Bulk commodity spot leading price generation method and system based on basis adjustment

Abstract

The application discloses a bulk commodity spot leading price generation method and system based on basis adjustment, and through acquisition of a futures data source and a spot data source, the spot data source comprising a benchmark data source and a backup data source, judgment of whether the benchmark data source is updated, switching to the backup data source if the benchmark data source is not updated, reading previous date futures, current date futures and previous day spot, calculation of futures price fluctuation, query of a basis adjustment coefficient table for daily price fluctuation of a futures main contract to determine a corresponding subfile and basis change value of the futures price fluctuation, calculation of a spot price for publishing, and realization of calculation and publishing of bulk commodity spot price data under the premise of full consideration of regularity influence of futures price fluctuation on a spot basis before opening of a futures market, so that the demand of users for a transaction strategy in a market is met.

Description

Technical Field

[0001] This invention belongs to the field of commodity data service technology, specifically involving a method and system for generating leading spot prices of commodities based on basis adjustment, which is applicable to spot price analysis and decision support for financial institutions, industrial clients, and data service platforms. Background Technology

[0002] Currently, commodity spot price data relies on third-party data providers (such as Zhuochuang Information, Steel Union, and Shanghai Metals Market), which suffer from issues such as release delays (e.g., releases after 11:00 AM or in the afternoon) and data instability (missing or delayed releases on some trading days). These issues affect users' need for timely basis analysis and arbitrage trading in futures markets.

[0003] When calculating spot price data for bulk commodities, existing spot price compilation methods mostly use a single data source or a simple weighted average, which do not fully consider the real-time guiding role of the futures market on spot prices. This leads to a disconnect between prices and real market dynamics, and the accuracy is lower compared with data published by third-party data providers. Summary of the Invention

[0004] The purpose of this invention is to calculate and publish commodity spot price data before the futures market opens, taking into full account the regular impact of futures price fluctuations on the spot basis, so as to meet users' needs for trading strategies during trading hours.

[0005] To achieve the above-mentioned objectives, the present invention provides a method for generating leading spot prices for commodities based on basis adjustment, comprising the following steps:

[0006] Obtain futures and spot data sources. Spot data sources include benchmark data sources and backup data sources. Determine if the benchmark data source has been updated. If not, switch to the backup data source and read the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the backup data source. If updated, read the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the benchmark data source. Based on the previous day's futures, the current day's futures, and the previous day's spot prices, calculate the futures price change, look up the daily price change of the main futures contract in the basis adjustment coefficient table, determine the corresponding tiers and basis change values ​​for the futures price change, and calculate the spot price. The spot price will be published.

[0007] Preferably, the futures data source is a price snapshot of the main futures contract obtained in real time via API, which describes overnight overseas market trading information.

[0008] Preferably, the benchmark data source is a standardized spot price published by a third-party institution.

[0009] Preferably, the backup data source is the spot price of the same specifications from a backup third-party institution.

[0010] Preferably, the daily price change of the main futures contract and the corresponding basis change value are obtained within a preset time period. The daily price change of the main futures contract is divided into preset thresholds, and the arithmetic mean of the basis change value of each threshold is calculated. The basis adjustment coefficient table is constructed by combining the daily price change of the main futures contract and the preset thresholds.

[0011] The present invention also provides a commodity spot leading price generation system based on basis adjustment, which adopts the basis adjustment-based commodity spot leading price generation method described above. The system includes: The input layer obtains futures data sources and spot data sources. The spot data sources include the benchmark data source and the backup data source. The computational layer includes a basis dynamic adjustment module and a dual-source switching module: The dual-source switching module is used to determine whether the benchmark data source has been updated. If it has not been updated, it switches to the backup data source and reads the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the backup data source. If it has been updated, it reads the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the benchmark data source. The basis dynamic adjustment module is used to calculate the futures price change based on the previous day's futures, the current day's futures, and the previous day's spot price, query the daily price change of the main futures contract in the basis adjustment coefficient table, determine the corresponding tiers and basis change values ​​for the futures price change, and calculate the spot price. The output layer is used to publish spot prices.

