Using BigQuant’s Data SDK for Stock Data and Intraday Factors
Summary
The document explains how members access BigQuant market data through its Python SDK. It outlines installation and login, describes checking table permissions, and demonstrates querying selected daily stock fields over a date range. It also shows how to calculate a five-day moving average and how to construct an early-session volume slope from minute bars using a grouped regression formula.
The examples illustrate data retrieval and basic feature engineering, rather than a tested trading strategy. The document repeatedly advises limiting both selected fields and date ranges to avoid excessive quota use or failed queries, and cautions against fetching large minute datasets. It focuses on Chinese market tables and member access; permissions and available tables depend on the account. No performance evidence or validation of the example factors is provided.
Key ideas
- The SDK provides a query interface for retrieving data and working with stored tables.
- Restrict queries to needed fields, instruments, and dates to manage data quotas.
- A moving average can be calculated within a query using a built-in function.
- An early-session volume slope can be formed by regressing minute volume on elapsed time.
- The examples demonstrate data processing, not evidence that the factors predict returns.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.