A Short Nancy Pelosi Trading Bot Backtest Compared with SPY
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Summary
This QuantStats tear sheet reports a short backtest of a strategy labeled as a Nancy Pelosi trading bot and compares it with SPY. The displayed test period runs from January 19 to February 12, 2026, using Yahoo data. The report lists returns, risk measures, time invested, drawdowns, and other performance statistics. It reports a 2 percent strategy total return against 1 percent for SPY, alongside a larger maximum drawdown and higher annualized volatility for the strategy.
The document does not describe the bot’s signals, holdings, trade execution, or how the strategy uses the namesake’s trades, so the mechanism cannot be assessed from this report. Its short observation window and lack of methodological detail limit the conclusions that can be drawn from the metrics; the annualized figures should not be treated as evidence of durable performance. The report also cautions that past performance does not predict future results. This is performance reporting, not a reproducible strategy specification.
Key ideas
- The report compares a Pelosi-labeled strategy with SPY over a short period in early 2026.
- It shows higher total return for the strategy alongside greater maximum drawdown and annualized volatility.
- The report provides performance statistics but does not explain the bot’s trading rules or holdings.
- The brief test window limits the conclusions that can be drawn from its annualized metrics.
Tags
Full text
# nancy pelosi trading bot
Tearsheet (generated by QuantStats)
pelosi-2agent Compared to SPY 19 Jan, 2026 - 12 Feb, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource yahoo | Backtest time 19:05 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
39.01%
Total Return ⓘ
2%
Max Drawdown ⓘ
-8.23%
RoMaD ⓘ
4.74
Longest DD Days ⓘ
14
Sharpe ⓘ
0.79
Sortino ⓘ
1.36
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.59%3.59%
Time in Market68.0%57.0%
Total Return1%2%
CAGR% (Annual Return)8.62%39.01%
Sharpe0.40.79
RoMaD3.354.74
Corr to Benchmark1.00.03
Prob. Sharpe Ratio49.82%51.8%
Smart Sharpe0.350.68
Sortino0.61.36
Smart Sortino0.521.18
Sortino/√20.420.96
Smart Sortino/√20.370.84
Omega1.071.18
Max Drawdown-2.57%-8.23%
Longest DD Days1614
Volatility (ann.)13.09%51.31%
R^20.00.0
Information Ratio0.040.04
Calmar3.354.74
Skew0.281.42
Kurtosis2.447.97
Expected Daily%0.02%0.09%
Expected Monthly%0.27%1.09%
Expected Yearly%0.54%2.19%
Daily Value-at-Risk-1.1%-4.3%
Expected Shortfall (cVaR)-1.4%-6.52%
MTD-1.55%-6.95%
3M0.54%2.19%
6M0.54%2.19%
YTD0.54%2.19%
1Y0.54%2.19%
3Y (ann.)8.62%39.01%
5Y (ann.)8.62%39.01%
10Y (ann.)8.62%39.01%
All-time (ann.)8.62%39.01%
Best Day1.92%9.82%
Worst Day-1.54%-6.52%
Best Month2.12%9.82%
Worst 1-Month Return-1.55%-6.95%
Best Year0.54%2.19%
Worst Year0.54%2.19%
Avg. Drawdown-2.57%-4.67%
Avg. Drawdown Days168
Recovery Factor0.230.37
Ulcer Index0.010.03
Serenity Index-1.08-0.07
Annualized Return on Risk Capital309.45%388.26%
Worst 3-Month Return--
Time to Recovery (Days)71
5th Percentile Tail Loss-1.17%-2.99%
Time Underwater (Days)1615
Percent Positive Months50.050.0
Avg. Up Month2.12%9.82%
Avg. Down Month-1.55%-6.95%
Win Days11.7612.5
Loss Days13.2412.5
Win Days%47.06%50.0%
Win Month%50.0%50.0%
Win Quarter%100.0%100.0%
Win Year%100.0%100.0%
Beta-0.12
Alpha-0.43
Correlation-3.17%
Treynor Ratio--11.32%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
20260.542.194.02+
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-302026-02-12-8.2314
2026-01-272026-01-27-1.111
2026-09-29T21:29:24.205331
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.263634
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.319496
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.399146
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.539701
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.683393
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.803787
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:24.914010
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:25.035303
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:25.195583
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:25.364648
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:25.501764
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T21:29:25.782008
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
last_namePelosi
agent_max_model_calls120
agent_researcher_modelopenai/gpt-6-luna
agent_trader_modelopenai/gpt-6-luna
agent_model_calls36
agent_researcher_calls18
agent_researcher_cache_hits0
agent_researcher_tool_calls73
agent_researcher_input_tokens1368396
agent_researcher_output_tokens41715
agent_researcher_total_tokens1410111
agent_researcher_thinking_tokens34163
agent_researcher_cached_input_tokens1214368
agent_researcher_cache_write_input_tokens0
agent_researcher_uncached_input_tokens154028
agent_researcher_tool_use_input_tokens0
agent_researcher_latency_ms_total599552
agent_researcher_latency_ms_avg33308.44
agent_researcher_first_event_latency_ms_avg3797.28
agent_researcher_detail_parquetlogs/pelosi-2agent_2026-09-29_21-10_6B8PIT_agent_detail.parquet
agent_trader_calls18
agent_trader_cache_hits0
agent_trader_tool_calls170
agent_trader_input_tokens1952863
agent_trader_output_tokens35472
agent_trader_total_tokens1988335
agent_trader_thinking_tokens25597
agent_trader_cached_input_tokens1806634
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens146229
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total537351
agent_trader_latency_ms_avg29852.83
agent_trader_first_event_latency_ms_avg4179.56
agent_trader_detail_parquetlogs/pelosi-2agent_2026-09-29_21-10_6B8PIT_agent_detail.parquet
BACKTESTING_DATA_SOURCEyahooShown 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.