CN116645210A - Air control method, system, equipment and medium for resource management products - Google Patents
Air control method, system, equipment and medium for resource management products Download PDFInfo
- Publication number
- CN116645210A CN116645210A CN202310090053.6A CN202310090053A CN116645210A CN 116645210 A CN116645210 A CN 116645210A CN 202310090053 A CN202310090053 A CN 202310090053A CN 116645210 A CN116645210 A CN 116645210A
- Authority
- CN
- China
- Prior art keywords
- resource management
- data
- information
- combination
- air control
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000004458 analytical method Methods 0.000 claims abstract description 56
- 238000011160 research Methods 0.000 claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 16
- 238000012216 screening Methods 0.000 claims abstract description 16
- 230000035515 penetration Effects 0.000 claims abstract description 9
- 238000007726 management method Methods 0.000 claims description 113
- 238000004590 computer program Methods 0.000 claims description 9
- 238000003860 storage Methods 0.000 claims description 7
- 238000004519 manufacturing process Methods 0.000 claims 1
- 238000011156 evaluation Methods 0.000 abstract description 20
- 239000006185 dispersion Substances 0.000 abstract description 4
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 239000000203 mixture Substances 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000012946 outsourcing Methods 0.000 description 5
- 238000004141 dimensional analysis Methods 0.000 description 4
- 238000012351 Integrated analysis Methods 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 238000005304 joining Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000014509 gene expression Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/06—Asset management; Financial planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Operations Research (AREA)
- General Physics & Mathematics (AREA)
- Technology Law (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application discloses a wind control method, a system, equipment and a medium for resource management products, wherein the wind control method comprises the following steps: acquiring investment and research analysis data of resource management products; determining resource and management product combination information according to the research analysis data; performing net worth processing on the information of the resource management product combination and the external data to obtain wind control data of the target resource management product; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product. The application realizes screening evaluation before throwing and dynamic tracking of performance after throwing through integrating analysis processing on throwing and researching data and external data covering the whole process of investment management outside the commission, thereby reasonably and efficiently acquiring and processing the data, being embodied in the wind control evaluation of resource management products, being beneficial to accurately evaluating the performance of the investment, dynamically giving out the optimal combination of investment advice based on the performance analysis and attribution analysis, and realizing asset configuration and risk dispersion.
Description
Technical Field
The application belongs to the technical field of air control of resource management products, and particularly relates to an air control method, an air control system, air control equipment and air control media of resource management products.
Background
According to the latest resource management requirements, the resource management products are subjected to nested investment, and the combination calculation is required according to the penetration principle; and a large amount of fund research data is needed for realizing the bottom asset penetration statistics, and the data collection statistics difficulty is high due to the lack of a unified data management system and scientific integration, so that the traditional manual collection statistics mode is low in efficiency and easy to make mistakes, the user experience is poor, the requirements are difficult to meet, and the rapid development of the company management scale cannot be met. Furthermore, with the accelerated development of business, the scale of assets is rapidly increased, investment standards are increasingly enriched, the number of products and transaction channels is greatly increased, the operation pressure of companies is rapidly increased, and huge operation risks are faced. The wind control capability is one of the core competitiveness of the foundation, and various supervision specifications, investors' wind control requirements, company internal control and the like all provide very high requirements for wind control. The current manual statistics mode is lack of real-time performance, so that effective regulation of data is difficult to realize, and the requirements of investment and wind control are more and more difficult to meet.
Disclosure of Invention
The application aims to overcome the defects in the prior art and provides a wind control method, a system, equipment and a medium for resource management products.
The application solves the technical problems by the following technical scheme:
the application provides a wind control method of resource management products, which comprises the following steps:
acquiring investment and research analysis data of resource management products;
determining resource and management product combination information according to the research analysis data;
performing net worth processing on the information of the resource management product combination and the external data to obtain wind control data of the target resource management product; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product.
Preferably, the wind control data further comprises early warning information corresponding to the resource and management product combination information and external data; the step of determining the resource and management product combination information according to the research analysis data further comprises the following steps:
and acquiring the early warning information according to a preset threshold value.
