The re-rights factor is a key adjustment coefficient used in the stock market to adjust historical price data. It reflects the cumulative effect of equity changes caused by ex-rights and dividend events such as company dividends, bonus shares, rights issues, etc. It aims to eliminate stock price gaps and make historical price trends continuously comparable.
The core function of the re-righting factor is to calculate the re-righting price (pre-right re-right, post-right re-right, fixed-point re-right). Forward restoration is to adjust the previous stock price based on the current stock price; backward restoration is to adjust the subsequent stock price based on the stock's first day of listing price.
(A) Calculate the backward restoration price: backward restoration price = original price * restoration factor. For example, to calculate the backward rebalancing price of the closing price, simply multiply the closing price (sp) by the rebalancing factor (yz) in the same row.
(B) Calculate the forward re-righting price: first, obtain the latest re-righting factor of the current security, then divide the current day's re-righting factor by the latest re-righting factor to obtain the "previous re-righting factor", and finally, multiply the closing price on the calculation day by the "previous re-righting factor" to obtain the forward re-righting price.
It should be noted that the specific calculation formula of the reweighting factor is not unique. The above formula is a calculation method based on the details of ex-rights and ex-dividends. In practical applications, there are other algorithms, such as the re-weighting algorithm based on the price increase or decrease (re-weighting factor = (1 + increase or decrease) × the re-weighting factor of the previous trading day), or directly calculating the re-weighting factor of the day for flexible range re-weighting. The weighting factors derived from different algorithms or data sources may differ slightly.
Stock restoration factor =
Closing price on the equity registration date* (1+ bonus shares per share – transfer of capital reserve per share – rights issue per share)
/(closing price on equity registration date – cash distribution per share + rights issue per share * rights issue price).
Basic feature broadcast
The restoration factor is the key to calculating the stock restoration price and reflects the cumulative effect of historical equity changes. The basic calculation formula is that the re-righting factor is equal to the current period's share capital divided by the previous period's share capital.
According to different restoration benchmarks, the application methods of restoration factors are mainly divided into forward restoration, backward restoration and fixed-point restoration. Forward restoration adjusts the historical price based on the current stock price. The calculation formula is that the price after restoration is equal to the price before restoration divided by the restoration factor. For backward restoration, the subsequent price is adjusted based on the historical price, such as the price on the first day of listing. The calculation formula is that the price after restoration is equal to the price before restoration multiplied by the restoration factor. Fixed-point rebalancing is to select a specific date as the base point for adjustment.
In addition to calculation methods based on changes in equity, there are other algorithms, such as the price increase and decrease weighting algorithm. The formula is that the re-weighting factor is equal to one plus the increase or decrease multiplied by the re-weighting factor of the previous trading day.
From the perspective of calculation period, the re-weighting factor can be divided into the current-day re-weighting factor and the cumulative re-weighting factor. The day's re-righting factor facilitates the flexible calculation of the re-righting price in a specified time interval. Accumulated reweighting factors such as post-accumulation reweighting factor cp_b and pre-accumulation reweighting factor cp_f are used for continuous adjustment from the starting point or end point.
Application broadcast
In stock investment analysis, weighted data can more accurately reflect the actual price trend of stocks and the true income of investors. In quantitative trading, the restoration process is used to eliminate the impact of dividends, bonuses, stock splits and other rights and interest events on stock price trends, so that stock prices on different dates are comparable.
For example, taking Kweichow Moutai (600519.SH) as an example, when the rights and interest event occurred on July 25, 2002, the calculated restoration factor was 1.11828 and the former restoration factor was 0.89423. In the DolphinDB database, the calculation of the re-righting factor and the generation of the re-righting market can be realized by writing code steps.
There are many methods for calculating the re-right price. Due to different data caliber or calculation method, the obtained re-right price will also be different; there are many algorithms for the re-righting factor, such as the increase and decrease re-weighting algorithm.
Impact broadcast
By correcting historical prices, the main function of the restoration factor is to eliminate stock price gaps caused by dividends, bonus shares, rights issues and other rights and interest events, so that prices in different periods are continuously comparable.
The re-righting data calculated based on the re-weighting factor can more truly reflect the actual price trend of the stock and the true income of investors, improving the accuracy of the analysis.
Related research reports
The restoration factor is the key to calculating the restoration price and is the cumulative effect of historical changes in equity or interest events. Based on the selection of benchmark points, restoration of rights is mainly divided into front restoration, rear restoration and fixed-point restoration. The forward restoration is based on the current stock price, and the calculation formula is price after restoration = price before restoration ÷ restoration factor; the backward restoration is based on the price of the stock on the first day of listing, and the calculation formula is price after restoration = price before restoration × restoration factor. There are many specific algorithms for reweighting factors, such as the rise and fall reweighting method, calculations based on changes in equity, etc. Different algorithms may lead to different results.
The calculation formula of the price increase and decrease re-weighting method is the re-weighting factor = (1 + price increase and decrease) × the re-weighting factor of the previous trading day. Its advantage is that the calculation is flexible, and the "day reweighting factor" can be used to calculate only the required interval to avoid the cumulative factor being too large or too small. The algorithm calculation formula based on changes in equity is re-righting factor = current period’s equity/last period’s equity. The former restoration of rights keeps the current price intuitive and easy to compare with the current price; the latter restoration of rights maintains the stability of historical prices and makes it easy to observe the long-term real increase.
The re-weighting process is not only applicable to the price, but also to the trading volume. The post-reweighting volume data is obtained by multiplying the original trading volume and the re-weighting factor. In quantitative trading or financial databases such as DolphinDB, the specific steps to implement the calculation of re-righting factors and the generation of re-righting market prices include storing the un-re-righting market data, separately calculating and storing the post-re-righting and pre-re-righting factors. Stock software such as Tongdaxin provides functional example ideas for calculating the reweighting factor.
Due to differences in data caliber, ex-rights and ex-dividend information records or specific algorithms, there may be differences in the calculation results of the re-weighting factor from different sources. In practice, there may be errors between self-calculated reweighting data and data provided by third-party data vendors. It is necessary to pay attention to the consistency of data sources and calculation methods.
