CN114049044A - Combined strategy evaluation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the application provides a combination strategy evaluation method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. Acquiring operation data of the combination strategy in a set time period, respectively determining N capacity indexes of the combination strategy according to the operation data of the combination strategy, and determining the comprehensive attribute of the combination strategy according to the N capacity indexes. And comprehensively evaluating the quality of the fund combination strategy based on a plurality of capacity indexes, and evaluating the fund combination strategy from the profit alone. And different weights can be assigned to different capability indexes according to different expected types, the comprehensive attributes of a fund combination strategy are considered in multiple aspects from multiple angles, and the most accurate and optimal evaluation is given.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a method and an apparatus for evaluating a combination policy, an electronic device, and a storage medium.
Background
With the development of funds and stocks in recent years, the concept of funds and stocks has become well known, and various strategic combinations of funds and stocks in the team have become one of the important concerns for users.
In the prior art, the way to evaluate the quality of the combination strategy is through a well-known sharp ratio (sharp ratio), but the sharp ratio only focuses on the profit situation of one combination strategy, so that the situation of evaluating one combination strategy is often not accurate enough.
Therefore, how to implement a method for evaluating a combination strategy from multiple aspects is an urgent problem to be solved.
Disclosure of Invention
In order to solve the above-mentioned problems in the prior art, embodiments of the present application provide a method and an apparatus for evaluating a combination policy, an electronic device, and a storage medium, which can evaluate the merits of a multi-angle and multi-aspect detuning combination policy and accurately determine the comprehensive attributes of the combination policy.
In a first aspect, an embodiment of the present application provides a combined policy evaluation method, where the method includes:
acquiring operation data of a combination strategy in a set time period;
respectively determining N capacity indexes of the combined strategy according to the operation data of the combined strategy; wherein N is an integer greater than 1;
and determining the comprehensive attributes of the combined strategy according to the N capability indexes of the combined strategy.
In one possible embodiment, the N capability indicators include at least two of a benefit capability, a fallback control capability, a balancing capability, a timing capability, and a base selection capability.
In a possible implementation manner, the N is 5, and the determining N capability indicators of the combination policy according to the operation data of the combination policy respectively includes:
determining the benefit capability of the combination strategy according to the operation data of the combination strategy;
determining the withdrawal control capability of the combined strategy according to the operation data of the combined strategy;
determining the balance capability of the combination strategy according to the operation data of the combination strategy;
determining the time selection capability of the combination strategy according to the operation data of the combination strategy;
and determining the base selection capability of the combined strategy according to the operation data of the combined strategy.
In one possible embodiment, the operational data includes a gain; the determining the benefit capability of the combination strategy according to the operation data of the combination strategy comprises the following steps:
and determining the benefit capability of the combination strategy according to the benefit rate of the combination strategy in any unit time period and the number of the unit time periods with the benefit rates in the set time period.
In one possible embodiment, the operational data includes a rollback impact value; the determining, according to the operation data of the combination policy, a withdrawal control capability of the combination policy includes:
aiming at each unit time period contained in the set time period, respectively determining the withdrawal capability value of each unit time period according to the withdrawal influence value of each unit time period to obtain a plurality of withdrawal capability values;
and determining the withdrawal control capability of the combination strategy according to the maximum capability value in the obtained plurality of withdrawal capability values.
In one possible embodiment, the determining, for each unit time period included in the set time period, a withdrawal capability value for each unit time period based on the withdrawal influence value for each unit time period includes:
for each unit time period, respectively performing the following operations:
taking the unit time period as a current time period, and determining the maximum influence value in the candidate withdrawal influence values corresponding to the current time period; the candidate withdrawal influence values corresponding to the current time period comprise the withdrawal influence value of the current time period and the withdrawal influence value of each unit time period before the current time period;
and determining the withdrawal capability value of the current time period according to the maximum influence value and the withdrawal influence value of the current time period.
In one possible embodiment, the operational data includes a gain; determining the balancing capability of the combination strategy according to the operation data of the combination strategy comprises the following steps:
determining the fluctuation rate of the combination strategy according to the gain rate of each unit time period contained in the set time period;
and determining the balance capability of the combination strategy according to the fluctuation rate.
