CN113344689A - Financial data processing method, device and equipment - Google Patents
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Abstract
The application provides a financial data processing method, device and equipment. The method comprises the following steps: and the client acquires the service configuration information and the algorithm configuration information of the service configuration interface. And the client determines a processing module corresponding to each algorithm configuration information according to the algorithm configuration information. The client can determine the association relationship among the plurality of processing modules according to a preset estimation algorithm. The client can realize the mutual reference among the processing modules according to the association relationship. And the client calculates the service configuration information of the financial product according to the data model and determines the valuation result of the financial product. The method improves the flexibility of data module construction.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a financial data processing method, apparatus, and device.
Background
In financial data processing algorithms, commonly used valuation methods may include market methods, revenue methods, cost methods, and the like. In actual use, the user can select one or more valuation methods to measure the fair value of a financial product.
Currently, in financial software, each financial product has its corresponding data model. For example, different financial products such as stocks, futures, gold, bonds, etc. may have different data models. The setting of the data model may be determined according to business parameters of the financial product.
However, the data model constructed separately for each financial product is prone to be solidified, and thus the data model has poor flexibility.
Disclosure of Invention
The application provides a financial data processing method, device and equipment, which are used for solving the problem that in the prior art, business parameters are solidified to a data model to cause poor flexibility of the data model.
In a first aspect, the present application provides a financial data processing method, applied to a client running a financial data processing program, where the financial data processing program includes a plurality of configuration interfaces, and each configuration interface corresponds to a financial product; the method comprises the following steps:
acquiring a plurality of service configuration information and a plurality of algorithm configuration information which are input through the configuration interface, wherein the service configuration information is used for indicating service parameters of the financial product, and the algorithm configuration information is used for indicating input parameters of the preset valuation algorithm;
selecting a plurality of processing modules from a processing module set according to the plurality of algorithm configuration information, and determining the incidence relation among the plurality of processing modules according to the preset valuation algorithm;
constructing a data model of the financial product according to the plurality of processing modules and the incidence relations between the plurality of processing modules;
and determining an evaluation result of the financial product according to the data model of the financial product and the service configuration information.
Optionally, the plurality of processing modules includes a first processing module and a second processing module; the constructing a data model of the financial product according to the plurality of processing modules and the association between the plurality of processing modules comprises:
and determining a reference relationship between the first processing module and the second processing module according to the association relationship.
Optionally, the processing module includes a data interface, and the data interface is configured to implement reference between the first processing module and the second processing module according to an association relationship of the data model.
Optionally, the method further comprises:
responding to a selection instruction, and selecting an input parameter of the algorithm configuration information or a service parameter of the service configuration information in the configuration table of the financial product maintenance interface;
or,
and responding to an editing instruction, and inputting the input parameters of the algorithm configuration information or the business parameters of the business configuration information in the configuration table of the financial product maintenance interface.
Optionally, the method further comprises:
and displaying the estimation result on the financial product maintenance interface, wherein the estimation result comprises a rate of return curve.
Optionally, the method further comprises:
and displaying the processing modules corresponding to the algorithm configuration information and the association relationship between the processing modules on the financial product maintenance interface.
In a second aspect, the present application provides a financial data processing apparatus, which is applied to a client running a financial data processing program, where the financial data processing program includes a plurality of configuration interfaces, and each configuration interface corresponds to a financial product; the apparatus, comprising:
the acquisition unit is used for acquiring a plurality of service configuration information and a plurality of algorithm configuration information which are input through the configuration interface, wherein the service configuration information is used for indicating service parameters of the financial product, and the algorithm configuration information is used for indicating input parameters of the preset valuation algorithm;
the first determining unit is used for selecting a plurality of processing modules from a processing module set according to the plurality of algorithm configuration information and determining the incidence relation among the plurality of processing modules according to the preset valuation algorithm;
a construction unit configured to construct a data model of the financial product based on the plurality of processing modules and the association relationship between the plurality of processing modules;
and the second determining unit is used for determining an evaluation result of the financial product according to the data model of the financial product and the service configuration information.