Preferably, the step of acquiring the research analysis data of the resource management product comprises the following steps:
and screening and updating the research analysis data based on at least one index in the resource management products and the corresponding fund managers and management companies.
Preferably, the step of determining the resource management product combination information according to the research analysis data includes:
analyzing the screened and updated lapping analysis data according to a preset model combination to determine the resource management product combination information; the preset model combination comprises at least one of an MV mean variance model, a BL mean variance model, a risk price reduction model and a risk budget model.
The application also provides a wind control system of the resource management product, which comprises:
the data acquisition module is used for acquiring the research analysis data of the resource management products;
the information determining module is used for determining the combination information of the resource management products according to the research analysis data;
the air control module is used for carrying out net value processing on the information of the resource management product combination and the external data so as to obtain air control data of the target resource management product; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product.
Preferably, the wind control data further comprises early warning information corresponding to the resource and management product combination information and external data; the wind control module is also used for acquiring the early warning information according to a preset threshold value.
Preferably, the data acquisition module is further configured to:
and screening and updating the research analysis data based on at least one index in the resource management products and the corresponding fund managers and management companies.
Preferably, the information determining module is specifically configured to:
analyzing the screened and updated lapping analysis data according to a preset model combination to determine the resource management product combination information; the preset model combination comprises at least one of an MV mean variance model, a BL mean variance model, a risk price reduction model and a risk budget model.
The application also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the air control method of the resource management product is realized when the processor executes the computer program.
The application also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the air control method of the resource management product.
The application has the positive progress effects that: the application provides a wind control method, a system, equipment and a medium for resource management products, which are used for carrying out integrated analysis processing on investment data and external data covering the whole process of outsourcing investment management, realizing screening evaluation before investment, dynamic tracking of performance after investment and evaluation of resource management products in all markets, thereby reasonably and efficiently acquiring and processing data of each channel, reflecting the data in the wind control evaluation of the resource management products, being beneficial to accurately carrying out the evaluation of the investment performance, dynamically giving out investment advice optimization combinations based on the performance analysis and attribution analysis, and realizing asset configuration and risk dispersion.
Drawings
Fig. 1 is a flowchart of a method for controlling air flow of a resource management product according to embodiment 1 of the present application.
Fig. 2 is a schematic block diagram of an air control system for resource management products according to embodiment 2 of the present application.
Fig. 3 is a block diagram of a risk system for resource management products according to embodiment 2 of the present application.
Fig. 4 is a block diagram of an electronic product according to embodiment 3 of the present application.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
The air control method of the resource management product provided in this embodiment may be executed in an intelligent terminal, a computer terminal, a network device, a chip module, or a similar computing device. Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the described embodiments of the application may be combined with other embodiments.
It will be appreciated that "system," "apparatus," "unit" and/or "module" as used herein is one method for distinguishing between different components, elements, parts, portions or assemblies of different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.
As used in this specification, the terms "a," "an," "the," and/or "the" are not intended to be limiting, but rather are to be construed as covering the singular and the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
Example 1
The embodiment specifically provides a wind control method for resource management products, as shown in fig. 1, including the following steps:
s1, acquiring investment and research analysis data of resource management products;
s2, determining the combination information of the resource management products according to the research analysis data;
s3, carrying out net value processing on the combination information of the resource management products and the external data to obtain wind control data of the target resource management products; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product.
The external data can be automatically fetched from a database, a third party interface, a mail and other channels which accord with the template format, and historical data can be imported into the database in batches through the data table document; and combining the combination information of the resource management products and external data, and further configuring an estimated value table and a net value table template, so that wind control management is performed on the basis of updated fusion data.
