quantlab.dataset.massive.day_bars

The Day aggregate panel built from Massive’s daily day_aggs files, on the Massive ticker axis.

MassiveDayBarDataset reads the Day aggregates the Massive client keeps in the raw tier (quantlab.dataset.massive.raw, data type day_aggs), one file per trading day, and returns the dense (timestamp, symbol) panel its store massive_day_bars_1d holds (#352; the two-store pattern of the Trade bars, ADR 0031).

• The variables are the file’s, unchanged: open, high, low, close, volume and n_trades (the file’s transactions), as float64 (DAY_BAR_VARIABLES). Prices are raw: no split or dividend adjustment.

• One bar per trading day, labelled with its date (midnight, like SEP’s bars). The days are those of the raw tier’s files; a file whose day is not an XNYS session is refused.

• The symbol axis is the Massive ticker, exactly as the files spell it (BRK.A, AApB), every ticker kept, exchange test symbols included. A column is a ticker, not a security: reading the store as securities goes through the Ticker map (quantlab.dataset.massive.ticker_map). No Sharadar data is read.

• A ticker absent from a day’s file has NaN prices and zero volume and n_trades that day.

• The store grows at its end. update() appends the raw days after the store’s last; a ticker first met on one of them is appended at the end of the symbol axis in place (ADR 0032), with no bar over the days before, so a backfill and a daily update are the same operation. With end_date=None the range is every raw day, so the daily update extends the store from its own component.json.

Examples

Needs day-aggregate files under <raw_data_dir_path>/day_aggs:

config = MassiveDayBarsDatasetConfig(
    zarr_file_path="/data/quantlab/market/massive/massive_day_bars_1d/massive_day_bars_1d.zarr",
    raw_data_dir_path="/data/quantlab/downloads/massive",
    start_date="2016-10-10",
)
ds = MassiveDayBarDataset(config).update(granularity="year")
panel = ds.panel("2024-11-26", "2024-11-29")

Classes

MassiveDayBarDataset

Dense Day aggregate panel on the Massive ticker axis; see the module docstring.