HKUDS/Vibe-Trading · error · ValueError

as_of is required for an empty series

Error message

as_of is required for an empty series

What it means

When as_of is omitted, preferred_return_amount measures at the latest flow date, which is impossible for an empty series, so an explicit as_of is mandatory in that case.

Solutions

1. Pass an explicit as_of date, e.g. as_of="2024-12-31"
2. Skip empty series in batch jobs before calling

Example fix

# before
preferred_return_amount(empty_series, rate=0.08)

# after
preferred_return_amount(empty_series, rate=0.08, as_of="2024-12-31")

if series.is_empty and as_of is None:
    as_of = period_end_date  # supply explicit measurement date

When it happens

Trigger: Calling preferred_return_amount on an empty CashFlowSeries with as_of=None (the default).

Common situations: Running the calculation over a batch of funds where some have no contributions yet; filters that removed all flows before the call.

Understand the failure class

Background: "missing required argument" and "the following required arguments were not provided": what required-argument errors mean and how to fix them — this error's family across 20 libraries.

Related errors

• compounding= is not one of
• contribution on is after as_of= ; a preferred return cannot…
• preferred rate must be non-negative, got
• carry_rate must be in
• catch_up_rate= must exceed carry_rate= , otherwise the…

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/6b37b42610e2f5b1. Report an issue: GitHub.

Appendix: source

Thrown at agent/src/quantlib/fundmath.py:975

            for an empty series.
    """
    _require_series(series)
    if rate < 0.0:
        raise ValueError(f"preferred rate must be non-negative, got {rate!r}")
    if compounding not in PREFERRED_COMPOUNDING:
        raise ValueError(
            f"compounding={compounding!r} is not one of {PREFERRED_COMPOUNDING}"
        )
    if days_per_year <= 0:
        raise ValueError(f"days_per_year must be positive, got {days_per_year!r}")

    contributions = tuple(series.filter(kind=contribution_kinds))
    if not contributions:
        return 0.0

    if as_of is None:
        if series.is_empty:
            raise ValueError("as_of is required for an empty series")
        measurement = max(series.dates())
    else:
        measurement = normalize_date(as_of, field_name="as_of")

    total = 0.0
    for flow in contributions:
        years = (measurement - flow.date).days / days_per_year
        if years < 0.0:
            raise ValueError(
                f"contribution on {flow.date} is after as_of={measurement}; a "
                "preferred return cannot accrue backwards"
            )
        principal = -flow.amount
        if compounding == "compound":
            total += principal * ((1.0 + rate) ** years - 1.0)
        else:
            total += principal * rate * years
    return total

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