CN114693458A - Visualized processing method of fund data and fund combination data and related components - Google Patents
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Abstract
The invention discloses a visualized processing method and related components of fund data and fund combination data, wherein the method comprises the steps of respectively counting profit index data, risk index data and dynamic adjustment index data in fund combinations; grading according to a preset grading rule to respectively obtain corresponding profit grading, risk grading and dynamic adjustment grading; respectively assigning the profit attribute, the risk attribute and the dynamic adjustment attribute of the visualization identifier corresponding to the fund combination according to the profit score, the risk score and the dynamic adjustment score to obtain corresponding attribute values; and responding to an operation instruction of a user, and displaying the visualization identification corresponding to the fund combination and the attribute value corresponding to the attribute on a display interface. The invention has the advantages that the core characteristics of the investment strategy, the fund combination and the actual running market performance are imaged into an easily understood diagram by an attribute assignment mode, and the simple visualization of complex and changeable fund data and fund combination data is realized.
Description
Technical Field
The invention relates to the technical field of data visualization, in particular to a visualized processing method of fund data and fund combination data and related components.
Background
In the current existing fund investment advisor service, a service mode of 'full authority delegation' is proposed: in this mode, a fund investment institution can directly operate a customer account to execute an investment decision after being authorized by a customer, and directly buy fund shares to construct various fund combinations, so that the matching of the investment demand of the customer and various investment strategies is realized, the risk dispersion effect of asset allocation is combined with alpha excess income of fund products, the irrational investment and sale are avoided, and investors are guided to invest for a long time, so that the method has epoch significance and practical value, and becomes one of important modes for improving the profit experience of the customer.
However, the fund is not sailing in the promotion process, and even faces the situation of calling but not calling once, and the reason is that the fund is thrown and paid and further promotes the threshold on the basis of the original fund investment: the fund product is used for managing a package of security products, and the fund is paid in the management of the original security products, so that a second management for the package of the security products is added. Therefore, the investment institution needs to spend great effort on customer education and market cultivation, and not only needs to emphasize the base selection strategy of investment service, but also needs to introduce the stock selection and debt selection strategy of each fund product in a position; the method mainly emphasizes the level of putting a management team on duty, and also gives consideration to the capability of introducing fund managers, and in the process, a large number of financial professional terms are inevitably required to be involved, large, complex and similar data are listed, and complex formulas and indexes are calculated. Thus, while fund investment is intended to assist investors in investing fund products, it is difficult to understand and accept the fund because of the complex logic therein and the lack of proper guidance of the investor for the users by the investment institutions. Therefore, it is necessary to provide a method for visualizing fund data and fund combination data to guide users to make rational investment decisions in view of the shortcomings of the existing products and technologies.
Disclosure of Invention
The embodiment of the invention provides a visualized processing method and related components of fund data and fund combination data, and aims to solve the problems that the existing fund data and fund combination data are complex in logic and lack of guidance, so that vast investors are difficult to understand and decide.
In order to solve the technical problems, the invention aims to realize the following technical scheme: the method for visually processing the fund data and fund combination data comprises the following steps:
responding to an investment target selected by a user on a display interface, confirming a target investment strategy and a basic fund combination, generating a dynamic adjustment index and a basic attribute of an visualized identification, and displaying;
the method comprises the steps of counting data of each profit index in a fund combination, carrying out scoring processing on the data of each profit index under the same dimensionality according to a preset scoring rule to obtain a plurality of first scores, and carrying out weighted calculation on the first scores according to the weight of each profit index to obtain the profit scores, wherein the profit indexes comprise: the method comprises the following steps of (1) carrying out weighted average annual and arbitrary job return data on the ratio data of various types of bottom assets, fund combinations, principal investment direction data of a position fund product, performance data of position fund under multiple time dimensions, ranking conditions compared with similar funds and fund managers;
counting the data of each risk index in the fund combination, scoring the data of each risk index in the same dimension according to a preset scoring rule to obtain a plurality of second scores, and performing weighted calculation on the second scores according to the weight of each risk index to obtain risk scores, wherein the risk indexes comprise: a weighted average profitability probability of the position-taken fund in a plurality of time dimensions, a weighted average sharp ratio of the position-taken fund in a plurality of time dimensions, and a weighted average maximum pullback rate of the position-taken fund in a plurality of time dimensions;
counting data of each dynamic adjustment index in the fund combination, scoring the data of each dynamic adjustment index in the same dimension according to a preset scoring rule to obtain a plurality of third scores, and performing weighted calculation on the third scores according to the weight of each dynamic adjustment index to obtain a dynamic adjustment score, wherein the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a stable force index and an activity force index;
acquiring an visualization identifier corresponding to the fund combination type, and respectively assigning profit attributes, risk attributes and dynamic adjustment attributes of the visualization identifier according to the profit scores, the risk scores and the dynamic adjustment scores to obtain attribute values of the profit attributes, the risk attributes and the dynamic adjustment attributes;
and responding to an operation instruction of a user, and displaying the visualization identification corresponding to the fund combination type and the attribute value of the corresponding attribute on a display interface.
