CN117455319A - Financial index model calculation processing method, electronic equipment and processing medium - Google Patents
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Abstract
The invention discloses a processing method, electronic equipment and a processing medium for financial index model calculation, and relates to the technical field of financial science and technology. One embodiment of the method comprises the following steps: the processing request of index data can be calculated aiming at a financial object, and a target model matched with the financial object is selected from a plurality of registered financial models; and acquiring parameters and corresponding parameter values of the target model, so as to calculate index data corresponding to the financial object by using a calculation strategy and the parameter values contained in the target model. The embodiment of the invention improves the flexibility, the universality and the expansibility of the processing aiming at the financial index model calculation.
Description
Technical Field
The present invention relates to the technical field of financial science and technology, and in particular, to a processing method, an electronic device, and a processing medium for calculating a financial index model.
Background
In a financial product, index data of various financial indexes corresponding to various types of financial objects (e.g., bonds, stocks, foreign exchange, etc.) are generally required to be computationally processed.
The existing method for calculating index data is often to write an interface and business code for different financial objects according to the calculation and document requirements of the financial indexes of the different financial objects, process parameter data required by the interface for the developed interface, and the like. The existing method has the problems of poor flexibility, poor generality and lack of expansibility of processing of financial index model calculation, and meanwhile, the development cost of processing financial index data is increased.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a processing method, an electronic device, and a processing medium for calculating a financial index model, which are capable of selecting a target model matching a financial object from a plurality of registered financial models according to a processing request of calculating index data of the financial object; and acquiring parameters and corresponding parameter values of the target model, so as to calculate index data corresponding to the financial object by using a calculation strategy and the parameter values contained in the target model. According to the embodiment of the invention, the flexibility, the universality and the expansibility of the processing of the financial index model calculation are improved, and the code coupling degree of the processing of the financial index model calculation is reduced.
To achieve the above object, according to an aspect of the embodiments of the present invention, there is provided a processing method for calculating a financial index model, including: receiving a processing request aiming at a financial object, and analyzing a unique identifier of the financial object, a to-be-processed index of the financial object and a to-be-processed time range from the processing request; selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object; acquiring one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed; and calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
Optionally, calculating, by using the target model and the corresponding parameter values, index data of the to-be-processed index corresponding to the financial object in the to-be-processed time range includes: determining an interface type corresponding to the target model; under the condition that the interface type is an asynchronous interaction mode, timing batch task information of the target model is obtained, so that the step of calculating index data of the to-be-processed index corresponding to the financial object in the to-be-processed time range is executed according to the timing batch task information, and the calculated index data is persisted; and under the condition that the interface type is a synchronous interaction mode, directly executing the step of calculating the index data of the to-be-processed index corresponding to the financial object within the to-be-processed time range, and storing the index data into a memory.
Optionally, the processing method of financial index model calculation further includes: providing model configuration pages for various financial models; receiving, by the model configuration page, the following various configuration information provided by a user: a financial model to be configured, a calculation index of the financial model, parameters required by calculating the calculation index, a calculation strategy required by calculating the calculation index, and a data source of parameter values of the parameters; and storing and registering each financial model according to the configuration information received from the plurality of model configuration pages.
Optionally, the obtaining one or more parameters corresponding to the calculation policy and parameter values corresponding to the parameters in a time range to be processed includes: acquiring the parameter type of the parameter, and directly acquiring a parameter value corresponding to the parameter under the condition that the parameter type is a global parameter; and under the condition that the parameter type is a non-global parameter, analyzing the data source bound with the parameter, and acquiring a parameter value corresponding to the parameter in a time range to be processed from the data source.
Optionally, the calculating the index data of the to-be-processed index corresponding to the financial object in the to-be-processed time range includes: acquiring a calculation task corresponding to index data of the index to be processed corresponding to the financial object in the time range to be processed, and determining a calculation task type corresponding to the calculation task; splitting the combined task into a plurality of basic tasks under the condition that the computing task type is the combined task; and respectively executing each basic task, and carrying out combined calculation on calculation results obtained by each basic task to obtain index data corresponding to the combined task.
