microsoft/qlib · error · ValueError

method {method} is not supported!

Error message

method {method} is not supported!

What it means

Raised in qlib/backtest/report.py by the fulfillment-rate (FFR) metric calculator. The method argument controls how per-order FFR values are combined and only supports 'mean' (simple average), 'amount_weighted' (weighted by absolute deal amount), and 'value_weighted' (weighted by absolute trade value). Any other method string raises ValueError.

Source

Thrown at qlib/backtest/report.py:568

        pa_config = indicator_config.get("pa_config", {})
        self._agg_base_price(inner_order_indicators, decision_list, trade_exchange, pa_config=pa_config)  # TODO
        self._agg_order_price_advantage()

    def _cal_trade_fulfill_rate(self, method: str = "mean") -> Optional[BaseSingleMetric]:
        if method == "mean":
            return self.order_indicator.transfer(
                lambda ffr: ffr.mean(),
            )
        elif method == "amount_weighted":
            return self.order_indicator.transfer(
                lambda ffr, deal_amount: (ffr * deal_amount.abs()).sum() / (deal_amount.abs().sum()),
            )
        elif method == "value_weighted":
            return self.order_indicator.transfer(
                lambda ffr, trade_value: (ffr * trade_value.abs()).sum() / (trade_value.abs().sum()),
            )
        else:
            raise ValueError(f"method {method} is not supported!")

    def _cal_trade_price_advantage(self, method: str = "mean") -> Optional[BaseSingleMetric]:
        if method == "mean":
            return self.order_indicator.transfer(lambda pa: pa.mean())
        elif method == "amount_weighted":
            return self.order_indicator.transfer(
                lambda pa, deal_amount: (pa * deal_amount.abs()).sum() / (deal_amount.abs().sum()),
            )
        elif method == "value_weighted":
            return self.order_indicator.transfer(
                lambda pa, trade_value: (pa * trade_value.abs()).sum() / (trade_value.abs().sum()),
            )
        else:
            raise ValueError(f"method {method} is not supported!")

    def _cal_trade_positive_rate(self) -> Optional[BaseSingleMetric]:
        def func(pa):
            return (pa > 0).sum() / pa.count()

View on GitHub (pinned to 79633dd950)

Solutions

1. Use one of the three supported methods: 'mean', 'amount_weighted', or 'value_weighted'.
2. If a custom aggregation is required, subclass the indicator calculator and override _cal_ffr instead of passing a new method string.
3. Verify the exact spelling in the workflow YAML — matching is exact and case-sensitive.

Example fix

# before
indicator_config = {'ffr': {'method': 'median'}}
# after
indicator_config = {'ffr': {'method': 'mean'}}  # or 'amount_weighted' / 'value_weighted'

SUPPORTED = {'mean', 'amount_weighted', 'value_weighted'}
if method not in SUPPORTED:
    raise ValueError(f'method must be one of {sorted(SUPPORTED)}')
# only then build the indicator config

def is_ffr_method(m: str) -> bool:
    return m in {'mean', 'amount_weighted', 'value_weighted'}

try:
    ffr = calc._cal_ffr(method)
except ValueError:
    ffr = calc._cal_ffr('mean')  # explicit safe default, log a warning

When it happens

Trigger: Passing method to the FFR indicator via the report config, e.g. {'ffr': {'method': 'median'}}, or calling the internal _cal_ffr(method=...) with an unsupported string.

Common situations: Users extend portfolio analysis workflows and try to add a new weighting (e.g. 'share_weighted' or 'median') through config alone without subclassing the indicator calculator; or they typo 'amount_weighted' as 'amountweighted'.

Related errors

• This type of input {rtype} is not supported
• file "{}" does not exist
• Only py/yml/yaml/json type are supported now!
• trade_calendar is necessary for getting TradeRangeByTime.
• The decision didn't provide an index range

AI-assisted analysis of microsoft/qlib@79633dd950 (2026-08-15). Data as JSON: /api/errors/4a3f9f0f740ac340. Report an issue: GitHub.