Building Historical A-Share Index Constituents and Price Data for Factor Research

Summary

This article explains how to assemble historical Chinese A-share index constituents and daily price data for multi-factor research in VeighNa, using the Xuntouyan data service. Its example follows the CSI 300 over a stated historical date range. It first downloads sector and stock-list change histories, then queries the constituent list for each trading day and saves the date-indexed membership history in AlphaLab. Tracking past membership helps avoid survivorship bias and defines the stocks available to a historical strategy.

The workflow then loads the union of historical constituents, downloads their bar data along with the index series, and stores the results for later research and backtesting. It also shows configuring per-stock trading costs and contract settings, noting that cost assumptions affect backtest realism. The article is an implementation walkthrough, not an evaluation of a factor strategy: it reports no predictive results or backtest performance. Its process is designed for equities, and the article cautions that other asset classes have different data needs; the example also depends on access to the named data service and compatible platform setup.

Key ideas

• Historical constituent snapshots let researchers account for index membership changes and reduce survivorship bias.
• The workflow saves a constituent list for each trading day before collecting price history.
• Historical bars are downloaded for all unique constituents and the index benchmark.
• Backtest contract settings include trading cost assumptions that influence simulated results.
• The example targets A-share equities and does not assess the performance of a factor strategy.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.