Another object of the present invention is to provide a fund data and fund combination data visualization processing apparatus, including:
the selection unit is used for responding to the investment target selected by the user on the display interface, confirming the target investment strategy and the basic fund combination, generating the dynamic adjustment index and the basic attribute of the visualized identification, and displaying the dynamic adjustment index and the basic attribute;
the first scoring unit is used for counting the data of each profit index in the fund combination, scoring the data of each profit index in the same dimension according to a preset scoring rule to obtain a plurality of first scores, and performing weighted calculation on the first scores according to the weight of each profit index to obtain profit scores, wherein the profit indexes comprise: the method comprises the following steps of (1) carrying out weighted average annual and arbitrary job return data on the ratio data of various types of bottom assets, fund combinations, principal investment direction data of a position fund product, performance data of position fund under multiple time dimensions, ranking conditions compared with similar funds and fund managers;
the second scoring unit is used for counting the data of each risk index in the fund combination, scoring the data of each risk index in the same dimension according to a preset scoring rule to obtain a plurality of second scores, and performing weighted calculation on the second scores according to the weight of each risk index to obtain risk scores, wherein the risk indexes comprise: the weighted average profitability of the position-holding fund in a plurality of time dimensions, the weighted average sharp ratio of the position-holding fund in a plurality of time dimensions, and the weighted average maximum withdrawal rate of the position-holding fund in a plurality of time dimensions;
the third scoring unit is used for counting data of each dynamic adjustment index in the fund combination, scoring the data of each dynamic adjustment index in the same dimensionality according to a preset scoring rule to obtain a plurality of third scores, and performing weighted calculation on the third scores according to the weight of each dynamic adjustment index to obtain a dynamic adjustment score, wherein the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a stable force index and an activity force index; the hit power indicators include: the yield of the over-annual evolution, the fluctuation rate deviation degree, the alpha value and the beta value, wherein the balance force index comprises: excess annual rate of return, fluctuation rate deviation, alpha value, beta value, the restoring force index includes: excess annual rate of return, maximum withdrawal deviation degree, fluctuation rate deviation degree, the steady force index includes: excess annual rate of return, the maximum combined withdrawal deviation degree, the activity index includes: the weighted average positive income probability and the average expansion amplitude in a certain time period under a plurality of time dimensions are reduced by years. According to different settings of each dynamic adjustment index, the calculation weights of each item of specific data included in the dynamic adjustment index are obviously different.
The attribute unit is used for acquiring an visualized identifier corresponding to the fund combination type and a corresponding dynamic adjustment index, and respectively assigning the profit attribute, the risk attribute and the dynamic adjustment attribute of the visualized identifier according to the profit score, the risk score and the dynamic adjustment score to obtain attribute values of the profit attribute, the risk attribute and the dynamic adjustment attribute;
and the display unit is used for responding to an operation instruction of a user and displaying the visualization identification corresponding to the fund combination type and the attribute value corresponding to the attribute on a display interface.
In addition, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor, when executing the computer program, implements the method for visualizing the fund data and the fund combination data according to the first aspect.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to execute the method for visualizing processing fund data and fund combination data according to the first aspect.
The embodiment of the invention discloses a fund data and fund combination data visualization processing method and related components, wherein the method comprises the steps of respectively counting profit index data, risk index data and dynamic adjustment index data in fund combinations, carrying out scoring processing according to a preset scoring rule, carrying out weighting calculation after obtaining a plurality of corresponding first scores, second scores and third scores, and then obtaining profit scores, risk scores and dynamic adjustment scores; respectively assigning the profit attribute, the risk attribute and the dynamic adjustment attribute of the visualization identifier corresponding to the fund combination according to the profit score, the risk score and the dynamic adjustment score to obtain attribute values of the profit attribute, the risk attribute and the dynamic adjustment attribute; and responding to an operation instruction of a user, and displaying the visualization identification corresponding to the fund combination and the attribute value of the corresponding attribute on a display interface. The embodiment of the invention has the advantages that the core characteristics of the combination of the investment strategy and the fund and the actual running market performance are imaged into an easily understood diagram in an attribute numerical mode, and the complex and variable fund data and fund combination data are simply and visually displayed.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for visualizing fund data and fund combination data according to an embodiment of the present invention;
FIG. 2 is a schematic subflow diagram of a method for visualizing fund data and fund combination data according to an embodiment of the present invention;
FIG. 3 is an exemplary diagram of an interface for dynamically adjusting metrics and base attributes for generating visual identifiers by selecting investment goals and risk tolerance according to an embodiment of the present invention;
FIG. 4 is an exemplary diagram of an interface for adjusting fund combinations and changing visual identifiers according to risk levels thereof according to an embodiment of the present invention;
FIG. 5 is an exemplary diagram of an interface for further adjusting fund combinations according to risk levels thereof to accomplish visual identification confirmation, according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an exemplary main interface for displaying the visualized identifiers, the fund combinations and the attribute units corresponding to the visualized identifiers according to the embodiment of the present invention;
FIG. 7 is a detailed information exemplary diagram showing investment strategies for fund combinations corresponding to the visualized identifiers according to the embodiment of the present invention;
fig. 8 is an exemplary diagram of a detail interface for showing scoring indexes in the profit attribute of the fund combination corresponding to the visual identifier according to the embodiment of the present invention;
FIG. 9 is an exemplary diagram illustrating the level information and level rights corresponding to the visual identifier according to an embodiment of the present invention;
FIG. 10 is a schematic block diagram of an apparatus provided by an embodiment of the present invention;
FIG. 11 is a schematic block diagram of a computer device provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for visualizing fund data and fund combination data according to an embodiment of the present invention;
as shown in fig. 1, the method includes steps S101 to S106.
