Recovering Raw Stock Prices from Fully Adjusted Daily Data
Summary
The discussion explains how to interpret a Chinese stock daily-bar dataset that stores fully back-adjusted prices. It says the dataset includes a back-adjustment factor and describes recovering the underlying market price by dividing the adjusted close by that factor. This lets a researcher compare the resulting price with an unadjusted quote series.
The replies distinguish this dataset from a charting platform’s display of back-adjusted prices, which may change as the visible chart range changes. They also state that research can use the adjusted series while backtesting fills and live trading use actual prices, keeping simulated execution aligned with tradable prices. The post is a short community answer rather than a full data specification: it does not define the factor’s construction, address all corporate actions, or provide validation across securities and dates. Users should verify the convention and fields for their own dataset before applying the conversion.
Key ideas
- The daily stock series is described as fully back-adjusted and includes an adjustment factor.
- Dividing the adjusted close by the factor is presented as a way to recover the underlying price.
- The recovered price can be compared with an unadjusted quote series for a consistency check.
- The discussion recommends using actual prices for simulated fills and live trading alignment.
- Adjustment conventions may differ across data providers and charting tools.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.