Expanding Walk-Forward
Validation workflow · Equity ETFs · Daily
The rules, in plain English
Expanding walk-forward works like the rolling version, except the training window keeps growing from the start of the data while the test window slides forward. That gives later folds more history to learn from. The published example runs 48 folds; it is a validation workflow, not a portfolio backtest.
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 folds, expanding training window against a sliding test window (slice diagnostics).
Get all 50 in the workbook
Every strategy, its rules, metrics, and verdict — losers included — in one spreadsheet you can sort, filter, and study offline.
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.