CN113781220A - Distributed stock transaction matching system and method - Google Patents
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Abstract
The invention discloses a distributed stock transaction matching system and a distributed stock transaction matching method, and relates to the technical field of stock transactions. The invention comprises the following steps: acquiring a behavior log of a user and searching keywords to acquire stocks in which the user is interested; predicting the daily profitability of the stocks interested by the user according to the K-line graph of the stocks; the yield rate in the day is matched with stocks which are interested by the user; counting the matching results into a column and deleting matches which do not accord with the rules by combining with a rule base; sending the matched data to a buyer terminal; and storing the stock market information and the transaction information and sending the stock market information and the transaction information to the seller terminal. The invention obtains the stocks which are interested by the user through the daily behavior log of the user, predicts the daily earning rate of the stocks which are interested by the user by using the K-line graph of the stocks, and matches the daily earning rate with the stocks which are interested by the user, thereby improving the demand of the user for buying the stocks and increasing the trading rate of the stocks.
Description
Technical Field
The invention belongs to the technical field of stock trading, and particularly relates to a distributed stock trading matching system and a distributed stock trading matching method.
Background
The rapid development of the internet has enabled the electronic management system to have a wide and important application in various industries. In the stock market with ever-expanding market information and trade requirement, the electronic trade mode has the advantages of fast speed, low cost, breaking through site limitation, etc. and can meet the requirement of trade amount and minimize the loss caused by time delay to make people master the market quotation timely.
However, the domestic trading system needs to face tens of millions of stock holders, the trading demand is huge, and the stock market quotation changes instantly, so that high requirements are put forward on the performance of the trading system. Meanwhile, the Chinese trading system is centralized management, and all stock trading information is directly processed in a trading exchange system. And if the matching capability is low, the time delay is serious, and great loss can be brought to investors.
Therefore, the application document provides a distributed stock transaction matching system and a distributed stock transaction matching method, which can effectively solve the problems.
Disclosure of Invention
The invention aims to provide a distributed stock trading matching system and a distributed stock trading matching method.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention relates to a distributed stock transaction matching system, which comprises a buyer terminal, a seller terminal, a distributed server, at least one matching server and a database server, wherein the buyer terminal is connected with the seller terminal;
the buyer terminal is used for an investor to access the distributed server and execute corresponding operations through searching, inquiring, purchasing and paying;
the seller terminal is used for sending transaction request information to the distribution server;
the distributed server is used for receiving the purchase order, generating order information according to the purchase order and distributing the order information to a matching server;
the matching server is used for performing matching transaction with the real-time quotation according to the order information and sending transaction data to the database server;
the database server is used for modifying and storing the user information according to the transaction data;
the distributed server comprises a plurality of working nodes in different organization ranges; the buyer terminal and the seller terminal are respectively in communication connection with a plurality of working points.
As a preferred technical scheme, the distributed server comprises a data acquisition module, a data preprocessing module and a user management module;
the data acquisition module is used for acquiring user registration entry data and user behavior logs issued on a network and a database server through a distributed crawler technology; the data preprocessing module is used for preprocessing the data acquired by the data acquisition module; the user management module is used for constructing application models corresponding to all users, and aiming at each user model, the user management module comprises corresponding user registration input data and a user behavior log.
As a preferred technical scheme, the distributed server comprises an interest recommendation module, a real-time stock analysis module and a stock matching module;
the interest recommendation module is used for obtaining the interest degree of each keyword interested by the user according to the attention behavior of each announcement information concerned by the user in the user behavior log;
the real-time stock analysis module is used for acquiring the trend of a K line graph of the stock in real time for prediction and arranging a yield sequence in the current day;
and the stock matching module is used for matching the stocks which are interested by the user and the return rate of the stocks in the interest field.
As a preferred technical solution, the interest recommendation module calculates, for each piece of advertisement information, a degree of interest of each user in the piece of advertisement information according to the keyword extracted from the piece of advertisement information and a degree of interest of each user in the extracted keyword, and recommends the piece of advertisement information to N users with the highest degree of interest, where N is an integer greater than 0; establishing an industry knowledge graph, finding the upstream and downstream relation of keywords interested by a user by using the inference relation of the industry knowledge graph, and recommending the notice information interested by the user and the stocks meeting the profitability of the information to the user.
As a preferred technical solution, the data preprocessing module comprises the following working steps:
step Y1: filtering dirty data in the data;
step Y2: classifying the data to remove repeated and similar data;
step Y3: and packaging the data into a standard data format so as to extract and analyze the data according to requirements.