[0012] This invention provides a method and system for generating leading spot prices for commodities with basis adjustment. It acquires futures and spot data sources, including a benchmark data source and a backup data source. The system determines if the benchmark data source has been updated; if not, it switches to the backup data source. It reads the previous day's futures, the current day's futures, and the previous day's spot prices, calculates the futures price change, and queries the basis adjustment coefficient table to determine the corresponding tiers and basis changes for the main futures contract's daily price change. Finally, it calculates and publishes the spot price. This method calculates and publishes commodity spot price data before the futures market opens, fully considering the regular impact of futures price fluctuations on the spot basis, thus meeting users' needs for intraday trading strategies. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the process for generating leading spot prices for commodities based on basis adjustment, provided in an embodiment of the present invention. Figure 2This is a schematic diagram of the structure of a commodity spot leading price generation system based on basis adjustment provided in an embodiment of the present invention; The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims. Detailed Implementation

[0014] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0015] like Figure 1 As shown, this embodiment of the invention provides a method for generating leading spot prices for commodities based on basis adjustment. The steps of the method are as follows: Obtain futures and spot data sources. Spot data sources include benchmark data sources and backup data sources.

[0016] The futures data source is a real-time price snapshot of the main futures contract, obtained through an Application Programming Interface (API), which describes overnight overseas market trading information. Typically, a snapshot of the main futures contract's price at 10:00 AM is obtained. The benchmark data source is a standardized spot price published by a third-party institution, such as the price of Shanghai rebar HRB400 20mm. The backup data source is a backup spot price of the same specification from a third-party institution (redundancy design).

[0017] Determine if the benchmark data source has been updated. If not, switch to the backup data source and read the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the backup data source. If updated, read the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the benchmark data source.

[0018] According to the previous day's futures Futures on the same day And the spot price the day before yesterday Calculate the price change of futures contracts (Futures Price Change Rate) Refer to the basis adjustment coefficient table to find the daily price change ΔF of the main futures contract and determine the futures price change. Corresponding tiers and basis variation values (Basis Adjustment Value) Calculates the spot price. .

[0019] The formula for calculating the percentage change in futures prices is as follows:

[0020] The formula for calculating spot prices is as follows:

[0021] The spot price will be published.

[0022] Get the daily price change of the main futures contract over the past two years and corresponding basis change value The daily price fluctuation of the main futures contract The basis variation value is calculated for each tier based on a preset threshold. The arithmetic mean, combined with the daily price change of the main futures contract. And a basis adjustment coefficient table is constructed based on preset threshold tiers, see Table 1 (e.g., when ΔF∈[0%,2%), ΔB=+120 yuan / ton).

[0023] Table 1 Basis Adjustment Factors

[0024] The preset threshold categories are <-4%, [-4%,-2%), [-2%,0%), [0%,2%), [2%,4%),>4%.

[0025] like Figure 2 As shown, embodiments of the present invention also provide a commodity spot leading price generation system based on basis adjustment, employing the basis adjustment-based commodity spot leading price generation method described above. The system includes: The input layer is used to obtain futures data sources and spot data sources. The spot data sources include the benchmark data source and the backup data source.

[0026] The computational layer includes a basis dynamic adjustment module and a dual-source switching module: The dual-source switching module is used to determine whether the benchmark data source has been updated. If it has not been updated, it switches to the backup data source and reads the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the backup data source. If it has been updated, it reads the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the benchmark data source. It monitors the update status of the benchmark data source in real time (time window: 9:55-10:05) and automatically switches to the backup source in case of an anomaly (the benchmark data source is not updated before 10:00).

[0027] The basis dynamic adjustment module is used to calculate the futures price change based on the previous day's futures, the current day's futures, and the previous day's spot prices. It then queries the basis adjustment coefficient table to determine the daily price change of the main futures contract, identifies the corresponding tiers and basis changes for the futures price changes, and calculates the spot price. The basis adjustment coefficient table (Excel attachment) presents the tier thresholds and adjustment values ​​in tabular form.

[0028] The output layer is used to publish spot prices (such as RBSP.NM) to terminals and databases at 10:00, such as Wind and EDB (Economic Database). The spot price display interface shows the presentation of spot price indicators in the Wind terminal (e.g., `RBSP.NM`).

[0029] Dual-source switching logic: A heartbeat mechanism is used to monitor the update status of the data source, with a response delay of less than 5 seconds.

