CN113377670A - Self-adaptive high-performance transaction simulation method and system suitable for financial industry - Google Patents
Self-adaptive high-performance transaction simulation method and system suitable for financial industry Download PDFInfo
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Abstract
The invention provides a self-adaptive high-performance transaction simulation method and system suitable for the financial industry, which relate to the technical field of transaction simulation and comprise the following steps: verifying, extracting and preparing historical exchange message information, and establishing a data warehouse; checking message data in a data warehouse, classifying according to message specificity, and establishing a message model based on a decision tree; aiming at a received exchange message, determining an exchange simulation system corresponding to the exchange message by using the generated message model; and starting the exchange simulation system to simulate the transaction. In the invention, different exchanges are adaptively matched by utilizing a decision tree algorithm, the simulation of the transaction behaviors of all exchanges and various service behaviors of the exchanges is realized, and the method can be efficiently applied to performance test.
Description
Technical Field
The invention relates to the technical field of transaction simulation, in particular to a self-adaptive high-performance transaction simulation method and system suitable for the financial industry.
Background
In the performance test of the core trading system in the financial field, a full-link performance test is required, but the simulation test environment of the real exchange cannot provide proper performance test time for a dealer, and the exchange needs to be simulated.
The existing transaction simulation system only simulates transaction aiming at the transaction system of one exchange according to the message. However, the transaction behavior involved in each transaction is different, and accordingly the transaction system is also different.
Obviously, the existing transaction simulation system cannot perform adaptive transaction simulation and cannot meet the actual requirements of the financial industry on transaction simulation.
Disclosure of Invention
In view of the above, the invention provides a self-adaptive high-performance transaction simulation method and system suitable for the financial industry, which realize transaction simulation through a self-adaptive decision tree algorithm so as to meet the actual requirements of the financial industry on transaction simulation.
Therefore, the invention provides the following technical scheme:
the invention provides a self-adaptive high-performance transaction simulation method suitable for the financial industry, which comprises the following steps:
s1, verifying, extracting and preparing the historical exchange message information, and establishing a data warehouse;
s2, checking the message data in the data warehouse, classifying according to the message specificity, and establishing a message model based on a decision tree;
s3, aiming at the received exchange message, determining an exchange simulation system corresponding to the exchange message by using the generated message model;
and S4, starting the exchange simulation system to simulate the transaction.
2. The adaptive high-performance transaction simulation method applicable to the financial industry as claimed in claim 1, wherein S2 specifically comprises:
s2.1, calculating according to an entropy gain algorithm, and regarding the message with the largest information gain as an initial node;
wherein, the entropy gain algorithm is as follows:
calculating an empirical entropy h (D) of the data set D;
calculating the empirical conditional entropy H (D | A) of the feature A on the data set D;
g(D,A)＝H(D)-H(D|A)；
wherein, CkIs each element, C, in the data set DiIs the attribute Y or N number of each element in feature A;
s2.2, traversing each segmentation mode of each message;
s2.3, dividing the node into two nodes N1 and N2;
s2.4, continues to execute S2.2 and S2.3 on N1 and N2, respectively, until each node is the final property category.
The invention also provides a self-adaptive high-performance transaction simulation system suitable for the financial industry, which comprises:
the data warehouse module is used for verifying, extracting and preparing the historical exchange message information and establishing a data warehouse;
the message model module is used for checking message data in the data warehouse, classifying the message data according to message specificity and establishing a message model based on a decision tree;
the exchange determination module is used for determining an exchange simulation system corresponding to the exchange message by using the generated message model aiming at the received exchange message;
and the simulation transaction module is used for starting the exchange simulation system to simulate the transaction.
The invention has the advantages and positive effects that:
in the technical scheme provided by the invention, different exchanges are adaptively matched by utilizing a decision tree algorithm, the simulation of the transaction behaviors of all exchanges and various service behaviors of the exchanges is realized, the expandability of newly added services of the exchanges is good, and the method can be efficiently applied to performance testing.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic workflow diagram of an adaptive high-performance transaction simulation method suitable for the financial industry according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a preliminary decision tree generated in the embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention simulates the transaction behavior of the exchange, and utilizes a machine learning algorithm to automatically learn and conjecture an applicable exchange transaction simulation system according to a received system message, automatically starts the exchange transaction simulation system, simulates the transaction and returns a proper transaction message.
Referring to fig. 1, the work flow of the adaptive high-performance transaction simulation method applicable to the financial industry in the embodiment of the present invention is divided into three parts:
the method comprises a message preprocessing stage, a message model design stage and a message production stage.
1. A message preprocessing stage:
in the stage, firstly, data mining analysis is carried out on the message information of the exchange, namely, a large amount of message information is analyzed, the category of a certain message is determined according to the analysis, the task of the stage is to verify, extract and prepare a large amount of original messy exchange message information, and the exchange message which is subjected to data conversion and data cleaning technology is used for establishing a data warehouse.