S101, responding to an investment target selected by a user on a display interface, confirming a target investment strategy and a basic fund combination, generating a dynamic adjustment index and a basic attribute of an visualized identifier, and displaying;
s102, counting data of each profit index in the fund combination, scoring the data of each profit index in the same dimension according to a preset scoring rule to obtain a plurality of first scores, and performing weighted calculation on the first scores according to the weight of each profit index to obtain profit scores, wherein the profit indexes comprise: the method comprises the following steps of (1) carrying out weighted average annual and arbitrary job return data on the ratio data of various types of bottom assets, fund combinations, principal investment direction data of a position fund product, performance data of position fund under multiple time dimensions, ranking conditions compared with similar funds and fund managers;
s103, counting the data of each risk index in the fund combination, scoring the data of each risk index in the same dimension according to a preset scoring rule to obtain a plurality of second scores, and performing weighted calculation on the second scores according to the weight of each risk index to obtain risk scores, wherein the risk indexes comprise: the weighted average profitability of the position-holding fund in a plurality of time dimensions, the weighted average sharp ratio of the position-holding fund in a plurality of time dimensions, and the weighted average maximum withdrawal rate of the position-holding fund in a plurality of time dimensions;
s104, counting the data of each dynamic adjustment index in the fund combination, scoring the data of each dynamic adjustment index in the same dimension according to a preset scoring rule to obtain a plurality of third scores, and performing weighted calculation on the third scores according to the weight of each dynamic adjustment index to obtain dynamic adjustment scores;
in the step, the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a stable force index and an activity index; the hit metrics include: the yield of the over-annual growth, the fluctuation rate deviation, the alpha value and the beta value, and the balance force indexes comprise: excess annual rate of return, fluctuation rate deviation degree, alpha value, beta value, restoring force index include: the yield of the over-annual return, the maximum withdrawal deviation degree and the fluctuation rate deviation degree, and the stability index comprises: the overannual rate of return, the maximum withdrawal degree of deviation of combination, the activity index includes: the weighted average positive income probability and the average expansion amplitude in a certain time period under multiple time dimensions are reduced into years. It should be noted that, according to different settings of each dynamic adjustment index, there is a significant difference in the calculation weight of each item of specific data included therein;
specifically, the dynamic adjustment index may be used to distinguish different types of fund combinations, for example, the dynamic adjustment index may refer to a fund investment combination mainly based on high-risk and high-income equity type investments when the dynamic adjustment index is a hit index, refer to a fund investment combination of high-risk and high-income type mixed type with rapid asset increment when the dynamic adjustment index is a balance index, refer to a medium-risk and win-swell type fund investment combination of mixed type when the dynamic adjustment index is a restoring index, refer to a medium-low risk and fixed-income type fund investment combination when the dynamic adjustment index is a stable index, refer to a low-risk and idle fund management type fund investment combination when the dynamic adjustment index is an activity index;
s105, acquiring an visualization identifier corresponding to the fund combination type and a corresponding dynamic adjustment index, and respectively assigning the profit attribute, the risk attribute and the dynamic adjustment attribute of the visualization identifier according to the profit score, the risk score and the dynamic adjustment score to obtain attribute values of the profit attribute, the risk attribute and the dynamic adjustment attribute;
and S106, responding to an operation instruction of a user, and displaying the visualization identification corresponding to the fund combination type and the attribute value corresponding to the attribute on a display interface.
In this embodiment, as shown in fig. 6, for each fund combination, in order to enable a user to quickly and intuitively know respective advantages of a casting strategy and a casted fund product, an visualization identifier corresponding to the fund combination and an attribute value corresponding to the attribute are displayed through an interface, core features of the casting strategy and the fund combination and actual running market performance are visualized into an easily understood diagram, and the method has the advantage of performing concise visualization on complex and variable fund data and fund combination data, thereby guiding the user to make investment decisions.
The embodiment also gives attribute values to the profit attribute, the risk attribute and the dynamic adjustment attribute, and displays the attribute details through the attribute interface, so that a user can conveniently and comprehensively know the attribute details;
first, a presentation process of attribute values assigned to profit attributes by profit scores is introduced:
in an exemplary scenario, referring to fig. 8, fig. 8 is a detail interface of the profit attribute in fig. 6, and fig. 8 shows 7 resolutions of profit scores and scores of each of the scores, i.e. 7 first scores a1-a7, which are: individual fund type proportion data a1 (score 9/10), fund combination mastery investment direction data a2 (score 8/10), fund product performance data A3 in six months in taken position (score 8/10), fund product performance data a4 in one year in taken position (score 7/10), fund product performance data a5 in two years in taken position (score 8/10), fund product performance data a6 in three years in taken position (score 9/10), fund manager weighted average annual employment return data a7 (score 7/10);
the specific score may be calculated by a predetermined scoring rule for the data of each profitability index in the same dimension, which is illustrated as a1, and the predetermined scoring rule for each fund type proportion data may be:
10 min: more than 80% of stock type fund products, bond type fund products or currency fund products are taken in a position less than 5%;
9 min: more than 65% of the stock type fund products, the bond type fund products or the currency fund products are taken in a position less than 8%;
8 min: stock type fund products, bond type fund products or currency fund products which are more than 50% lower than the position taken by the position;
7, dividing: more than 70% of the mixed fund products are taken in a position, and the stock fund products are less than 25%;
and 6, dividing into: the stock type fund product accounts for more than 60 percent of the taken position, and is less than 20 percent;
and 5, dividing: more than 50% of the mixed fund products are taken in a position, and the stock fund products are less than 15%;
and 4, dividing: bond type fund products with the position of more than 50 percent are taken, the mixed type fund products are less than 25 percent, and the stock type fund products are less than 15 percent;
and 3, dividing: bond type fund products with the position of 65 percent or more, mixed type fund products less than 20 percent and stock type fund products less than 10 percent;
and 2, dividing: bond type fund products with the position of more than 80 percent are taken, the mixed type fund products are less than 15 percent, and the stock type fund products are less than 5 percent;
1 minute: bond type fund products or currency fund products which are more than 90 percent of the taken position, less than 5 percent of mixed fund products and no stock type fund products;
0 minute: over 95% of the bond-type fund or monetary fund products are taken, the hybrid fund or stock-type fund is not included.
Based on this, it can be understood that the predetermined scoring rule about a2 is a field score of the principal investment of fund combination, and different fields correspond to different scores; the predetermined scoring rule about A3-A6 is the performance fluctuation score of the fund products in the taken positions under different periods, and different fluctuation conditions correspond to different scores; the predetermined scoring rules for A7 are the fund manager's weighted average annual exertional reward score, with different reward scores corresponding to different scores; the predetermined scoring rules for the particular a1-a7 may be adjusted according to the actual application scenario.
According to the scores of A1-A7, the formula: (a1+ a2+0.5 × A3+0.5 × a4+0.5 × a5+0.5 × a6+ a7)/5, and a profit score of 8 was calculated and obtained; namely, the profit score 8 is assigned to the profit attribute of the visualized identification to obtain the attribute value of the profit attribute, and the user can intuitively know the profit attribute of the fund combination from the interface so as to make a decision.
And then, introducing a process of displaying the attribute values assigned to the risk attributes by the risk scores in the step:
in an exemplary scenario, in response to a user selecting a risk attribute, a details interface for the risk attribute is entered, where 8 resolutions for risk scores and scores for each of the 8 second scores B1-B8 may be shown in the details interface, respectively: a weighted average profitability probability B1 of a position fund under seven days of holding, a weighted average profitability probability B2 of a position fund under 3 months of holding, a weighted average profitability probability B3 of a position fund under 6 months of holding, a weighted average profitability probability B4 of a position fund under 1 year of holding, a weighted average Sharper ratio B5 of a position fund under 1 year of holding, a weighted average Sharper ratio B6 of a position fund under 3 years of holding, a weighted average maximum withdrawal B7 of a position fund under 1 year of holding, and a weighted average maximum withdrawal B8 of a position fund under 3 years of holding;
the specific score is calculated on the data of each risk index in the same dimension through a preset scoring rule, so that the specific score of B1-B8 is obtained, as can be understood, the preset scoring rule of B1 is the size score of the weighted average profit probability of the position-holding fund in seven days, and the sizes of different weighted average profit probabilities correspond to different scores; b2, the predetermined scoring rule is the score of the weighted average profit probability of the position fund under the condition of holding for 3 months, and different weighted average profit probabilities correspond to different scores; b3, the predetermined scoring rule is the score of the weighted average profit probability of the position fund under the condition of holding for 6 months, and different weighted average profit probabilities correspond to different scores; the predetermined scoring rule of B4 is the score of the weighted average profit probability of the position fund under the condition of holding for 1 year, and different weighted average profit probabilities correspond to different scores; the predetermined scoring rule of B5 is the size score of the weighted average sharp ratio of the position fund under 1 year, and different weighted average sharp ratios correspond to different scores; the predetermined scoring rule of B6 is the size score of the weighted average sharp ratio of the position fund under 3 years, and different weighted average sharp ratios correspond to different scores; b7, wherein the preset scoring rule is the weighted average maximum withdrawal proportion score of the position fund under 1 year, and different proportions correspond to different scores; b8, wherein the preset scoring rule is the weighted average maximum withdrawal proportion score of the position fund under 3 years, and different proportions correspond to different scores; the preset scoring rules of the specific B1-B8 can be adjusted according to actual application scenes;
according to the scores of B1-B8, the score is determined by the formula: (B1+ B2+ B3+ B4+ B5+ B6+ B7+ B8)/8, and calculating and obtaining a specific score of the risk score; namely, the specific score of the risk score is assigned to the risk attribute of the visual identification to obtain the attribute value of the risk attribute, and the user can intuitively know the risk attribute of the fund combination from the interface so as to make a decision.
Finally, the display process of the attribute value assigned to the dynamic adjustment attribute by the dynamic adjustment score is introduced:
fig. 3 is an interface for a user to select an investment target, taking the case that the user chooses to pursue excess return and is willing to bear high risk as an example, the system generates an investment portfolio whose investment strategy is mainly based on equity type investments biased toward high risk and high profit types, determines a dynamic adjustment index as a hit index, and calculates a basic attribute of an visualized identifier.
Taking the dynamic adjustment indexes as the hit force indexes for example, namely scoring the data of each hit force index under the same dimensionality according to a preset scoring rule to obtain a plurality of third scores, and performing weighted calculation on the third scores according to the weight of each hit force index to obtain the hit force scores; assigning the hit attribute of the visualization identifier according to the hit power score to obtain the attribute value of the hit attribute;
in an exemplary scenario, in response to a user selection of a hit property, a detail interface for the hit property may be entered, in which 4 resolutions for the hit force score and a score for each bar, i.e., 4 third scores C1-C4, may be shown: the yield of overyear aging is C1, the fluctuation deviation degree is C2, the alpha value is C3, and the beta value is C4;
the data of each hit power index is calculated under the same dimensionality through a preset scoring rule, so that specific scores of C1-C4 are obtained, the preset scoring rule of C1 is understood to be the score of the excess annual profitability of the fund combination, which is actually expressed in 1 year and is compared with the performance benchmark, and different profitability values correspond to different scores; c2, obtaining scores of the volatility of the fund combination compared with the tracking target in 1 year, wherein different degrees of deviation correspond to different scores; c3, wherein the predetermined scoring rule is that the actual performance of the fund combination under 1 year is different from the selected scaled alpha value score, and different alpha values correspond to different scores; c4, wherein the predetermined scoring rule is that the actual performance of the fund combination under 1 year is compared with the score of the selected target beta value, and different beta values correspond to different scores;
according to the scores of C1-C4, the score is represented by the formula: (C1+0.5C2+ C3+0.5C4)/3, calculating and obtaining a specific score of the hit power score; namely, the specific score of the hit power score is assigned to the hit attribute of the visual identification to obtain the attribute value of the hit attribute, and the user can intuitively know the hit attribute of the fund combination from the interface so as to make a decision.
