Market data management method, system, device and storage medium

Abstract

The application discloses a kind of market data management method, system, equipment and storage medium.The method comprises: extracting at least one current source market data of target product from the data cache table of pre-set;Based on the historical source market data stored in the market database relative to the target product, determine the reference evaluation data corresponding to at least one data analysis model set in advance;From each current source market data, select the input data input into each data analysis model, combine the corresponding reference evaluation data, obtain the data analysis result output by each data analysis model;According to each data analysis result, determine the release market data of the target product.In the embodiment of the application, the accuracy of market data release is realized by managing market data based on current source market data and historical source market data, the efficiency of automatic detection in financial industry is improved, the problem of system vulnerability is better solved, and potential risks are eliminated.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of data processing, in particular to a market data management method, system, device and storage medium. BACKGROUND

[0002] With the continuous rise of the business in various fields of the financial industry, the market data of the financial industry has become various. It is well known that the market data of the financial industry, such as the market data of foreign exchange, the market data of precious metals, and the market data of some derivatives, etc. The real-time changes of these market data also reflect the changes of some markets in the financial field, and are the basis for the transaction between the financial industry and the customers.

[0003] The market data is the most basic and important part in the transaction process. The financial industry can only obtain the market data in time to better understand the changes of the current market, thereby better serving individuals. In the prior art, the financial industry obtains the market data from the primary market, directly publishes the secondary market through the manual spread method, and trades with customers. The market data is not further analyzed, so that the market data is prone to errors in publication, and there are system vulnerability problems, which brings great risks and hidden dangers to the financial industry. SUMMARY

[0004] The present application provides a market data management method, system, device and storage medium to realize accurate determination of the market data published to the secondary market.

[0005] In a first aspect, the embodiment of the present application provides a market data management method, comprising:

[0006] extracting at least one current source market data of a target product from a preset data cache table;

[0007] determining the reference evaluation data corresponding to the at least one data analysis model based on the historical source market data stored in the market database relative to the target product;

[0008] selecting input data of each data analysis model from each current source market data, combining the corresponding reference evaluation data, and obtaining the data analysis result output by each data analysis model;

[0009] determining the published market data of the target product according to each data analysis result.

[0010] In a second aspect, the embodiment of the present application further provides a market data management system, which comprises:

[0011] a current data extraction module configured to extract at least one current source market data of a target product from a preset data cache table;

[0012] a reference data determining module, configured to determine reference evaluation data corresponding to at least one data analysis model according to historical source market data stored in the market database and relative to the target product;

[0013] an analysis result obtaining module, configured to obtain data analysis results output by each data analysis model by selecting input data of each data analysis model from each current source market data and combining corresponding reference evaluation data;

[0014] a data publishing module, configured to determine publishing market data of the target product according to each data analysis result.

[0015] In a third aspect, an embodiment of the present application further provides a computer device, comprising:

[0016] one or more processors,

[0017] a storage device configured to store one or more programs,

[0018] when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the market data management method according to any one of the first aspect.

[0019] In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the market data management method according to the first aspect.

[0020] In the technical solution provided by this invention, at least one current source market data of the target product is extracted from a preset data cache table. Based on the historical source market data stored in the market database relative to the target product, benchmark evaluation data corresponding to at least one pre-set data analysis model is determined. Then, input data for each data analysis model is selected from each current source market data. Combined with the corresponding benchmark evaluation data, the data analysis results output by each data analysis model are obtained. Finally, the published market data of the target product is determined based on the data analysis results. This technical solution, by extracting at least one current source market data of the target product from a preset data cache table and then extracting historical source market data relative to the target product from the market database, determines the benchmark evaluation data corresponding to at least one pre-set data analysis model based on the extracted current source market data and historical source market data. Compared with existing technologies, the data analysis model effectively avoids error-prone problems when publishing market data in the financial industry. Furthermore, after the market data is published, collecting and further analyzing the published market data enables self-checking within the financial industry system and reduces various risks and hidden problems in the financial industry. Attached Figure Description

[0021] Figure 1 This is a flowchart of a market data management method according to Embodiment 1 of the present invention;

[0022] Figure 2 This is a flowchart of a market data management method according to Embodiment 2 of the present invention;

[0023] Figure 2a This is a flowchart of a market data management method according to Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of a market data management system according to Embodiment 3 of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of a computer device according to Embodiment 4 of the present invention; Detailed Implementation

[0026] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0027] The term "include" and variations thereof, as used in the present disclosure, shall mean "including, but not limited to". The term "based on" means "based, at least in part, on". The term "one embodiment" means "at least one embodiment".

[0028] It should be noted that similar reference numerals and letters refer to similar items throughout the accompanying drawings, and therefore, once an item is defined in one drawing, it is not necessary to further define and explain it in subsequent drawings. Meanwhile, in the description of the present disclosure, the terms "first", "second", and the like are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

[0029] Embodiment one

[0030] Figure 1 A flowchart of a market data management method provided for embodiment one of the present disclosure, the present embodiment can be applicable to the case of monitoring and analyzing market data, which can be executed by a market data management system. The system is realized by software and / or hardware, and can be configured in a computer device.

[0031] The method specifically includes the following steps:

[0032] S101, extracting at least one current source market data of a target product from a preset data cache table.

[0033] The preset data cache table can be understood as a pre-set cache data table in the cache server, which is used to store real-time incoming source market data. The preset data cache table can be understood as storing the market data content that needs to be frequently accessed in a system closer to the user and with faster access speed, so as to improve the content access speed. The cache server can be a server for storing frequently accessed content.