Optionally, in the case that the computing task type is a combined task, after splitting the combined task into a plurality of basic tasks, the method further includes: for each of the basic tasks, performing: and executing batch preloading on each basic task by adopting a streaming loading strategy, and/or loading parameter values which are contained in the basic tasks and are required for calculating indexes to be processed into a memory.
Optionally, the selecting a target model that matches the unique identifier and the index to be processed from multiple registered financial models further includes: searching a target model matched with the unique identifier and the index to be processed from a plurality of financial models of a preset registration mark; and calling the target model by utilizing a dynamic reflection calling strategy.
In order to achieve the above object, according to a second aspect of the embodiments of the present invention, there is provided a processing apparatus for calculating a financial index model, comprising: the system comprises a model determining module, a parameter determining module and a data calculating module; wherein,
the determining model module is used for receiving a processing request aiming at a financial object, and analyzing a unique identifier, a to-be-processed index and a to-be-processed time range of the financial object to be processed from the processing request; selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object;
The parameter determining module is used for obtaining one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed;
and the calculation data module is used for calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
Optionally, the processing device for calculating the financial index model is configured to calculate, using the target model and the corresponding parameter values, index data of a to-be-processed index corresponding to the financial object within the to-be-processed time range, where the processing device includes: determining an interface type corresponding to the target model; under the condition that the interface type is an asynchronous interaction mode, timing batch task information of the target model is obtained, so that the step of calculating index data of the to-be-processed index corresponding to the financial object in the to-be-processed time range is executed according to the timing batch task information, and the calculated index data is persisted; and under the condition that the interface type is a synchronous interaction mode, directly executing the step of calculating the index data of the to-be-processed index corresponding to the financial object within the to-be-processed time range, and storing the index data into a memory.
Optionally, the processing device for calculating the financial index model is further used for providing a model configuration page for a plurality of financial models; receiving, by the model configuration page, the following various configuration information provided by a user: a financial model to be configured, a calculation index of the financial model, parameters required by calculating the calculation index, a calculation strategy required by calculating the calculation index, and a data source of parameter values of the parameters; and storing and registering each financial model according to the configuration information received from the plurality of model configuration pages.
Optionally, the processing device for calculating the financial index model is configured to obtain one or more parameters corresponding to the calculation policy and parameter values corresponding to the parameters in a time range to be processed, and includes: acquiring the parameter type of the parameter, and directly acquiring a parameter value corresponding to the parameter under the condition that the parameter type is a global parameter; and under the condition that the parameter type is a non-global parameter, analyzing the data source bound with the parameter, and acquiring a parameter value corresponding to the parameter in a time range to be processed from the data source.
Optionally, the processing device for calculating the financial index model is configured to calculate index data of a to-be-processed index corresponding to the financial object in the to-be-processed time range, and includes: acquiring a calculation task corresponding to index data of the index to be processed corresponding to the financial object in the time range to be processed, and determining a calculation task type corresponding to the calculation task; splitting the combined task into a plurality of basic tasks under the condition that the computing task type is the combined task; and respectively executing each basic task, and carrying out combined calculation on calculation results obtained by each basic task to obtain index data corresponding to the combined task.
Optionally, the processing device of the financial index model calculation is configured to, in a case where the calculation task type is a combined task, split the combined task into a plurality of basic tasks, further include: for each of the basic tasks, performing: and executing batch preloading on each basic task by adopting a streaming loading strategy, and/or loading parameter values which are contained in the basic tasks and are required for calculating indexes to be processed into a memory.
Optionally, the processing device for calculating the financial index model is configured to select a target model matching the unique identifier and the index to be processed from multiple registered financial models, and further includes: searching a target model matched with the unique identifier and the index to be processed from a plurality of financial models of a preset registration mark; and calling the target model by utilizing a dynamic reflection calling strategy.
To achieve the above object, according to a third aspect of an embodiment of the present invention, there is provided an electronic device for processing financial index model calculation, comprising: one or more processors; and a storage means for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method as recited in any of the processing methods of financial index model calculation described above.
To achieve the above object, according to a fourth aspect of the embodiments of the present invention, there is provided a computer-readable medium (processing medium) having stored thereon a computer program, characterized in that the program, when executed by a processor, implements a method as set forth in any one of the processing methods of financial index model calculation described above.
