Datayes Exchange High-Frequency Quotes Factor Data Newly Launched, Technical Digging Trading Signals！

Datayes has recently launched two new types of factor libraries for China A-shares. The factors are constructed using high-frequency quotes from the exchanges and cover various types of rich features.

Stock daily frequency feature data is based on Tonglian's rich and stable quotes and derivative data, and utilizes cluster computing resources to calculate a total of 7 dimensions of stock liquidity, momentum, volatility, turnover share, capital flow, correlation and other factor libraries on a daily basis.

The upstream data, in addition to daily frequency, also uses snapshots and minute-level quotes. This underlying data covers more gainful information relative to 424 and boutique factors, which helps investors to reduce upfront investment and improve research efficiency. This data is updated every trading day and covers all A-share stocks, which is convenient for quantitative research.

HF to Low Frequency Factor Library is a derivative result based on the mining of daily features of HF K-lines, snapshots and tick-by-tick data. These low-frequency factors are derived from more micro and multi-dimensional features with better alpha attributes as well as incremental overlay unlike traditional factors.

The data can be traced back to 2011, and includes dimensions such as return distribution, volume distribution, volume-price correlation, liquidity, buying and selling pressure, and capital movement, totaling 122 factors, covering the entire A-share market.

The factors after switching to low-frequency are derived in multiple dimensions relying on the richness and complexity of high-frequency data. These factors have low correlation with each other and are rich in information content, which is suitable for a variety of scenarios such as quantitative stock selection and feature input for machine learning models.