[{"data":1,"prerenderedAt":31},["ShallowReactive",2],{"strategy-wf01":3},{"id":4,"name":5,"family":6,"tags":7,"universe":9,"bars":10,"rules":11,"sizing":12,"cadence":12,"original":13,"testable":14,"not_testable_reason":15,"prompt":16,"deviation":13,"source_file":17,"prompt_note":18,"collection":19,"collection_name":20,"bars_label":21,"universe_short":22,"rule_short":11,"links":23,"verdict":30,"result":13,"chart":13},"WF01","Rolling Walk-Forward Validation","Validation workflow",[8],"Walk-forward","XLB, XLE, XLF, XLI, XLK, XLP, XLU, XLV and XLY","daily","Re-checks the SMA(50/200) sector rule (W01) on sliding train/test windows.","-",null,false,"A validation workflow around W01's rule rather than a strategy of its own. Orbital covers part of the same ground for every strategy: its Backtesting list discounts the Sharpe for every configuration tried, and each report resamples the trades 1,000 times.","Trade the sector ETFs XLB, XLE, XLF, XLI, XLK, XLP, XLU, XLV and XLY on daily bars. Buy an ETF with 11% of equity when its 50-day SMA is above its 200-day SMA, and sell it when the 50-day falls below the 200-day. Long only; uninvested capital stays in cash. Then check it with a rolling walk-forward, keeping the rule the same in every window: three training windows of about four years that slide forward two years at a time, each ending three weeks before the two-year test window that follows it. Backtest each window separately with $100,000: training 2016-11-21 to 2020-10-09 and test 2020-11-02 to 2022-10-28; training 2018-10-31 to 2022-10-07 and test 2022-10-31 to 2024-10-30; training 2020-11-02 to 2024-10-09 and test 2024-10-31 to 2026-10-30. That is six backtests. When all six have finished, compare them in one table with annual return, Sharpe and maximum drawdown, and say whether each test window kept up with its training window and whether the test Sharpe fell from one window to the next.","example_wf_01_rolling_walkforward.py","Closest Orbital version: Orbital has no walk-forward tool, so each window is its own backtest, starting from cash, of this library's version of W01 (a fixed 11% of equity per ETF), and four-year training windows with two-year tests make six backtests where the original's 24-month and 6-month windows would need more than 30. The three-week gap is the original's purge of 5 trading days plus 1% of the training window, and nothing is fitted, as in the original's default mode, so each window only asks whether the fixed rule kept working.","retest","The viral 50, re-tested","Daily","9 sector ETFs",[24,27],[25,26],"Source code","https://github.com/QuantJourneyOrg/quantjourney-bt/blob/main/strategies/example_wf_01_rolling_walkforward.py",[28,29],"Original results","https://backtester.quantjourney.cloud/strategies/example-wf-01-rolling-walkforward","skip",1794261303665]