One embodiment of the above invention has the following advantages or benefits: the processing request of index data can be calculated aiming at a financial object, and a target model matched with the financial object is selected from a plurality of registered financial models; and acquiring parameters and corresponding parameter values of the target model, so as to calculate index data corresponding to the financial object by using a calculation strategy and the parameter values contained in the target model. According to the embodiment of the invention, the flexibility, the universality and the expansibility of the processing for the financial index model calculation are improved, the code coupling degree of the processing for the financial index model calculation is reduced, and the development efficiency is improved.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a flow chart of a method for processing financial index model calculation according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an environment configuration page according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a processing device for calculating a financial index model according to an embodiment of the present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be applied;
fig. 5 is a schematic diagram of a computer system suitable for use in implementing an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the technical scheme of the invention, the related processes of collecting, using, storing, sharing, transferring and the like of the personal information of the user accord with the regulations of related laws and regulations, the user needs to be informed and obtain the consent or the authorization of the user, and when the personal information of the user is applicable, the technical processes of de-identification and/or anonymization and/or encryption are performed on the personal information of the user.
After the financial data is collected, we will de-identify the data by technical means.
As shown in fig. 1, an embodiment of the present invention provides a processing method for calculating a financial index model, which may include the following steps:
step S101: and receiving a processing request aiming at the financial object, and analyzing the unique identification of the financial object, the index to be processed of the financial object and the time range to be processed from the processing request.
Specifically, in the embodiment of the present invention, the financial object is, for example, one object of a bond, a stock, a foreign exchange, or a combination of multiple objects, each of which has a corresponding unique identifier, and for any one financial object, generally includes a plurality of indexes (indexes to be processed) to be calculated and index values of the indexes within a set range (i.e., a time range to be processed); for example, the index is, for example: the interest rate of bonds exchanges contract values, the full value of foreign exchange European options, etc.
Step S102: selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object.
Specifically, in the embodiment of the invention, a financial model required for calculating financial index data, namely a financial object and a binding relation of one-to-one mapping between indexes and a financial model, can be dynamically searched and determined; the financial models take a model API (application program interface) as an example, and each financial model (such as an interface and the like) encapsulates a calculation strategy of the index to be processed for the financial object, and it is understood that the calculation strategy (such as one or more calculation formulas) of the index for a financial object is set according to requirements. In the description of the present invention, the financial model is a financial index model, and the calculation of the financial index model is the steps of executing the calculation according to the financial index model.
Further, the financial model corresponds to one or more parameters, the embodiment of the invention can configure the corresponding financial model for various indexes through the page, and when the financial model (API) is called, the corresponding API is called in a dynamic reflection mode according to the registration information of the model API, and the function contained by the executor is executed. Therefore, for the calculation request of the index (for example, the full price index of the bond) of any financial object, a matched target model can be first searched out from a plurality of financial indexes for the index of the financial object, and the target model is packaged with a calculation strategy of the index to be processed (for example, the full price index of the bond) of the financial object. The step of calculating the full price of the bond is performed by executing the target model later.
Further, providing a model configuration page for a plurality of financial models; receiving, by the model configuration page, the following various configuration information provided by a user: a financial model to be configured, a calculation index of the financial model, parameters required by calculating the calculation index, a calculation strategy required by calculating the calculation index, and a data source of parameter values of the parameters; and storing and registering each financial model according to the configuration information received from the plurality of model configuration pages. Specifically, the embodiment of the invention enables the developer (or the demander) to directly modify, add and delete the financial model on the page through a plurality of configuration interfaces, thereby improving the expansibility and flexibility of managing the financial model.
For example, in the case of adding a financial model, registration management for the model API may be performed using the model management module. When registering a newly added model, clicking the newly added model on a model management interface, and inputting various information aiming at the newly added model; the identification code of the financial model in the model management is generally the service name of the registration function, namely the name of the code hierarchy @ Component mark, the computing container can acquire the corresponding Java bean executed under the Spring framework through the service name, and then the acquired model parameters are transferred to the execution function corresponding to the computing strategy.
