@qtsurfer/api-client
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    Type Alias WalkForwardFold

    What one fold concluded. The out-of-sample row is the answer; the in-sample figure is only there to be compared against it, since any grid produces a flattering in-sample winner — that is what optimizing does. The gap between them is the whole reading.

    type WalkForwardFold = {
        foldIx: number;
        inSampleFrom: number;
        inSampleSharpe: number;
        inSampleTo: number;
        outOfSample: SweepRunRow;
        outOfSampleTo: number;
        params: { [key: string]: unknown };
        vectorsRun: number;
    }
    Index
    foldIx: number

    Position in the walk-forward sequence, oldest first.

    inSampleFrom: number

    First index of the optimization window, into the prepared session.

    inSampleSharpe: number

    How that winner scored on the window it was chosen on.

    inSampleTo: number

    End of the optimization window, exclusive — and where scoring begins.

    outOfSample: SweepRunRow
    outOfSampleTo: number

    End of the scoring window, exclusive.

    params: { [key: string]: unknown }

    The parameter vector that won this fold's optimization window.

    vectorsRun: number

    Vectors this fold evaluated in-sample before picking its winner.