Momentum and News Trading Bot: Short Backtest Results Versus SPY
Summary
This report presents a short backtest of a strategy labeled “momentum-news-generic” against SPY, using Yahoo data. Over the stated period, the strategy had a slightly negative total return, negative annualized return, negative Sharpe and Sortino ratios, and a larger maximum drawdown than SPY. Its reported time in the market was higher than the benchmark’s, while its correlation with SPY was low. These figures offer a limited example of how a performance tear sheet compares return, risk, market exposure, and benchmark relationship.
The report gives no description of the bot’s signals, news source, momentum rules, portfolio construction, or execution assumptions, so its method cannot be evaluated or reproduced from this document. The test spans only a short period in January 2026, making annualized and multi-year figures especially unrepresentative. No inference about durable performance is warranted; the report itself also states that past performance does not predict future results.
Key ideas
- The tear sheet compares a strategy labeled momentum-news-generic with SPY.
- Reported strategy returns and risk-adjusted performance were negative over the stated test period.
- The strategy had a larger maximum drawdown and higher market exposure than the benchmark.
- The document does not explain the strategy's signals, news inputs, or execution rules.
- The brief test period limits what can be inferred from annualized and multi-year statistics.
Tags
Full text
# momentum and news ai trading bot
Tearsheet (generated by QuantStats)
momentum-news-generic Compared to SPY 4 Jan, 2026 - 15 Jan, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource yahoo | Backtest time 11:40 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
-14.98%
Total Return ⓘ
-0%
Max Drawdown ⓘ
-1.75%
RoMaD ⓘ
-8.54
Longest DD Days ⓘ
7
Sharpe ⓘ
-1.17
Sortino ⓘ
-1.71
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.56%3.56%
Time in Market67.0%75.0%
Total Return1%-0%
CAGR% (Annual Return)24.3%-14.98%
Sharpe2.59-1.17
RoMaD35.19-8.54
Corr to Benchmark1.00.16
Prob. Sharpe Ratio67.18%39.04%
Smart Sharpe1.59-0.72
Sortino4.73-1.71
Smart Sortino2.9-1.05
Sortino/√23.35-1.21
Smart Sortino/√22.05-0.74
Omega1.50.76
Max Drawdown-0.69%-1.75%
Longest DD Days37
Volatility (ann.)6.41%14.8%
R^20.030.03
Information Ratio-0.12-0.12
Calmar35.19-8.54
Skew0.450.28
Kurtosis0.144.91
Expected Daily%0.05%-0.04%
Expected Monthly%0.66%-0.49%
Expected Yearly%0.66%-0.49%
Daily Value-at-Risk-0.5%-1.31%
Expected Shortfall (cVaR)-0.5%-1.75%
MTD0.66%-0.49%
3M0.66%-0.49%
6M0.66%-0.49%
YTD0.66%-0.49%
1Y0.66%-0.49%
3Y (ann.)24.3%-14.98%
5Y (ann.)24.3%-14.98%
10Y (ann.)24.3%-14.98%
All-time (ann.)24.3%-14.98%
Best Day0.66%1.81%
Worst Day-0.49%-1.75%
Best Month0.66%-0.49%
Worst 1-Month Return0.66%-0.49%
Best Year0.66%-0.49%
Worst Year0.66%-0.49%
Avg. Drawdown-0.51%-1.15%
Avg. Drawdown Days25
Recovery Factor0.960.26
Ulcer Index0.00.01
Serenity Index-4.9-2.87
Annualized Return on Risk Capital2,895.24%-845.65%
Worst 3-Month Return--
Time to Recovery (Days)10
5th Percentile Tail Loss-0.4%-1.07%
Time Underwater (Days)510
Percent Positive Months100.00.0
Avg. Up Month--
Avg. Down Month--
Win Days6.06.67
Loss Days6.05.33
Win Days%50.0%55.56%
Win Month%100.0%0.0%
Win Quarter%100.0%0.0%
Win Year%100.0%0.0%
Beta-0.38
Alpha--0.21
Correlation-16.44%
Treynor Ratio--10.66%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
20260.66-0.49-0.74-
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-052026-01-07-1.753
2026-01-092026-01-15-0.547
2026-09-29T23:26:46.328747
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.370708
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.515607
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.571978
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.616299
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.662053
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.714836
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.766609
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.816153
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.861574
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.900416
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:46.952636
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:26:47.004224
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
agent_max_model_calls40
agent_trader_modelopenai/gpt-6-luna
agent_model_calls9
agent_trader_calls9
agent_trader_cache_hits0
agent_trader_tool_calls131
agent_trader_input_tokens1537597
agent_trader_output_tokens86699
agent_trader_total_tokens1624296
agent_trader_thinking_tokens12115
agent_trader_cached_input_tokens1429777
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens107820
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total699690
agent_trader_latency_ms_avg77743.33
agent_trader_first_event_latency_ms_avg2588.22
agent_trader_detail_parquetlogs/momentum-news-generic_2026-09-29_23-15_QgGFGC_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.