CN109934701B - Risk assessment method and device for share right pledge - Google Patents
Risk assessment method and device for share right pledge Download PDFInfo
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Abstract
The invention relates to the field of investment and financing, in particular to a risk assessment method and a device for share pledge, wherein the method comprises the following steps: synchronizing bottom-layer original data into a kudu database through a Binlog process; performing multi-table correlation calculation on original data in the kudu database through Impala SQL to obtain an intermediate result table; reading an intermediate result table in the kudu database through a TAF process, performing risk evaluation operation according to share right pledge data in the table, and storing a risk evaluation result into Redis; and providing the content of the share pledge service through an external interface of the TAF framework so that a user can obtain a risk assessment result. According to the method, the kudu synchronization is adopted, the multi-table correlation calculation is carried out by utilizing the distributed calculation characteristic of the big data platform, the complex risk evaluation operation is carried out through the TAF service, the obtained evaluation result can help the stockholders to know the risk of the company share pledge, and the method has a high reference value.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the field of investment and financing, in particular to a risk assessment method and device for share pledge.
[ background of the invention ]
In recent years, under the background of leveraging macro-economy, enterprise financing is difficult, and share-right pledge is used as a financing means and is used by the enterprise capitalization as a means for supplementing company liquidity. The share right pledge is specifically a financing behavior that stockholders pledge shares to security traders to obtain financing funds, and is essentially a financing behavior that stocks are mortgages, the security traders collect financing fees, and the pledge is released after the expiration, and the stocks are assigned to the stockholders. If the market value of the pledge stock account is lower than the early warning line, the replenishment is required; if the market value of the pledge stock account is lower than the tie line, the dealer has the right to sell the stock directly to ensure the safety of the capital.
Because A shares of the capital investment are not in a halt, the stock prices of a plurality of companies are chopped, a plurality of stock prices touch the pre-warning price and the flat stock price, and once a large number of stocks of the capital investment of the east stock touch the flat stock price, if the stocks are not timely replenished, the stocks suffer from the risk of strong flatness, and the situation can bring two important influences: firstly, a financial institution discards a large amount of company stocks in a second-level market, and further promotes the company stock price to drop; secondly, strong expectation causes the second-class market sharers to generate panic emotion, thereby throwing off a large amount of company stocks. Under the condition, if the stockholders cannot know the company pledge status in time, the risk of the company pledge is difficult to be effectively evaluated, and further investment risk is brought. Although some products such as APP related to stocks can help the stockholders to know the company pledge status, most of the products have the problems of long time consumption in the aspects of data storage, data synchronization, data calculation and the like, and are poor in stability, and comprehensive and systematic evaluation and prejudgment are not performed on pledge risks, so that the stockholders cannot know the company pledge risks in time; the related share right pledge data source can not be presented to the stock, so that the stock can not trace the source to perform information return visit and can not judge the credibility of the related data; and the external interface is slowly called, and the user experience is poor.
In view of the above, it is an urgent problem in the art to overcome the above-mentioned drawbacks of the prior art.
[ summary of the invention ]
The technical problems to be solved by the invention are as follows:
when a company has a share right pledge, the traditional method consumes long time in the aspects of data storage, data synchronization, data calculation and the like, comprehensive and systematic evaluation and prejudgment are not carried out on pledge risks, and stockholders cannot know the risk of the share right pledge of the company in time; the related share right pledge data source can not be presented to the shareholders, the information return visit can not be carried out by tracing the source, and the credibility of the related data is difficult to judge; the external interface is slow to call, and the user experience is poor.
The invention achieves the above purpose by the following technical scheme:
in a first aspect, the present invention provides a risk assessment method for a stock right pledge, including:
synchronizing various original data related to the share right pledge in the bottom database into the kudu database through a Binlog process;
performing multi-table correlation calculation on various original data in the kudu database through Impala SQL to obtain a corresponding share right pledge intermediate result table;
reading an intermediate result table in the kudu database through a TAF process, performing risk evaluation operation according to share right pledge data in the intermediate result table, and storing a finally obtained risk evaluation result into Redis;
and providing the content of the share pledge service through an external interface of the TAF framework so that the user can obtain a corresponding risk assessment result.
