Building Stock Valuation and Operating Factors in a Data View
Summary
The document shows a SQL query that combines Chinese stock data with valuation, profitability, growth, liquidity, leverage, turnover, and price-volume measures. Examples include book-to-market, earnings-to-price, sales-to-price, cash-flow-to-price, EBITDA relative to enterprise value, and a ratio comparing short and long volume-weighted average prices. It also calculates moving averages, lagged returns, and financial ratios from reported company data.
The query filters a sample period and attempts to save the result as a reusable data view. The reported failure says the account lacks permission to use an underlying daily stock dataset as a child of that view. The document offers no fix, factor tests, investment results, or validation of the calculations; several ratios may also require careful handling of missing data or zero denominators. Its useful content is therefore the range of factor constructions illustrated, rather than guidance on resolving the platform permission error.
Key ideas
- The query combines valuation, growth, profitability, liquidity, and leverage measures into a stock factor dataset.
- It constructs book-to-market, earnings-to-price, sales-to-price, and cash-flow-to-price ratios from company data.
- Rolling volume-weighted average prices and a lagged price return add market-based features.
- Saving the query as a reusable view fails because the account lacks access to an underlying dataset.
- The document does not report backtest results or explain how to resolve the access restriction.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.