Optionally, the plurality of processing modules includes a first processing module and a second processing module; the building unit is specifically configured to determine, according to the association relationship, a reference relationship between the first processing module and the second processing module.
Optionally, the processing module includes a data interface, and the data interface is configured to implement reference between the first processing module and the second processing module according to an association relationship of the data model.
Optionally, the obtaining unit is specifically configured to select, in response to a selection instruction, an input parameter of the algorithm configuration information or a service parameter of the service configuration information in the configuration table of the financial product maintenance interface; or, in response to an editing instruction, inputting the input parameters of the algorithm configuration information or the business parameters of the business configuration information in the configuration table of the financial product maintenance interface.
Optionally, the apparatus further comprises:
and the display unit is used for displaying the estimation result on the financial product maintenance interface, and the estimation result comprises a yield curve.
Optionally, the display unit is further configured to display, on the financial product maintenance interface, processing modules corresponding to the algorithm configuration information and an association relationship between the processing modules.
In a third aspect, the present application provides a client, including: a memory and a processor;
the memory is used for storing program instructions; the processor is configured to invoke program instructions in the memory to perform the method of financial data processing in the first aspect and any one of the possible designs of the first aspect.
In a fourth aspect, the present application provides a readable storage medium, in which a computer program is stored, and when the computer program is executed by at least one processor of a client, the client performs the financial data processing method according to the first aspect and any one of the possible designs of the first aspect.
In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by at least one processor of a client, causes the client to perform the method of financial data processing of the first aspect as well as any one of the possible designs of the first aspect.
The financial data processing method provided by the application comprises the steps of obtaining the service configuration information and the algorithm configuration information of the service configuration interface; determining a processing module corresponding to each algorithm configuration information according to the algorithm configuration information; determining an incidence relation among a plurality of processing modules according to a preset estimation algorithm; according to the incidence relation, realizing the mutual reference among all the processing modules; and calculating the service configuration information of the financial product according to the data model, and determining the valuation result of the financial product, thereby realizing the effect of improving the flexibility of the construction of the data module.
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In order to more clearly illustrate the technical solutions in the present application or 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 application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic diagram of a configuration interface of a financial data processing program according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for processing financial data according to an embodiment of the present application;
FIG. 3 is a diagram illustrating a data module according to an embodiment of the present application;
FIG. 4 is a flow chart of another method of financial data processing according to an embodiment of the present application;
FIG. 5 is a graphical illustration of a profitability curve provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of a financial data processing apparatus according to an embodiment of the present application;
fig. 7 is a schematic diagram of a hardware structure of a client according to an embodiment of the present disclosure.
Detailed Description
To make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be clearly and completely described below with reference to the drawings in the present application, and it is obvious that the described embodiments are some, but not all embodiments of the present application. 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 application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged where appropriate. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein.
The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
Also, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise.
It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, items, species, and/or groups thereof.
The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.
In financial data processing algorithms, commonly used valuation methods may include market methods, revenue methods, cost methods, and the like. In actual use, the user can select one or more valuation methods to measure the fair value of a financial product. When a user measures the fair value by using a plurality of estimation methods, the reasonability of each estimation result is considered, and the money which can represent the fair value most under the current condition is selected as the fair value. Taking the earning method as an example, the earning method is an estimation method for converting future money amount into single present value. The revenue method is particularly applicable to financial products that generate cash flows at multiple points in the future: such as bonds, interest rate falls, cross currency falls, etc. Due to the time value of the currency, when calculating the fair value of the financial products, cash flows at different time points need to be converted into the same time point and then accumulated, so that the fair value of the financial products at the time point is obtained. When using the revenue method for estimation, how to select the appropriate discount factor is very important for the accuracy of the fair value measurement. The selection of the discount factor not only reflects the time value of the currency, but also reflects factors such as credit risk and liquidity risk included in future cash flow.
