Scorecard — naive_momentum_20

This project is a research and evaluation tool. It is not financial, investment, or trading advice. It does not execute trades or connect to brokerages. It exists to help researchers and practitioners rigorously measure how trading-agent frameworks actually perform — including, and especially, when they perform badly. Backtest results are not predictive of live performance. You are responsible for any decisions you make.

Run

Universe: bundled_synthetic (3 tickers)
Window: 2020-01-06 → 2024-12-31 (1259 trading days)
Cost model: constant_bps_5
Annualization: 252
Generated: 2026-05-15T09:25:25.239102+00:00

Net-of-cost performance

Metric	Value
Net total return	+13.0526%
Net annualized return	+2.4860%
Sharpe (annualized)	+0.333
Sharpe 95% CI (annualized) — HAC q=7, η=0.97	[-0.530, +1.196]
PSR (vs SR=0)	0.7719
Sortino (annualized, MAR=0)	+0.490
Information Ratio (vs buy-and-hold, ann.)	-0.854

Drawdown

Metric	Value
Max drawdown	-12.5898%
Longest underwater stretch	398 trading days
Calmar ratio	+0.197

Charts

Per-ticker breakdown

Ticker	Decisions	Non-FLAT	Hit rate	Mean contribution	Sharpe (ann.)
SYN-A	1259	640	0.500	-0.0000%	-0.002
SYN-B	1259	676	0.496	+0.0084%	+0.411
SYN-C	1259	690	0.491	+0.0078%	+0.403

Baselines (same window, same cost model)

Baseline	Net total return	Sharpe (ann.)
buy_and_hold	+55.6254%	+0.829
naive_momentum_20	+13.0526%	+0.333
random	-51.1864%	-1.425

Calibration

Not evaluable: the adapter did not emit a confidence. We do not fabricate a probability where the framework provided none.

Flags

No flags raised.

agent-backtest-lab is a research tool. Not financial advice. Not a trading system. Backtests don't predict the future.

Built by Betty Guo (Dongxin Guo / 郭东欣), PhD candidate, University of Hong Kong, advised by Prof. Siu-Ming Yiu. ORCID: 0009-0000-2388-1072. Apache-2.0.