As a preferred implementation mode, the wind control data also comprises early warning information corresponding to the combination information of the resource management products and the external data; the step of determining the resource management product combination information according to the research analysis data further comprises the following steps: and acquiring early warning information according to a preset threshold value. Specifically, the threshold value setting is carried out on the index of the product in the warehouse, which needs to be tracked and pre-warned, so that the long-term tracking and pre-warning can be conveniently carried out, and the warning item can inform the manager through the backlog; in addition, all data kneaded after the net worth processing can be visually tracked in the management cockpit.
In a preferred embodiment, the step of acquiring the research analysis data of the resource management product comprises the following steps:
screening and updating the research analysis data based on at least one index in the resource management products and the corresponding fund managers and management companies. Specifically, index screening is carried out on three dimensions of the fund product, the management company and the fund manager to obtain an alternative product, and the alternative product is added into a self-selection library; and further screening the products in the self-selection library through a comparison analysis flow, and adding the re-selected products into an asset configuration flow. Further, historical performance-based composition returns, contextual analysis, and future performance distribution simulation analysis may be performed on the configured composition to determine a product composition for joining the product library.
In a preferred embodiment, the step of determining the resource product combination information according to the research analysis data includes:
according to the preset model combination analysis, screening and updating the research analysis data to determine resource management product combination information; the preset model combination comprises at least one of an MV mean variance model, a BL mean variance model, a risk price reduction model, a risk budget model and a self-defined weight model.
Any plurality of market public fund products or self-owned fund products can be selected for any combination, and the types and types of the products are not limited; the combination parameters are divided into two parts, one part is a product parameter part and comprises an amount to be charged, an early warning amount, a loss stopping amount and time parameter selection, wherein the amount to be charged is needed to be charged; and secondly, the constraint condition part is used for adjusting different investment targets according to different constraint conditions under each model.
According to the air control method for the resource management products, integrated analysis processing is carried out on the investment data and the external data covering the whole process of investment management outside the commission, pre-investment screening evaluation, post-investment performance dynamic tracking and all-market resource management product evaluation are achieved, so that data of all channels are reasonably and efficiently acquired and processed, the data are reflected in the air control evaluation of the resource management products, the accurate evaluation of investment performance is facilitated, and investment advice optimal selection combinations are dynamically given on the basis of performance analysis and attribution analysis, and asset configuration and risk dispersion are achieved. Further, based on the macro economy and capital market database, an original investment model is built by applying a machine learning algorithm and a financial theory, and full-flow investment analysis service from transaction strategies to performance analysis is provided; constructing multi-level and multi-dimensional analysis evaluation indexes of outsourcing managers according to the basic information of the institutions, corresponding past investment performance information, warehouse holding data information and the like, and comprehensively comparing the multi-level and multi-dimensional analysis evaluation indexes with all markets to realize scientific evaluation and optimization of outsourcing managers; the method realizes the construction of the fund combination from top to bottom according to the risk preference and the macroscopic economic cycle of the investors, continuously and comprehensively tracks the performance and the risk exposure degree of the combination, timely gives out the warehouse holding adjustment suggestion, forms a complete closed loop, and assists the investors to efficiently and conveniently manage the investment combination.
Example 2
Corresponding to the air control method of the resource management product described above, the embodiment also provides an air control system of the resource management product. The following will describe each. It should be noted that, the air control system of the resource management product of this embodiment may be, for example: the individual chip, chip module or electronic device may also be a chip or chip module integrated in the electronic device. With respect to each of the apparatuses and each of the modules/units included in the products described in the above embodiments, it may be a software module/unit, a hardware module/unit, or a software module/unit, and a hardware module/unit. For example, for each device or product applied to or integrated on a chip, each module/unit included in the device or product may be implemented in hardware such as a circuit, or at least part of the modules/units may be implemented in software program, where the software program runs on a processor integrated inside the chip, and the rest (if any) of the modules/units may be implemented in hardware such as a circuit; for each device and product applied to or integrated in the chip module, each module/unit contained in the device and product can be realized in a hardware manner such as a circuit, different modules/units can be located in the same component (such as a chip, a circuit module and the like) or different components of the chip module, or at least part of the modules/units can be realized in a software program, the software program runs on a processor integrated in the chip module, and the rest (if any) of the modules/units can be realized in a hardware manner such as a circuit; for each device, product, or application to or integrated with the terminal, each module/unit included in the device, product, or application may be implemented by using hardware such as a circuit, different modules/units may be located in the same component (for example, a chip, a circuit module, or the like) or different components in the terminal, or at least part of the modules/units may be implemented by using a software program, where the software program runs on a processor integrated inside the terminal, and the remaining (if any) part of the modules/units may be implemented by using hardware such as a circuit.
