HKUDS/Vibe-Trading · error · ValueError

No common dates and assets between factor_panel and forward_

Error message

No common dates and assets between factor_panel and forward_returns

What it means

IC analysis correlates factor values with forward returns per date per shared asset set; if the intersection of dates or of column (asset) labels is empty, no correlation is computable.

Source

Thrown at agent/src/quantlib/factormodel.py:785

    Returns:
        :class:`FactorICResult` containing mean IC, IC IR, t-statistic, p-value,
        higher moments, and full IC time series.

    Raises:
        ValueError: If inputs are empty, share no common dates or assets, or method is unknown.
    """
    if method not in ("spearman", "pearson"):
        raise ValueError(f"method must be 'spearman' or 'pearson', got {method!r}")

    if factor_panel.empty or forward_returns.empty:
        raise ValueError("factor_panel and forward_returns must be non-empty")

    # Align dates and assets
    common_dates = factor_panel.index.intersection(forward_returns.index)
    common_assets = factor_panel.columns.intersection(forward_returns.columns)

    if common_dates.empty or common_assets.empty:
        raise ValueError("No common dates and assets between factor_panel and forward_returns")

    f_sub = factor_panel.loc[common_dates, common_assets]
    r_sub = forward_returns.loc[common_dates, common_assets]

    ic_records: dict[object, float] = {}

    for date in common_dates:
        f_row = f_sub.loc[date].dropna()
        r_row = r_sub.loc[date].dropna()
        shared = f_row.index.intersection(r_row.index)
        if len(shared) < min_cross_section:
            continue

        f_vals = f_row.loc[shared].to_numpy(dtype=float)
        r_vals = r_row.loc[shared].to_numpy(dtype=float)

        if method == "spearman":
            f_vals = rankdata(f_vals)

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Compare the index/column dtypes and values of both frames
2. Normalize dates with pd.to_datetime on both indexes
3. Map asset identifiers to a common scheme before the call

Example fix

# before
ic = factor_ic_analysis(panel, rets)
# after
rets.index = pd.to_datetime(rets.index)
rets = rets.rename(columns=id_map)
ic = factor_ic_analysis(panel, rets)

assert (factor_panel.index.intersection(forward_returns.index).size > 0
        and factor_panel.columns.intersection(forward_returns.columns).size > 0)

When it happens

Trigger: Panel dates are DatetimeIndex(2024-01) while returns use Timestamps, or asset tickers differ ('AAPL' vs 'AAPL_EQ').

Common situations: Date dtype mismatch (date vs datetime vs string) between data sources; one feed uses FIGI/ISIN while the other uses tickers.

Related errors

• portfolio_exposures and factor_returns share no factor; expo
• No matching assets between weights ({sorted(w_series.index)}
• No matching factors between exposures ({sorted(X.columns)})
• method must be 'spearman' or 'pearson', got {method!r}
• factor_panel and forward_returns must be non-empty

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/313cd3d43398d0e1. Report an issue: GitHub.