Fear and Greed Bot Backtest: Short Sample and Risk Metrics
Document Lumibot
Summary
The document presents a QuantStats tear sheet for a strategy named fear-greed-plain-v2, compared with SPY over a brief January 2026 test period. It reports returns, drawdowns, risk-adjusted metrics, benchmark correlation, time in the market, and daily gains and losses. The strategy’s stated name suggests a fear-and-greed signal, but no entry, exit, or position-sizing rules are explained, so the trading method cannot be reconstructed from this report.
The reported strategy total return is zero, with annualized return of 1.52%, maximum drawdown of -0.57%, negative Sharpe and Sortino ratios, and -0.42 correlation to SPY. The report also gives lower volatility and smaller reported tail losses than the benchmark over this sample. These figures describe only the stated short test window; annualized and multi-year figures shown in the tear sheet do not represent independent long-term observations. The document supplies no trades, signal definitions, transaction costs, or out-of-sample evidence, and explicitly cautions that past performance does not predict future results.
Key ideas
- The tear sheet compares a named fear-and-greed strategy with SPY over a short January 2026 period.
- The report lists risk and return measures, including drawdown, volatility, Sharpe ratio, and benchmark correlation.
- The strategy's entry and exit rules are not provided, so the signal cannot be evaluated or reproduced from this document.
- Annualized and multi-year statistics extrapolated from this brief sample offer little evidence of durable performance.
Tags
Full text
# fear and greed index trading bot
Tearsheet (generated by QuantStats)
fear-greed-plain-v2 Compared to SPY 4 Jan, 2026 - 22 Jan, 2026
Benchmark is SPY | LumiBot 4.6.3 | DataSource yahoo | Backtest time 8:16 | Generated by QuantStats (Lumiwealth Version) (v.1.1.5)
Annual Return ⓘ
1.52%
Total Return ⓘ
0%
Max Drawdown ⓘ
-0.57%
RoMaD ⓘ
2.68
Longest DD Days ⓘ
8
Sharpe ⓘ
-0.68
Sortino ⓘ
-0.91
Key Performance Metrics
MetricSPYStrategy
Risk-Free Rate3.58%3.58%
Time in Market64.0%69.0%
Total Return0%0%
CAGR% (Annual Return)3.78%1.52%
Sharpe0.06-0.68
RoMaD1.52.68
Corr to Benchmark1.0-0.42
Prob. Sharpe Ratio47.1%48.28%
Smart Sharpe0.05-0.65
Sortino0.07-0.91
Smart Sortino0.07-0.87
Sortino/√20.05-0.65
Smart Sortino/√20.05-0.61
Omega1.010.9
Max Drawdown-2.53%-0.57%
Longest DD Days108
Volatility (ann.)11.94%3.0%
R^20.180.18
Information Ratio-0.01-0.01
Calmar1.52.68
Skew-1.69-0.5
Kurtosis6.460.84
Expected Daily%0.01%0.0%
Expected Monthly%0.18%0.07%
Expected Yearly%0.18%0.07%
Daily Value-at-Risk-1.02%-0.25%
Expected Shortfall (cVaR)-2.04%-0.37%
MTD0.18%0.07%
3M0.18%0.07%
6M0.18%0.07%
YTD0.18%0.07%
1Y0.18%0.07%
3Y (ann.)3.78%1.52%
5Y (ann.)3.78%1.52%
10Y (ann.)3.78%1.52%
All-time (ann.)3.78%1.52%
Best Day1.15%0.31%
Worst Day-2.04%-0.37%
Best Month0.18%0.07%
Worst 1-Month Return0.18%0.07%
Best Year0.18%0.07%
Worst Year0.18%0.07%
Avg. Drawdown-1.43%-0.29%
Avg. Drawdown Days64
Recovery Factor0.090.13
Ulcer Index0.010.0
Serenity Index-1.06-5.45
Annualized Return on Risk Capital139.18%251.45%
Worst 3-Month Return--
Time to Recovery (Days)20
5th Percentile Tail Loss-0.65%-0.25%
Time Underwater (Days)1213
Percent Positive Months100.0100.0
Avg. Up Month0.18%0.07%
Avg. Down Month--
Win Days9.510.23
Loss Days9.58.77
Win Days%50.0%53.85%
Win Month%100.0%100.0%
Win Quarter%100.0%100.0%
Win Year%100.0%100.0%
Beta--0.11
Alpha-0.02
Correlation--42.08%
Treynor Ratio-33.19%
EOY Returns vs Benchmark
YearSPYStrategyMultiplierWon
20260.180.070.40-
Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2026-01-152026-01-22-0.578
2026-01-092026-01-12-0.244
2026-01-052026-01-05-0.061
2026-09-29T23:28:05.026387
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.073313
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.116660
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.172635
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.324893
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.373323
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.425264
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.477317
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.528352
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.576954
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.620941
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.673654
image/svg+xml
Matplotlib v3.10.9, https://matplotlib.org/
2026-09-29T23:28:05.724389
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_calls46
agent_researcher_input_tokens973883
agent_researcher_output_tokens13122
agent_researcher_total_tokens987005
agent_researcher_thinking_tokens9855
agent_researcher_cached_input_tokens894419
agent_researcher_cache_write_input_tokens0
agent_researcher_uncached_input_tokens79464
agent_researcher_tool_use_input_tokens0
agent_researcher_latency_ms_total219971
agent_researcher_latency_ms_avg16920.85
agent_researcher_first_event_latency_ms_avg3873.92
agent_researcher_detail_parquetlogs/fear-greed-plain-v2_2026-09-29_23-19_dvQHWq_agent_detail.parquet
agent_trader_calls13
agent_trader_cache_hits0
agent_trader_tool_calls117
agent_trader_input_tokens1175040
agent_trader_output_tokens16906
agent_trader_total_tokens1191946
agent_trader_thinking_tokens10162
agent_trader_cached_input_tokens1083673
agent_trader_cache_write_input_tokens0
agent_trader_uncached_input_tokens91367
agent_trader_tool_use_input_tokens0
agent_trader_latency_ms_total274966
agent_trader_latency_ms_avg21151.23
agent_trader_first_event_latency_ms_avg3811.54
agent_trader_detail_parquetlogs/fear-greed-plain-v2_2026-09-29_23-19_dvQHWq_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.