HK IPO AI metric guide
How to read model, backtest, allotment prediction and scenario metrics shown across HK IPO AI.
P90 relative error
P90 relative error means about 90% of historical backtest samples had error at or below this level.
Read explainerWeighted relative error
Weighted relative error gives more importance to application tiers or samples that matter more for allocation decisions.
Read explainerExpected lots
Expected lots is the model-estimated average allocation. It is not a guaranteed number of lots.
Read explainerReference rating
The reference rating is an informational rating generated from public data, historical samples and stage-specific market signals.
Read explainerBacktest hit rate
Backtest hit rate is the share of historical samples where the model's direction call matched the actual result.
Read explainerTop2 coverage
Top2 coverage checks whether the actual outcome lands in the model's two most likely scenarios.
Read explainerSample weight
Sample weight is the relative influence a historical IPO has in backtest statistics.
Read explainerGrey market anchor
Grey market anchor uses pre-listing grey market performance as one short-term input for first-day judgment.
Read explainerData coverage
Data coverage describes whether key fields and model inputs are available for the current IPO stage.
Read explainer