The method of the embodiment of the invention can be packaged into a model calculation engine, and based on the model calculation engine, a user can acquire index data corresponding to the financial index under the condition of inputting the financial object to be processed, the index to be processed and the time to be processed. When the environment corresponding to the model calculation engine is configured by providing a page, the configuration of static data and the configuration of dynamic index calculation required by calculation strategies are included. Wherein the configured objects include: financial model (i.e., financial model to be configured), environmental configuration, index management (i.e., calculation index of the financial model, parameters required to calculate the calculation index), calculation container (calculation policy required to calculate the calculation index, data source of parameter values of the parameters, etc.), task management, and the like.
Step S103: and acquiring one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed.
In particular, by providing a configuration page that enables a demander or developer to configure one or more parameters required by any financial model, it is understood that for one financial model, there is a sequential relationship between the multiple parameters; thus acquiring the order relation when acquiring the parameters; the parameter formats required by the model API may also be processed when each parameter is subsequently transferred to the financial model to which it belongs, for example, commas are used as separation symbols among a plurality of parameters, etc.
Further, the parameter type may be a global parameter or a non-global parameter (e.g., an operating parameter); namely, the obtaining one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a waiting time range includes: acquiring the parameter type of the parameter, and directly acquiring a parameter value corresponding to the parameter under the condition that the parameter type is a global parameter; and under the condition that the parameter type is a non-global parameter, analyzing the data source bound with the parameter, and acquiring a parameter value corresponding to the parameter in a time range to be processed from the data source. For example, the global parameter is a CNY risk-free slope curve, and the corresponding parameter value is a string "noriskcurrve_cny", etc.; the operation parameter (non-global parameter) is, for example, asseinfo, and the corresponding parameter value thereof may be a configured bound data source, for example, tradeinfo [ #assetBId ], that is, the parameter value of assetBInfo parameter is obtained according to the data corresponding to the assetBId field in the tradeinfo; for another example, when the calculation index is the interest rate interchange contract value, it includes the respective parameters and the corresponding parameter data shown in table 1.
TABLE 1
It follows that the algorithm logic for calculating the interest rate interchange contract valuation pricing (i.e., index) is complex, which is associated with various calculation strategies such as zero interest rate curve, floating interest rate reset interval interest rate, single complex interest calculation formula, etc. Thus, parameters and their formats associated with the calculation strategy for interest interchange contract valuation pricing are also more complex, with curve data, fixed end information, floating end information, etc. It can be seen that if the code is developed directly for the calculation of the index, a developer is required to understand the meaning of the parameter, so that the cost of the developer and the time is improved. The processing method for calculating the financial index model provided by the invention can be used for configuring various information such as financial models, parameters related to calculation strategies, data sources with bound parameters and the like, and can be used for uniformly packaging calls corresponding to all the financial models into a model engine, so that a user of the model engine can provide calculation objects, calculation indexes and index time (namely unique identification of the financial objects, indexes to be processed of the financial objects and time ranges to be processed), other various parameter information calculation containers can be automatically acquired through configuration of a pricing environment, and the preparation work of corresponding data is completed, the development workload corresponding to the call of the model engine is simplified, and the development efficiency is improved to a great extent.
Step S104: and calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
Specifically, in the embodiment of the invention, the interface API corresponding to the financial model has a plurality of interface types; therefore, calculating the index data of the to-be-processed index corresponding to the financial object within the to-be-processed time range by using the target model and the corresponding parameter value comprises the following steps: determining an interface type corresponding to the target model; under the condition that the interface type is an asynchronous interaction mode, timing batch task information of the target model is obtained, so that the step of calculating index data of the to-be-processed index corresponding to the financial object in the to-be-processed time range is executed according to the timing batch task information, and the calculated index data is persisted; and under the condition that the interface type is a synchronous interaction mode, directly executing the step of calculating the index data of the to-be-processed index corresponding to the financial object within the to-be-processed time range, and storing the index data into a memory.