Currently, in financial software, each financial product has its corresponding data model. The data model includes a data processing flow for implementing a fair value calculation of the financial product. Wherein the valuation method may be the same method for different financial products. The codes of different financial products may have the same or similar logic according to the same valuation method. However, business data (market data) of different financial products is necessarily different. For example, financial products such as stocks, futures, gold, bonds, etc. may have different market data. In order to deal with the different obtained service data, different algorithm configurations must exist in the data model of the service data. The data model can solidify the algorithm configuration into a program to ensure that the data model can correctly calculate an estimation result when processing the corresponding financial product. The mode of solidifying the algorithm configuration into the program can reduce the reference relation among the hierarchies, and the data structure is relatively horizontal and convenient to develop.
However, the consistency of the algorithm is necessarily high between data models of different financial products. After the data models are independently constructed for each financial product, the common data processing logic is inevitably redundant in each data model. Meanwhile, as the algorithm configuration is solidified into the data model in each data model, once the logic of the data model needs to be modified, all the codes of the data model need to be modified inevitably, and the problem of poor flexibility of the data model exists. Meanwhile, different financial products use different data models, so that the relation among data is not recorded and displayed, and business verification and later analysis are not convenient.
In order to solve the problems, the application provides a financial data processing method. The method is implemented by a financial data processing program. The financial data processing program is run on the client. When the client runs the financial data processing program, a configuration interface can be displayed in the display interface of the client according to financial products. The financial data processing program may include a plurality of configuration interfaces, each configuration interface corresponding to a financial product. In the application, the client can obtain a plurality of service configuration information and a plurality of algorithm configuration information for inputting through the configuration interface. The business configuration information is used for indicating business parameters of the financial product. The algorithm configuration information is used to indicate input parameters of a preset estimation algorithm. The client selects a plurality of processing modules from the set of processing modules according to the plurality of algorithm configuration information. And the client determines the incidence relation among the processing modules according to a preset estimation algorithm. And the client side constructs a data model of the financial product according to the plurality of processing modules and the incidence relation among the plurality of processing modules. And the client determines the valuation result of the financial product according to the data model and the service configuration information of the financial product. By the method, the processing module required to be used can be determined according to the requirement of each financial product, so that the construction flexibility of the data module is greatly improved.
The technical solution of the present application will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is a schematic diagram illustrating a configuration interface of a financial data processing program according to an embodiment of the present application. The configuration interface includes a plurality of pieces of configuration information as shown in fig. 1. The configuration information includes service configuration information, such as release date, bond expiration date, first payment date, and the like. The method also comprises algorithm configuration information, such as currency, net price, interest-bearing mode and the like. The user may enter the configuration interface upon selecting a financial product. Each financial product corresponds to a configuration interface. For example, a configuration interface for a bond-type financial product is shown in FIG. 1. In the configuration interface, the user can select different algorithm configuration information and service configuration information for different bond types. Alternatively, the user may enter different algorithm configuration information and service configuration information. For example, the user may determine different issue dates and bond expiration dates from different kinds of bonds. As another example, different types of bonds may have different currencies. In addition, different financial products may have different configuration interfaces. The different configuration interfaces may have different algorithm configuration information and service configuration information.
In the present application, a client is used as an execution subject to execute the financial data processing method of the following embodiment. Specifically, the execution subject may be a hardware device of the client, or a software application in the client, or a computer-readable storage medium on which the software application implementing the following embodiment is installed, or code of the software application implementing the following embodiment.
FIG. 2 is a flow chart illustrating a method for processing financial data according to an embodiment of the present application. The financial data processing method of the embodiment is applied to the client. The client runs a financial data processing program, the financial data processing program comprises a plurality of configuration interfaces, and each configuration interface corresponds to a financial product. As shown in fig. 2, with the client as the execution subject, the method of this embodiment may include the following steps:
s101, acquiring a plurality of service configuration information and a plurality of algorithm configuration information input through a configuration interface, wherein the service configuration information is used for indicating service parameters of financial products, and the algorithm configuration information is used for indicating input parameters of a preset valuation algorithm.
