volkit.datasets

This module contains sample datasets

volkit.datasets.spxw(min_volume=0, D=None, *, full=False)

Load a sample SPXW options slice and apply simple filters.

Parameters:

• min_volume (int, default 0) – Minimum per-option trade volume required for both the call and the put at a given strike. Rows are kept only if C_vol >= min_volume and P_vol >= min_volume. Use 0 to disable the volume filter.

• D (int or None, default None) – If provided, keep only rows whose computed calendar days-to-expiry equals this value. For example, D=7 keeps only the 7-calendar-day slice. Use None to keep all expiries.

• full (bool, default False) –

  Select between a compact, most-relevant schema (False) and a full schema (True).

  When full=False (default), return:

  • ["K", "D", "T"] — strike and days/time to expiry

  • ["F_bid", "F_ask"] — underlying future quotes

  • ["C_bid", "C_ask", "P_bid", "P_ask"] — call/put quotes

  • ["C_vol", "P_vol"] — call/put traded volume (day)

  When full=True, additionally include:

  • ["quote_date", "expiration_date"] — actual datetimes

  • ["C_bid_size", "C_ask_size", "P_bid_size", "P_ask_size"] — order book sizes

  • ["C_oi", "P_oi"] — open interest

Returns:

One row per strike with at least: K, D, T and the selected extra columns.

Return type:

pandas.DataFrame

Notes

• T uses 252 trading days/year to align with options practice. If you prefer ACT/365 or ACT/ACT, convert after loading.

• Date columns (quote_date, expiration_date) are parsed as datetimes.

Examples

Load defaults (compact schema): >>> df = spxw()

Keep only options with at least 100 contracts traded on both sides: >>> df = spxw(min_volume=100)

Work with a single tenor (e.g., 7 days to expiry): >>> df_7 = spxw(D=7)

Get the full column set: >>> df_full = spxw(full=True)