Rolling Walk-Forward
Validation workflow · Equity ETFs · Daily
The rules, in plain English
This is not a trading strategy; it is a way of checking one honestly. Rolling walk-forward testing trains on a fixed-length window of history, tests on the next slice, then rolls both windows forward — 48 folds in the published example, with a purge gap before each test slice. We show it as a workflow example, with no portfolio backtest published.
The published backtest
| Total return | — |
|---|---|
| CAGR (annual growth rate) | — |
| Sharpe ratio | — |
| Maximum drawdown (worst peak-to-trough fall) | — |
| Win rate | — |
| Profit factor | — |
| Risk grade (our shorthand, from the published figures) | Not graded |
| Asset class | Equity ETFs |
| Style | Validation workflow |
| Timeframe | Daily |
| Type | Walk-forward |
— means no figure was published for this strategy. Ungraded and workflow entries publish diagnostics rather than a graded portfolio backtest, so some metrics are not published for them.
Honest verdict
Workflow example — no portfolio backtest published
This is a workflow example, not a portfolio strategy, so there is no return to judge. Its value is in how it tests other strategies — treat it as a method for avoiding self-deception, not as a way to make money by itself.
Walk-forward note
48 rolling train/test folds with a pre-OOS purge gap (slice diagnostics, not independent out-of-sample evidence).
Get all 50 in the workbook
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Attribution: strategy and published backtest results from the QuantJourney open-source library (Apache-2.0), via quants.md — published backtest results by QuantJourney, reproduced with attribution. Results are hypothetical backtest results based on historical data; they are not live trading results and do not guarantee future performance. Educational content only — not financial advice, and not a recommendation to buy, sell, or hold any security.