In this embodiment, a user may input algorithm configuration information and service configuration information in a configuration interface of a client. And the client side client acquires the service configuration information and the algorithm configuration information of the service configuration interface. The configuration interface may be as shown in fig. 1. The business configuration information is used for indicating business parameters of the financial product. For example, the issue date, bond expiration date, first payment date, etc. as shown in fig. 1. Wherein the algorithm configuration information is used for indicating input parameters of a preset estimation algorithm. For example, currency, net price, interest bearing, etc. as shown in fig. 1.
In one example, the user may trigger a selection instruction in each text box of the configuration interface shown in FIG. 1 by way of selection. And responding to the selection instruction, and selecting the input parameters of the algorithm configuration information or the service parameters of the service configuration information in the configuration interface.
In another example, the user may input text in each text amount of the configuration interface shown in fig. 1 by way of input, triggering an editing instruction. And responding to the editing instruction, and inputting the input parameters of the algorithm configuration information or the service parameters of the service configuration information in the configuration interface.
And S102, selecting a plurality of processing modules from the processing module set according to the plurality of algorithm configuration information.
In this embodiment, after obtaining the plurality of algorithm configuration information of the configuration interface, the client may determine, according to the algorithm configuration information, one processing module corresponding to each algorithm configuration information. Wherein one algorithm configuration information corresponds to one processing module. One processing module may correspond to one or more processing modules. The processing module is used for completing a processing step of the preset estimation algorithm. For example, as shown in fig. 3, the processing module may be a calendar holiday module, business day rule module, interest rate module, interest method module, etc.
S103, determining the association relation among the processing modules according to a preset estimation algorithm.
In this embodiment, the client may determine the association relationship between the processing modules in S102 according to a preset estimation algorithm. The association relationship may specifically be a reference relationship between the processing modules. For example, as shown in fig. 3, the association relationship between the respective processing modules may refer to the calendar holiday module and the business day rule module for the pay-per-day frequency module.
And S104, constructing a data model of the financial product according to the plurality of processing modules and the incidence relation among the plurality of processing modules.
In this embodiment, after determining the association relationship between each processing module and each processing module, the client may implement mutual reference between each processing module according to the association relationship. For example, as shown in FIG. 3, the interest method module may reference a pay-per-day frequency module. The pay-per-day frequency module may reference a calendar vacation module and a business day rules module. The client can realize the establishment of the whole data model according to the incidence relation. For example, the data model may be as shown in FIG. 3, ultimately implementing a cash flow analysis.
In one example, the process of establishing the reference relationship of the data model may include:
and the client determines a first processing module and a second processing module in the plurality of processing modules according to the association relationship. And an association relationship exists between the first processing module and the second processing module. The client can determine a reference relationship between the first processing module and the second processing module according to the association relationship. And the client determines the reference between the first processing module and the second processing module according to the reference relation between the first processing module and the second processing module. For example, when a relationship references a first processing module to a second processing module, it may be constructed in such a way that the first processing module references the second processing module. When the relationship references the first processing module for the second processing module, it may be constructed in a manner that references the first processing module for the second processing module.
In one example, each processing module may further include a data interface. The data interface is used for realizing application among the functional modules. For example, when a first data module references a second data module, the first data module may implement the reference of the second data module by calling a data interface of the second data module.
And S105, determining an estimation result of the financial product according to the data model and the service configuration information of the financial product.
In this embodiment, after the client completes the construction of the data model, the client may calculate the service configuration information of the financial product according to the data model, and determine the estimation result of the financial product.