[0034] It can be known that the target product is the source product of the source market data. For example, it can be precious metals, foreign exchange, or derivatives, which are not limited in the present embodiment. The precious metals refer to valuable metals, such as gold, silver, etc.; foreign exchange refers to the flow of currency between countries and the exchange of the currency of one country into the currency of another country for trading or other purposes; and the derivatives can be forward, futures, and swaps, etc.

[0035] It should be noted that the source market data refers to the quotation data of the market quotation agency. The current source market data can be understood as the real-time input source market data from the market quotation agency at the current execution time. For each target product, there is one or more current source market data provided by the market quotation source agency in the preset data cache table, and at least one current source market data can be directly obtained from the data cache table through the present step.

[0036] In the embodiment, the financial industry's market receiver continuously receives the primary market source market data from the market information agencies in real time, and then stores the received source market data in the data cache table in the cache server and in the database, for the analysis of the market data by the financial industry and the real-time quotation.

[0037] It should be noted that the way of extracting at least one current source market data of the target product from the preset data cache table can be that the market quotation agencies of the primary market continuously send the quotation source data of each market to the financial industry in real time, and the financial industry stores the source market data in the preset data cache table and in the database after receiving the source market data, and when the financial industry wants to know the current source market data of a product, the current source market data provided by one or more market quotation agencies of the target product can be extracted from the preset data cache table.

[0038] S102, based on the historical source market data of the relative target product stored in the market database, determining the benchmark evaluation data corresponding to the at least one pre-set data analysis model.

[0039] The market database can be understood as a warehouse for organizing, storing and managing data according to data structure, and is a long-term storage in a computer, an organized, shareable and unified management of a large amount of data collection. The market data in the market database comes from the quotation source data of the target product by the primary market data agency, and the real-time quotation source data and the previous quotation source data are stored in the market database. The storage space of the market database is very large, and can store millions of data, ten million data, and hundreds of millions of data. Moreover, the market database does not store data randomly, but has certain rules, so as to improve the efficiency of data query in the market database.

[0040] It can be known that the historical source market data can be understood as the quotation source data of the target product stored in the market database in a certain period of time before. For example, the historical source market data can be the quotation source data two weeks ago, one month ago, or one year ago, and the embodiment does not limit this.

[0041] In the embodiment, the data analysis model can be understood as a selected model for analyzing and processing data. For example, the data analysis model can be a horizontal analysis model, a vertical analysis model, etc.

[0042] It should be noted that the benchmark evaluation data can be understood as formed by processing and analyzing the input data of the data horizontal analysis model and the data vertical analysis model. The data processing and analysis can be understood as summarizing the historical source market data of the target product in a certain period of time, and then calculating the average value of the historical source market data quotation of the target product in this period of time. It can also be that the multi-path source market data of the target product in a certain period of time is summarized to obtain the difference of the multi-path source market data quotation of the target product in this period of time. It can also be that the difference between the historical source market data quotation of the target product in this period of time and the current real-time market data is calculated. The present embodiment does not limit this.

[0043] It can be known that the benchmark evaluation data can be understood as the standard for evaluating the market data. The benchmark evaluation data can include: horizontal benchmark evaluation data and vertical benchmark evaluation data, which are used to evaluate whether the real-time market data in the data horizontal analysis model and the data vertical analysis model is within a reasonable range.

[0044] It should be noted that based on the historical source market data of the target product stored in the market database, the method for determining the benchmark evaluation data corresponding to the at least one data analysis model set in advance is: first, obtaining the historical source market data of each path of the target product from the preset market database, then for each path of the historical source market data, obtaining the corresponding first historical time point data based on at least one historical time point, which is used to determine the horizontal benchmark evaluation data corresponding to the data horizontal analysis model, and finally obtaining the corresponding second historical time point data based on each path of the historical source market data at a specified historical time point, which is used to determine the vertical benchmark evaluation data corresponding to the data vertical analysis model.

[0045] S103, selecting input data for each data analysis model from each path of the current source market data, and obtaining the data analysis result output by each data analysis model in combination with the corresponding benchmark evaluation data.

[0046] Among them, each path of the current source market data can be understood as the market quotation source data of multiple market data institutions. For example, it can be the quotation source data of the target product of A market data quotation institution, or the quotation source data of the target product of B market data quotation institution.

[0047] It should be noted that before selecting input data of each data analysis model from the current source market data, the input market data needs to be processed and analyzed, and then the processed and analyzed data is input into each data analysis model. Among them, the data processing and analysis can be to summarize the historical source market data of the target product in a certain period of time, and then calculate the average value of the historical source market data quotation of the target product in this period of time; it can also be to summarize the multi-source market data of the target product in a certain period of time, and then calculate the difference value of the multi-source market data quotation of the target product in this period of time. Among them, the certain period of time in the past can be one month ago, one year ago, or two years ago, and the embodiment does not limit it. Among them, the near period of time can be one day ago, or one hour ago, and the embodiment does not limit it.

[0048] In the embodiment, the data analysis result can be understood as a reasonable analysis result obtained by combining the horizontal and / or vertical data analysis of the target product related to one and / or multiple current source market data and historical source market data with the corresponding benchmark evaluation data.

[0049] It should be noted that one of the target source market data is selected from the current source market data of each target product as the input data of the data horizontal analysis model, and then the historical market data average value of the same type of target product in a certain period of time is obtained from the market database. Finally, the target source market data is calculated by difference with the horizontal benchmark evaluation data to obtain the first floating data. If the first floating data is less than the first floating threshold, the target source market data is determined as the first qualified market data, and is used as the horizontal data analysis result of the data horizontal analysis model.

[0050] It should be noted that the current source market data of each target product is used as the input data of the data vertical analysis model, and then the market data average value of each target product of the same type in a certain period of time is obtained from the preset data cache table. Finally, the current source market data of each target product is calculated by difference with the vertical benchmark evaluation data to obtain the second floating data sequence, and the second floating data less than the second floating threshold in the second floating data sequence is determined. The current source market data associated with each second floating data is determined as the second qualified market data, and the obtained each second qualified market data is used as the vertical data analysis result of the data vertical analysis model.

[0051] S104, according to each data analysis result, determining the release market data of the target product.

[0052] It can be known that publishing market data can be understood as publishing the market data of the final target product to the secondary market for real-time trading. The secondary market refers to the place where issued securities are bought and sold, and is the market for the transfer of ownership of securities. It provides liquidity for security holders, who can sell securities for cash when needed, and provides investment opportunities for new savers.

[0053] It needs to be known that according to the data analysis results, the way to determine the publishing market data of the target product is: through data horizontal analysis model and data vertical analysis model, so that the first qualified market data in the horizontal data analysis result and each second qualified market data contained in the vertical data analysis result are obtained. After obtaining the first qualified market data and the second qualified market data, data screening is needed, qualified market data is retained, unqualified market data is screened out, and target market data of the target product is obtained. Then after obtaining the target market data, a certain pricing strategy needs to be performed on the obtained target market data of the target product, and the pricing strategy needs to have a regulatory threshold range, and then the market data of the target product can be published to the secondary market for trading.

[0054] In this embodiment, the market data published to the secondary market for trading can be fed back to the preset data cache table and the market database, which is used for quality report analysis of the market data of the financial industry and risk assessment of the financial industry, so that the pricing strategy can be more accurate and better serve the customers.

[0055] In the technical solution provided by the embodiment of the application, at least one current source market data of a target product is extracted from a preset data cache table, historical source market data corresponding to the target product is stored in a market database, a reference evaluation data corresponding to at least one data analysis model is determined, input data of each data analysis model is selected from each current source market data, the input data is combined with the corresponding reference evaluation data, data analysis results output by each data analysis model are obtained, and finally the publishing market data of the target product is determined according to each data analysis result. Through the management of the market data based on the current source market data and the historical source market data, the accuracy of the market data publishing is realized, the automatic detection efficiency of the financial industry is improved, the problem of system vulnerability is better solved, and the potential hidden danger of the enterprise is eliminated.

[0056] Optionally, after determining the publishing market data of the target product according to the data analysis results, the method further includes:

[0057] Determine the quality analysis report of the target product based on the published market data and in combination with at least one quality analysis model set in advance.

[0058] The quality analysis model can be understood as a quality analysis report formed according to a quality random analysis model, a quality reverse analysis model and a quality extreme analysis model.

[0059] It should be noted that the quality analysis report can be understood as containing three aspects. The first aspect is derived from the quality analysis model, and a certain random historical market data in a certain period of time is randomly taken from the market database. The taken data is first processed by dispersion, and then the historical random data of the target product is randomly extracted. Then, the extracted data is compared with the current source market data and the published market data in the secondary market, and the comparison result is taken as a piece of quality analysis information of the target product. The second aspect is derived from the quality reverse analysis model. The market data published in the secondary market is input into the source market quotation agency in the primary market, and the corresponding rules are calculated to obtain the quoted source market data. After obtaining the calculation rules of the authoritative quotation agency in the primary market in the financial industry, a set of algorithms with different logic but consistent market quotation data are formed by AI machine learning and other methods, and the corresponding reverse market data is obtained. The published market data is compared with each reverse market data, and the comparison result is taken as a piece of quality analysis information of the target product. The third aspect is derived from the quality extreme analysis model. The historical market data of the target product is determined from the market database, the floating interval of the target product is determined, the published market data is compared with the floating interval of the market data, and the comparison result is taken as a piece of quality analysis information of the target product.

[0060] Optionally, the quality analysis model set in advance includes a quality random analysis model, a quality reverse analysis model and a quality extreme analysis model.

[0061] Correspondingly, the quality analysis report of the target product is determined based on the published market data and in combination with at least one quality analysis model set in advance, which includes:

[0062] The historical random data of the target product is randomly selected from the market database by the quality random analysis model.

[0063] The historical random data is compared with each current source market data and the published market data.

[0064] The comparison result is taken as a piece of quality analysis information of the corresponding quality analysis report of the target product.

[0065] In the embodiment, the quality random analysis model is used to analyze the comparison result of the historical random data of the selected target product in the market database within a certain period of time and each current source market data and the published market data. The quality reverse analysis model is used to analyze the comparison result of the published market data and the reverse market data. The quality extreme analysis model is used to analyze the comparison result of the published market data and the floating interval or threshold of the historical market data of the relative target product in the market database.

[0066] The historical random data can be understood as the historical market data in the market database within a certain period of time. The selected historical market data within the period of time is processed, and then the historical market data is randomly selected.

[0067] It can be known that each current source market data can be understood as the source market data of the real-time quotation of the authoritative quotation source data institution in the primary market.

[0068] In the embodiment, the published market data is the market data published to the secondary market for transaction.

[0069] It can be known that the quality analysis information can be understood as the analysis result of the market data information displayed in the quality report. According to the quality analysis information, the financial industry can better find the loopholes of the system, can self-check the potential hidden dangers existing in the financial industry, can more accurately quote to the secondary market, and can better serve the customers.

[0070] Optionally, based on the published market data, at least one quality analysis model is determined, and a quality analysis report of the target product is determined, including:

[0071] Each reverse market data is obtained by using a set of reverse calculation rules to perform reverse calculation on each current source market data through the quality reverse analysis model.

[0072] The published market data is compared with each reverse market data, and the comparison result is used as a piece of quality analysis information of the quality analysis report corresponding to the target product.

[0073] It should be noted that the reverse calculation rule can be understood as a back-to-back calculation rule. When the source market quotation data of the market data quotation institution in the primary market is input, a corresponding rule is used to calculate the quoted source market data. After the calculation rule of the primary market market data institution is obtained in the financial industry, the financial industry will form a set of logical methods different from the calculation rule of the primary market market data institution, but the market quotation data is consistent. The calculation rule of the source market quotation data input of the primary market market data institution is calculated back to back.

[0074] In the embodiment, the reverse market data can be understood as a set of reverse market data formed by the financial industry according to other algorithms, which has different logic but consistent market quotation data.

[0075] Optionally, based on the published market data, in combination with the pre-set at least one quality analysis model, a quality analysis report of the target product is determined, which includes:

[0076] Through the quality extreme analysis model, based on the historical market data of the target product in the market database, the market data floating interval of the target product is determined.

[0077] The published market data is compared with the market data floating interval, and the comparison result is used as a piece of quality analysis information of the quality analysis report corresponding to the target product.

[0078] It can be known that the market data floating interval can be understood as the upper and lower floating interval of the target product obtained from the historical market data in the market database within a certain period of time. For example, the upper and lower floating interval of the target product market data within January 2018 to December 2020 can be 4-6.

[0079] It should be noted that the comparison between the market data published to the secondary market and the market data floating interval can be used as a piece of quality analysis information of the quality analysis report. Through the quality extreme analysis model, based on the critical value, illegal data and the like, the ability of the financial industry to respond to special or extreme situations is further detected.

[0080] Embodiment two

[0081] Figure 2 A flowchart of a market data management method is provided for the second embodiment of the application. The embodiment is further refined on the basis of the above-mentioned embodiments. Specifically, it can include the following steps:

[0082] S201, extracting at least one current source market data of the target product from the pre-set data cache table.

[0083] It can be known that one or more current source market data of the target product is extracted from the pre-set data cache table.

[0084] Specifically, the embodiment can determine the reference evaluation data corresponding to the pre-set at least one data analysis model through the historical source market data of the target product stored in the market database. The specific steps can be S202 to S204:

[0085] S202, obtaining each historical source market data of the target product from the pre-set market database.

[0086] Specifically, from the market database, the historical source market data of the target product from multiple market data quotation institutions in the primary market can be obtained.

[0087] It should be noted that the manner of obtaining each historical source market data of the target product from the preset market database is that the quotation source market data of the primary market market data institution is continuously stored in the preset cache table and the market database in real time, and then the multiple historical source market data of the target product can be extracted from the market database.

[0088] S203, for each historical source market data, based on the corresponding first historical time point data at least one historical time point, determine the corresponding horizontal reference evaluation data of the data horizontal analysis model;

[0089] Among them, the first historical time point data can be understood as selecting one historical source market data of the target product in a certain period in the data horizontal analysis model. The first historical time point data is the historical market data obtained from the market database.

[0090] It can be known that the data horizontal analysis model is used to analyze the comparison of one historical source market data of the target product in a certain period after data processing with the current target product source market data.

[0091] It should be noted that the horizontal reference evaluation data can be understood as the horizontal reference evaluation data obtained by processing one historical source market data of the target product in a certain period, such as calculating the mean, difference, etc.

[0092] S204, based on the corresponding second historical time point data of each historical source market data at the specified historical time point, determine the corresponding vertical reference evaluation data of the data vertical analysis model.

[0093] Among them, the second historical time point data can be understood as selecting multiple historical source market data of the target product in a certain period in the data vertical analysis model. The second historical time point data is the market data obtained from the cache table.

[0094] It can be known that the data vertical analysis model is used to analyze the comparison of the current source market data in each preset cache table of the target product after data processing with the current real-time target product source market data.

[0095] It should be noted that the vertical reference evaluation data can be understood as the vertical reference evaluation data obtained by processing the current source market data in each preset cache table of the target product, such as calculating the mean, derivative, etc.

[0096] Specifically, by selecting input data of each data analysis model from each current source market data, and combining with the corresponding benchmark evaluation data, the data analysis result output by each data analysis model can be obtained. Specifically, S205 to S209:

[0097] S205, select a target source market data from each current source market data as the input data of the data horizontal analysis model, and calculate the difference between the target source market data and the horizontal benchmark evaluation data to obtain the first floating data;

[0098] It should be noted that the first floating data can be understood as being calculated by the difference between the target source market data and the horizontal benchmark evaluation data. Wherein, the difference between the target source market data and the horizontal benchmark evaluation data can be understood as the value obtained by subtracting the target source market data from the horizontal benchmark evaluation data.

[0099] S206, if the first floating data is less than the first floating threshold, determine each target source market data as the first qualified market data, and as the horizontal data analysis result of the data horizontal analysis model.

[0100] Wherein, the first floating threshold can be understood as the threshold floating range of the target product in the data horizontal analysis model. The first qualified market data is determined according to the first floating data in the horizontal model. If the first floating data is less than the first floating threshold, each target source market data is determined as the first qualified market data.

[0101] It can be known that the horizontal data analysis result can be qualified market data, or unqualified market data.

[0102] S207, use each current source market data as the input data of the data vertical analysis model, determine the difference between each current source market data and the vertical benchmark evaluation data to obtain the second floating data sequence;

[0103] It should be noted that the second floating data sequence is obtained by calculating the difference between each target product current source market data and the vertical benchmark evaluation data. According to the second floating data, it can be judged whether it belongs to the qualified data in the data vertical analysis model. The second floating data less than the second floating threshold in the second floating data sequence is determined, and the current source market data respectively associated with each second floating data is determined as the second qualified market data.

[0104] S208, determine the second floating data less than the second floating threshold in the second floating data sequence, and determine the current source market data respectively associated with each second floating data as the second qualified market data;

[0105] The second floating threshold can be understood as a threshold floating range of the target product in the data longitudinal analysis model. The second floating data is data less than the second floating threshold obtained from the second floating data sequence.

[0106] S209, taking each second qualified market data as a longitudinal data analysis result of the data longitudinal analysis model.

[0107] Specifically, after obtaining the second qualified market data, it can be taken as a longitudinal data analysis result of the data longitudinal analysis model.

[0108] It can be known that the transverse data analysis result can be qualified market data or unqualified market data.

[0109] Specifically, according to each data analysis result, the release market data of the target product can be determined. Specifically, S210 to S211:

[0110] S210, based on the first qualified market data in the transverse data analysis result and each second qualified market data contained in the longitudinal data analysis result, a target market data is obtained by screening;

[0111] In this embodiment, the qualified target market data can be screened from the first qualified market data in the transverse data analysis result and each second qualified market data contained in the longitudinal data analysis result. The target market data can be understood as market data released to the secondary market.

[0112] It should be noted that the target market data screening method is: according to the first qualified market data in the transverse data analysis result and each second qualified market data contained in the longitudinal data analysis result, the target market data in which all the data meet the conditions is selected as the output target market data.

[0113] S211, using a set market data adjustment strategy and threshold supervision condition to process the target market data, and obtaining the release market data of the target product.

[0114] The set market data adjustment strategy can be a strategy for adjusting the screened target market data in the financial industry. For example, the screened target market data can be processed by adding or subtracting the spread. For example, when the output of the screened target market data is 5.0, the regulatory department of the financial industry can add a spread of 0.2, and output with a pricing strategy of 5.2.

[0115] It should be noted that the threshold supervision can be understood as the need for threshold supervision and control before the target market data is released to the secondary market for trading. Under the set market data adjustment strategy, it cannot exceed the threshold supervision and control range.

[0116] In the technical solution provided by the embodiment of the application, for each piece of historical source market data, the corresponding horizontal reference evaluation data of the data horizontal analysis model is determined based on the corresponding first historical time point data at at least one historical time point, the corresponding vertical reference evaluation data of the data vertical analysis model is determined based on the corresponding second historical time point data of each piece of historical source market data at a specified historical time point, then the target market data of the target product is obtained based on the corresponding horizontal reference evaluation data of the data horizontal analysis model and the corresponding vertical reference evaluation data of the data vertical analysis model, and the publishing market data of the target product is obtained by processing the target market data through the set market data adjustment strategy and the threshold supervision condition. The embodiment improves the financial industry system automation test efficiency through the data horizontal analysis model and the data vertical analysis model, further realizes the accuracy of market data publishing, and eliminates potential risks in the financial industry.

[0117] For example, in order to better understand the method of market data management, the following steps can be taken Figure 2a As a flowchart of a market data management method. It can include the following steps:

[0118] a1. The market receiver of the financial industry continuously receives the primary market source market data reported by the authoritative market quotation agency in real time.

[0119] a2. The financial industry stores the received source market data in the preset cache server and market database.

[0120] a3. The data for the data horizontal analysis model is processed by a horizontal data processing strategy, and any target source market data is selected from the current source market data of each target product as the input data of the data horizontal analysis model, and then the historical market data of the same target product within a certain period of time is obtained from the market database for processing.

[0121] a4. The target source market data and the horizontal reference evaluation data are calculated by difference to obtain first floating data. If the first floating data is less than the first floating threshold, each target source market data is determined as first qualified market data, and is used as the horizontal data analysis result of the data horizontal analysis model.

[0122] a5. The current source market data of each target product is used as the input data of the data vertical analysis model, and then the market data of the same target product within a certain period of time is obtained from the preset data cache table for processing.

[0123] a6. Calculate the difference between the current source market data of each target product and the longitudinal benchmark evaluation data to obtain the second floating data sequence. Determine the second floating data in the second floating data series that is less than the second floating threshold. Determine the current source market data associated with each second floating data as the second qualified market data. The obtained second qualified market data are used as the longitudinal data analysis results of the data longitudinal analysis model.

[0124] a7. After obtaining the first and second qualified market data, it is necessary to filter the data, retain the qualified market data, and filter out the unqualified market data to obtain the target market data for the target product.

[0125] a8. Develop a pricing strategy based on the target market data of the target product.

[0126] a9. Pricing strategies need to have a regulated threshold range.

[0127] a10. Market data for the target product is published on the secondary market for trading.

[0128] a11. The market data used for the quality stochastic analysis model is processed using a random data processing strategy. A certain period of randomly released historical market data is randomly selected from the market database. The selected data is first shuffled, and then the historical random data of the target product is randomly extracted and input into the quality stochastic analysis model.

[0129] A12. The quality stochastic analysis model can include source market data units, relay market data units, and consumer market data units. The source market data unit stores historical random data from the market data database. The relay market data unit stores current source market data output from a pre-set cache table. The consumer market data unit stores market data published to the secondary market. Source market data is generated randomly, and the relay and consumer market data units change as the source market data changes. The current source market data and the market data published to the secondary market are compared, and the comparison result is used as a quality analysis piece of information for the target product.

[0130] a13. A reverse data processing strategy is used to process market data used in the quality reverse analysis model. When traders in the financial industry believe that there is a problem with the data for a certain day, it can be used to perform reverse analysis to determine whether there is a problem with the market price. Quality reverse analysis can be performed.

[0131] a14、In the quality reverse analysis model, a fixed rule consumer market information unit and a quotation unit calculated by the quality reverse analysis rule can be included. The fixed rule consumer market information unit can be a fixed release of secondary market market information data, and the quotation unit calculated by the quality reverse analysis rule is used for reverse calculation of market information data in the financial industry. The market information data of the consumer market information unit is an expected value generated according to a fixed rule. The data generation rule of the quotation unit calculated by the quality reverse analysis rule is the same as that of the consumer market information unit, but the logical path is different. In the quality reverse analysis model, a set of algorithms with different logic but consistent market quotation data are formed by AI machine learning and other methods. The source market information data is compared with the current source market information data in the cache, and the comparison result is used as a piece of quality analysis information of the target product.

[0132] a15、The market information data for the quality extreme model is subjected to an extreme data processing strategy. The market information data floating interval of the target product is determined relative to the historical market information data or the threshold value of the target product in the market information database.

[0133] a16、In the quality extreme model, an extreme consumer market information unit and a preset market reference price unit can be included. The extreme consumer market information unit can be extreme secondary market release data, and the preset market reference price unit can be a preset market reference price data. The extreme consumer market information unit data is critical or significantly exceeds the preset market reference price unit. The published market information data is compared with the market information data floating interval, and the comparison result is used as a piece of quality analysis information of the target product.

[0134] a17、Finally, a quality report analysis is formed. From the quality report analysis, whether the financial industry system has vulnerabilities, whether the target market information data published to the secondary market is accurate, and the like can be fed back, so that hidden problems in the financial industry can be eliminated, and the market information release of the financial industry can be more accurate.

[0135] Embodiment three

[0136] Figure 3 A structure diagram of a market information data management system provided by the embodiment three of the application is provided. The market information data management system provided by the embodiment can be realized by software and / or hardware, and can be configured in a server to realize the market information data management method in the embodiment of the application. As shown in the figure, the system can specifically include a current data extraction module 301, a reference data determination module 302, an analysis result obtaining module 303, and a data release module 304. Figure 3

[0137] The current data extraction module 301 is configured to extract at least one current source market information data of a target product from a preset data cache table.​

[0138] The reference data determination module 302 is configured to determine reference evaluation data corresponding to at least one data analysis model according to historical source market data stored in the market database and corresponding to the target product;

[0139] The analysis result obtaining module 303 is configured to select input data of each data analysis model from each current source market data, and obtain data analysis results output by each data analysis model in combination with corresponding reference evaluation data;

[0140] The data publishing module 304 is configured to determine publishing market data of the target product according to each data analysis result.

[0141] In the technical scheme provided by the embodiment of the application, the current data extraction module extracts at least one current source market data of the target product from the preset data cache table, the reference data determination module determines reference evaluation data corresponding to at least one data analysis model according to historical source market data stored in the market database and corresponding to the target product, the analysis result obtaining module selects input data of each data analysis model from each current source market data, and obtains data analysis results output by each data analysis model in combination with corresponding reference evaluation data, and finally the data publishing module determines publishing market data of the target product according to each data analysis result. The technical scheme described above in the embodiment of the application can manage market data based on current source market data and historical source market data, realize the accuracy of market data publishing, better solve the problem of system vulnerability, eliminate potential risks of enterprises, and improve the efficiency of automatic testing.

[0142] Optionally, on the basis of each of the above embodiments, the reference data determination module 302 can specifically include:

[0143] The historical data acquisition unit is specifically configured to acquire each historical source market data of the target product from the preset market database;

[0144] The horizontal data determination unit is specifically configured to determine horizontal reference evaluation data corresponding to the data horizontal analysis model according to first historical time point data corresponding to at least one historical time point for each historical source market data;

[0145] The vertical data determination unit is specifically configured to determine vertical reference evaluation data corresponding to the data vertical analysis model according to second historical time point data corresponding to each historical source market data at a specified historical time point.

[0146] Optionally, on the basis of each of the above embodiments, the analysis result obtaining module 303 can specifically include:

[0147] a transverse result obtaining unit configured to obtain, as input data of a data transverse analysis model, target source market data selected from each of the current source market data, and obtain a transverse data analysis result output by the data transverse analysis model in combination with transverse reference evaluation data corresponding to the target source market data;

[0148] Specifically, the transverse result obtaining unit can be specifically configured to:

[0149] perform difference calculation on the target source market data and the transverse reference evaluation data to obtain first floating data;

[0150] if the first floating data is less than a first floating threshold, determine each of the target source market data as first qualified market data, and use the first qualified market data as the transverse data analysis result of the data transverse analysis model.

[0151] a longitudinal result obtaining unit configured to use each of the current source market data as input data of a data longitudinal analysis model, and obtain a longitudinal data analysis result output by the data longitudinal analysis model in combination with the longitudinal reference evaluation data.

[0152] Specifically, the longitudinal data result obtaining unit can be specifically configured to:

[0153] determine a difference between each of the current source market data and the longitudinal reference evaluation data to obtain a second floating data sequence;

[0154] determine second floating data less than a second floating threshold in the second floating data sequence, and determine current source market data respectively associated with each of the second floating data as second qualified market data;

[0155] use each of the second qualified market data as the longitudinal data analysis result of the data longitudinal analysis model.

[0156] Optionally, on the basis of each of the above embodiments, the data publishing module 304 can specifically include:

[0157] a target data screening unit configured to screen a target market data based on first qualified market data in the transverse data analysis result and each of second qualified market data contained in the longitudinal data analysis result;

[0158] a publishing data determining unit configured to process the target market data by using a set market data adjustment strategy and threshold supervision condition to obtain publishing market data of the target product.

[0159] Optionally, the apparatus can further include:

[0160] The data quality analysis module is configured to, after obtaining the release market data of the target product, determine a quality analysis report of the target product based on the release market data and in combination with at least one quality analysis model previously set.

[0161] Optionally, the quality analysis model previously set includes a quality random analysis model, a quality reverse analysis model and a quality extreme analysis model.

[0162] Correspondingly, the data quality analysis module can be specifically configured to:

[0163] The quality random analysis model is configured to randomly select historical random data of the target product from the market database.

[0164] The historical random data are compared with each current source market data and the release market data respectively.

[0165] The comparison result is taken as a piece of quality analysis information of the quality analysis report corresponding to the target product.

[0166] Optionally, the data quality analysis module can be specifically configured to:

[0167] The quality reverse analysis model is configured to perform reverse calculation on each current source market data by using a set reverse calculation rule to obtain corresponding reverse market data.

[0168] The release market data are compared with each reverse market data, and the comparison result is taken as a piece of quality analysis information of the quality analysis report corresponding to the target product.

[0169] Optionally, the data quality analysis module can be specifically configured to:

[0170] The quality extreme analysis model is configured to determine a market data floating interval of the target product based on historical market data of the target product in the market database.

[0171] The release market data are compared with the market data floating interval, and the comparison result is taken as a piece of quality analysis information of the quality analysis report corresponding to the target product.

[0172] Embodiment Four

[0173] Figure 4 A structural schematic diagram of an apparatus / terminal / server provided for the fourth embodiment of the present application is shown in FIG. 4, which includes a processor 401, a memory 402, an input device 403 and an output device 404. The number of processors 401 in the apparatus / terminal / server can be one or more. Figure 4 Figure 4 ​The processor 401 in the device / terminal / server, the memory 402, the input device 403 and the output device 404 can be connected through a bus or other means, Figure 4 The processor 401 in the device / terminal / server, the memory 402, the input device 403 and the output device 404 can be connected through a bus or other means,

[0174] The memory 402 is a computer readable storage medium, which can be used to store software programs, computer executable programs and modules, such as program instructions / modules (for example, the current data extraction module 301, the reference data determination module 302, the analysis result obtaining module 303 and the data publishing module 304) of the market data management method in the embodiment of the application. The processor 401 executes the software programs, instructions and modules stored in the memory 402, thereby performing various functional applications and data processing of the device / terminal / server, that is, implementing the market data management method described above.

[0175] The memory 401 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and application programs required by at least one function; the data storage area can store data created according to the use of the terminal and the like. In addition, the memory 402 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device or other non-volatile solid-state memory device. In some examples, the memory 402 can further include a memory remotely arranged with respect to the processor 401, which can be connected to the device / terminal / server through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0176] The input device 403 can be used to receive input digital or character information, and generate key signal input related to the user settings and function control of the device / terminal / server. The output device 404 can include a display device such as a display screen.

[0177] Embodiment five

[0178] The embodiment five of the application further provides a storage medium containing computer executable instructions, which are used to execute a market data management method when executed by a computer processor, and the method comprises the following steps:

[0179] Extracting at least one current source market data of a target product from a preset data cache table;

[0180] Determining reference evaluation data corresponding to at least one preset data analysis model based on historical source market data of the target product stored in a market database;

[0181] Select input data of each data analysis model from current source market data, combine with corresponding benchmark evaluation data, and obtain data analysis results output by each data analysis model;

[0182] According to the data analysis results, determine the release market data of the target product.

[0183] Of course, the storage medium provided by the embodiment of the present application includes computer executable instructions, which are not limited to the method operations described above, and can also perform related operations in the market data management method provided by any embodiment of the present application.

[0184] Through the above description of the embodiments, those skilled in the art can clearly understand that the present application can be realized by software and necessary general hardware, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solutions of the present application or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a FLASH, a hard disk or an optical disk, etc., including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the method described in each embodiment of the present application.

[0185] It is worth noting that in the above embodiment of the search device, each unit and module included is only divided according to functional logic, but is not limited to the above division, as long as the corresponding function can be realized; in addition, the specific name of each functional unit is only for easy distinction, and does not limit the protection scope of the present application.

[0186] Note that the above is only the preferred embodiment of the present application and the technical principle applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and those skilled in the art can make various obvious changes, readjustments and substitutions without departing from the scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A market data management method, characterized in that, include: Extract at least one current source market data for the target product from a preset data cache table; wherein, the preset data cache table is a cached data table in the cache server that is set in advance to store the source market data that comes in in real time; Based on the historical source market data stored in the market database relative to the target product, determine the benchmark evaluation data corresponding to at least one pre-set data analysis model; Input data is selected from various current market data sources and used to input data into each data analysis model. Combined with corresponding benchmark evaluation data, the data analysis results output by each data analysis model are obtained. Before selecting input data from various current market data sources, the input market data is processed and parsed. The processed and parsed data is then used as input data into each data analysis model. Based on the data analysis results, the release market data for the target product is determined; The pre-defined data analysis models include: horizontal data analysis models and vertical data analysis models; Accordingly, determining the benchmark evaluation data corresponding to each pre-set data analysis model based on the historical source market data stored in the market database relative to the target product includes: Retrieve historical market data of the target product from various sources from a pre-set market data database; For each source of historical market data, based on the first historical time point data corresponding to at least one historical time point, determine the horizontal benchmark evaluation data corresponding to the horizontal analysis model of the data. Based on the second historical time point data corresponding to the historical market data of each source at a specified historical time point, determine the longitudinal benchmark evaluation data corresponding to the data longitudinal analysis model; The data horizontal analysis model is used to analyze the comparison between historical market data of a target product over a certain period of time, after data processing, and the current source market data of the target product. The data longitudinal analysis model is used to analyze the current source market data in each preset cache table of the target product after data processing and compare it with the current real-time source market data of the target product. Specifically, the input data for each data analysis model is selected from various current market data sources and combined with corresponding benchmark evaluation data to obtain the data analysis results output by each data analysis model, including: Select any target source market data from the current source market data as the input data for the data horizontal analysis model, and combine it with the horizontal benchmark evaluation data corresponding to the target source market data to obtain the horizontal data analysis results output by the data horizontal analysis model; The current market data from various sources is used as input data for the longitudinal data analysis model. Combined with the longitudinal benchmark evaluation data, the longitudinal data analysis results output by the longitudinal data analysis model are obtained. The step of determining the release market data of the target product based on the data analysis results includes: Based on the first qualified market data in the horizontal data analysis results and the second qualified market data included in the vertical data analysis results, a target market data is obtained by filtering. The target market data is processed using a set market data adjustment strategy and threshold monitoring conditions to obtain the release market data of the target product; After determining the market data for the target product based on the analysis results of each of the aforementioned data, the method further includes: Based on the published market data and combined with at least one pre-set quality analysis model, a quality analysis report for the target product is determined.

2. The method according to claim 1, characterized in that, The process of combining the target source market data with the corresponding horizontal benchmark evaluation data set to obtain the horizontal data analysis results output by the horizontal data analysis model includes: The difference between the target source market data and the horizontal benchmark evaluation data is calculated to obtain the first floating data; If the first floating data is less than the first floating threshold, each of the target source market data is determined as the first qualified market data and used as the horizontal data analysis result of the horizontal data analysis model.

3. The method according to claim 1, characterized in that, The process of combining the longitudinal benchmark evaluation data to obtain the longitudinal data analysis results output by the longitudinal data analysis model includes: Determine the difference between each current source market data and the longitudinal benchmark evaluation data to obtain the second floating data sequence; Identify the second floating data in the second floating data series that is less than the second floating threshold, and determine the current source market data associated with each of the second floating data as the second qualified market data; Each of the second qualified market data is used as the longitudinal data analysis result of the data longitudinal analysis model.

4. The method according to claim 1, characterized in that, The process of determining a quality analysis report for the target product based on the published market data and at least one pre-defined quality analysis model includes: The quality reverse analysis model uses the set reverse calculation rules to perform reverse calculations on each current source market data to obtain the corresponding reverse market data. The published market data is compared with each of the reverse market data, and the comparison result is used as a quality analysis information in the quality analysis report corresponding to the target product.

5. The method according to claim 1, characterized in that, The process of determining a quality analysis report for the target product based on the published market data and at least one pre-defined quality analysis model includes: Using a quality stochastic analysis model, historical random data relative to the target product is randomly selected from the market data database. The historical random data is compared with each current source market data and the published market data; The comparison result will be used as a quality analysis piece of information in the quality analysis report corresponding to the target product.

6. The method according to claim 1, characterized in that, The process of determining a quality analysis report for the target product based on the published market data and at least one pre-defined quality analysis model includes: Using a quality extreme analysis model, the fluctuation range of the target product's market data is determined based on historical market data relative to the target product in the market database. The published market data is compared with the fluctuation range of the market data, and the comparison result is used as a quality analysis information in the quality analysis report corresponding to the target product.

7. A market data management system, characterized in that, The system includes: The current data extraction module is used to extract at least one current source market data of the target product from a preset data cache table; wherein, the preset data cache table is a cached data table in the cache server that is set in advance and is used to store the source market data that comes in in real time; The benchmark data determination module is used to determine benchmark evaluation data corresponding to at least one pre-set data analysis model based on historical source market data stored in the market database relative to the target product. The analysis result acquisition module is used to select input data from various current source market data and input it into each of the data analysis models. Combined with the corresponding benchmark evaluation data, the module obtains the data analysis results output by each data analysis model. Before selecting input data from various current source market data and inputting it into each data analysis model, the module processes and parses the input market data and inputs the processed and parsed data into each data analysis model. The data publishing module is used to determine the market data for the target product based on the data analysis results. The analysis result acquisition module specifically includes: a horizontal result acquisition unit, used to select any target source market data from each current source market data as input data for the horizontal data analysis model, and combine it with the horizontal benchmark evaluation data corresponding to the target source market data to obtain the horizontal data analysis result output by the horizontal data analysis model; and a vertical result acquisition unit, used to take each current source market data as input data for the vertical data analysis model, and combine it with the vertical benchmark evaluation data to obtain the vertical data analysis result output by the vertical data analysis model. The data publishing module specifically includes: a target data filtering unit, which is used to filter and obtain a target market data based on the first qualified market data in the horizontal data analysis results and the second qualified market data included in the vertical data analysis results; and a publishing data determination unit, which is used to process the target market data using a set market data adjustment strategy and threshold regulatory conditions to obtain the publishing market data of the target product. The system further includes a data quality analysis module, which, after obtaining the market data for the target product, determines a quality analysis report for the target product based on the market data and in conjunction with at least one pre-set quality analysis model.

8. A computer device, characterized in that, include: One or more processors, Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement a market data management method as described in any one of claims 1-6.

9. A computer storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements a market data management method as described in any one of claims 1-6.

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