Capital deployment: 2 Backtests
We backtested 2 capital deployment strategies across ETFs. 0 beat the benchmark before correction; best −4.6 pts/yr.
Every result below is the strategy's annualized return minus an equal-weight benchmark, rebalanced daily, on the same assets and days. Strategies are charged real trading costs; the benchmark pays none. Data stops at the discovery cutoff. See the full family index, the full method and every result, or download the raw registry (JSON).
0 of 2 strategies finished ahead of the benchmark on the raw number, and 0 had an unadjusted p-value under 0.05. After one correction across all 688 tests in the registry, 0 passed, so no result here is a confirmed edge. Scored 2026-10-03, using data up to 2025-03-15. Method: see the evidence page.
How to read these results
"Ahead" means a higher return than the benchmark in this historical test, and "behind" means a lower one. Neither is a confirmed edge. A strategy is only counted as working if it survives a correction for how many strategies were tried, because testing hundreds of ideas will throw up some lucky winners by chance. Capital deployment is grouped by the signal it trades on, not by the asset it was tested on, and every strategy here saw only data up to the same cutoff date, so none could see data another could not.
Results
- Does waiting briefly for dips improve dollar-cost averaging? (ETFs): behind the benchmark by 4.6 percentage points a year. Not statistically significant. Source: retail trading content: dollar cost averaging dip deadline finite reserve investment timing.
- Does value averaging without new deposits improve ETF deployment? (ETFs): behind the benchmark by 5.4 percentage points a year. Not statistically significant. Source: retail trading content: Michael Edleson value averaging finite reserve no external deposits.