A Short SPY 0DTE Options Bot Backtest
Document Lumibot
Summary
This report compares a SPY 0DTE options strategy with SPY over a brief backtest covering January 4–6, 2026. It presents standard performance and risk measures, including returns, drawdown, Sharpe ratio, volatility, time in the market, and benchmark correlation. The strategy’s reported total return is approximately zero, with a negative annualized return and Sharpe ratio, while SPY shows a positive total return for the period. The strategy also has negative correlation to the benchmark in the report.
The results are descriptive rather than evidence of a reliable trading edge. The test spans only a few days, so annualized figures and risk metrics are especially unstable and cannot establish how the bot would perform across market regimes. The report names Alpaca as the data source and lists the AI agents and their call counts, but it does not explain the strategy’s decision rules, option selection, execution assumptions, transaction costs, or position sizing. The results therefore offer little basis for judging robustness or live performance.
Key ideas
- The report evaluates a SPY 0DTE options strategy against SPY over a very short period.
- It includes return, drawdown, Sharpe, volatility, market exposure, and benchmark correlation metrics.
- The strategy’s reported return and risk-adjusted performance are negative for the tested window.
- A few days of data cannot support reliable conclusions about annualized performance or robustness.
- The report omits the strategy rules, option selection process, and execution cost assumptions.
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Full text
# 0dte options ai trading bot
Tearsheet (generated by QuantStats)
0dte-plain-v2 Compared to SPY 4 Jan, 2026 - 6 Jan, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource alpaca | Backtest time 39:51 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
-27.24%
Total Return ⓘ
-0%
Max Drawdown ⓘ
-0.17%
RoMaD ⓘ
-156.57
Longest DD Days ⓘ
-
Sharpe ⓘ
-22.97
Sortino ⓘ
-15.8
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.52%3.52%
Time in Market34.0%67.0%
Total Return1%-0%
CAGR% (Annual Return)193.76%-27.24%
Sharpe10.5-22.97
RoMaD--156.57
Corr to Benchmark1.0-0.83
Prob. Sharpe Ratio--
Smart Sharpe6.06-13.26
Sortino464.26-15.8
Smart Sortino268.04-9.12
Sortino/√2328.28-11.18
Smart Sortino/√2189.53-6.45
Omega30.760.0
Max Drawdown--0.17%
Longest DD Days--
Volatility (ann.)6.53%1.07%
R^20.70.7
Information Ratio-0.66-0.66
Calmar--156.57
Skew1.730.32
Kurtosis--
Expected Daily%0.2%-0.06%
Expected Monthly%0.59%-0.17%
Expected Yearly%0.59%-0.17%
Daily Value-at-Risk-0.36%-0.15%
Expected Shortfall (cVaR)-0.36%-0.15%
MTD0.59%-0.17%
3M0.59%-0.17%
6M0.59%-0.17%
YTD0.59%-0.17%
1Y0.59%-0.17%
3Y (ann.)193.76%-27.24%
5Y (ann.)193.76%-27.24%
10Y (ann.)193.76%-27.24%
All-time (ann.)193.76%-27.24%
Best Day0.59%0.0%
Worst Day0.0%-0.11%
Best Month0.59%-0.17%
Worst 1-Month Return0.59%-0.17%
Best Year0.59%-0.17%
Worst Year0.59%-0.17%
Avg. Drawdown--0.17%
Avg. Drawdown Days--
Recovery Factor-1.0
Ulcer Index0.00.0
Serenity Index--7.09
Annualized Return on Risk Capital--12,166.67%
Worst 3-Month Return--
Time to Recovery (Days)00
5th Percentile Tail Loss0.0%-0.11%
Time Underwater (Days)02
Percent Positive Months100.00.0
Avg. Up Month--
Avg. Down Month--
Win Days3.00.0
Loss Days0.03.0
Win Days%100.0%0.0%
Win Month%100.0%0.0%
Win Quarter%100.0%0.0%
Win Year%100.0%0.0%
Beta--0.14
Alpha--0.11
Correlation--83.37%
Treynor Ratio-26.93%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
20260.59-0.17-0.29-
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-052026-01-06-0.172
2026-09-30T00:12:16.179039
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.226150
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.267923
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.324572
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.476375
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.524806
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.575602
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.627049
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.676396
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.728180
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.769849
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.817684
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-30T00:12:16.865787
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_calls200
agent_researcher_modelopenai/gpt-6-luna
agent_trader_modelopenai/gpt-6-luna
agent_model_calls104
agent_researcher_calls52
agent_researcher_cache_hits0
agent_researcher_tool_calls949
agent_researcher_input_tokens9387870
agent_researcher_output_tokens101656
agent_researcher_total_tokens9489526
agent_researcher_thinking_tokens47624
agent_researcher_cached_input_tokens8588694
agent_researcher_cache_write_input_tokens0
agent_researcher_uncached_input_tokens799176
agent_researcher_tool_use_input_tokens0
agent_researcher_latency_ms_total1535571
agent_researcher_latency_ms_avg29530.21
agent_researcher_first_event_latency_ms_avg2642.79
agent_researcher_detail_parquetlogs/0dte-plain-v2_2026-09-29_23-32_c9JZhf_agent_detail.parquet
agent_trader_calls52
agent_trader_cache_hits0
agent_trader_tool_calls361
agent_trader_input_tokens4849828
agent_trader_output_tokens54159
agent_trader_total_tokens4903987
agent_trader_thinking_tokens33310
agent_trader_cached_input_tokens4366953
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens482875
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total843673
agent_trader_latency_ms_avg16224.48
agent_trader_first_event_latency_ms_avg2848.88
agent_trader_detail_parquetlogs/0dte-plain-v2_2026-09-29_23-32_c9JZhf_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.