Preferably, the risk assessment operation specifically includes:
estimating a flat price based on the share right pledge data in the intermediate result table, and calculating the risk score of each pledge according to the distance between the share price of each pledge and the flat price;
and taking the proportion of the number of the stocks of each pledge to the total pledge number as weight, and performing weighted calculation on the risk scores of each pledge to obtain first comprehensive risk scores of all pledges so that the user can determine the risk of the pledge of the right of the stock according to the first comprehensive risk scores.
Preferably, after obtaining the first composite risk score of all pledges through weighted calculation of the risk score of each pledge, the method further comprises:
determining a corresponding risk coefficient according to the proportion of the total pledges in the total stock, and combining the first comprehensive risk score and the risk coefficient to obtain a second comprehensive risk score;
and determining the proportion of the single-stranded east pledge in the stock book held by the single-stranded east pledge, and when the proportion of the single-stranded east pledge exceeds the preset proportion, adding a preset value on the basis of the second comprehensive risk score to obtain a third comprehensive risk score so that the user can determine the risk of the share-right pledge according to the third comprehensive risk score.
Preferably, the interface mode of the external interface of the TAF frame is specifically:
the TAF has a protocol calling interface; alternatively, the HTTP post request invokes the interface.
Preferably, the original data includes one or more items of listed company pledge announcement content, share right pledge related statistical information, information of each shareholder of the listed company, historical stock price of the listed company and historical card stop information; wherein the data source of the raw data comprises one or more of financial data, market data, and crawler data.
Preferably, before performing the risk assessment operation, the method further comprises:
respectively establishing corresponding access links according to data source positions corresponding to various original data, and scoring the credibility of the various original data based on a data source;
and after risk assessment operation is carried out, storing the data source access link and the credibility scoring result corresponding to each original data into Redis along with the risk assessment result so as to be conveniently acquired by a user.
Preferably, after the credibility scoring is performed on the various original data based on the data source, the credibility scoring results of the various original data are compared with a preset scoring value to judge the credibility of the various original data;
and when the risk assessment operation is carried out, discarding the original data with the credibility score smaller than the preset score value, and only carrying out calculation according to the original data with the credibility score larger than or equal to the preset score value.
Preferably, before performing the risk assessment operation, the method further comprises:
matching data contents of the same original data from different data sources; if the data contents are not matched in a consistent manner, comparing the information release time nodes corresponding to the same kind of original data from different data sources to judge the sequence of the time nodes;
calculating according to the data at the most rear of the time node when risk assessment operation is carried out; or continuously judging the credibility score corresponding to the most posterior data of the time node, and if the corresponding credibility score is greater than or equal to a preset score value, calculating based on the most posterior data of the time node.
Preferably, when the risk assessment operation is performed, a time tag is set for the risk assessment result according to the time node of the operation, and the time tag is stored in Redis together with the risk assessment result, so that the risk assessment result finally obtained by the user carries the corresponding time tag.
In a second aspect, the present invention further provides a risk assessment apparatus for a stock right pledge, including at least one processor and a memory, where the at least one processor and the memory are connected through a data bus, and the memory stores instructions executable by the at least one processor, and the instructions are used to complete the risk assessment method for a stock right pledge according to the first aspect after being executed by the processor.
