Active Buy Shock
factor.formula
The active buying impact coefficient is estimated using a linear regression model.
in:
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is the selling impact coefficient, which indicates the marginal impact of unit active selling volume on the return rate of stock i in the time interval t. This coefficient reflects the downward pressure of the selling power on the stock price.
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is the buying impact coefficient, which indicates the marginal impact of unit active buying volume on the return rate of stock i in the t time interval. This coefficient is the core of this factor and reflects the upward push of buyer power on stock prices.
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is the active selling volume of stock i in time interval t, usually measured by transaction amount or number of transactions. It should be noted that active selling here refers to transactions initiated by the seller, rather than simple selling behavior. Active selling orders can usually be identified by methods such as Tick Rule or Lee-Mick Rule.
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is the active buying volume of stock i in time interval t, usually measured by transaction amount or number of transactions. Similar to active selling, active buying here refers to transactions initiated by the buyer. Active buying orders can also be identified by methods such as Tick Rule or Lee-Mick Rule.
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is the rate of return of stock i in time interval t. You can choose the rate of return of different time frequencies (such as minutes, hours, days, etc.) according to your needs.
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It is the intercept term of the regression model, which represents the expected return of the stock in the absence of active buying and selling transactions.
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is the residual term of the regression model, which represents the random fluctuations that cannot be explained by the model.
factor.explanation
The active buying impact factor quantifies the impact of active buying volume on stock returns through a linear regression model. The numerical value of this factor reflects the magnitude of the change in stock price returns caused by a unit of active buying volume within a given time interval. This factor is based on microstructure theory and believes that trading behavior has a significant impact on stock price changes, especially in a high-frequency trading environment. The active buying impact factor is usually positive, indicating that increased buyer power will lead to rising stock prices. However, affected by investors' loss aversion, the impact of seller power (i.e., active selling impact) on stock prices may be more significant. Therefore, when constructing a quantitative strategy, the relative effects of active buying and selling impacts should be considered and adjusted according to the specific market environment and trading products. This factor is mainly used to measure the strength of buyer power at the liquidity impact level, and can be used in combination with other factors (such as momentum factor, turnover rate factor, etc.) to improve the predictive ability of the quantitative model.