Short Backtest of an AI Credit Spread Strategy Against SPY
Document Lumibot
Summary
The document is a QuantStats tear sheet comparing a credit-spread strategy with SPY over January 4–22, 2026. It reports that the strategy had a slightly negative total return and annualized return, a small maximum drawdown, and negative Sharpe and Sortino ratios. The benchmark also lost value during the reported period, while the strategy showed low correlation to it and lower measured volatility. The report includes additional risk and return statistics, drawdown dates, and a summary of the backtest configuration.
This is a very short evaluation window, so annualized figures and risk ratios are unstable and should not be treated as evidence of durable performance. The document provides no description of how the bot chooses spreads, sets strikes or expirations, manages positions, or handles transaction costs. Its evidence is limited to this single reported backtest, and the report itself cautions that past performance does not predict future results.
Key ideas
- The tear sheet compares a credit-spread strategy with SPY over a short January 2026 period.
- The strategy's reported return and risk-adjusted ratios were negative.
- Its measured volatility and maximum drawdown were lower than SPY's in this sample.
- The report does not explain the bot's trade selection or position-management rules.
- The short sample limits conclusions about future or long-term performance.
Tags
Full text
# put credit spread ai trading bot
Tearsheet (generated by QuantStats)
credit-spread-plain-v2 Compared to SPY 4 Jan, 2026 - 22 Jan, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource alpaca | Backtest time 21:42 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
-0.49%
Total Return ⓘ
-0%
Max Drawdown ⓘ
-0.2%
RoMaD ⓘ
-2.48
Longest DD Days ⓘ
7
Sharpe ⓘ
-4.02
Sortino ⓘ
-4.87
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.58%3.58%
Time in Market58.0%58.0%
Total Return-0%-0%
CAGR% (Annual Return)-7.98%-0.49%
Sharpe-0.92-4.02
RoMaD-3.16-2.48
Corr to Benchmark1.00.04
Prob. Sharpe Ratio38.28%39.88%
Smart Sharpe-0.64-2.77
Sortino-1.14-4.87
Smart Sortino-0.79-3.35
Sortino/√2-0.81-3.44
Smart Sortino/√2-0.56-2.37
Omega0.830.54
Max Drawdown-2.53%-0.2%
Longest DD Days107
Volatility (ann.)11.63%0.99%
R^20.00.0
Information Ratio0.030.03
Calmar-3.16-2.48
Skew-1.71-0.59
Kurtosis7.041.77
Expected Daily%-0.02%-0.0%
Expected Monthly%-0.41%-0.02%
Expected Yearly%-0.41%-0.02%
Daily Value-at-Risk-1.02%-0.09%
Expected Shortfall (cVaR)-2.04%-0.14%
MTD-0.41%-0.02%
3M-0.41%-0.02%
6M-0.41%-0.02%
YTD-0.41%-0.02%
1Y-0.41%-0.02%
3Y (ann.)-7.98%-0.49%
5Y (ann.)-7.98%-0.49%
10Y (ann.)-7.98%-0.49%
All-time (ann.)-7.98%-0.49%
Best Day1.15%0.09%
Worst Day-2.04%-0.14%
Best Month-0.41%-0.02%
Worst 1-Month Return-0.41%-0.02%
Best Year-0.41%-0.02%
Worst Year-0.41%-0.02%
Avg. Drawdown-1.43%-0.08%
Avg. Drawdown Days64
Recovery Factor0.150.12
Ulcer Index0.010.0
Serenity Index-1.21-16.39
Annualized Return on Risk Capital-310.75%-235.43%
Worst 3-Month Return--
Time to Recovery (Days)21
5th Percentile Tail Loss-0.65%-0.08%
Time Underwater (Days)1214
Percent Positive Months0.00.0
Avg. Up Month--
Avg. Down Month-0.41%-0.02%
Win Days8.646.91
Loss Days10.3612.09
Win Days%45.45%36.36%
Win Month%0.0%0.0%
Win Quarter%0.0%0.0%
Win Year%0.0%0.0%
Beta-0.0
Alpha--0.0
Correlation-4.39%
Treynor Ratio--966.58%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
2026-0.41-0.020.06+
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-162026-01-22-0.207
2026-01-142026-01-14-0.071
2026-01-082026-01-12-0.035
2026-01-062026-01-06-0.011
2026-09-29T23:54:07.957703
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.007747
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.055070
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.115376
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.161656
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.215058
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.271663
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.326427
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.380626
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.435515
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.483094
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.539563
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:54:08.596042
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_calls26
agent_researcher_calls13
agent_researcher_cache_hits0
agent_researcher_tool_calls431
agent_researcher_input_tokens3559038
agent_researcher_output_tokens45548
agent_researcher_total_tokens3604586
agent_researcher_thinking_tokens22403
agent_researcher_cached_input_tokens3317570
agent_researcher_cache_write_input_tokens0
agent_researcher_uncached_input_tokens241468
agent_researcher_tool_use_input_tokens0
agent_researcher_latency_ms_total942251
agent_researcher_latency_ms_avg72480.85
agent_researcher_first_event_latency_ms_avg3116.23
agent_researcher_detail_parquetlogs/credit-spread-plain-v2_2026-09-29_23-32_ps7tFd_agent_detail.parquet
agent_trader_calls13
agent_trader_cache_hits0
agent_trader_tool_calls203
agent_trader_input_tokens2264752
agent_trader_output_tokens25781
agent_trader_total_tokens2290533
agent_trader_thinking_tokens12954
agent_trader_cached_input_tokens2070785
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens193967
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total357979
agent_trader_latency_ms_avg27536.85
agent_trader_first_event_latency_ms_avg3141.23
agent_trader_detail_parquetlogs/credit-spread-plain-v2_2026-09-29_23-32_ps7tFd_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.