Compared with the prior art, the invention has the beneficial effects that:
according to the share right pledge risk assessment method, kudu synchronization is adopted, bottom layer original data are synchronized into kudu through a Binlog process, multi-table correlation calculation is carried out by utilizing the high throughput and distributed calculation characteristics of a large data platform to obtain a corresponding intermediate result table, then complicated risk assessment calculation is carried out through TAF service, the data processing time consumption is short, the obtained assessment result can help the sharers to know the risk of the company share right pledge, and the light of a lighthouse in a chaotic market is found; meanwhile, the stockholders can directly acquire related data sources and credibility scores, so that the information return visit and the data credibility judgment can be facilitated by tracing the sources, and the user experience is improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 is a flowchart of a risk assessment method for a stock pledge according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a risk assessment operation process of a stock pledge according to an embodiment of the present invention;
fig. 3 is a block diagram illustrating the architecture level design and data flow of a share pledge product according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating an evaluation result obtained through an HTTP request according to an embodiment of the present invention;
FIG. 5 is a flowchart of a risk assessment algorithm according to an embodiment of the present invention;
fig. 6 is a business logic block diagram of a risk assessment operation according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating the effect of proportional trend of the pool right pledge according to the embodiment of the present invention;
FIG. 8 is a diagram illustrating the effect of the share pledge statistics according to the present invention;
FIG. 9 is a diagram illustrating the effect of the risk level of the equity pledge according to the embodiment of the present invention;
fig. 10 is an architecture diagram of a risk assessment device for a stock pledge according to an embodiment of the present invention.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below 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 are not intended to limit the invention.
The intelligent terminal of the embodiments of the present invention may exist in various forms, including but not limited to:
(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications. Such terminals include smart phones (e.g., iphones), multimedia phones, and functional phones, among others.
(2) Ultra mobile personal computer device: the equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include: PDA, MID, and UMPC devices, etc., such as ipads.
(3) A portable entertainment device: such devices can display and play video content, and generally also have mobile internet access features. This type of device comprises: video players, handheld game consoles, and intelligent toys and portable car navigation devices.
Meanwhile, the basic definitions and formulas used in the estimation of the flat-bin prices in example 1 are described:
(1) financing cost: the fee collected by security dealer in the process of stock right pledge financing is generally 8-10%;
(2) stock base price: taking the arithmetic mean of 20 trading days before the pledge date as a reference price;
(3) the mass retention rate: taking the stock as a mortgage, multiplying a coefficient as a value reference, wherein the coefficient is the mortgage rate;
(4) initial trading price (pledge price): stock base price · pledge rate;
(5) total amount of financing: initial trading price:numberof pledges;
(6) annual financing interest: total financing amount is financing cost;
(7) daily financing interest: annual financing interest/365;
(8) leveling line ratio: generally taking 140 percent; the ratio of the early warning lines: the proportion is generally 160%.
In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other. The invention will be described in detail below with reference to the figures and examples.
Example 1:
the embodiment of the invention develops a corresponding share pledge function based on a share pledge product, provides a risk evaluation method of the share pledge, and can help the share to know the company pledge condition and predict the risk. The share pledge product generally refers to an APP with a related function, and when the user uses the APP through the intelligent terminal, the risk assessment result of the share pledge can be obtained.
As shown in fig. 1, the risk assessment method provided by the embodiment of the present invention includes:
and step 10, synchronizing various original data related to the share right pledge in the bottom database into the kudu database through a Binlog process.
In combination with the process flow of the share-right pledge operation shown in fig. 2 and the data flow direction in the share-right pledge product shown in fig. 3, the bottom database (i.e., MySQL database in the figure) is mainly used to store various data related to the most original share-right pledge, which is called original data for short. The original data comprises one or more items of data such as the mortgage announcement content of the listed company, the related statistical information of the share right mortgage, the information of each shareholder of the listed company, the historical stock price and the historical card stop information of the listed company and the like. The data sources of the original data mainly comprise financial data, market data and crawler data; the financial data refers to data provided by a financial service provider, the market data refers to data provided by a market center, and the crawler data refers to data provided by each media, website, and the like.
The big data platform dependent on the share weight pledge storage calculation can use Hadoop, HDFS, ZOOKEEPER, kudu, SPARK and other related components, and is subjected to dimension degradation on the aspect of use by combining with a data real-time synchronization component Binlog, so that the understanding and the service development of developers are facilitated. According to the embodiment of the invention, a kudu synchronization mode is adopted, and by monitoring the change of the MySQL database in real time, various underlying original data can be synchronized into the kudu database by a MySQL Binlog process through TAF service, wherein the kudu database is a middle-layer large data platform.
the maximum computing advantage of the middle-layer big data platform is distributed computing capacity and MapReduce characteristics, so that the middle-layer big data platform has the capacity of rapidly reading mass data and performing multi-table associated data query. With continuing to combine with fig. 2 and fig. 3, in the middle-layer big data platform, according to the business requirements, the multi-table correlation calculation of the mass data is performed through Impala SQL by using the high throughput and distributed calculation characteristics of the big data platform, the information associated tables distributed in various tables and related to the share-right pledge are queried, a plurality of new intermediate tables of the share-right pledge products are stored, and the corresponding intermediate result table of the share-right pledge is obtained, so that the data processing is rapid and the time consumption is short.
