CN113643137A

CN113643137A - Risk prediction method, device, medium and electronic equipment for investment portfolio

Info

Publication number: CN113643137A
Application number: CN202110997530.8A
Authority: CN
Inventors: 王文俊; 张翔
Original assignee: Taikang Asset Management Co ltd; Taikang Insurance Group Co Ltd
Current assignee: Taikang Asset Management Co ltd; Taikang Insurance Group Co Ltd
Priority date: 2021-08-27
Filing date: 2021-08-27
Publication date: 2021-11-12

Abstract

The embodiment of the application provides a risk prediction method, a risk prediction device, a risk prediction medium and electronic equipment for investment portfolios, and relates to the technical field of computers, wherein the method comprises the following steps: acquiring investment details corresponding to the investment combination; calculating specific risk ratio according to the investment amount of each product in the asset combination of the specific investment object in the investment detail, and determining the risk amount of the specific investment object according to the specific risk ratio; determining the target risk ratio of the general investment object according to the attribute corresponding to the general investment object in the investment detail, and determining the risk amount corresponding to the general investment object according to the target risk ratio; predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively; and displaying the investment portfolio, the risk amount of each investment object and the investment amount of each product in the asset portfolio based on the investment object affiliation represented by the investment detail. Therefore, the investment risk calculation precision of the asset combination and the completeness of the risk calculation result displayed to the user can be improved.

Description

Risk prediction method, device, medium and electronic equipment for investment portfolio

Technical Field

The present application relates to the field of computer technologies, and in particular, to a risk prediction method for an investment portfolio, a risk prediction apparatus for an investment portfolio, a computer-readable medium, and an electronic device.

Background

Generally, portfolios have a top-down trading structure, and compliance testing of portfolios is typically limited to a top-level, i.e., compliance testing is performed only for each item of investment product contained in the portfolios. However, each investment product in the investment portfolio usually includes a plurality of sub-products, and the plurality of sub-products do not participate in the existing compliance check, so that the risk calculation result of the existing compliance check has no penetrability, therefore, the risk calculation result displayed to the user only includes the risk prediction value of the top investment object in the investment portfolio, and if the investment object includes the deep portfolio and there is a risk product in the portfolio, the risk product does not participate in the risk calculation in the compliance check process. This not only results in a less accurate risk calculation result, but also results in a less than complete risk calculation result being presented to the user.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present application and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.

Disclosure of Invention

An object of the embodiments of the present application is to provide a risk prediction method for an investment portfolio, a risk prediction apparatus for an investment portfolio, a computer readable medium and an electronic device, which can determine a multi-level object to be detected through depth detection of a general investment object and a specific investment object including an asset portfolio in the investment portfolio, so as to improve penetration and depth of risk calculation, and further improve accuracy of investment risk calculation for the asset portfolio and completeness of risk calculation results displayed to a user.

A first aspect of an embodiment of the present application provides a risk prediction method for an investment portfolio, the method including:

acquiring investment details corresponding to the investment combination; wherein the investment details include general investment objects and specific investment objects comprising portfolios;

calculating a specific risk ratio of a specific investment object according to the investment amount of each product in the portfolio of the specific investment object, and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object;

determining a target risk ratio of the general investment object according to the attribute corresponding to the general investment object, and determining a risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object;

predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively;

and displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object, and the investment amount of each product in the asset portfolio based on the investment detail representation of the membership relationship of the investment objects.

In an exemplary embodiment of the present application, the investment details are represented in the form of a node tree, the node tree includes a plurality of levels of nodes, a root node in the node tree is used for representing the investment portfolio, child nodes in the node tree are used for representing the general investment object and the specific investment object, and grandchild nodes in the node tree are used for representing products in the investment portfolio of the specific investment object.

In an exemplary embodiment of the present application, calculating a specific risk ratio for a particular investment object based on an investment amount for each product in a portfolio of the particular investment object comprises:

determining a particular risky product in the portfolio of the particular investment object; wherein the risk assessment value corresponding to a specific risk product is higher than the risk assessment values of other risk products in the portfolio;

calculating the ratio of the investment amount corresponding to the specific risk product to the total investment amount corresponding to the asset combination;

the ratio is determined as a specific risk to a specific investment object.

In an exemplary embodiment of the present application, determining a risk amount corresponding to a particular investment object based on a particular risk share and an investment amount corresponding to the particular investment object includes:

calculating a first product of the specific risk proportion and the investment amount corresponding to the specific investment object, and determining the first product as the risk amount corresponding to the specific investment object;

and determining the risk amount corresponding to the general investment object according to the target risk proportion and the investment amount corresponding to the general investment object, wherein the method comprises the following steps:

and calculating a second product of the target risk proportion and the investment amount corresponding to the general investment object, and determining the second product as the risk amount corresponding to the general investment object.

In an exemplary embodiment of the present application, predicting a risk amount corresponding to an investment portfolio based on risk amounts corresponding to a general investment objective and a specific investment objective, respectively, includes:

determining a weighted sum between the risk amount of the general investment object and the risk amount of the specific investment object;

and determining the weighted sum as the risk amount corresponding to the investment portfolio.

In an exemplary embodiment of the present application, the method further includes:

and if the detected risk amount is larger than the preset amount, feeding back a prompt message for indicating that the investment risk exists in the investment portfolio.