[0030] Dynamic basis model: It quantifies the nonlinear relationship (non-simple linear fitting) between futures price fluctuations and basis changes using historical data, thus solving the problem of neglecting the timeliness of market transmission in traditional methods.

[0031] Taking HRB400 20mm rebar as an example: Previous day's data: =3,850 yuan / ton, =3,700 yuan / ton Futures price at 10:00 AM that day: =3,750 yuan / ton Futures price change: =(3,750-3,700) / 3,700 ≈ -1.35% → Belongs to the [-2%, 0%) range Refer to the basis adjustment factor table: = +150 yuan / ton (historical statistical value) Generate spot price: = 3,750 + (3,850 - 3,700) + 150 = 3,750 + 150 + 150 = 4,050 yuan / ton.

[0032] This invention, through obtaining futures and spot data sources (including a benchmark data source and a backup data source), determines whether the benchmark data source has been updated. If not, it switches to the backup data source, reads the previous day's futures, the current day's futures, and the previous day's spot prices, calculates the futures price change, queries the basis adjustment coefficient table to determine the corresponding tiers and basis changes for the futures price change of the main futures contract, and calculates and publishes the spot price. This allows for the calculation and publication of commodity spot price data before the futures market opens, fully considering the regular impact of futures price fluctuations on the spot basis, thus meeting users' needs for intraday trading strategies.

[0033] The embodiments of this invention have user value. Financial institutions can conduct pre-market basis analysis (such as arbitrage opportunity identification) based on leading prices, more than 2 hours earlier than competitors on average. Industrial clients can optimize hedging decisions and reduce spot procurement risks by stabilizing price indices.

[0034] The embodiments of this invention also have commercial value, breaking the monopoly of third-party data, forming Wind's own data assets, enhancing its voice in the commodity field, improving user stickiness through EDB data subscription and terminal services, and expanding market share.

Claims

1. A method for generating leading spot prices for commodities based on basis adjustment, characterized in that, Includes the following steps: Obtain futures and spot data sources. Spot data sources include benchmark data sources and backup data sources. Determine if the benchmark data source has been updated. If not, switch to the backup data source and read the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the backup data source. If updated, read the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the benchmark data source. Based on the previous day's futures, the current day's futures, and the previous day's spot prices, calculate the futures price change, look up the daily price change of the main futures contract in the basis adjustment coefficient table, determine the corresponding tiers and basis change values ​​for the futures price change, and calculate the spot price. The spot price will be published.

2. The method for generating leading spot prices for commodities based on basis adjustment as described in claim 1, characterized in that, The futures data source is a price snapshot of the main futures contract obtained in real time via API, which describes overnight overseas market trading information.

3. The method for generating leading spot prices for commodities based on basis adjustment as described in claim 1, characterized in that, The benchmark data source is a standardized spot price published by a third-party institution.

4. The method for generating leading spot prices for commodities based on basis adjustment as described in claim 1, characterized in that, The backup data source is the spot price of the same specifications from a backup third-party institution.

5. The method for generating leading spot prices for commodities based on basis adjustment as described in claim 1, characterized in that, Obtain the daily price change of the main futures contract and the corresponding basis change within a preset time period. Divide the daily price change of the main futures contract into preset thresholds, calculate the arithmetic mean of the basis change for each threshold, and construct the basis adjustment coefficient table by combining the daily price change of the main futures contract and the preset thresholds.

6. A commodity spot leading price generation system based on basis adjustment, characterized in that, The system employs the basis-adjusted leading spot price generation method for commodities as described in claim 1, wherein the system comprises: The input layer obtains futures data sources and spot data sources. The spot data sources include the benchmark data source and the backup data source. The computational layer includes a basis dynamic adjustment module and a dual-source switching module: The dual-source switching module is used to determine whether the benchmark data source has been updated. If it has not been updated, it switches to the backup data source and reads the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the backup data source. If it has been updated, it reads the previous day's futures and current day's futures from the futures data source, as well as the previous day's spot from the benchmark data source. The basis dynamic adjustment module is used to calculate the futures price change based on the previous day's futures, the current day's futures, and the previous day's spot price, query the daily price change of the main futures contract in the basis adjustment coefficient table, determine the corresponding tiers and basis change values ​​for the futures price change, and calculate the spot price. The output layer is used to publish spot prices.

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