Further, the embodiment of the invention provides management of calculation tasks of the financial model when index calculation is performed; specifically, the calculating the index data of the index to be processed corresponding to the financial object within the time range to be processed includes: acquiring a calculation task corresponding to index data of the index to be processed corresponding to the financial object in the time range to be processed, and determining a calculation task type corresponding to the calculation task; splitting the combined task into a plurality of basic tasks under the condition that the computing task type is the combined task; and respectively executing each basic task, and carrying out combined calculation on calculation results obtained by each basic task to obtain index data corresponding to the combined task. Specifically, the computing tasks include basic tasks and combined tasks, the combined tasks include a group of basic tasks, when the computing container is used for executing computing, the computing container firstly identifies the execution mode of the tasks, if the computing container is used for executing computing, the combined tasks are required to be split into the basic tasks, then various data configured by the pricing environment are called for respective execution, preferably, for the combined task types, each basic task included in the combined task can be determined in advance, operations such as preloading and the like are performed according to the task types so as to improve the efficiency of processing the data, and further, the result data obtained after the execution of different basic tasks is completed are correspondingly synthesized so as to obtain index data.
Further, in the case that the computing task type is a combined task, after splitting the combined task into a plurality of basic tasks, the method further includes: for each of the basic tasks, performing: and executing batch preloading on each basic task by adopting a streaming loading strategy, and/or loading parameter values which are contained in the basic tasks and are required for calculating indexes to be processed into a memory. By this step, the calculation efficiency for the combined task is improved. When the combined task is executed, various data such as parameter values corresponding to parameters, intermediate results output by functions corresponding to calculation strategies and the like can be shared through a memory, and a streaming loading strategy is adopted to execute batch preloading on each basic task, meanwhile, the streaming loading problem is also considered, so that the loading process and the calculation process are parallel, and multi-stream merging and flow control are realized; wherein, the content management can store data in the memory according to the key-value format. When the streaming type loading data is adopted, streaming inquiry can be adopted for reading the data from a data source, so that the parameter data flows into the memory like stream elements, and can also flow into the memory according to a set sequence according to a service rule. Corresponding parameter data is needed in the calculation process and is obtained from the memory through key values. Thereby realizing the parallel loading process and calculation process.
Further, the selecting a target model matching the unique identifier and the index to be processed from a plurality of registered financial models, further includes: searching a target model matched with the unique identifier and the index to be processed from a plurality of financial models of a preset registration mark; and calling the target model by utilizing a dynamic reflection calling strategy. Specifically, the preset registration mark can be a financial model mark marked by a code hierarchy @ Component, and the computing container can acquire a corresponding executed java bean under the Spring framework through the name of a service corresponding to the financial model mark so as to transmit the acquired model parameter to an execution function corresponding to a computing strategy based on the execution of the java bean; further, the embodiment of the invention can execute the call to the target model (API) through a dynamic reflection call strategy, wherein dynamic reflection refers to the property and method of dynamically loading and dynamically updating the object when the program runs so as to meet the call requirement to the required API in the program. Therefore, the execution method of the calculation strategy in the model improves the flexibility of calculation indexes and realizes code decoupling, and based on the dynamic reflection calling strategy, the distributed scheduling execution, abnormal feedback, operation log information acquisition and other functions can be executed.
Further preferably, in the embodiment of the invention, the unified storage, query and use of index results are realized by carrying out standardized processing on the calculation result return values in the system based on the data braiding technology, a library table is not required to be respectively built according to algorithm package sources, algorithm models, asset types and the like, technical requirements on technicians are reduced, calculation result return information can be dynamically configured in the device, the problem of poor data braiding performance caused by factors such as financial index complicacy, data structure diversification, data field customization and the like is solved, and the flexibility, the universality and the expansibility of data management are improved. The embodiment of the invention realizes unified storage, inquiry and use of the financial index data by applying the data braiding technology to the financial data processing, and improves the flexibility, the universality and the expansibility of data management. Among other things, data braiding (Data Fabric) is a comprehensive Data management and integration method that uses a set of technical components to manage, integrate, and process Data from disparate Data sources that can be better understood and utilized.
As shown in fig. 2, the embodiment of the invention provides a structural schematic diagram of an environment configuration page; the environment configuration page includes: an environment management page, an index management page, a model management page and a parameter management page.
The environment configuration page is an entry of the configuration page for various financial models; wherein the environment management page comprises a maintenance page for the environment definition and configuration, for example maintaining a hierarchical relationship of the environment in a tree structure. By clicking the new addition, modification and deletion buttons, the corresponding maintenance functions of the financial model environment are completed. Computing tasks, global parameters and the like can be configured through the environment management page; the index management page is one or more configuration pages that can provide indexes associated with the financial model; the model management page may provide a configuration page (including adding models, modifying existing models, etc.) for various data, such as financial objects, pending indicators of the fused objects, computing policies, etc., contained by one or more financial models. The parameter management page provides configuration of data such as data sources for various parameters and parameter values for various computing strategies.
As shown in fig. 3, an embodiment of the present invention provides a processing apparatus 300 for calculating a financial index model, including: a determination model module 301, a determination parameter module 302, and a calculation data module 303; wherein,
the determining model module is used for receiving a processing request aiming at a financial object, and analyzing a unique identifier, a to-be-processed index and a to-be-processed time range of the financial object to be processed from the processing request; selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object;
The parameter determining module is used for obtaining one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed;
and the calculation data module is used for calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
The embodiment of the invention also provides an electronic device for processing the financial index model calculation, which comprises: one or more processors; and a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method provided by any of the embodiments described above.
The embodiment of the invention also provides a computer readable medium, on which a computer program is stored, which when executed by a processor implements the method provided by any of the above embodiments.
FIG. 4 illustrates an exemplary system architecture 400 of a processing method of financial index model calculation or processing apparatus of financial index model calculation to which embodiments of the present invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405. The network 404 is used as a medium to provide communication links between the terminal devices 401, 402, 403 and the server 405. The network 404 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
A user may interact with the server 405 via the network 404 using the terminal devices 401, 402, 403 to receive or send messages or the like. Various client applications, such as a financial product client application, etc., may be installed on the terminal devices 401, 402, 403.
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting various client applications including, but not limited to, smartphones, tablets, laptop and desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server providing support for client applications used by the user with the terminal devices 401, 402, 403. The background management server can process the received processing request for the financial object, and feed back index data of the index to be processed corresponding to the financial object within the time range to be processed to the terminal device.
It should be noted that, the processing method for calculating the financial index model provided in the embodiment of the present invention is generally executed by the server 405, and accordingly, the processing device for calculating the financial index model is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, there is illustrated a schematic diagram of a computer system 500 suitable for use in implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not impose any limitation on the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input section 506 including a keyboard, a mouse, and the like; an output portion 507 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The drive 510 is also connected to the I/O interface 505 as needed. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as needed so that a computer program read therefrom is mounted into the storage section 508 as needed.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 509, and/or installed from the removable media 511. The above-described functions defined in the system of the present invention are performed when the computer program is executed by a Central Processing Unit (CPU) 501.
The computer readable medium shown in the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules and/or units involved in the embodiments of the present invention may be implemented in software, or may be implemented in hardware. The described modules and/or units may also be provided in a processor, e.g., may be described as: a processor includes a determination model module, a determination parameter module, and a calculation data module. The names of these modules do not in any way limit the module itself, and for example, the deterministic model module may also be described as "a module that selects a target model that matches the unique identifier and the index to be processed" from among a plurality of registered financial models.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to include: receiving a processing request aiming at a financial object, and analyzing a unique identifier of the financial object, a to-be-processed index of the financial object and a to-be-processed time range from the processing request; selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object; acquiring one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed; and calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
According to the embodiment of the invention, the processing request of calculating index data of the financial object can be selected from a plurality of registered financial models to be matched with the target model of the financial object; and acquiring parameters and corresponding parameter values of the target model, so as to calculate index data corresponding to the financial object by using a calculation strategy and the parameter values contained in the target model. According to the embodiment of the invention, the flexibility, the universality and the expansibility of the processing for the financial index model calculation are improved, the code coupling degree of the processing for the financial index model calculation is reduced, and the development efficiency is improved.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for processing financial index model calculations, comprising:
receiving a processing request aiming at a financial object, and analyzing a unique identifier of the financial object, a to-be-processed index of the financial object and a to-be-processed time range from the processing request;
Selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object;
acquiring one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed;
and calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
calculating index data of the to-be-processed index corresponding to the financial object within the to-be-processed time range by using the target model and the corresponding parameter value, wherein the index data comprises:
determining an interface type corresponding to the target model;
under the condition that the interface type is an asynchronous interaction mode, timing batch task information of the target model is obtained, so that the step of calculating index data of the to-be-processed index corresponding to the financial object in the to-be-processed time range is executed according to the timing batch task information, and the calculated index data is persisted;
And under the condition that the interface type is a synchronous interaction mode, directly executing the step of calculating the index data of the to-be-processed index corresponding to the financial object within the to-be-processed time range, and storing the index data into a memory.
3. The method as recited in claim 1, further comprising:
providing model configuration pages for various financial models;
receiving, by the model configuration page, the following various configuration information provided by a user: a financial model to be configured, a calculation index of the financial model, parameters required by calculating the calculation index, a calculation strategy required by calculating the calculation index, and a data source of parameter values of the parameters;
and storing and registering each financial model according to the configuration information received from the plurality of model configuration pages.
4. The method according to claim 1, characterized in that it comprises:
the obtaining one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed includes:
the parameter type of the parameter is obtained,
under the condition that the parameter type is a global parameter, directly acquiring a parameter value corresponding to the parameter;
And under the condition that the parameter type is a non-global parameter, analyzing the data source bound with the parameter, and acquiring a parameter value corresponding to the parameter in a time range to be processed from the data source.
5. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the calculating the index data of the index to be processed corresponding to the financial object within the time range to be processed comprises the following steps:
acquiring a calculation task corresponding to index data of the index to be processed corresponding to the financial object in the time range to be processed, and determining a calculation task type corresponding to the calculation task;
splitting the combined task into a plurality of basic tasks under the condition that the computing task type is the combined task;
and respectively executing each basic task, and carrying out combined calculation on calculation results obtained by each basic task to obtain index data corresponding to the combined task.
6. The method of claim 5, wherein the step of determining the position of the probe is performed,
in the case that the computing task type is a combined task, after splitting the combined task into a plurality of basic tasks, the method further comprises:
for each of the basic tasks, performing:
A streaming loading strategy is adopted to execute batch preloading on each basic task,
and/or the number of the groups of groups,
and loading parameter values which are contained in the basic task and are required for calculating the index to be processed into a memory.
7. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the selecting the target model matched with the unique identifier and the index to be processed from a plurality of registered financial models, further comprises:
searching a target model matched with the unique identifier and the index to be processed from a plurality of financial models of a preset registration mark;
and calling the target model by utilizing a dynamic reflection calling strategy.
8. A processing device for calculating a financial index model, comprising: the system comprises a model determining module, a parameter determining module and a data calculating module; wherein,
the determining model module is used for receiving a processing request aiming at a financial object, and analyzing a unique identifier, a to-be-processed index and a to-be-processed time range of the financial object to be processed from the processing request; selecting a target model matched with the unique identifier and the index to be processed from a plurality of registered financial models; the target model is packaged with a calculation strategy aiming at the index to be processed of the financial object;
The parameter determining module is used for obtaining one or more parameters corresponding to the calculation strategy and parameter values corresponding to the parameters in a time range to be processed;
and the calculation data module is used for calculating index data of the index to be processed corresponding to the financial object within the time range to be processed by using the target model, the calculation strategy and the corresponding parameter value.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-7.
10. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-7.
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| CN115827084A (en) * | 2022-09-28 | 2023-03-21 | 中国建设银行股份有限公司 | Data processing method, device, equipment and storage medium |
| CN117035065A (en) * | 2023-10-10 | 2023-11-10 | 浙江大华技术股份有限公司 | Model evaluation method and related device |
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| CN112613717A (en) * | 2020-12-17 | 2021-04-06 | 安徽兆尹信息科技股份有限公司 | Financial data processing method and storage medium |
| CN115827084A (en) * | 2022-09-28 | 2023-03-21 | 中国建设银行股份有限公司 | Data processing method, device, equipment and storage medium |
| CN117035065A (en) * | 2023-10-10 | 2023-11-10 | 浙江大华技术股份有限公司 | Model evaluation method and related device |
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