And step 30, reading an intermediate result table in the kudu database through the TAF process, performing risk evaluation operation according to share right pledge data in the intermediate result table, and storing the finally obtained risk evaluation result into Redis.
In the embodiment of the invention, for the part of complex logic operation in the share right pledge, the post-processing of TAF service is needed. Continuing to refer to fig. 2 and fig. 3, after the middle layer data linkage table is processed and calculated, the middle layer TAF data analysis is performed, in this layer, the TAF process exports share right pledge data in the middle result table from the big data platform kudu database, and performs complex logic operation including risk assessment operation, early warning price calculation, flat stock price calculation and the like according to the share right pledge data, and then stores the finally obtained risk assessment result into Redis, which is convenient for the interface layer to read. The complex logic operation in the embodiment of the invention is mainly risk assessment operation, namely corresponding risk scoring is carried out according to the share right pledge condition of listed companies for the reference of users.
And step 40, providing the content of the share pledge service through an external interface of the TAF framework so that the user can obtain a corresponding risk assessment result.
In the embodiment of the invention, the external interface service developed by the TAF framework provides a stable and high-concurrency external interface, and the interface mode can use a TAF self-protocol calling interface, namely, a TAF client calls a TAF server interface; an HTTP POST request retrieval interface may also be used, that is, an external service accesses the result data set through an HTTP POST request to obtain a risk assessment result in a Jason format, as shown in fig. 4, so that a user may obtain data more conveniently, flexibly, and efficiently. For convenience of deployment and use of clients, the content of the share pledge service can be provided externally through the HTTP interface, and at the moment, only one authentication service with a unique port needs to be provided externally, and data is returned in a jason format.
The result data set in fig. 4 is a data set of the risk assessment result, that is, data that the corresponding share right pledge APP product can provide to the user, and mainly includes stock codes of the listed company, the current stock price, the total risk score of the share right pledge situation of the listed company, the trend of the number of the share right pledge stocks of the listed company in the recent year, and the trading data of each share right pledge, and the like, where the trading data of each share right pledge further includes the share right of the listed company, the number of the share right of the. Therefore, through the external interface of the TAF framework, the user can obtain any share right pledge data in the result data set, not only the risk score; specifically, the user can realize the switching of the display page through actions such as clicking and sliding on the corresponding share pledge APP product, so that the corresponding risk assessment result can be browsed.
The share-right pledge risk assessment method provided by the embodiment of the invention adopts a kudu synchronization mode, various original data at the bottom layer are synchronized into kudu through a Binlog process, multi-table correlation calculation is carried out by utilizing the distributed calculation characteristic of a large data platform to obtain an intermediate result table, risk assessment operation is carried out through TAF service, the data source is wide, the calculation is accurate and fast, the obtained assessment result can help the stakeholders to know the risk of the company share-right pledge, and the light of a lighthouse in a chaotic market is found; and the external interface service developed through the TAF framework can provide a stable and high-concurrency external interface, so that the user experience is improved.
In step 30, the process of the risk assessment operation may refer to fig. 5, which specifically includes:
This step carries out risk scoring for each pledge, wherein the estimation of the flat price is as follows: the flat bin price is the number of flat bin lines/pledges; assuming that the pay-per-day ratio is 30 days, the flat rate is (total financing amount + 30 financing interest per day) and is typically 140%. After the flat-price is determined, a risk score is calculated for each pledge, for example: assuming that the current stock price falls by t% to reach the flat stock price, when t > is 50, the score x is 0; when 0< t <50, the score x is 100-2 x t; when t < > 0, the score x is 100. Of course, the specific score can be flexibly set according to the actual situation, and is not limited uniquely.
And step 302, taking the ratio of the number of the shares of each pledge to the total pledge number as a weight, and obtaining first comprehensive risk scores of all pledges through weighted calculation of the risk scores of each pledge so that a user can determine the risk of the pledge according to the first comprehensive risk scores.
In the step, the comprehensive risk score is carried out on all the pledges according to the risk score x of each pledge. For any pledge, assuming the number of pledges is m, and the number of all pledges currently in the pledge is n, the weight of the pledge is y ═ m/n × 100%. After determining the weight value of each pledget, the first composite risk score p for all pledgets is the sum of x y for each pledget.
With reference to fig. 6, the steps 301 and 302 mainly calculate the risk value from the price dimension, and the pledge basic data in the figure is the share pledge data extracted from the intermediate result table. Generally, price factors are the most important factors influencing risk assessment, and a first comprehensive risk score p is obtained through price and then can be directly stored in Redis, so that a user can obtain the first comprehensive risk score p through a corresponding APP product, and then the share right pledge risk is preliminarily determined according to the score p.
And 303, determining a corresponding risk coefficient according to the proportion of the total pledge in the total stock, and combining the first comprehensive risk score and the risk coefficient to obtain a second comprehensive risk score.
In the actual evaluation, the total pledge proportion is also an important attention index, and when the total pledge shares account for the total stock account is too large, once a pledge risk occurs, a serious consequence will be generated. Thus, in addition to considering price considerations, this step further calculates risk values starting from the overall pledge scale dimension. Taking the total pledge proportion as a coefficient, namely a risk coefficient g, the second composite risk score F ═ p × g is finally obtained after the total pledge proportion is considered.
Further, since the total pledge proportion is an important attention index, besides being used for calculating the risk score, the total pledge proportion trend graph can be presented in a graph mode in a certain time dimension, as shown in fig. 7, when the user obtains a corresponding risk assessment result, the user can simultaneously obtain the corresponding share pledge proportion trend graph to help the citizens pay attention to the total pledge risk. Wherein, the time dimension can be flexibly set, such as the last year; if the time to market does not expire a year, the start time may be counted from the time to market.
And 304, confirming the proportion of the single-stranded eastern pledge in the held stock book, and when the proportion of the single-stranded eastern pledge exceeds the preset proportion, adding a preset value on the basis of the second comprehensive risk score to obtain a third comprehensive risk score so that the user can determine the risk of the equity pledge according to the third comprehensive risk score.
In actual evaluation, too large proportion of single-stranded east pledge is also a relatively large risk, so in the step, pledge statistics is further carried out from the dimensionality of the single-stranded east pledge proportion, and a risk value is calculated; the statistical range is the stock in the pledge at present, and the proportion of the pledge of each stockholder in the stock held by the stockholder is counted according to the stockholders. The preset proportion and the preset value can be flexibly set according to actual conditions, and if the preset value is a, in the embodiment, the risk is high when the single-stranded eastern pledge proportion exceeds 50%, the risk is medium when 20% -50%, and the risk is low when the risk is less than 20%, the preset proportion can be 50%. If the number of stockholder pledges accounts for more than 50% of the held stock tickets, the risk level needs to be improved, the second comprehensive risk score F can be increased by a, and a third comprehensive risk score F' is obtained; the risk may not be adjusted, or a value smaller than a may be added based on the original F, which is not limited herein.
Meanwhile, the data of the single-stranded east pledge proportion can be presented to the user, as shown in fig. 8, when the user obtains a corresponding risk assessment result, the corresponding single-stranded east pledge proportion condition can be obtained at the same time, the stockholder can be helped to see out the stockholder with the higher pledge proportion at a glance, and the risk can be known in time.
As can be seen from fig. 6, the embodiment of the present invention starts with three dimensions of price, total pledge proportion and single-east pledge proportion, comprehensively considers various factors related to pledges, and calculates a simple result, i.e., a final risk score F', by using a complex logic algorithm, thereby helping the stakeholders to know the pledge risk of the company at a glance.