The invention relates to a distributed stock transaction matching method, which comprises the following steps:
step S1: acquiring a behavior log of a user and searching keywords to acquire stocks in which the user is interested;
step S2: predicting the daily profitability of the stocks interested by the user according to the K-line graph of the stocks;
step S3: the yield rate in the day is matched with stocks which are interested by the user;
step S4: counting the matching results into a column and deleting matches which do not accord with the rules by combining with a rule base;
step S5: sending the matched data to a buyer terminal;
step S6: and storing the stock market information and the transaction information and sending the stock market information and the transaction information to the seller terminal.
As a preferred technical solution, in step S2, the daily profitability is represented by an ARCH model using a stock K-line graph, and the formula of the ARCH model is as follows:
in the formula, ytRepresenting normalized high-frequency intra-day trading profitability σ of a stockt 2Is the time-varying conditional variance, { εtIs a standard normally distributed white noise sequence which is independently and identically distributed;
the data output by the ARCH model adopts a Portmentau Q method, and the detected statistics are as follows:
where n is the sample size, q represents the maximum delay order of the autocorrelation function, ρiIs the i-th order autocorrelation function of the residual sequence.
As a preferred technical solution, in step S3, after matching of stock information is successful, it is verified whether the user information, account and delegation under the user meet the rule base, and if an error occurs, the user is fed back; the rule base can encapsulate various stock trading mechanisms, rules, time and fluctuation range in the stock trading process for limitation, and users can define the rules according to conditions.
The invention has the following beneficial effects:
the invention obtains the stocks which are interested by the user through the daily behavior log of the user, predicts the daily earning rate of the stocks which are interested by the user by using the K-line graph of the stocks, and matches the daily earning rate with the stocks which are interested by the user, thereby improving the demand of the user for buying the stocks and increasing the trading rate of the stocks.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a distributed stock trading matching system according to the present invention;
fig. 2 is a diagram of steps of a distributed stock transaction matching method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention is a distributed stock transaction matching system, which includes a buyer terminal, a seller terminal, a distributed server, at least one matching server and a database server;
the buyer terminal is used for an investor to access the distributed server and execute corresponding operations through searching, inquiring, purchasing and paying; the buyer terminal is a stock buyer smart phone, iPad and a computer.
The seller terminal is used for sending transaction request information to the distribution server;
the distributed server is used for receiving the purchase order, generating order information according to the purchase order and distributing the order information to one matching server;
the matching server is used for performing matching transaction with the real-time quotation according to the order information and sending transaction data to the database server;
the database server is used for modifying and storing the user information according to the transaction data;
the distributed server comprises a plurality of working nodes in different organization ranges; the buyer terminal and the seller terminal are respectively connected with the plurality of working points in a communication mode.
The database server includes:
user management, which is mainly used for maintaining the personal and account information, entrustment and the like of a user; the system administrator maintains and manages the user information;
the entrusting (order) management is mainly used for managing and maintaining entrusting of the user, and comprises entrusting modification, cancellation and query operations;
and the system transaction rule base is used for maintaining, modifying, adding, deleting and the like the market transaction rules by an administrator, so that the system conforms to a market operation mechanism and normally operates in a market environment.
The distributed server comprises a data acquisition module, a data preprocessing module and a user management module;
the data acquisition module is used for acquiring user registration entry data and user behavior logs issued on a network and a database server through a distributed crawler technology; the data preprocessing module is used for preprocessing the data acquired by the data acquisition module; and the user management module is used for constructing application models corresponding to all users, and aiming at each user model, the user management module comprises corresponding user registration entry data and a user behavior log.
The distributed server comprises an interest recommendation module, a real-time stock analysis module and a stock matching module;
the interest recommendation module is used for obtaining the interest degree of each keyword interested by the user according to the attention behavior of each announcement information concerned by the user in the user behavior log;
the real-time stock analysis module is used for acquiring the trend of a stock K line graph in real time for prediction and arranging a yield sequence in the current day;
the stock matching module is used for matching the interested stocks of the user and the current profit rate of the stocks in the interested field; the stock matching module is the core of the whole system, and after a user places an order, matching transaction is carried out on the customer order according to rules formulated in the rule system and set algorithms.