According to the financial data processing method, the client side obtains the service configuration information and the algorithm configuration information of the service configuration interface. After the client acquires the plurality of algorithm configuration information of the configuration interface, a processing module corresponding to each algorithm configuration information can be determined according to the algorithm configuration information. The client can determine the association relationship among the plurality of processing modules according to a preset estimation algorithm. After determining the association relationship between each processing module and each processing module, the client can implement mutual reference between each processing module according to the association relationship. After the client completes the construction of the data model, the client can calculate the service configuration information of the financial product according to the data model and determine the valuation result of the financial product. In the application, the data model is constructed, so that the construction flexibility of the data module is greatly improved.
FIG. 4 is a flow chart illustrating another method of financial data processing according to an embodiment of the present application. On the basis of the embodiments shown in fig. 2 and fig. 3, as shown in fig. 4, with the client as the execution subject, the method of this embodiment may include the following steps:
s201, acquiring a plurality of service configuration information and a plurality of algorithm configuration information input through a configuration interface, wherein the service configuration information is used for indicating service parameters of financial products, and the algorithm configuration information is used for indicating input parameters of a preset valuation algorithm.
S202, selecting a plurality of processing modules from the processing module set according to the plurality of algorithm configuration information.
S203, determining the association relation among the processing modules according to a preset estimation algorithm.
And S204, constructing a data model of the financial product according to the plurality of processing modules and the incidence relation among the plurality of processing modules.
S205, determining an estimation result of the financial product according to the data model and the service configuration information of the financial product.
Steps S201 to S205 are similar to steps S101 to S105 in the embodiment of fig. 2, and are not described again in this embodiment.
And S205, displaying an estimation result on a configuration interface, wherein the estimation result comprises a yield curve.
In this embodiment, the client may also display the evaluation result in the configuration interface. For example, when the estimation result is a yield curve, the yield curve may be as shown in fig. 5. Wherein the horizontal axis represents the remaining term. The vertical axis represents interest rate. The point in this axis represents that the final profitability is Y for the remaining term of X days. Wherein, any remaining period in the X horizontal axis, Y is the interest rate corresponding to the remaining period.
S206, displaying processing modules corresponding to the algorithm configuration information on the configuration interface, and displaying the association relationship among the processing modules.
In this embodiment, the client may further display each processing module in the configuration interface. For example, as shown in fig. 3, the data model may include processing modules such as cash flow analysis, profitability curves, interpolation methods, and the like. The client can also display the association relationship among the processing modules in the configuration interface. For example, as shown in FIG. 3, the references between the data modules may be indicated by arrows and text.
According to the financial data processing method, the client side obtains the service configuration information and the algorithm configuration information of the service configuration interface. And the client determines a processing module corresponding to each algorithm configuration information according to the algorithm configuration information. The client can determine the association relationship among the plurality of processing modules according to a preset estimation algorithm. The client can realize the mutual reference among the processing modules according to the association relationship. And the client calculates the service configuration information of the financial product according to the data model and determines the valuation result of the financial product. The client can also display the evaluation result in a configuration interface. The client can also display each processing module in the configuration interface. The client can also display the association relationship among the processing modules in the configuration interface. In the application, the data model is constructed, so that the construction flexibility of the data module is greatly improved.
Fig. 6 is a schematic structural diagram illustrating a financial data processing apparatus according to an embodiment of the present application. The financial data processing method of the embodiment is applied to the client. The client runs a financial data processing program, the financial data processing program comprises a plurality of configuration interfaces, and each configuration interface corresponds to a financial product. As shown in fig. 6, the financial data processing apparatus 10 of the present embodiment is configured to implement the operation corresponding to the client in any one of the method embodiments described above, and the financial data processing apparatus 10 of the present embodiment includes:
the acquiring unit 11 is configured to acquire a plurality of service configuration information and a plurality of algorithm configuration information input through the configuration interface, where the service configuration information is used to indicate service parameters of the financial product, and the algorithm configuration information is used to indicate input parameters of a preset valuation algorithm.
The first determining unit 12 is configured to select a plurality of processing modules from the processing module set according to the plurality of algorithm configuration information, and determine an association relationship between the plurality of processing modules according to a preset estimation algorithm.
And the construction unit 13 is used for constructing a data model of the financial product according to the plurality of processing modules and the incidence relation among the plurality of processing modules.
And a second determining unit 14 for determining an estimation result of the financial product according to the data model of the financial product and the service configuration information.
In one example, the plurality of processing modules includes a first processing module and a second processing module. The constructing unit 13 is specifically configured to determine, according to the association relationship, a reference relationship between the first processing module and the second processing module.
In one example, the processing module includes a data interface for implementing a reference between the first processing module and the second processing module according to an association of the data model.
In one example, the obtaining unit 11 is specifically configured to select, in response to a selection instruction, an input parameter of the algorithm configuration information or a service parameter of the service configuration information in a configuration table of the financial product maintenance interface. Or, in response to the editing instruction, inputting the input parameters of the algorithm configuration information or the business parameters of the business configuration information in a configuration table of the financial product maintenance interface.
In one example, an apparatus further comprises: a display unit 15.
In one example, the display unit is further configured to display the estimation result on the financial product maintenance interface, and the estimation result includes a profitability curve.
In one example, the display unit is further used for displaying processing modules corresponding to the algorithm configuration information and the association relationship among the processing modules on the financial product maintenance interface.
The financial data processing apparatus 10 provided in the embodiment of the present application may implement the method embodiment, and for details of the implementation principle and the technical effect, reference may be made to the method embodiment, and details of the embodiment are not described herein again.
Fig. 7 shows a hardware structure diagram of a client according to an embodiment of the present application. As shown in fig. 7, the client 20 is configured to implement operations corresponding to the client in any of the method embodiments described above, where the client 20 of this embodiment may include: memory 21, processor 22.
A memory 21 for storing a computer program. The Memory 21 may include a Random Access Memory (RAM), a Non-Volatile Memory (NVM), at least one disk Memory, a usb disk, a removable hard disk, a read-only Memory, a magnetic disk or an optical disk.
And a processor 22 for executing the computer program stored in the memory to implement the financial data processing method in the above-described embodiments. Reference may be made in particular to the description relating to the method embodiments described above. The Processor 22 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
Alternatively, the memory 21 may be separate or integrated with the processor 22.
When memory 21 is a separate device from processor 22, client 20 may also include bus 23. The bus 23 is used to connect the memory 21 and the processor 22. The bus 23 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The client provided in this embodiment may be used to execute the financial data processing method, and the implementation manner and the technical effect thereof are similar, and this embodiment is not described herein again.
The present application also provides a computer-readable storage medium, in which a computer program is stored, and the computer program is used for implementing the methods provided by the above-mentioned various embodiments when being executed by a processor.
The computer-readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a computer readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the computer readable storage medium. Of course, the computer readable storage medium may also be integral to the processor. The processor and the computer-readable storage medium may reside in an Application Specific Integrated Circuit (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the computer-readable storage medium may also reside as discrete components in a communication device.
In particular, the computer-readable storage medium may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random-Access Memory (SRAM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The present application also provides a computer program product comprising a computer program stored in a computer readable storage medium. The computer program can be read by at least one processor of the device from a computer-readable storage medium, and execution of the computer program by the at least one processor causes the device to implement the methods provided by the various embodiments described above.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules may be combined or may be 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, devices or modules, and may be in an electrical, mechanical or other form.
Wherein the modules may be physically separated, e.g. mounted at different locations of one device, or mounted on different devices, or distributed over multiple network elements, or distributed over multiple processors. The modules may also be integrated, for example, in the same device, or in a set of codes. The respective modules may exist in the form of hardware, or may also exist in the form of software, or may also be implemented in the form of software plus hardware. The method and the device can select part or all of the modules according to actual needs to achieve the purpose of the scheme of the embodiment.
When the respective modules are implemented as integrated modules in the form of software functional modules, they may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor to execute some steps of the methods according to the embodiments of the present application.
It should be understood that, although the respective steps in the flowcharts in the above-described embodiments are sequentially shown as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or at least partially with respect to other steps or sub-steps of other steps.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: it is also possible to modify the solutions described in the previous embodiments or to substitute some or all of them with equivalents. 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 application.
Claims (10)
1. The financial data processing method is applied to a client, wherein the client runs a financial data processing program, the financial data processing program comprises a plurality of configuration interfaces, and each configuration interface corresponds to a financial product; the method comprises the following steps:
acquiring a plurality of service configuration information and a plurality of algorithm configuration information which are input through the configuration interface, wherein the service configuration information is used for indicating service parameters of the financial product, and the algorithm configuration information is used for indicating input parameters of the preset valuation algorithm;
selecting a plurality of processing modules from a processing module set according to the plurality of algorithm configuration information, and determining the incidence relation among the plurality of processing modules according to the preset valuation algorithm;
constructing a data model of the financial product according to the plurality of processing modules and the incidence relations between the plurality of processing modules;
and determining an evaluation result of the financial product according to the data model of the financial product and the service configuration information.
2. The financial data processing method of claim 1 wherein the plurality of processing modules includes a first processing module and a second processing module; the constructing a data model of the financial product according to the plurality of processing modules and the association between the plurality of processing modules comprises:
and determining a reference relationship between the first processing module and the second processing module according to the association relationship.
3. The financial data processing method of claim 1 or 2 wherein the processing modules include a data interface for enabling referencing between two of the processing modules according to the association of the data models.
4. The financial data processing method of claim 1 or 2, further comprising:
responding to a selection instruction, and selecting the input parameters of the algorithm configuration information or the service parameters of the service configuration information in the configuration interface;
or,
and responding to an editing instruction, and inputting the input parameters of the algorithm configuration information or the service parameters of the service configuration information in the configuration plane.
5. The financial data processing method of claim 1 or 2, further comprising:
and displaying the estimation result on the configuration interface, wherein the estimation result comprises a yield curve.
6. The financial data processing method of claim 1 or 2, further comprising:
and displaying the processing modules corresponding to the algorithm configuration information and the association relationship among the processing modules on the configuration interface.
7. The financial data processing device is applied to a client, the client runs a financial data processing program, the financial data processing program comprises a plurality of configuration interfaces, and each configuration interface corresponds to a financial product; the apparatus, comprising:
the acquisition unit is used for acquiring a plurality of service configuration information and a plurality of algorithm configuration information which are input through the configuration interface, wherein the service configuration information is used for indicating service parameters of the financial product, and the algorithm configuration information is used for indicating input parameters of the preset valuation algorithm;
the first determining unit is used for selecting a plurality of processing modules from a processing module set according to the plurality of algorithm configuration information and determining the incidence relation among the plurality of processing modules according to the preset valuation algorithm;
a construction unit configured to construct a data model of the financial product based on the plurality of processing modules and the association relationship between the plurality of processing modules;
and the second determining unit is used for determining an evaluation result of the financial product according to the data model of the financial product and the service configuration information.
8. A financial data processing apparatus, characterized in that the apparatus comprises: a memory, a processor;
the memory is used for storing a computer program; the processor is configured to implement the financial data processing method according to any one of claims 1 to 6, in accordance with the computer program stored in the memory.
9. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, is adapted to implement the financial data processing method according to any one of claims 1 to 6.
10. A computer program product, characterized in that it comprises a computer program which, when executed by a processor, implements the financial data processing method of any one of claims 1 to 6.
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| CN117437064A (en) * | 2023-12-18 | 2024-01-23 | 凯美瑞德（苏州）信息科技股份有限公司 | Method, apparatus, electronic device and computer readable medium for processing financial data |
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