Specifically, as shown in fig. 2, the air control system of the resource management product of the present embodiment includes:
the data acquisition module 1 is used for acquiring the research analysis data of the resource management products;
the information determining module 2 is used for determining the combination information of the resource management products according to the research analysis data;
the wind control module 3 is used for carrying out net value processing on the combination information of the resource management products and the external data so as to obtain wind control data of the target resource management products; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product.
The external data can be automatically fetched from a database, a third party interface, a mail and other channels which accord with the template format, and historical data can be imported into the database in batches through the data table document; and combining the combination information of the resource management products and external data, and further configuring an estimated value table and a net value table template, so that wind control management is performed on the basis of updated fusion data.
As a preferred implementation mode, the wind control data also comprises early warning information corresponding to the combination information of the resource management products and the external data; the wind control module 3 is further configured to obtain early warning information according to a preset threshold value. Specifically, the threshold value setting is carried out on the index of the product in the warehouse, which needs to be tracked and pre-warned, so that the long-term tracking and pre-warning can be conveniently carried out, and the warning item can inform the manager through the backlog; in addition, all data kneaded after the net worth processing can be visually tracked in the management cockpit.
As a preferred embodiment, the data acquisition module 1 is further configured to:
screening and updating the research analysis data based on at least one index in the resource management products and the corresponding fund managers and management companies. Specifically, index screening is carried out on three dimensions of the fund product, the management company and the fund manager to obtain an alternative product, and the alternative product is added into a self-selection library; and further screening the products in the self-selection library through a comparison analysis flow, and adding the re-selected products into an asset configuration flow. Further, historical performance-based composition returns, contextual analysis, and future performance distribution simulation analysis may be performed on the configured composition to determine a product composition for joining the product library.
As a preferred embodiment, the information determining module 2 is specifically configured to:
according to the preset model combination analysis, screening and updating the research analysis data to determine resource management product combination information; the preset model combination comprises at least one of an MV mean variance model, a BL mean variance model, a risk price reduction model, a risk budget model and a custom weight model.
Any plurality of market public fund products or self-owned fund products can be selected for any combination, and the types and types of the products are not limited; the combination parameters are divided into two parts, one part is a product parameter part and comprises an amount to be charged, an early warning amount, a loss stopping amount and time parameter selection, wherein the amount to be charged is needed to be charged; secondly, the two are constraint condition parts, the constraint conditions under each model are different, and the adjustment can be carried out according to different investment targets
Referring to fig. 3, a block diagram of an air management system for a resource management product is also shown.
According to the air control system for the resource management products, integrated analysis processing is carried out on the investment data and the external data covering the whole process of investment management outside the commission, pre-investment screening evaluation, post-investment performance dynamic tracking and all-market resource management product evaluation are achieved, so that data of all channels are reasonably and efficiently acquired and processed, the data are reflected in the air control evaluation of the resource management products, the accurate evaluation of investment performance is facilitated, and investment advice optimal selection combinations are dynamically given based on performance analysis and attribution analysis, and asset configuration and risk dispersion are achieved. Further, based on the macro economy and capital market database, an original investment model is built by applying a machine learning algorithm and a financial theory, and full-flow investment analysis service from transaction strategies to performance analysis is provided; constructing multi-level and multi-dimensional analysis evaluation indexes of outsourcing managers according to the basic information of the institutions, corresponding past investment performance information, warehouse holding data information and the like, and comprehensively comparing the multi-level and multi-dimensional analysis evaluation indexes with all markets to realize scientific evaluation and optimization of outsourcing managers; the method realizes the construction of the fund combination from top to bottom according to the risk preference and the macroscopic economic cycle of the investors, continuously and comprehensively tracks the performance and the risk exposure degree of the combination, timely gives out the warehouse holding adjustment suggestion, forms a complete closed loop, and assists the investors to efficiently and conveniently manage the investment combination.