And in the matching process, the system also comprises a rule base module which is used for packaging various market mechanisms and rules in the stock transaction process, such as time limit, fluctuation amplitude, tax stamp rate and the like. The maintenance and modification can be conveniently carried out in the subsequent system modification and expansion;
the verification module verifies whether the user information, the account and the entrustment under the user meet the system requirements, and feeds back the user information, the account and the entrustment to the user if the user information, the account and the entrustment under the user meet the system requirements;
a message processing module which is used for receiving and sending messages such as order entrusting, examination inquiring, cancellation, modification and the like, and sending and quotation of processing results;
the database operation module defines an operation method for the database;
the business execution module provides a method for realizing various operations, and because various business operations (entrusted query, entrusted modification, withdrawal and the like) relate to query, addition, deletion, modification and other operations on the database in the matching realization process, a DAO layer is designed to isolate the dependence of the last business operation on specific SQL statements and the database;
the data storage management module is mainly used for storing and managing the entrusted queue query message, the queue, the message sending queue and the like.
The interest recommending module calculates the interest degree of each user in the announcement information according to the keywords extracted from the announcement information and the interest degree of each user in the extracted keywords, and recommends the announcement information to N users with the highest interest degree, wherein N is an integer greater than 0; establishing an industry knowledge graph, finding the upstream and downstream relation of keywords interested by a user by using the inference relation of the industry knowledge graph, and recommending the announcement information interested by the user and the stocks meeting the profitability of the information to the user.
The data preprocessing module comprises the following working steps:
step Y1: filtering dirty data in the data;
step Y2: classifying the data to remove repeated and similar data;
step Y3: and packaging the data into a standard data format so as to extract and analyze the data according to requirements.
The flow of the distributed server after matching is completed is as follows: and the entrusting receiving queue maintains a set of received to-be-matched entrusting information and provides an interface for adding and extracting the entrusting information. And a query receiving queue, which is used for maintaining a set of received query messages to be processed and providing an interface for adding and extracting the query messages. And the message sending queue stores stock market information, transaction results and the like and provides an interface for adding and extracting market information. The entrusting information is an entrusting quotation request information set of the user, provides an interface for adding, extracting and deleting entrusting requests and verifying whether entrusting meets requirements or not, and adopts Hashset as a data organization mode; and running a timing thread to periodically traverse the request set, canceling the expired entrusts (the valid period of the entrusts in China is 1 day, and ordering is needed again if the current day is the second day of transaction), and blocking and suspending the thread if the quotation request is 0. Stock information-maintaining the information set of stocks, providing an interface for adding and extracting stock information. Hashset is used as a data organization form, and each stock comprises two matching entrusting queues for buying and selling. And the matching queue stores and maintains the entrusting information which is not matched or not completely matched, and provides an interface for adding, extracting and deleting entrusting. Customer information, namely maintaining account information and entrustment information of a customer and providing an information adding, extracting and deleting interface. And adopting Hash Set as a data organization form. Transaction records-transaction record information is maintained, and an add and extract information interface is provided. And the transaction message sending thread acquires the transaction message from the transaction queue to send. And (4) receiving, modifying and canceling the thread by delegation, wherein the three kinds of delegation processing information are sent to a delegation queue. And a query receiving thread, wherein the query information of the user is received and sent to a query queue. And a quotation issuing thread, namely acquiring quotation from the quotation information and sending the quotation. And the matching thread is used for matching the entrusts in the entrusted receiving queue and the matching queue by using a matching algorithm, updating stock information, client information, entrusted information and quotation information in time, generating a transaction record and storing the transaction record into the transaction record. And the query processing thread acquires the entrusted query information from the query queue, then calls corresponding database operation on the entrusted query information, acquires a query result and then adds the query result into the transaction message sending queue for sending.
Referring to fig. 2, the present invention is a method for matching distributed stock transactions, comprising the following steps:
step S1: acquiring a behavior log of a user and searching keywords to acquire stocks in which the user is interested;
step S2: predicting the daily profitability of the stocks interested by the user according to the K-line graph of the stocks;
step S3: the yield rate in the day is matched with stocks which are interested by the user;
step S4: counting the matching results into a column and deleting matches which do not accord with the rules by combining with a rule base;
step S5: sending the matched data to a buyer terminal;
step S6: and storing the stock market information and the transaction information and sending the stock market information and the transaction information to the seller terminal.
In step S2, the daily profitability is determined by using a stock K-line map as follows:
in the formula, ytRepresenting normalized high-frequency daily trading profitability of stocks
Is the time-varying conditional variance, { εtIs a standard normally distributed white noise sequence which is independently and identically distributed;
data output by the ARCH model adopts a Portmentau Q method, and the detected statistics are as follows:
where n is the sample size, q represents the maximum delay order of the autocorrelation function, ρiIs the i-th order autocorrelation function of the residual sequence.
In step S3, after matching of stock information is successful, verifying whether the user information, the account and the entrustment under the user are in accordance with the rule base, and if an error occurs, feeding back to the user; the rule base can encapsulate various stock trading mechanisms, rules, time and fluctuation range in the stock trading process for limitation, and users can define the rules according to conditions.
It should be noted that, in the above system embodiment, each included unit is only divided according to functional logic, but is not limited to the above division as long as the corresponding function can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
In addition, it is understood by those skilled in the art that all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing associated hardware, and the corresponding program may be stored in a computer-readable storage medium.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (8)
1. A distributed stock transaction matching system is characterized by comprising a buyer terminal, a seller terminal, a distributed server, at least one matching server and a database server;
the buyer terminal is used for an investor to access the distributed server and execute corresponding operations through searching, inquiring, purchasing and paying;
the seller terminal is used for sending transaction request information to the distribution server;
the distributed server is used for receiving the purchase order, generating order information according to the purchase order and distributing the order information to a matching server;
the matching server is used for performing matching transaction with the real-time quotation according to the order information and sending transaction data to the database server;
the database server is used for modifying and storing the user information according to the transaction data;
the distributed server comprises a plurality of working nodes in different organization ranges; the buyer terminal and the seller terminal are respectively in communication connection with a plurality of working points.
2. The distributed stock transaction matching system of claim 1, wherein the distributed server comprises a data acquisition module, a data preprocessing module, and a user management module;
the data acquisition module is used for acquiring user registration entry data and user behavior logs issued on a network and a database server through a distributed crawler technology; the data preprocessing module is used for preprocessing the data acquired by the data acquisition module; the user management module is used for constructing application models corresponding to all users, and aiming at each user model, the user management module comprises corresponding user registration input data and a user behavior log.
3. The distributed stock transaction matching system of claim 1, wherein the distributed server comprises an interest recommendation module, a real-time stock analysis module, and a stock matching module;
the interest recommendation module is used for obtaining the interest degree of each keyword interested by the user according to the attention behavior of each announcement information concerned by the user in the user behavior log;
the real-time stock analysis module is used for acquiring the trend of a K line graph of the stock in real time for prediction and arranging a yield sequence in the current day;
and the stock matching module is used for matching the stocks which are interested by the user and the return rate of the stocks in the interest field.
4. The distributed stock trading matching system of claim 3, wherein the interest recommendation module calculates the interest level of each user in each piece of announcement information according to the keywords extracted from the piece of announcement information and the interest level of each user in the extracted keywords, and recommends the piece of announcement information to the N users with the highest interest level, wherein N is an integer greater than 0; establishing an industry knowledge graph, finding the upstream and downstream relation of keywords interested by a user by using the inference relation of the industry knowledge graph, and recommending the notice information interested by the user and the stocks meeting the profitability of the information to the user.
5. The distributed stock transaction matching system and method as claimed in claim 2, wherein the data preprocessing module is operated as follows:
step Y1: filtering dirty data in the data;
step Y2: classifying the data to remove repeated and similar data;
step Y3: and packaging the data into a standard data format so as to extract and analyze the data according to requirements.
6. A distributed stock transaction matching method is characterized by comprising the following steps:
step S1: acquiring a behavior log of a user and searching keywords to acquire stocks in which the user is interested;
step S2: predicting the daily profitability of the stocks interested by the user according to the K-line graph of the stocks;
step S3: the yield rate in the day is matched with stocks which are interested by the user;
step S4: counting the matching results into a column and deleting matches which do not accord with the rules by combining with a rule base;
step S5: sending the matched data to a buyer terminal;
step S6: and storing the stock market information and the transaction information and sending the stock market information and the transaction information to the seller terminal.
7. The distributed stock transaction matching method of claim 1, wherein in step S2, the daily profitability is represented by an ARCH model using a stock K-line graph, and the formula of the ARCH model is as follows:
in the formula, ytRepresenting normalized high-frequency daily trading profitability of stocks
Is the time-varying conditional variance, { εtIs a standard normally distributed white noise sequence which is independently and identically distributed;
the data output by the ARCH model adopts a Portmentau Q method, and the detected statistics are as follows:
where n is the sample size, q represents the maximum delay order of the autocorrelation function, ρiIs the i-th order autocorrelation function of the residual sequence.
8. The distributed stock transaction matching method of claim 1, wherein in step S3, after matching of stock information is successful, it is verified whether user information, account and entrustment under the user are in accordance with the rule base, and if an error occurs, the user is fed back; the rule base can encapsulate various stock trading mechanisms, rules, time and fluctuation range in the stock trading process for limitation, and users can define the rules according to conditions.
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