2. A model design stage:
in the stage, the message data needs to be deeply checked, classified according to the message specificity, and subjected to rule induction and cutting by using a decision tree algorithm in data mining to form a tree structure of the message; then, the message is minimally subdivided, the message data is divided into one result set or a plurality of result sets, and a message model based on a decision tree is established.
In the embodiment of the invention, a data set D { exchange, deep exchange }, CkIs each element in a data set D, and is characterized by A { spot concentrated bidding trading platform, spot concentrated bidding trading, comprehensive financial service platform, protocol trading, non-trading processing platform, upper-certificate LOF trading and message conditions }, CiIs the number of attributes Y or N of each element in feature a, see table 1 and the final generated preliminary decision tree diagram 2.
The ID3 algorithm is a top-down greedy search algorithm, i.e., the attribute with the largest information gain is selected as the current decision attribute to ensure that the daily branching depth of the decision tree is as small as possible, so that the obtained decision tree redundancy is minimal. The basic steps of the message decision tree model construction are as follows:
s2.1, calculating according to an entropy gain algorithm, and taking a message (such as a spot centralized bidding trading platform) with the largest information gain as an initial node;
wherein, the entropy gain algorithm is as follows:
the empirical entropy h (D) of the dataset D is calculated:
calculating the empirical conditional entropy H (D | a) of feature a on data set D:
g(D，A)＝H(D)-H(D|A)；
s2.2, starting to traverse each segmentation mode (Y or N) of each message (spot in-stock bid transaction platform); for example, in the above embodiment, the splitting manner of the spot bidding transaction platform is a spot bidding transaction (Y) or a comprehensive financial service platform (N), and the traversing splitting manner is that the spot bidding transaction platform belongs to a spot bidding transaction (Y) or a comprehensive financial service platform (N).
S2.3, dividing the system into two nodes N1 (spot bidding transaction) and N2 (comprehensive financial service platform);
s2.4, continue executing steps S2.2 and S2.3 on N1 and N2, respectively, until each node is the final attribute category (exchange category, deep exchange, trade, etc.).
The embodiment of the invention adopts the decision tree model, has good readability and descriptive property, and is beneficial to manual analysis; the method has high efficiency, the decision tree only needs to be constructed once and used repeatedly, and the maximum calculation times of each prediction do not exceed the depth of the decision tree.
3. A message production stage:
the stage is a determined transaction stage of the simulated transaction of the exchange simulated transaction system, a proper exchange simulated transaction system is selected and started by utilizing the message generated in the data analysis stage, and then proper transaction type return message data is selected and started (for example, the received message is of an inquiry type, a request type, a notification type and the like, which type of transaction type is returned according to the message distinction), and the real behavior of the exchange is simulated.
In the technical scheme provided by the embodiment of the invention, different exchanges are adaptively matched by utilizing a decision tree algorithm, the simulation of the transaction behaviors of all exchanges and various service behaviors of the exchanges is realized, the expandability of newly added services of the exchanges is good, and the method can be efficiently applied to performance testing.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. An adaptive high-performance transaction simulation method suitable for the financial industry, the method comprising:
s1, verifying, extracting and preparing the historical exchange message information, and establishing a data warehouse;
s2, checking the message data in the data warehouse, classifying according to the message specificity, and establishing a message model based on a decision tree;
s3, aiming at the received exchange message, determining an exchange simulation system corresponding to the exchange message by using the generated message model;
and S4, starting the exchange simulation system to simulate the transaction.
2. The adaptive high-performance transaction simulation method applicable to the financial industry as claimed in claim 1, wherein S2 specifically comprises:
s2.1, calculating according to an entropy gain algorithm, and regarding the message with the largest information gain as an initial node;
wherein, the entropy gain algorithm is as follows:
calculating an empirical entropy h (D) of the data set D;
calculating the empirical conditional entropy H (D | A) of the feature A on the data set D;
g(D,A)＝H(D)-H(D|A)；
wherein, CkIs each element, C, in the data set DiIs the attribute Y or N number of each element in feature A;
s2.2, traversing each segmentation mode of each message;
s2.3, dividing the node into two nodes N1 and N2;
s2.4, continues to execute S2.2 and S2.3 on N1 and N2, respectively, until each node is the final property category.
3. An adaptive high-performance transaction simulation system suitable for use in the financial industry, the system comprising:
the data warehouse module is used for verifying, extracting and preparing the historical exchange message information and establishing a data warehouse;
the message model module is used for checking message data in the data warehouse, classifying the message data according to message specificity and establishing a message model based on a decision tree;
the exchange determination module is used for determining an exchange simulation system corresponding to the exchange message by using the generated message model aiming at the received exchange message;
and the simulation transaction module is used for starting the exchange simulation system to simulate the transaction.
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| CN110473101A (en) * | 2019-08-15 | 2019-11-19 | 中国银行股份有限公司 | Mock trading message processing method and device |
| CN111062803A (en) * | 2019-12-04 | 2020-04-24 | 中国银行股份有限公司 | Financial business query and review method and system |
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