Example 3
Fig. 4 is a schematic structural diagram of an electronic device according to the present embodiment. The electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the air control method of the asset management product in the above embodiment when executing the program. The electronic device 30 shown in fig. 4 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present application.
As shown in fig. 4, the electronic device 30 may be embodied in the form of a general purpose computing device, which may be a server device, for example. Components of electronic device 30 may include, but are not limited to: the at least one processor 31, the at least one memory 32, a bus 33 connecting the different system components, including the memory 32 and the processor 31.
The bus 33 includes a data bus, an address bus, and a control bus.
Memory 32 may include volatile memory such as Random Access Memory (RAM) 321 and/or cache memory 322, and may further include Read Only Memory (ROM) 323.
Memory 32 may also include a program/utility 325 having a set (at least one) of program modules 324, such program modules 324 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The processor 31 executes various functional applications and data processing, such as the air control method of the asset product of the present application as described above, by running a computer program stored in the memory 32.
The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). Such communication may be through an input/output (I/O) interface 35. Also, model-generating device 30 may also communicate with one or more networks, such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet, via network adapter 36. As shown in fig. 4, network adapter 36 communicates with the other modules of model-generating device 30 via bus 33. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in connection with the model-generating device 30, including, but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, data backup storage systems, and the like.
It should be noted that although several units/modules or sub-units/modules of an electronic device are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more units/modules described above may be embodied in one unit/module in accordance with embodiments of the present application. Conversely, the features and functions of one unit/module described above may be further divided into ones that are embodied by a plurality of units/modules.
Example 4
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in the air control method of the asset management product of the above embodiment. Wherein the readable storage medium may employ more specifically may include, but is not limited to: portable disk, hard disk, random access memory, read only memory, erasable programmable read only memory, optical storage device, magnetic storage device, or any suitable combination of the foregoing.
In a possible embodiment, the application may also be realized in the form of a program product comprising program code for causing a terminal device to carry out the steps in a method of wind control implementing a resource product as described above, when the program product is run on the terminal device. Wherein the program code for carrying out the application may be written in any combination of one or more programming languages, the program code may execute entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device, partly on a remote device or entirely on the remote device.
While specific embodiments of the application have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and the scope of the application is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the application, but such changes and modifications fall within the scope of the application.
Claims (10)
1. The air control method of the resource management product is characterized by comprising the following steps:
acquiring investment and research analysis data of resource management products;
determining resource and management product combination information according to the research analysis data;
performing net worth processing on the information of the resource management product combination and the external data to obtain wind control data of the target resource management product; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product.
2. The method for air control of resource management products according to claim 1, wherein the air control data further comprises early warning information corresponding to the combination information of the resource management products and external data; the step of determining the resource and management product combination information according to the research analysis data further comprises the following steps:
and acquiring the early warning information according to a preset threshold value.
3. The method of claim 1, wherein the step of obtaining analysis data for inventory production comprises:
and screening and updating the research analysis data based on at least one index in the resource management products and the corresponding fund managers and management companies.
4. The method of claim 3, wherein the step of determining the asset and management product combination information based on the lapping analysis data comprises:
analyzing the screened and updated lapping analysis data according to a preset model combination to determine the resource management product combination information; the preset model combination comprises at least one of an MV mean variance model, a BL mean variance model, a risk price reduction model and a risk budget model.
5. A system for air control of resource management products, comprising:
the data acquisition module is used for acquiring the research analysis data of the resource management products;
the information determining module is used for determining the combination information of the resource management products according to the research analysis data;
the air control module is used for carrying out net value processing on the information of the resource management product combination and the external data so as to obtain air control data of the target resource management product; the wind control data comprise performance penetration information and performance tracking information corresponding to the target resource management product.