In an exemplary embodiment of the present application, the investment amount corresponding to the portfolio includes an investment amount corresponding to a particular investment object, and the investment amount corresponding to the portfolio does not include an investment amount for each product in the portfolio.

In an exemplary embodiment of the present application, the attributes corresponding to the generic investment object include at least: implicit asset attributes, specific asset attributes, direct asset attributes; wherein the implicit asset attribute, the specific asset attribute, and the direct asset attribute respectively correspond to different target risk fractions.

In an exemplary embodiment of the present application, the displaying of the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment objective and the specific investment objective, and the investment amount of each product in the portfolio based on the investment objective affiliation characterized by the investment details includes:

determining the risk amount corresponding to the investment portfolio as first-level visual data, the risk amount corresponding to a general investment object and a specific investment object as second-level visual data, and the investment amount of each product in the asset portfolio as third-level visual data based on the investment object membership represented by the investment detail;

integrating the first-level visual data, the second-level visual data and the third-level visual data into a multi-level visual table, and displaying the multi-level visual table; the first-level visual data are obtained through calculation based on the second-level visual data, and the second-level visual data are obtained through calculation based on the third-level visual data.

A second aspect of an embodiment of the present application provides a risk prediction apparatus for a portfolio, comprising:

the data acquisition unit is used for acquiring investment details corresponding to the investment portfolio; wherein the investment details include general investment objects and specific investment objects comprising portfolios;

the risk data determining unit is used for calculating the specific risk ratio of the specific investment object according to the investment amount of each product in the asset combination of the specific investment object and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object;

the risk data determining unit is also used for determining a target risk ratio of the general investment object according to the attribute corresponding to the general investment object and determining a risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object;

the risk prediction unit is used for predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively;

and the risk data display unit is used for displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object and the investment amount of each product in the asset portfolio based on the investment object membership represented by the investment details.

In an exemplary embodiment of the present application, the risk data determining unit calculates a specific risk proportion for a specific investment object based on investment amounts of respective products in a portfolio of the specific investment object, including:

the ratio is determined as a specific risk to a specific investment object.

In an exemplary embodiment of the present application, the determining a risk amount corresponding to the specific investment object according to the specific risk percentage and the investment amount corresponding to the specific investment object by the risk data determining unit includes:

and the risk data determining unit determines the risk amount corresponding to the general investment object according to the target risk proportion and the investment amount corresponding to the general investment object, and comprises the following steps:

In an exemplary embodiment of the present application, the risk prediction unit predicts the risk amount corresponding to the investment portfolio based on the risk amounts corresponding to the general investment objective and the specific investment objective, respectively, including:

In an exemplary embodiment of the present application, the apparatus further includes:

and the message feedback unit is used for feeding back a prompt message for indicating that the investment combination has the investment risk when the risk amount is detected to be larger than the preset amount.

In an exemplary embodiment of the present application, the risk data presentation unit presents, based on the investment object affiliation represented by the investment details, a risk amount corresponding to the investment portfolio, a risk amount corresponding to the general investment object and the specific investment object, and an investment amount of each product in the portfolio, including:

According to a third aspect of embodiments of the present application, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the risk prediction method for a portfolio as described in the first aspect of the embodiments above.

According to a fourth aspect of embodiments of the present application, there is provided an electronic apparatus, including: one or more processors; a storage device for storing one or more programs which, when executed by one or more processors, cause the one or more processors to implement the method for risk prediction of a portfolio as described in the first aspect of the embodiments above.

According to a fifth aspect of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the method provided in the various alternative implementations described above.

The technical scheme provided by the embodiment of the application can have the following beneficial effects:

technical solutions provided in some embodiments of the present application specifically include: acquiring investment details corresponding to the investment combination; wherein the investment details include general investment objects and specific investment objects comprising portfolios; calculating a specific risk ratio of a specific investment object according to the investment amount of each product in the portfolio of the specific investment object, and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object; determining a target risk ratio of the general investment object according to the attribute corresponding to the general investment object, and determining a risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object; predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively; and displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object, and the investment amount of each product in the asset portfolio based on the investment detail representation of the membership relationship of the investment objects. By implementing the embodiment of the application, on one hand, the multi-level object to be detected can be determined through the depth detection of a general investment object in the investment portfolio and a specific investment object comprising the investment portfolio, so that the penetrability and the depth of risk calculation are improved, and further the investment risk calculation precision of the investment portfolio and the completeness of risk calculation results displayed to users are improved. On the other hand, the investment details corresponding to the investment portfolio can be automatically obtained, risk calculation is carried out on each object and the sub-objects contained in the objects in the investment details, and the automation degree of the investment risk calculation is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 schematically shows a schematic diagram of an exemplary system architecture of a risk prediction method for a portfolio and a risk prediction apparatus for a portfolio to which embodiments of the present application can be applied;

FIG. 2 schematically illustrates a block diagram of a computer system suitable for use in implementing an electronic device of an embodiment of the present application;

FIG. 3 schematically illustrates a flow chart of a risk prediction method for a portfolio in accordance with an embodiment of the present application;

FIG. 4 schematically illustrates a plurality of portfolio model schematics according to one embodiment of the present application;

FIG. 5 schematically illustrates a detailed view of a portfolio model according to one embodiment of the present application;

FIG. 6 schematically illustrates a flow chart of a risk prediction method for a portfolio in accordance with another embodiment of the present application;

fig. 7 schematically shows a block diagram of a risk prediction device for a portfolio in an embodiment in accordance with the present application.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present application.

Furthermore, the drawings are merely schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

Fig. 1 is a schematic diagram illustrating a system architecture of an exemplary application environment to which a risk prediction method for a portfolio and a risk prediction apparatus for the portfolio according to an embodiment of the present application can be applied.

As shown in fig. 1, the system architecture 100 may include one or more of

user terminals

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

user terminals

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few. The

user terminals

101, 102, 103 may be various electronic devices having a display screen, including but not limited to desktop computers, portable computers, smart phones, tablet computers, and the like. It should be understood that the number of user terminals, networks and servers in fig. 1 is merely illustrative. There may be any number of user terminals, networks, and servers, as desired for an implementation. For example, server 105 may be a server cluster comprised of multiple servers, or the like.

For example, the server 105 may obtain investment details corresponding to the investment portfolio; wherein the investment details include general investment objects and specific investment objects comprising portfolios; calculating a specific risk ratio of a specific investment object according to the investment amount of each product in the portfolio of the specific investment object, and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object; determining a target risk ratio of the general investment object according to the attribute corresponding to the general investment object, and determining a risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object; predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively; and displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object, and the investment amount of each product in the asset portfolio based on the investment detail representation of the membership relationship of the investment objects.

FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.

It should be noted that the computer system 200 of the electronic device shown in fig. 2 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

As shown in fig. 2, the computer system 200 includes a Central Processing Unit (CPU)201 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)202 or a program loaded from a storage section 208 into a Random Access Memory (RAM) 203. In the (RAM)203, various programs and data necessary for system operation are also stored. The (CPU)201, (ROM)202, and (RAM)203 are connected to each other by a bus 204. An input/output (I/O) interface 205 is also connected to bus 204.

The following components are connected to the (I/O) interface 205: an input portion 206 including a keyboard, a mouse, and the like; an output section 207 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 208 including a hard disk and the like; and a communication section 209 including a network interface card such as a LAN card, a modem, or the like. The communication section 209 performs communication processing via a network such as the internet. The driver 210 is also connected to the (I/O) interface 205 as necessary. A removable medium 211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is mounted on the drive 210 as necessary, so that a computer program read out therefrom is installed into the storage section 208 as necessary.

In particular, according to embodiments of the present application, the processes described below with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 209 and/or installed from the removable medium 211. The computer program, when executed by a Central Processing Unit (CPU)201, performs various functions defined in the methods and apparatus of the present application.

It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.

As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method as described in the embodiments below. For example, the electronic device may implement the various steps shown in fig. 3, and so on.

Referring to fig. 3, the present exemplary embodiment provides a risk prediction method for a portfolio, which may include the following steps S310 to S350, specifically:

step S310: acquiring investment details corresponding to the investment combination; wherein the investment details include general investment objects and specific investment objects comprising portfolios.

Step S320: and calculating the specific risk ratio of the specific investment object according to the investment amount of each product in the portfolio of the specific investment object, and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object.

Step S330: and determining a target risk ratio of the general investment object according to the attribute corresponding to the general investment object, and determining a risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object.

Step S340: and predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively.

Step S350: and displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object, and the investment amount of each product in the asset portfolio based on the investment detail representation of the membership relationship of the investment objects.

The above steps of the present exemplary embodiment will be described in more detail below.

In step S310, obtaining investment details corresponding to the investment portfolio; wherein the investment details include general investment objects and specific investment objects comprising portfolios.

Specifically, the investment portfolio may be understood as an investment plan, and the investment portfolio may include a plurality of investment targets, which may be general investment targets or specific investment targets, or other types of investment targets, and the embodiments of the present application are not limited thereto. Among other things, the investment objects may be financial products such as stocks, equities, stock type funds, equity plans, depository vouchers, insurance products, stock finger futures, commingled funds, equity plans, bonds, and the like.

Generally, the financial products can be equity type financial products and non-equity type financial products, and the stocks, the equity certificates, the stock type funds, the stock right plans, the deposit vouchers, the insurance products, the stock fingers, the futures and the mixed type funds belong to the equity type financial products; the closing fund, the bond plan and the bond belong to non-equity type financial products. The rights and interests assets are characterized in that: high risk, high benefit; the non-equity assets are characterized in that: the risk of the investment portfolio can be controlled by limiting the occupation ratio of the equity assets relative to the investment portfolio on the basis of the problem that the risk is easily caused if the occupation ratio of the equity assets in the investment portfolio is too high with low risk and low income.

The investment portfolio can comprise equity type financial products and non-equity type financial products, but sub-products contained in the non-equity type financial products can comprise equity type financial products.

In addition, the present application may be applied to an investment system including one or more portfolios, and as shown in fig. 4, a plurality of portfolios models may be shown in the open market investment system, which may specifically include: portfolio a410, portfolio B420, portfolio C430. Portfolio a410, portfolio B420, portfolio C430 are from a publication length of time 400 and portfolio a410, portfolio B420, portfolio C430 all contain an alternative product D440. The alternative products D440 may in turn include XX credit plans 441 and XX equity plans 442, the XX credit plan 441 for XX company G4411 and the XX equity plan 442 for XX company E4421. When calculating the risk amounts corresponding to the investment portfolio a410, the investment portfolio B420, and the investment portfolio C430, the penetration calculation may be performed on the classified product D440 based on steps S310 to S340, so as to calculate the risk amount with higher accuracy for the user to refer to.

In addition, the investment details may be represented in the form of a node tree, the node tree may include multiple layers of nodes, each layer of nodes represents one Dimension (Dimension) in the node tree, the Dimension of the node tree including the multiple layers of nodes may be represented as Dimension1-Dimension2 … … Dimension N, where N is a positive integer, and the database may store the node tree in a linked list structure based on the dimensions. The root node in the node tree is used for representing the investment portfolio, the child nodes in the node tree are used for representing the general investment object and the specific investment object, and the grandchild nodes in the node tree are used for representing products in the asset portfolio of the specific investment object. If each product in the asset combination comprises a plurality of child products, the nodes in the node tree can be extended by one level to represent that each product comprises a plurality of child products, wherein the level of the extended nodes is lower than that of the grandchild nodes. Specifically, the general investment object is used for representing an investment object which does not include child nodes, namely, a node corresponding to the general investment object is a terminal node; the specific investment object is used to characterize the investment object comprising the child node.

In addition, the attributes corresponding to a generic investment object include at least: implicit asset attributes, specific asset attributes, direct asset attributes; wherein the implicit asset attribute, the specific asset attribute, and the direct asset attribute respectively correspond to different target risk fractions. It should be noted that the implicit asset attribute corresponds to an external financial product (e.g., XX mixed-type fund) that cannot acquire the underlying position, and the target risk ratio corresponding to the implicit asset attribute may be a first fixed value (e.g., 20%); the specific asset attribute corresponds to an internal financial product (such as a pension product) and an amount planning financial product (such as an equity plan and a bond plan) which can acquire an underlying position, and the target risk proportion corresponding to the specific asset attribute can be calculated by an expression (the investment amount of a child product/the investment amount of a parent product) or (the target investment amount/the total bid amount); the direct asset attribute corresponds to a financial product (e.g., a stock) with an extremely high risk, and the corresponding target risk share may be a second fixed value (e.g., 100%).

As shown in fig. 5, taking investment portfolio a500 as an example, investment portfolio a500 may pass through debt planning M562 of the amounts of the node models. The node model may include investment details corresponding to the investment portfolio.

Specifically, portfolio a500 may comprise: a stock B510 corresponding to an investment amount of 10 ten thousand, an pension product E520 corresponding to an investment amount of 10 ten thousand, a ticket C530 corresponding to an investment amount of 20 ten thousand, an pension product F540 corresponding to an investment amount of 20 ten thousand, a hybrid fund D550 corresponding to an investment amount of 50 ten thousand, an alternative product G560 corresponding to an investment amount of 50 ten thousand, and a bond N570 corresponding to an investment amount of 35 ten thousand.

The pension product E520 includes a portfolio which is specifically a stock H521 corresponding to 100 ten thousand investment amount and a bond I522 corresponding to 400 ten thousand investment amount, the pension product F540 includes a portfolio which is specifically a bond J541 corresponding to 50 ten thousand investment amount and a deposit K542 corresponding to 30 ten thousand investment amount, and the alternative product G560 includes a portfolio which is specifically a equity plan L561 corresponding to 50 ten thousand investment amount and a credence plan M562 corresponding to 50 ten thousand investment amount.

It should be noted that the alternative product G560 may be understood as an investment plan, and may include, for example, an equity plan L561 and a debt plan M562, and the investment amounts corresponding to the equity plan L561 and the debt plan M562 respectively may also be understood as bid amounts.

Wherein, the node to which the investment portfolio A500 belongs is a father node; nodes to which the stock B510, the pension product E520, the ticket C530, the pension product F540, the mixed fund D550, the alternative product G560 and the bond N570 belong are child nodes under the father node; the nodes to which the stocks H521 and the bonds I522 belong are child nodes under the node to which the pension products E520 belong; the nodes of the bond J541 and the deposit K542 are child nodes under the node of the pension product F540; the nodes to which the equity plan L561 and the creditor plan M562 belong are child nodes under the node to which the classified product G560 belongs. The pension product E520, the pension product F540 and the alternative product G560 are all the specific investment objects containing the asset combination; stock B510, ticket C530, hybrid fund D550, and bond N570 are all the aforementioned general investment objects.

Since the stock B510, the ticket C530, the stock H521, the stock right plan L561 and the hybrid fund D550 belong to the equity type financial product, further, the ticket C530 and the stock B510 correspond to the direct asset attribute, the stock H521 belongs to the pension product E520, the pension product E520 corresponds to the specific asset attribute, the stock right plan L561 belongs to the alternative product G560, the alternative product G560 corresponds to the specific asset attribute, and the hybrid fund D550 is an external financial product, the hybrid fund D550 belongs to the implicit asset attribute.

Thus, the target risk ratio for the title C530 and the stock B510 may be 100%, the target risk ratio for the pension product E520 may be [ the investment amount of the stock H521/(the investment amount of the stock H521 + the investment amount of the bond I522) ], the target risk ratio for the alternative product G560 may be [ the investment amount of the equity plan L561/(the investment amount of the equity plan L561 + the investment amount of the bond plan M562) ], and the target risk ratio for the hybrid fund D550 may be 20%.

Based on this, the risk amount corresponding to portfolio a500 may be calculated according to the following expression:

the risk amount corresponding to the portfolio a500 is 100% stock B510 investment amount 10 ten thousand + [ stock H521 investment amount 100 ten thousand/(stock H521 investment amount 100 ten thousand + bond I522 investment amount 400 ten thousand) ], the pension amount of the pension product E520 investment amount 10 ten thousand + 100% right ticket C530 investment amount 10 ten thousand + 0% pension product F540 investment amount 10 ten thousand + 20% hybrid fund D550 investment amount 50 + [ investment amount of the equity plan L561 investment amount 50 ten thousand/(investment amount of the equity plan L561 investment amount 50 ten thousand + investment amount of the equity plan M562 investment amount 35 ten thousand 67 for the investment fund 510 ten thousand + 0% bond N570 of the alternative product G560.

If the net asset corresponding to portfolio a500 is 100 million, the amount of risk accounts for 67% of the net asset.

It should be noted that, because the pension product F540 does not contain equity assets, and the bond N570 does not belong to equity assets, the target risk ratios corresponding to the pension product F540 and the bond N570 are both 0, that is, the investment amounts corresponding to the pension product F540 and the bond N570 do not participate in the risk calculation process, so that the risk calculation result is not affected by non-equity assets, and the accuracy of the risk calculation result is improved.

In step S320, a specific risk ratio of the specific investment object is calculated according to the investment amount of each product in the portfolio of the specific investment object, and a risk amount corresponding to the specific investment object is determined according to the specific risk ratio and the investment amount corresponding to the specific investment object.

In particular, the specific risk ratio may comprise a proportion of a product investment amount of assets belonging to the equity class in the portfolio to a total investment amount of the portfolio. The investment amount corresponding to the portfolio includes an investment amount corresponding to a specific investment object, and the investment amount corresponding to the portfolio does not include an investment amount of each product in the portfolio.

For the step S320 of calculating the specific risk proportion of the specific investment object according to the investment amount of each product in the portfolio of the specific investment object, the specific implementation manner may be: determining a particular risky product in the portfolio of the particular investment object; wherein the risk assessment value corresponding to a specific risk product is higher than the risk assessment values of other risk products in the portfolio; calculating the ratio of the investment amount corresponding to the specific risk product to the total investment amount corresponding to the asset combination; the ratio is determined as a specific risk to a specific investment object. Therefore, the risk index can be calculated without being limited to direct position taking, the risk index can penetrate through the bottom layer asset, the direct position taking and the bottom layer asset are weighted and then merged for calculation, and the prediction precision of the actual risk can be improved.

The number of the specific risk products in the portfolio may be one or more, and the embodiments of the present application are not limited.

For the step S320, determining the risk amount corresponding to the specific investment object according to the specific risk percentage and the investment amount corresponding to the specific investment object, the specific implementation may be: and calculating a first product of the specific risk proportion and the investment amount corresponding to the specific investment object, and determining the first product as the risk amount corresponding to the specific investment object. Therefore, the more accurate risk amount corresponding to the specific investment object can be calculated according to the specific risk ratio, and the accuracy of the finally calculated risk amount can be improved by setting different risk ratios for different investment objects.

Specifically, calculating a first product of the specific risk share and the investment amount corresponding to the specific investment object may be expressed as: the specific risk ratio is the first product of the investment amount corresponding to the specific investment object (i.e., the risk amount corresponding to the specific investment object).

In step S330, a target risk ratio of the general investment object is determined according to the attribute corresponding to the general investment object, and a risk amount corresponding to the general investment object is determined according to the target risk ratio and the investment amount corresponding to the general investment object.

For the step S330, determining the risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object, a specific implementation may be: and calculating a second product of the target risk proportion and the investment amount corresponding to the general investment object, and determining the second product as the risk amount corresponding to the general investment object. Therefore, the more accurate risk amount corresponding to the general investment object can be calculated according to the target risk ratio, and the accuracy of the finally calculated risk amount can be improved by setting different risk ratios for different investment objects.

Specifically, calculating a second product of the target risk share and the investment amount corresponding to the general investment object may be expressed as: the target risk proportion is equal to the investment amount corresponding to the general investment object, and is equal to a second product (namely, the risk amount corresponding to the general investment object).

In step S340, a risk amount corresponding to the investment portfolio is predicted based on the risk amounts corresponding to the general investment object and the specific investment object, respectively.

For the step S340 of predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object, the specific implementation may be: determining a weighted sum between the risk amount of the general investment object and the risk amount of the specific investment object; and determining the weighted sum as the risk amount corresponding to the investment portfolio. Therefore, the risk amount with higher precision can be calculated according to the weight proportion corresponding to different investment objects, and the risk amount calculated based on the mode has higher reference value, so that the method is beneficial to assisting the user in carrying out the investment amount proportion adjustment.

Wherein, the weight of the risk amount of the general investment object and the risk amount of the specific investment object can be adjusted according to the requirement of the user (such as 1: 1, 1: 3, etc.).

Optionally, after step S330, the method further includes: and if the detected risk amount is larger than the preset amount, feeding back a prompt message for indicating that the investment risk exists in the investment portfolio. Therefore, the interactivity can be improved, the user can conveniently know that the investment risk exists in the investment portfolio in time, and the user can adjust the investment proportion of each investment object in the investment portfolio in time based on the known information, so that the use experience of the user is improved.

Specifically, if it is detected that the risk amount is greater than the preset amount, the manner of feeding back the prompt message indicating that the investment portfolio has the investment risk may specifically be: determining a net asset (e.g., 100 ten thousand) corresponding to the portfolio; calculating the product of a preset proportion (e.g. 30%) and the net asset as the preset amount (e.g. 30 ten thousand), if the detected risk amount (e.g. 40 ten thousand) is greater than the preset amount (e.g. 30 ten thousand), generating a prompt message for indicating that the investment combination has the investment risk, and feeding the prompt message back to the user terminal (e.g. a mobile phone, a tablet computer, a personal computer, a smart watch, a smart screen, a VR device, etc.), so that the user terminal displays the prompt message on a user interface. Further, if the detected risk amount is less than or equal to the preset amount, generating a prompt message for indicating that the investment portfolio has no investment risk, and feeding the prompt message back to the user terminal, so that the user terminal displays the prompt message on a user interface.

Based on this, the above method may further include: determining a difference between the risk amount and a preset amount; and generating an investment weight adjustment suggestion (for example, changing the investment amount of the stock from 10 ten thousand to 5 ten thousand) according to the difference and the investment amount corresponding to each investment object in the investment portfolio, and feeding back the investment weight adjustment suggestion to a user terminal, wherein the user terminal can display the investment weight adjustment suggestion for the user to refer to.

And, the above method may further comprise: when the user terminal detects the editing operation of the investment amount of any one investment object, the modified investment amount corresponding to the editing operation is fed back to the server, so that the server calculates a new risk amount according to the modified investment amount, and feeds the risk amount back to the user terminal, so that the user terminal dynamically changes the displayed original risk amount according to the risk amount, the user can know the latest risk amount based on the editing of the investment amount of any one or two investment objects in the investment portfolio, and the use experience of the user is improved.

In step S350, based on the affiliation of the investment targets represented by the investment details, the risk amount corresponding to the investment portfolio, the risk amounts corresponding to the general investment target and the specific investment target, and the investment amounts of the products in the portfolio are displayed. Wherein the investment object affiliation is used to characterize affiliations between products in the portfolio, general investment object, specific investment object, portfolio.

In an exemplary embodiment of the present application, the displaying of the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment objective and the specific investment objective, and the investment amount of each product in the portfolio based on the investment objective affiliation characterized by the investment details includes: determining the risk amount corresponding to the investment portfolio as first-level visual data, the risk amount corresponding to a general investment object and a specific investment object as second-level visual data, and the investment amount of each product in the asset portfolio as third-level visual data based on the investment object membership represented by the investment detail; integrating the first-level visual data, the second-level visual data and the third-level visual data into a multi-level visual table, and displaying the multi-level visual table; the first-level visual data are obtained through calculation based on the second-level visual data, and the second-level visual data are obtained through calculation based on the third-level visual data. Therefore, the richness of the visual data can be improved, and the interactive experience can be improved.

Based on the example shown in fig. 5, determining a risk amount (e.g., 67 ten thousand) corresponding to the investment portfolio (e.g., portfolio a) as primary visualization data based on the investment objective affiliation characterized by the investment details; determining the risk amount (e.g. 10 ten thousand, 20 ten thousand and 10 ten thousand) corresponding to a general investment object (e.g. stock B, a right C and a mixed fund D) and the risk amount (e.g. 2 ten thousand, 0 ten thousand and 25 ten thousand) corresponding to a specific investment object (e.g. pension product E, pension product F and another product G) as second-level visual data; determining the investment amount (e.g., 100 ten thousand, 400 ten thousand) of each product (e.g., stock H and bond I) in the portfolio 'pension product E' as three-level visualization data, determining the investment amount (e.g., 50 ten thousand, 30 ten thousand) of each product (e.g., bond J and deposit K) in the portfolio 'pension product F' as three-level visualization data, and determining the investment amount (e.g., 50 ten thousand) of each product (e.g., equity plan L and equity plan M) in the portfolio 'alternative product G' as three-level visualization data; after the data integration, a multi-level visualization table can be further obtained, and optionally, the multi-level visualization table can be represented as follows:

therefore, by implementing the risk prediction method for the investment portfolio shown in fig. 3, a plurality of levels of objects to be detected can be determined through the depth detection of the general investment objects in the investment portfolio and the specific investment objects comprising the investment portfolio, so as to improve the penetrability and depth of risk calculation, and further improve the accuracy of the investment risk calculation for the investment portfolio and the completeness of the risk calculation result displayed to the user. In addition, the investment details corresponding to the investment portfolio can be automatically obtained, risk calculation is carried out on each object and the sub-objects contained in the objects in the investment details, and the automation degree of the investment risk calculation is improved.

With reference to fig. 6, the embodiment of the present application may further provide another risk prediction method for investment portfolio by combining the steps shown in fig. 3 and the embodiment thereof, where as shown in fig. 6, the method may specifically include: step S610 to step S690.

Step S610: acquiring investment details corresponding to the investment combination; wherein the investment details include general investment objects and specific investment objects comprising portfolios.

Step S620: determining a particular risky product in the portfolio of the particular investment object; wherein the risk assessment value corresponding to a particular risky product is higher than the risk assessment values of other risky products in the portfolio.

Step S630: and calculating the ratio of the investment amount corresponding to the specific risk product to the total investment amount corresponding to the portfolio, and determining the ratio as the specific risk ratio of the specific investment object.

Step S640: and calculating a first product of the specific risk proportion and the investment amount corresponding to the specific investment object, and determining the first product as the risk amount corresponding to the specific investment object.

Step S650: and determining the target risk ratio of the general investment object according to the corresponding attribute of the general investment object.

Step S660: and calculating a second product of the target risk proportion and the investment amount corresponding to the general investment object, and determining the second product as the risk amount corresponding to the general investment object.

Step S670: determining a weighted sum between the risk amount of the general investment object and the risk amount of the specific investment object, and determining the weighted sum as the risk amount corresponding to the investment portfolio.

Step S680: and if the detected risk amount is larger than the preset amount, feeding back a prompt message for indicating that the investment risk exists in the investment portfolio.

Step S690: and displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object, and the investment amount of each product in the asset portfolio based on the investment detail representation of the membership relationship of the investment objects.

It should be noted that steps S610 to S690 correspond to the steps and embodiments shown in fig. 3, and for the specific implementation of steps S610 to S690, please refer to the steps and embodiments shown in fig. 3, which are not described herein again.

It can be seen that, by implementing the risk prediction method for an investment portfolio shown in fig. 6, a plurality of levels of objects to be detected can be determined through the depth detection of a general investment object in the investment portfolio and a specific investment object including the investment portfolio, so as to improve the penetrability and depth of risk calculation, and further improve the accuracy of the investment risk calculation for the investment portfolio and the completeness of risk calculation results displayed to users. In addition, the investment details corresponding to the investment portfolio can be automatically obtained, risk calculation is carried out on each object and the sub-objects contained in the objects in the investment details, and the automation degree of the investment risk calculation is improved.

Further, in the present exemplary embodiment, there is also provided a risk prediction apparatus for a portfolio, the execution steps of each unit in the apparatus correspond to fig. 3, and referring to fig. 7, the risk prediction apparatus 700 for a portfolio may include:

a data obtaining unit 710, configured to obtain investment details corresponding to the investment portfolio; wherein the investment details include general investment objects and specific investment objects comprising portfolios;

a risk data determining unit 720, configured to calculate a specific risk ratio of the specific investment object according to the investment amount of each product in the portfolio of the specific investment object, and determine a risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object;

the risk data determining unit 720 is further configured to determine a target risk ratio of the general investment object according to the attribute corresponding to the general investment object, and determine a risk amount corresponding to the general investment object according to the target risk ratio and an investment amount corresponding to the general investment object;

a risk prediction unit 730, configured to predict risk amounts corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object, respectively;

and the risk data display unit 740 is configured to display the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object, and the investment amount of each product in the portfolio based on the investment object dependency relationship represented by the investment details.

The investment details are represented in the form of a node tree, the node tree comprises a plurality of layers of nodes, a root node in the node tree is used for representing the investment portfolio, child nodes in the node tree are used for representing the general investment object and the specific investment object, and grandchild nodes in the node tree are used for representing products in the asset portfolio of the specific investment object. The investment amount corresponding to the investment portfolio includes an investment amount corresponding to a specific investment object, and the investment amount corresponding to the investment portfolio does not include the investment amount of each product in the asset portfolio. The attributes corresponding to a generic investment object include at least: implicit asset attributes, specific asset attributes, direct asset attributes; wherein the implicit asset attribute, the specific asset attribute, and the direct asset attribute respectively correspond to different target risk fractions.

It can be seen that, with the risk prediction apparatus for an investment portfolio shown in fig. 7, a plurality of levels of objects to be detected can be determined through the depth detection of a general investment object in the investment portfolio and a specific investment object including the investment portfolio, so as to improve the penetrability and depth of risk calculation, and further improve the accuracy of the investment risk calculation for the investment portfolio and the completeness of risk calculation results displayed to users. In addition, the investment details corresponding to the investment portfolio can be automatically obtained, risk calculation is carried out on each object and the sub-objects contained in the objects in the investment details, and the automation degree of the investment risk calculation is improved.

In an exemplary embodiment of the present application, the risk data determining unit 720 calculates a specific risk ratio for a specific investment object based on the investment amount of each product in the portfolio for the specific investment object, including:

the ratio is determined as a specific risk to a specific investment object.

Therefore, by implementing the optional embodiment, the calculation of the risk index is not limited to direct position taking, and can also penetrate through the bottom-layer asset, the direct position taking and the bottom-layer asset are weighted and then merged for calculation, and the prediction precision of the actual risk can be improved.

In an exemplary embodiment of the present application, the risk data determining unit 720 determines the risk amount corresponding to the specific investment object according to the specific risk percentage and the investment amount corresponding to the specific investment object, including:

and the risk data determining unit 720 determines the risk amount corresponding to the general investment object according to the target risk ratio and the investment amount corresponding to the general investment object, including:

Therefore, by implementing the optional embodiment, the more accurate risk amount corresponding to the specific investment object can be calculated according to the specific risk ratio, the more accurate risk amount corresponding to the general investment object can be calculated according to the target risk ratio, and the accuracy of the finally calculated risk amount can be improved by setting different risk ratios for different investment objects.

In an exemplary embodiment of the present application, the risk prediction unit 730 predicts the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment objective and the specific investment objective, respectively, including:

Therefore, by implementing the optional embodiment, the risk amount with higher precision can be calculated according to the weight proportion corresponding to different investment objects, and the risk amount calculated based on the method has higher reference value, thereby being beneficial to assisting the user to carry out the investment amount proportion adjustment.

and a message feedback unit (not shown) for feeding back a prompt message for indicating that the investment portfolio has investment risk when the risk amount is detected to be larger than the preset amount.

Therefore, by implementing the optional embodiment, the interactivity can be improved, the user can conveniently know that the investment risk exists in the investment portfolio in time, and the user can adjust the investment proportion of each investment object in the investment portfolio in time based on the acquired information, so that the use experience of the user is improved.

In an exemplary embodiment of the present application, the risk data displaying unit 740 displays the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment objective and the specific investment objective, and the investment amount of each product in the portfolio based on the investment objective affiliation represented by the investment details, including:

integrating the first-level visual data, the second-level visual data and the third-level visual data into a multi-level visual table, and displaying the multi-level visual table; the first-level visual data are obtained through calculation based on the second-level visual data, and the second-level visual data are obtained through calculation based on the third-level visual data. Therefore, the richness of the visual data can be improved, and the interactive experience can be improved.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

For details which are not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the risk prediction method for a portfolio described above for the present application for the details which are not disclosed in the embodiments of the apparatus of the present application, since the respective functional modules of the risk prediction apparatus for a portfolio correspond to the steps of the exemplary embodiments of the risk prediction method for a portfolio described above.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A method for risk prediction for a portfolio, comprising:

calculating a specific risk ratio of the specific investment object according to the investment amount of each product in the portfolio of the specific investment object, and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object;

and displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object and the investment amount of each product in the asset portfolio based on the affiliation of the investment objects represented by the investment details.

2. The method according to claim 1, wherein the investment details are represented in the form of a node tree, the node tree comprising a plurality of levels of nodes, a root node in the node tree representing the portfolio, child nodes in the node tree representing the general investment object and the specific investment object, and grandchild nodes in the node tree representing respective products in the portfolio of the specific investment object.

3. The method of claim 1, wherein calculating the specific risk ratio for the particular investment object based on the investment amount for each product in the portfolio for the particular investment object comprises:

determining a particular risky product in the portfolio of the particular investment object; wherein the risk assessment value corresponding to the specific risk product is higher than the risk assessment values of other risk products in the portfolio;

determining the ratio as a specific risk proportion for the specific investment object.

4. The method according to claim 1, wherein determining the amount of risk corresponding to the particular investment object based on the particular risk profile and the amount of investment corresponding to the particular investment object comprises:

5. The method according to claim 1, wherein predicting the risk amount corresponding to the portfolio based on the risk amounts corresponding to the general investment objective and the specific investment objective, respectively, comprises:

determining a weighted sum between the risk amount of the generic investment object and the risk amount of the specific investment object;

6. The method of claim 1, wherein presenting the risk amount corresponding to the portfolio, the risk amounts corresponding to the general investment objectives and the specific investment objectives, and the investment amount of each product in the portfolio based on the investment objective dependencies characterized by the investment details comprises:

determining the risk amount corresponding to the investment portfolio as primary visual data, the risk amount corresponding to the general investment object and the specific investment object as secondary visual data, and the investment amount of each product in the asset portfolio as tertiary visual data based on the affiliation of the investment objects represented by the investment details;

integrating the primary visual data, the secondary visual data and the tertiary visual data into a multi-level visual table, and displaying the multi-level visual table; the first-level visualization data are obtained through calculation based on the second-level visualization data, and the second-level visualization data are obtained through calculation based on the third-level visualization data.

7. The method according to any one of claims 1 to 6, wherein the attributes corresponding to the generic investment object include at least: implicit asset attributes, specific asset attributes, direct asset attributes; wherein the implicit asset attribute, the specific asset attribute, and the direct asset attribute each correspond to a different target risk ratio.

8. A risk prediction apparatus for a portfolio, comprising:

the risk data determining unit is used for calculating a specific risk ratio of the specific investment object according to the investment amount of each product in the portfolio of the specific investment object and determining the risk amount corresponding to the specific investment object according to the specific risk ratio and the investment amount corresponding to the specific investment object;

the risk data determining unit is further configured to determine a target risk ratio of the general investment object according to the attribute corresponding to the general investment object, and determine a risk amount corresponding to the general investment object according to the target risk ratio and an investment amount corresponding to the general investment object;

a risk prediction unit for predicting the risk amount corresponding to the investment portfolio according to the risk amounts corresponding to the general investment object and the specific investment object respectively;

and the risk data display unit is used for displaying the risk amount corresponding to the investment portfolio, the risk amount corresponding to the general investment object and the specific investment object and the investment amount of each product in the asset portfolio based on the investment object membership represented by the investment detail.

9. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out a method for risk prediction for a portfolio according to any one of claims 1-7.

10. An electronic device, comprising:

one or more processors;

a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a method of risk prediction for a portfolio according to any one of claims 1-7.