  Order flow imbalance can explain short-term changes in stock price. This
paper considers the change of non-minimum quotation units in real transactions,
and proposes a generalized order flow imbalance construction method to improve
Order Flow Imbalance (OFI) and Stationarized Order Flow Imbalance (log-OFI).
Based on the high-frequency order book snapshot data, we conducted an empirical
analysis of the CSI 500 constituent stocks. In order to facilitate the
presentation, we selected 10 stocks for comparison. The two indicators after
the improvement of the generalized order flow imbalance construction method
both show a better ability to explain changes in stock prices. Especially
Generalized Stationarized Order Flow Imbalance (log-GOFI), using a linear
regression model, on the time scales of 30 seconds, 1 minute, and 5 minutes,
the average R-squared out of sample compared with Order Flow Imbalance (OFI)
32.89%, 38.13% and 42.57%, respectively increased to 83.57%, 85.37% and 86.01%.
In addition, we found that the interpretability of Generalized Stationarized
Order Flow Imbalance (log-GOFI) showed stronger stability on all three time
scales.