6. The system for air control of resource management products of claim 5, wherein the air control data further comprises pre-warning information corresponding to the combination information of the resource management products and external data; the wind control module is also used for acquiring the early warning information according to a preset threshold value.
7. The system for air control of resource management products of claim 5, wherein the data acquisition module is further configured to:
and screening and updating the research analysis data based on at least one index in the resource management products and the corresponding fund managers and management companies.
8. The system for air control of resource management products of claim 7, wherein said information determining module is specifically configured to:
analyzing the screened and updated lapping analysis data according to a preset model combination to determine the resource management product combination information; the preset model combination comprises at least one of an MV mean variance model, a BL mean variance model, a risk price reduction model and a risk budget model.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method of air control of the resource management product of any one of claims 1-4.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements a method of wind control of a resource management product as claimed in any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310090053.6A CN116645210A (en) | 2023-01-29 | 2023-01-29 | Air control method, system, equipment and medium for resource management products |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310090053.6A CN116645210A (en) | 2023-01-29 | 2023-01-29 | Air control method, system, equipment and medium for resource management products |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116645210A true CN116645210A (en) | 2023-08-25 |
Family
ID=87614104
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310090053.6A Pending CN116645210A (en) | 2023-01-29 | 2023-01-29 | Air control method, system, equipment and medium for resource management products |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116645210A (en) |
-
2023
- 2023-01-29 CN CN202310090053.6A patent/CN116645210A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zeng et al. | Digital transformation and corporate total factor productivity: empirical evidence based on listed enterprises | |
| CN102663650A (en) | System for analyzing enterprise credit risk and application method thereof | |
| US20110153536A1 (en) | Computer-Implemented Systems And Methods For Dynamic Model Switching Simulation Of Risk Factors | |
| US20200387814A1 (en) | Multi-method system for optimal predictive model selection | |
| WO2020000689A1 (en) | Transfer-learning-based robo-advisor strategy generation method and apparatus, and electronic device and storage medium | |
| DK202370110A1 (en) | Environmental, social, and governance (esg) performance trends | |
| CN113822488A (en) | Risk prediction method and device for financing lease, computer equipment and storage medium | |
| CN113780667A (en) | Enterprise operation prediction method and system based on AI artificial intelligence | |
| CN110619407B (en) | Object sales prediction method and system, electronic device and storage medium | |
| Kolodiziev et al. | Selecting a Kind of Financial Innovation According to the Level of a Bank's Financial Soundness and Its Life Cycle Stage | |
| CN116645210A (en) | Air control method, system, equipment and medium for resource management products | |
| Zang | Construction of Mobile Internet Financial Risk Cautioning Framework Based on BP Neural Network | |
| Zhuang et al. | DyS-IENN: a novel multiclass imbalanced learning method for early warning of tardiness in rocket final assembly process | |
| Liu et al. | Dual‐stage time series analysis on multifeature adaptive frequency domain modeling | |
| Kumar | Risk Management and Digitization | |
| Zhou | Enterprise Financial Information Management System Based on Data Analysis Algorithm | |
| Zhou | Design of Intelligent Financial Investment Risk Prediction System Based on Edge Computing | |
| Müller | Multi-dimensional server consolidation for commercial off-the-shelf enterprise applications using shared performance counters | |
| US20160125538A1 (en) | Creative generation of financial portfolios | |
| Li et al. | Research on evaluation system and method of MES system for intelligent manufacturing | |
| Nikonova et al. | Digital transformation routes, data mining methods as a preliminary stage of predictive analytics in corporate finance | |
| Li et al. | Using Operations Research to Solve the Idea of Company Investment Resource Allocation | |
| Solodovnyk et al. | Information System Of Optimal Allocation Of Enterprise Development Resources. | |
| Stankov et al. | Digital Twin Management Systems–challenges, application, development | |
| Melnykova | Using of personalized approach for assessment of the financial condition of the company |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |