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Strategy: ma_crossover_50_200

1 variant(s) documented · earliest 2026-09-11 · latest 2026-09-11.

Variant Generated Registered Verdict
fast=50, slow=200 2026-09-11T16:38:20+00:00 ✓ PASS

Variant 1

Generated: 2026-09-11T16:38:20+00:00
Source report: 20260911_163820_ma_crossover_50_200.md
Registered: ✓ — 2026-09-11T16:38:20+00:00 (walk_forward_passed=True)

PASS

ma_crossover_50_200 variant 1 return and Sharpe comparison

Experiment

  • Period: 2015-01-02 to 2026-08-14 (2921 sessions)
  • Execution rule: close-derived weights are applied one session later
  • Transaction costs: 5.00 bps per unit of turnover
  • Cash return: 0%; taxes, slippage and market impact: not modeled
  • Parameters: fast=50, slow=200

Data provenance

  • Source: market-data-hub (adj_close; live rows included: False)
  • Requested symbols: SPY, QQQ
  • Validated common panel: 2015-01-02 to 2026-08-14; 2921 rows
  • Database: C:\Users\Administrator\Documents\GitHub\market-data-hub\market_data.duckdb
Symbol Last date Status Coverage score Stalled
QQQ 2026-08-14 00:00:00 ok 97.31 False
SPY 2026-08-14 00:00:00 ok 97.33 False

Research rationale

A slow trend filter may reduce severe drawdowns, but after costs it need not beat passive exposure.

For each ETF, hold it when its 50-day moving average is above its 200-day average; equal-weight active ETFs; otherwise cash.

Sources:

Known risks:

  • whipsaw and repeated transaction costs in sideways markets
  • parameter/data-mining sensitivity
  • cash return is modeled as zero in the MVP
  • one historical sample is not evidence of future profitability

Net backtest metrics

Metric Strategy Benchmark
Cumulative return 318.82% 500.62%
CAGR 13.15% 16.73%
Annualized volatility 16.74% 19.44%
Annualized Sharpe (rf=0) 0.82 0.89
Maximum drawdown -30.86% -30.86%
Annualized turnover 189.80% 8.63%
Transaction-cost drag (sum of daily rates) 1.10% 0.05%

Walk-forward / out-of-sample validation

Parameters were frozen before the chronological split. Each window is non-overlapping and backtested independently.

Window Role Period Sessions Return CAGR Volatility Sharpe Max drawdown Benchmark return Benchmark Sharpe Return delta Sharpe delta
development development 2015-01-02 to 2021-12-15 1752 144.26% 13.71% 17.40% 0.83 -30.86% 227.51% 1.00 -83.25% -0.17
oos_1 out_of_sample 2021-12-16 to 2026-08-14 1169 90.74% 14.94% 14.65% 1.02 -20.78% 86.52% 0.77 4.22% 0.26

Pass criterion: in every OOS window, strategy cumulative return and annualized Sharpe must each be at least the corresponding benchmark value.

Walk-forward verdict: PASS: coherent between development and OOS; the frozen strategy matches or beats the benchmark on return and Sharpe in every OOS window.

Giudizio / conclusion

Full-sample comparison: FAIL on this sample: lower net return and Sharpe than the benchmark.

Final validation judgment: PASS: coherent between development and OOS; the frozen strategy matches or beats the benchmark on return and Sharpe in every OOS window.

This remains historical research, not evidence of tradability or a recommendation. Promotion still requires parameter-robustness and multiple-testing checks plus a live paper period.

Ecosystem review

  • LazyFin: Do not recreate hierarchical portfolio optimization in LazyAlpha; the line was moved/retired from LazyFin and belongs to LazyPortfolio. (C:\Users\Administrator\Documents\GitHub\LazyFin\docs\status.md)
  • investmentcommittee: Keep B0/P0/Sa/PH/PF as methodological reference: same data, folds, costs and rebalance rules for honest comparisons; do not clone it 1:1. (C:\Users\Administrator\Documents\GitHub\investment-process-top-down-etf.md)