It can be understood that, for the introduction of the attribute value assigned to the dynamic adjustment attribute by the dynamic adjustment score in S103, interface display when the dynamic adjustment index is the equilibrium index, or when the dynamic adjustment index is the restoring force index, or when the dynamic adjustment index is the stabilizing force index, or when the dynamic adjustment index is the activity index may be specifically understood with reference to the process when the dynamic adjustment index is the hit force index; the attribute details of each index can be clearly shown, and the user can intuitively know each attribute of the fund combination from the interface display so as to make a decision.
It should be understood that the hit force indicator, balance force indicator, resilience indicator, stability force indicator, and activity force indicator included in the dynamic adjustment score are named, and different names may be changed as needed in an actual application scenario. Changing the name does not affect the corresponding computation logic behind each index.
It should also be understood that the market is in a vast change, the computer device shown in fig. 11 will collect relevant data in real time and keep updating, and the components, the visual identification and the related data, indexes, scores and attributes are in a dynamic change. Therefore, the adjustment of the calculation formula, the adjustment of the weight, the adjustment of the score term, and the like do not affect the technical solution of the overall invention. Specifically, the core content of the invention is to embody the core characteristics of the invested strategy, fund combination and actual running market expression into easily understood visualization identification and graphic representation instead of a specific formula or a scoring item of a certain attribute in an attribute assignment mode.
It should be further understood that the investment goals, risk tolerance, and investment preferences of the investor are not constant, and as the above changes, the basic attribute and the dynamic adjustment attribute of the visual identifier may also change, and in particular, the dynamic adjustment attribute may change from one of the hit force index, the balance force index, the restoring force index, the steady force index, and the activity force index to another, for example, from the hit force attribute of the equity type investment biased toward the high risk and high profit type to the steady force attribute biased toward the middle-low risk and low profit type investment portfolio, and at this time, the visual identifier may also change accordingly. Therefore, the invention can feed back the performance change of the market and the actual operation condition of the fund combination in time by the way of attribute assignment, graphic representation and visual representation display, and is more close to the actual investment target and expectation of the user.
In an embodiment, as shown in fig. 2, the method for visualizing and processing fund data and fund combination data further includes:
s201, responding to the risk bearing capacity and fund risk level selected by a user on a display interface, updating and adjusting a target investment strategy and a basic fund combination according to the risk level selected by the user, and synchronously updating an visualization identifier and an attribute value;
namely, the visual identification and the attribute value are fed back in real time along with the adjustment of the scheme and synchronously change.
S202, responding to an visualization identification selected by a user on a display interface, entering an attribute interface corresponding to the visualization identification, acquiring attribute values of a profit attribute, a risk attribute and a dynamic adjustment attribute, and displaying corresponding attribute information;
s203, responding to the detail introduction of the combined information selected by the user on the attribute interface, entering a detail interface corresponding to the combined information details, and displaying the corresponding detail information;
s204, responding to the detail introduction of the attribute information selected by the user on the attribute interface, entering a detail interface corresponding to the attribute details, and displaying the corresponding detail information;
s205, responding to the confirmation operation of the user, and completing the confirmation of the visualization identification.
The embodiment introduces a process of selecting fund combination by a user, and adopts visualization steps to guide the user; specifically, as shown in the display interface shown in fig. 3, the present embodiment divides the investment targets of the user into: the method comprises the following steps of flexibly using money, stably managing money, running and expanding, quickly gaining value and returning excess, wherein each target corresponds to five risk levels of low risk, medium and low risk, medium and high risk; each investment target also corresponds to different fund combinations and visual identifications; first, in response to the investment target selected by the user on the display interface, the selection of the investment target will generate dynamic adjustment indexes and basic attributes of visual identifiers, such as the selection of the "excess return" investment target illustrated in fig. 3, and correspondingly, one or more visual identifiers representing "excess return" will be shown on the interface, each visual identifier may refer to a corresponding fund combination, and the dynamic adjustment index corresponding to the "excess return" is the hit power, and the basic attributes are the hit power attributes.
Then, in response to the visual identifier selected by the user, such as the selection of the visual identifier illustrated in fig. 3, after receiving an operation instruction of a next step clicked by the user, the user jumps to an attribute interface of fig. 4 or fig. 5, for example, and displays attribute information of the selected visual identifier, and the user can intuitively obtain a profit attribute, a risk attribute, and a dynamic adjustment attribute and attribute value corresponding to the visual identifier in the attribute interface. The profit attribute, the risk attribute, the dynamic adjustment attribute and the attribute value are important attributes representing the policy direction of each fund combination, and the higher the attribute value is, the more the policy direction bias is represented. Specific attributes and attribute values are directly displayed below the visual identification so that a user can know the attributes more intuitively, and the user can click a detail-knowing button at the rear end point of each attribute value position for further viewing. The degree of attribute value integration can reflect whether the fund combination strategy generally meets the user expectation and the degree of the actual market performance. The user may further adjust the investment strategy and fund combination scheme in the interface according to his risk tolerance to match his risk characteristics, such as the attribute interface of fig. 4 or fig. 5, and may select investment asset preference, where the selected "prefer blue funding" option is lower in risk level than the "prefer growing stock" option, and select investment strategy preference, where the selected "passive index fund" is lower in risk level than the "actively managed fund" option. If the user wants to select the visual identification, the user can select the visual identification after clicking the next button after finishing the selection of the related options; then, the user jumps to a display interface shown in fig. 6, and the user can view the selected visual identification and the specific information of the corresponding fund combination in the display interface shown in fig. 6.
It should be understood that the investment asset preferences and investment strategy preferences shown here are not all options for measuring the risk level of the user, and in practical applications, more options are generated and displayed for the user to select according to different investment strategies and user personalized requirements, so as to achieve a good match between the risk characteristics of the fund combination and the risk characteristics of the user. The different topics and options do not affect the computational logic presented herein for combinations of funds and visual identification that a user fits through multiple option selections.
Further, in the display interface shown in fig. 6, after the user performs the operation of knowing the details clicked at the rear end of the position of the name and the attribute value of the customer portfolio, the user can jump to the next specified detailed information interface for more comprehensive understanding, for example, the "know details" button at the rear end of the position of the name of the customer portfolio shown in the display interface shown in fig. 6, and click on the display interface, the user can jump to the portfolio strategy detail interface shown in fig. 7, for example, and show the information of the performance portfolio, the portfolio asset configuration, the base selection strategy, and the like of the customer portfolio; for example, the "know details" button at the back end of the value location of the profit attribute shown in the display interface shown in fig. 6, clicking may jump to the details interface of the profit attribute shown in fig. 8, revealing a resolution on the profit score and a score for each bar.
In one embodiment, the method for visualizing the fund data and the fund combination data further comprises the following steps:
acquiring basic information data, position taking data, transaction data, operation data and behavior data of a user, summarizing all data, carrying out weighted calculation to obtain a summarized grade, comparing the summarized grade with the grade corresponding to the current grade of the visual identification, and if the summarized grade exceeds the grade corresponding to the current grade of the visual identification, updating and upgrading the visual identification and matching and issuing corresponding rights and interests for the user. The basic information data includes user birthdays, registration times and durations. The position data includes the investment amount, the investment duration and the kind of the held product. The transaction data includes: the method comprises the following steps of user account opening behavior, contract signing and service throwing behavior, risk assessment behavior, fund product purchasing behavior, redemption behavior, transfer behavior, dividend data obtaining and investment setting behavior. The behavior data comprises user activity degree, sharing behavior, friend invitation registration behavior, advertisement clicking behavior, live broadcast watching behavior, reward obtaining behavior, article reading behavior, video watching behavior, interaction behavior of a user with a consultant or customer service, check-in behavior, activity participating behavior, link clicking behavior, APP downloading behavior, login behavior, APP opening behavior and interaction behavior conducted on different channels online and offline.
In this embodiment, when a "know details" button at the rear end of a level classification clicked by a user on the interface shown in fig. 6, for example, is received, the user may jump to the display interface shown in fig. 9, and display information corresponding to the current level classification, such as a level corresponding to the current level classification, a corresponding current visual identifier, a corresponding next level visual identifier, and right content corresponding to the current level classification and the next level classification, and the information is displayed visually by using a graphic.
In one embodiment, the method for visualizing the fund data and the fund combination data further comprises the following steps:
responding to a replacement instruction of the user for the visualization identification on the display interface, calling the selected new visualization identification from the database or combining the selected new visualization identification with the fund combination in a user-defined manner according to elements in the database, and binding the selected new visualization identification with the fund combination;
and responding to a preview instruction of the user to the visualization identification on the display interface, displaying the previewed 3D model of the visualization identification, and performing rotation multi-dimensional display on the 3D model according to the rotation instruction of the user.
The embodiment can replace the visualization identification selected by the user, other replaceable visualization identifications of the same type are called from the database or are combined into a new visualization identification by customer self-definition according to elements in the database and displayed in a previewing mode according to the received replacement instruction of the current visualization identification, the rotational multi-dimensional display can be executed according to the received rotational display instruction in the display process, so that the user can preview more comprehensively and intuitively, and the replacement can be completed by binding the new visualization identification with the fund combination after the new visualization identification selected by the user is received.
In an embodiment, the method further comprises:
and responding to the selection of a newly added investment target on the display interface by the user, confirming the newly added target investment strategy and the basic fund combination, generating a dynamic adjustment index and a basic attribute of a new visualized identification, and displaying.
In this embodiment, an imaging identifier switching module may be disposed in the display interface for a user to operate a plurality of investment targets of different types and different risk levels at the same time, and it can be understood that the interface display method for the newly added investment target may refer to the description of the foregoing embodiment, and is not described herein again.
The embodiment of the invention also provides a visualized processing device of the fund data and fund combination data, which is used for executing any one embodiment of the visualized processing method of the fund data and fund combination data. Specifically, referring to fig. 10, fig. 10 is a schematic block diagram of a device for visualizing and processing fund data and fund combination data according to an embodiment of the present invention.
As shown in fig. 10, the device 1000 for visualizing and processing fund data and fund combination data includes: a selection unit 1001, a first scoring unit 1002, a second scoring unit 1003, a third scoring unit 1004, an attribute unit 1005, and a presentation unit 1006.
The selection unit 1001 is used for responding to the investment target selected by the user on the display interface, confirming the target investment strategy and the basic fund combination, generating the dynamic adjustment index and the basic attribute of the visualized identification, and displaying the dynamic adjustment index and the basic attribute;
the first scoring unit 1002 is configured to count data of each profit index in the fund combination, score the data of each profit index in the same dimension according to a predetermined scoring rule to obtain a plurality of first scores, and perform weighted calculation on the first scores according to weights of the profit indexes to obtain profit scores, where the profit indexes include: the method comprises the following steps of (1) carrying out weighted average annual and arbitrary job return data on the ratio data of various types of bottom assets, fund combinations, principal investment direction data of a position fund product, performance data of position fund under multiple time dimensions, ranking conditions compared with similar funds and fund managers;
the second scoring unit 1003 is configured to count data of each risk indicator in the fund combination, score the data of each risk indicator in the same dimension according to a predetermined scoring rule to obtain a plurality of second scores, and perform weighted calculation on the second scores according to weights of each risk indicator to obtain risk scores, where the risk indicators include: the weighted average profitability of the position-holding fund in a plurality of time dimensions, the weighted average sharp ratio of the position-holding fund in a plurality of time dimensions, and the weighted average maximum withdrawal rate of the position-holding fund in a plurality of time dimensions;
the third scoring unit 1004 is configured to count data of each dynamic adjustment index in the fund combination, perform scoring processing on the data of each dynamic adjustment index in the same dimension according to a predetermined scoring rule to obtain a plurality of third scores, and perform weighted calculation on the third scores according to weights of each dynamic adjustment index to obtain a dynamic adjustment score, where the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a stability force index, and an activity force index;
an attribute unit 1005, configured to obtain an visualization identifier corresponding to the fund combination type, and assign a profit attribute, a risk attribute, and a dynamic adjustment attribute of the visualization identifier according to the profit score, the risk score, and the dynamic adjustment score, respectively, to obtain attribute values of the profit attribute, the risk attribute, and the dynamic adjustment attribute;
the display unit 1006 is configured to display, in response to an operation instruction of a user, an visualization identifier corresponding to the fund combination type and an attribute value of a corresponding attribute on a display interface.
The device can be used for facilitating users to quickly and intuitively know respective advantages of the investment strategy and products, displaying the visualization identification corresponding to the fund combination and the attribute value corresponding to the attribute through the interface, and imaging the core characteristics of the investment strategy and the fund combination and the actual running market expression into an easily understood graphic representation.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The above-mentioned visual processing means of fund data and fund combination data may be implemented in the form of a computer program which can be run on a computer device as shown in fig. 11.
Referring to fig. 11, fig. 11 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device 1100 is a server, and the server may be an independent server or a server cluster including a plurality of servers.
Referring to fig. 11, the computer device 1100 includes a processor 1102, memory and network interface 1105 connected by a system bus 1101, where the memory may include non-volatile storage media 1103 and internal memory 1104.
The non-volatile storage medium 1103 may store an operating system 11031 and computer programs 11032. The computer program 11032, when executed, may cause the processor 1102 to perform a method of visualization of fund data and fund combination data.
The processor 1102 is configured to provide computing and control capabilities that support the operation of the overall computing device 1100.
The internal memory 1104 provides an environment for running the computer program 11032 in the nonvolatile storage medium 1103, and when the computer program 11032 is executed by the processor 1102, the processor 1102 may be caused to execute a method of visualizing the fund data and the fund combination data.
The network interface 1105 is used for network communications, such as to provide for the transmission of data information. Those skilled in the art will appreciate that the configuration shown in fig. 11 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing device 1100 to which aspects of the present invention may be applied, and that a particular computing device 1100 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
Those skilled in the art will appreciate that the embodiment of a computer device illustrated in fig. 11 does not constitute a limitation on the specific construction of the computer device, and that in other embodiments a computer device may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may only include a memory and a processor, and in such embodiments, the structures and functions of the memory and the processor are consistent with those of the embodiment shown in fig. 11, and are not described herein again.
It should be appreciated that in embodiments of the present invention, the Processor 1102 may be a Central Processing Unit (CPU), and the Processor 1102 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a non-volatile computer readable storage medium. The computer readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the method for visualization processing of fund data and fund combination data according to an embodiment of the present invention.
The storage medium is a physical and non-transitory storage medium, and may be various physical storage media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses, devices and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A visual processing method for fund data and fund combination data is characterized by comprising the following steps:
responding to an investment target selected by a user on a display interface, confirming a target investment strategy and a basic fund combination, generating a dynamic adjustment index and a basic attribute of an visualized identification, and displaying;
the method comprises the steps of counting data of each profit index in a fund combination, carrying out scoring processing on the data of each profit index in the same dimensionality according to a preset scoring rule to obtain a plurality of first scores, and carrying out weighted calculation on the first scores according to the weight of each profit index to obtain profit scores, wherein the profit indexes comprise: the method comprises the following steps of (1) carrying out weighted average annual and arbitrary job return data on the ratio data of various types of bottom assets, fund combinations, principal investment direction data of a position fund product, performance data of position fund under multiple time dimensions, ranking conditions compared with similar funds and fund managers;
counting the data of each risk index in the fund combination, scoring the data of each risk index in the same dimension according to a preset scoring rule to obtain a plurality of second scores, and performing weighted calculation on the second scores according to the weight of each risk index to obtain risk scores, wherein the risk indexes comprise: the weighted average profitability of the position-holding fund in a plurality of time dimensions, the weighted average sharp ratio of the position-holding fund in a plurality of time dimensions, and the weighted average maximum withdrawal rate of the position-holding fund in a plurality of time dimensions;
counting data of each dynamic adjustment index in the fund combination, scoring the data of each dynamic adjustment index in the same dimension according to a preset scoring rule to obtain a plurality of third scores, and performing weighted calculation on the third scores according to the weight of each dynamic adjustment index to obtain a dynamic adjustment score, wherein the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a stable force index and an activity force index;
acquiring an visualization identifier corresponding to the fund combination type and a corresponding dynamic adjustment index, and respectively assigning profit attributes, risk attributes and dynamic adjustment attributes of the visualization identifier according to the profit scores, the risk scores and the dynamic adjustment scores to obtain attribute values of the profit attributes, the risk attributes and the dynamic adjustment attributes;
and responding to an operation instruction of a user, and displaying the visualization identification corresponding to the fund combination type and the attribute value of the corresponding attribute on a display interface.
2. The method of claim 1, wherein the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a steady force index, and an activity force index; the hit power indicators include: the yield of the over-annual evolution, the fluctuation rate deviation degree, the alpha value and the beta value, wherein the balance force index comprises: excess annual rate of return, fluctuation rate deviation degree, alpha value, beta value, the restoring force index includes: excess annual rate of return, maximum withdrawal deviation degree, fluctuation rate deviation degree, the steady force index includes: excess annual rate of return, the maximum degree of deviation of withdrawing of combination, the activity index includes: the weighted average and the average expansion in a certain time period under multiple time dimensions are reduced to years, wherein different dynamic indexes correspond to different weight calculation algorithms.
3. The method for visualized processing of fund data and fund combined data according to claim 1, further comprising:
and responding to the risk bearing capacity and fund risk level selected by the user on the display interface, updating and adjusting the target investment strategy and the basic fund combination according to the risk level selected by the user, and synchronously updating the visualized identification and the attribute value.
4. The method of claim 3, further comprising the steps of:
responding to an visualization identification selected by a user on a display interface, entering an attribute interface corresponding to the visualization identification, acquiring attribute values of the profit attribute, the risk attribute and the dynamic adjustment attribute, and displaying corresponding attribute information;
responding to the detail introduction of the combined information selected by the user on the attribute interface, entering a detail interface corresponding to the combined information details, and displaying the corresponding detail information;
responding to the detail introduction of the attribute information selected by the user on the attribute interface, entering a detail interface corresponding to the attribute details, and displaying the corresponding detail information;
responding to the confirmation operation of the user and completing the confirmation of the visual identification.
5. The method for visualized processing of fund data and fund combined data according to claim 1, further comprising:
acquiring basic information data, position taking data, transaction data, operation data and behavior data of a user, summarizing all data, carrying out weighted calculation to obtain a summarized grade, comparing the summarized grade with the grade corresponding to the current grade of the visual identification, and if the summarized grade exceeds the grade corresponding to the current grade of the visual identification, updating and upgrading the visual identification and matching and issuing corresponding rights and interests for the user; the basic information data comprises user birthdays, registration time and duration; the position taking data comprises investment amount, investment duration and held product types; the transaction data includes: the method comprises the following steps of carrying out a user account opening behavior, a signing service investment behavior, a risk assessment behavior, a fund product purchasing behavior, a redemption behavior, a transfer behavior, dividend data acquisition and a fixed investment behavior; the behavior data comprises user activity degree, sharing behavior, friend invitation registration behavior, advertisement clicking behavior, live broadcast watching behavior, reward obtaining behavior, article reading behavior, video watching behavior, interaction behavior of a user with a consultant or customer service, sign-in behavior, activity participating behavior, link clicking behavior, APP downloading behavior, login behavior, APP opening behavior and interaction behavior conducted in different channels on line and off line.
6. The method for visualized processing of fund data and fund combined data according to claim 1, further comprising:
responding to a replacement instruction of the user for the visualization identification on the display interface, calling the selected new visualization identification from the database or combining the selected new visualization identification with the fund combination in a user-defined manner according to elements in the database, and binding the selected new visualization identification with the fund combination;
and responding to a preview instruction of the user to the visualization identification on a display interface, displaying the previewed 3D model of the visualization identification, and performing rotation multi-dimensional display on the 3D model according to the rotation instruction of the user.
7. The method for visualized processing of fund data and fund combined data according to claim 1, further comprising:
and responding to the selection of a newly added investment target on the display interface by the user, confirming the newly added target investment strategy and the basic fund combination, generating a dynamic adjustment index and a basic attribute of a new visualized identification, and displaying.
8. A visual processing device of fund data and fund combination data is characterized by comprising:
the selection unit is used for responding to the investment target selected by the user on the display interface, confirming the target investment strategy and the basic fund combination, generating the dynamic adjustment index and the basic attribute of the visualized identification and displaying the dynamic adjustment index and the basic attribute;
the first scoring unit is used for counting the data of each profit index in the fund combination, scoring the data of each profit index in the same dimension according to a preset scoring rule to obtain a plurality of first scores, and performing weighted calculation on the first scores according to the weight of each profit index to obtain profit scores, wherein the profit indexes comprise: the method comprises the following steps of (1) carrying out weighted average annual and arbitrary job return data on the ratio data of various types of bottom assets, fund combinations, principal investment direction data of a position fund product, performance data of position fund under multiple time dimensions, ranking conditions compared with similar funds and fund managers;
the second scoring unit is used for counting the data of each risk index in the fund combination, scoring the data of each risk index in the same dimension according to a preset scoring rule to obtain a plurality of second scores, and performing weighted calculation on the second scores according to the weight of each risk index to obtain risk scores, wherein the risk indexes comprise: the weighted average profitability of the position-holding fund in a plurality of time dimensions, the weighted average sharp ratio of the position-holding fund in a plurality of time dimensions, and the weighted average maximum withdrawal rate of the position-holding fund in a plurality of time dimensions;
the third scoring unit is used for counting data of each dynamic adjustment index in the fund combination, scoring the data of each dynamic adjustment index in the same dimensionality according to a preset scoring rule to obtain a plurality of third scores, and performing weighted calculation on the third scores according to the weight of each dynamic adjustment index to obtain a dynamic adjustment score, wherein the dynamic adjustment index is one of a hit force index, a balance force index, a restoring force index, a stable force index and an activity force index;
the attribute unit is used for acquiring an visualization identifier corresponding to the fund combination type, and respectively assigning the profit attribute, the risk attribute and the dynamic adjustment attribute of the visualization identifier according to the profit score, the risk score and the dynamic adjustment score to obtain attribute values of the profit attribute, the risk attribute and the dynamic adjustment attribute;
and the display unit is used for responding to an operation instruction of a user and displaying the visualization identification corresponding to the fund combination type and the attribute value corresponding to the attribute on a display interface.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method of visually processing fund data and fund combination data according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when being executed by a processor, implements the method for visualization processing of fund data and fund combination data according to any one of claims 1 to 7.
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