Further, in order to present the risk assessment result to the stockholders more intuitively, the final third comprehensive risk score F ' may be subjected to risk grade division, where the smaller the F ', the lower the risk grade, and the larger the F ', the higher the risk grade. Taking fig. 9 as an example, the pledge risk is divided into five levels from low risk to high risk, and the current pledge risk level is high risk. Different risk levels can be represented by different colors in the graph, for example, the color can be gradually deepened from low risk to high risk, and the color is dark red when the color is high risk, so that the visual effect is further enhanced through gradual change and contrast of the color, and the citizens can know the pledge risk more intuitively.
In summary, according to the risk assessment method provided by the embodiment of the invention, a user can obtain a required pledge risk assessment result by using a corresponding share pledge APP product, and corresponding risk scores and risk levels are displayed on a display page for the user to browse. Meanwhile, the corresponding share-right pledge proportion trend graph, single-east pledge proportion data and other related share-right pledge original data and the like can be browsed through page switching, and various information can be acquired.
As can be seen from fig. 2, the data sources are from three parties, and a channel credibility score can be further fed back for each source of the data, especially for crawler data, which is obtained from each media website in a manner that there is a large uncertainty in the true validity of the data. Thus, prior to performing the risk assessment operation, the method further comprises:
and respectively establishing corresponding access links according to data source positions corresponding to the various original data, and scoring the credibility of the various original data based on the data sources. Wherein, the access link is established to facilitate the subsequent access of the user; the credibility scoring can be performed according to the accuracy of the historical data of the corresponding data source, for example, for data provided by a certain website in the crawler data, if the accuracy of the information of the website is higher according to historical statistics, the corresponding original data can be given a higher credibility scoring, otherwise, a lower credibility scoring is given; market data and financial data may also be performed using similar means.
After the risk assessment operation is performed, the original data, the corresponding data source access link and the credibility scoring result can be directly stored into Redis together with the risk assessment result. Therefore, when the user browses the risk assessment result subsequently, the data source position and the credibility score thereof can be obtained deeply and hierarchically. For example, when a user performs a click operation on a presented risk assessment result interface, the interface is switched to form content presentation of a data source, and a corresponding data source access link and a credibility scoring result are given, so that a return visit function of information corresponding to the user is given, and the user can obtain a final risk assessment result and trace back to a source to obtain a corresponding data source. Furthermore, after the risk assessment operation is performed, the reliability comprehensive scoring can be performed on the obtained risk assessment result based on the reliability scoring of various original data, and the risk assessment result is stored in Redis so as to be conveniently obtained by a user.
For the original data with lower credibility score, if the original data is continuously used for subsequent risk assessment operation, the accuracy of the final risk assessment result is undoubtedly influenced. Therefore, a score value can be preset as a reference according to the actual situation, namely the preset score value; generally, the reliability of the raw data with the reliability score larger than or equal to the preset score value is higher, and the reliability of the raw data with the reliability score smaller than the preset score value is lower. Therefore, after the credibility scoring is carried out on various original data based on the data source, the credibility scoring results of the various original data can be compared with the preset scoring value so as to judge the credibility of the various original data; when the risk assessment operation is carried out, the original data with the credibility score smaller than the preset score value are discarded, and the calculation is carried out only according to the original data with the credibility score larger than or equal to the preset score value, so that the accuracy of the final result is ensured.
Further, since data of the stock market is updated faster, the latest data is more practical for the same kind of data. Therefore, considering the time problem of the data, before performing the risk assessment operation, the method further comprises:
matching data contents of the same original data from different data sources; and if the data contents are not matched and consistent, comparing the information release time nodes corresponding to the same kind of original data from different data sources to judge the sequence of the time nodes. Then, when the risk assessment operation is performed, calculation is performed based on the data at the most back of the time node. For example, information of each shareholder of company a can be obtained from three data sources (namely, market data, financial data and crawler data), the information under the three data sources is subjected to data content matching, if the matching is consistent, namely, the information of each shareholder of company a from different data sources is the same, the accuracy of the information is higher, and the information can be directly used for subsequent risk assessment operation; and if the matching is inconsistent, the publishing time nodes of the information in the three data sources need to be further compared, if the publishing time of the market data is later than that of the financial data and later than that of the crawler data, the information of all the stakeholders of the company A in the market data can be judged to belong to the latest data, the accuracy is higher, and therefore the information of all the stakeholders of the company A in the market data is used for subsequent risk assessment operation.
In order to further ensure the accuracy of the data, reliability evaluation can be added on the basis of time node judgment, namely after the time nodes of all data are compared, reliability scores corresponding to the data closest to the time nodes are continuously judged, and if the corresponding reliability scores are larger than or equal to a preset score value, calculation is carried out on the data closest to the time nodes; if the corresponding credibility score does not reach the standard (i.e. is smaller than the preset score value), the node is not adopted even after the time node is later. For example, after the information of each shareholder of company a in the travel situation data is judged to belong to the latest data, the credibility score of the data is further compared with the preset score value; if the credibility score is greater than or equal to the preset score value, the data can be continuously adopted for operation; if the credibility score is smaller than the preset score value, the accuracy of the data is reduced, the process can be returned to the next step, the data next to the time node is selected, and the evaluation process is repeated.
In addition to the comparison of the information distribution time nodes of the same kind of original data in different data sources, in an alternative scheme, a preset time point can be directly obtained according to requirements, data of the information distribution time before the preset time point is filtered out when risk assessment operation is carried out, and data of the information distribution time after the preset time point is selected for calculation, so that the effectiveness of the data is ensured. For example, data within a month may be selected for calculation, and data one month ago may be considered for the while.
Accordingly, since the data in the stock market is updated quickly, various original data may be updated continuously, and thus the risk assessment operation for the share pledge is also updated regularly, such as every few hours or every day; the newer evaluation results can be regarded as more effective and the reference meaning is larger. Therefore, when risk assessment operation is performed, a time tag can be set for the risk assessment result according to the time node of the operation, and the time tag is stored in Redis together with the risk assessment result, so that the risk assessment result finally obtained by a user carries the corresponding time tag. That is to say, when the user browses the risk assessment result through the APP product, the corresponding assessment result generation time may be presented on the display page at the same time, for example, the assessment result corresponding to the page display is calculated according to the data before 1 hour, and the user may judge that the assessment result is relatively new, so that the user has a relatively high reference value.
By the method, the stockholders can directly acquire the related data source and credibility score according to the risk assessment result, and the return visit function of the corresponding information of the users is given, so that the method is beneficial to root and source tracing of the users, more intuitively judges the credibility of the data, and avoids the lightning risk. Meanwhile, the judgment of the time node and the setting of the time label are added, so that the effectiveness of the data can be ensured, the effectiveness of the evaluation result is further ensured, and the reference value is increased.
Example 2:
on the basis of the risk assessment methods for the share pledge provided in the above embodiments 1 and 2, the present invention further provides a share pledge risk assessment apparatus for implementing the above methods, as shown in fig. 10, which is a schematic diagram of an apparatus architecture in an embodiment of the present invention. The risk assessment device of the stock pledge of the present embodiment includes one or more processors 21 and a memory 22. In fig. 10, one processor 21 is taken as an example.
The processor 21 and the memory 22 may be connected by a bus or other means, and fig. 10 illustrates the connection by a bus as an example.
The memory 22, as a non-volatile computer-readable storage medium for the risk assessment method of the share pledge, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the risk assessment method of the share pledge in embodiment 1. The processor 21 executes various functional applications and data processing of the risk assessment device of the stock right pledge by running the nonvolatile software program, instructions and modules stored in the memory 22, that is, implements the risk assessment method of the stock right pledge in embodiment 1.
The memory 22 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 22 may optionally include memory located remotely from the processor 21, and these remote memories may be connected to the processor 21 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The program instructions/modules are stored in the memory 22 and, when executed by the one or more processors 21, perform the risk assessment method of share pledge of embodiment 1 above, for example, perform the steps illustrated in fig. 1 and 5 described above.
Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the embodiments may be implemented by associated hardware as instructed by a program, which may be stored on a computer-readable storage medium, which may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. A risk assessment method for a stock pledge, comprising:
synchronizing various original data related to the share right pledge in the bottom database into the kudu database through a Binlog process;
performing multi-table correlation calculation on various original data in the kudu database through Impala SQL to obtain a corresponding share right pledge intermediate result table;
reading an intermediate result table in the kudu database through a TAF process, performing risk evaluation operation according to share right pledge data in the intermediate result table, and storing a finally obtained risk evaluation result into Redis;
providing share pledge service content through an external interface of the TAF frame so that a user can obtain a corresponding risk evaluation result;
wherein the risk assessment operation specifically comprises:
estimating a flat price based on the share right pledge data in the intermediate result table, and calculating the risk score of each pledge according to the distance between the share price of each pledge and the flat price; and taking the proportion of the number of the stocks of each pledge to the total pledge number as weight, and performing weighted calculation on the risk scores of each pledge to obtain first comprehensive risk scores of all pledges so that the user can determine the risk of the pledge of the right of the stock according to the first comprehensive risk scores.
2. The method of risk assessment of share pledge of claim 1, wherein after said obtaining a first composite risk score for all pledges by weighted calculation of the risk scores for each pledge, the method further comprises:
determining a corresponding risk coefficient according to the proportion of the total pledges in the total stock, and combining the first comprehensive risk score and the risk coefficient to obtain a second comprehensive risk score;
and determining the proportion of the single-stranded east pledge in the stock book held by the single-stranded east pledge, and when the proportion of the single-stranded east pledge exceeds the preset proportion, adding a preset value on the basis of the second comprehensive risk score to obtain a third comprehensive risk score so that the user can determine the risk of the share-right pledge according to the third comprehensive risk score.
3. The risk assessment method of the share pledge of claim 1, wherein the interface mode of the external interface of the TAF framework is specifically:
the TAF has a protocol calling interface; alternatively, the HTTP post request invokes the interface.
4. The risk assessment method of the share pledge of claim 1, wherein the original data comprises one or more of the pledge announcement content of the listed company, the statistical information related to the share pledge, the information of each shareholder of the listed company, the historical stock price of the listed company and the historical card stop information; wherein the data source of the raw data comprises one or more of financial data, market data, and crawler data.
5. The method of risk assessment of share pledge of claim 4, wherein prior to performing a risk assessment algorithm, the method further comprises:
respectively establishing corresponding access links according to data source positions corresponding to various original data, and scoring the credibility of the various original data based on a data source;
and after risk assessment operation is carried out, storing the data source access link and the credibility scoring result corresponding to each original data into Redis along with the risk assessment result so as to be conveniently acquired by a user.
6. The risk assessment method of share pledge of claim 5, wherein after said data-source-based source scores the credibility of each raw data, the credibility scoring result of each raw data is compared with a preset scoring value to determine the credibility of each raw data;
and when the risk assessment operation is carried out, discarding the original data with the credibility score smaller than the preset score value, and only carrying out calculation according to the original data with the credibility score larger than or equal to the preset score value.
7. The method of risk assessment of share pledge of claim 5, wherein prior to performing a risk assessment algorithm, the method further comprises:
matching data contents of the same original data from different data sources; if the data contents are not matched in a consistent manner, comparing the information release time nodes corresponding to the same kind of original data from different data sources to judge the sequence of the time nodes;
calculating according to the data at the most rear of the time node when risk assessment operation is carried out; or continuously judging the credibility score corresponding to the most posterior data of the time node, and if the corresponding credibility score is greater than or equal to a preset score value, calculating based on the most posterior data of the time node.
8. The risk assessment method of the share pledge of claim 1, wherein, during the risk assessment operation, a time tag is set for the risk assessment result according to the time node of the operation, and the time tag is stored in Redis together with the risk assessment result corresponding to the time node, so that the risk assessment result finally obtained by the user carries the corresponding time tag.
9. A risk assessment device for a stock pledge, comprising at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and wherein the memory stores instructions executable by the at least one processor, and wherein the instructions are configured to perform the method for assessing risk of a stock pledge according to any one of claims 1-8 after being executed by the processor.
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