117.44
agent_trader_detail_parquetlogs/iron-condor-2agent_2026-09-29_21-10_66ic34_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.