In one possible embodiment, the operational data includes a baseline benefit rate; the determining the time selection capability of the combination strategy according to the operation data of the combination strategy comprises the following steps:
according to the reference gain rate of each unit time period contained in the set time period, sequentially determining the time selection gains of each unit time period to obtain a time selection gain sequence;
determining the time selection benefit rate of the combination strategy according to the time selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the time selection rate of the combination strategy according to the ratio of the number of unit time periods with positive time selection benefit to the total number of the unit time periods contained in the set time period;
and determining the time selection capability of the combination strategy according to the time selection benefit rate and the time selection win rate.
In one possible embodiment, the operational data includes a baseline benefit rate; the determining the base selection capability of the combined strategy according to the operation data of the combined strategy comprises the following steps:
sequentially determining the base selection gain of each unit time period according to the reference gain rate of each unit time period contained in the set time period to obtain a base selection gain sequence;
determining the base selection benefit rate of the combination strategy according to the base selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the base selection rate of the combination strategy according to the ratio of the number of unit time periods with positive base selection benefit to the total number of the unit time periods contained in the set time period;
and determining the base selection capability of the combination strategy according to the base selection benefit rate and the base selection winning rate.
In a possible implementation manner, the determining the comprehensive attribute of the combination policy according to the N capability indicators of the combination policy includes:
and respectively determining the comprehensive attributes of the combination strategy corresponding to each expected type according to the N capability indexes of the combination strategy and the setting parameters of each expected type.
In a possible implementation manner, the determining, according to the N capability indicators of the combination policy and the setting parameters of each desired type, the comprehensive attribute of the combination policy corresponding to each desired type, respectively, includes:
for each expected type, respectively executing the following operations:
acquiring a setting parameter corresponding to the expected type; the setting parameters comprise weights corresponding to the N capacity indexes respectively;
and determining the comprehensive attribute of the combination strategy corresponding to the expected type according to the N capacity indexes and the corresponding weights.
In a second aspect, an embodiment of the present application provides a combined policy evaluation apparatus, where the apparatus includes:
the acquisition unit is used for acquiring the operation data of the combination strategy in a set time period;
the first determining unit is used for respectively determining N capacity indexes of the combined strategy according to the operation data of the combined strategy; wherein N is an integer greater than 1;
and the second determining unit is used for determining the comprehensive attribute of the combined strategy according to the N capacity indexes of the combined strategy.
In a possible implementation manner, N is 5, and the first determining unit is further configured to: determining the benefit capability of the combination strategy according to the operation data of the combination strategy;
determining the withdrawal control capability of the combined strategy according to the operation data of the combined strategy;
determining the balance capability of the combination strategy according to the operation data of the combination strategy;
determining the time selection capability of the combination strategy according to the operation data of the combination strategy;
and determining the base selection capability of the combined strategy according to the operation data of the combined strategy.
In a possible implementation, the operation data includes a benefit rate, and the first determining unit is further configured to:
and determining the benefit capability of the combination strategy according to the benefit rate of the combination strategy in any unit time period and the number of the unit time periods with the benefit rates in the set time period.
In a possible implementation, the operation data includes a retraction influence value, and the first determining unit is further configured to:
aiming at each unit time period contained in the set time period, respectively determining the withdrawal capability value of each unit time period according to the withdrawal influence value of each unit time period to obtain a plurality of withdrawal capability values;
and determining the withdrawal control capability of the combination strategy according to the maximum capability value in the obtained plurality of withdrawal capability values.
In a possible implementation, the first determining unit is further configured to:
for each unit time period, respectively performing the following operations:
taking the unit time period as a current time period, and determining the maximum influence value in the candidate withdrawal influence values corresponding to the current time period; the candidate withdrawal influence values corresponding to the current time period comprise the withdrawal influence value of the current time period and the withdrawal influence value of each unit time period before the current time period;
and determining the withdrawal capability value of the current time period according to the maximum influence value and the withdrawal influence value of the current time period.
In a possible implementation, the operation data includes a benefit rate, and the first determining unit is further configured to:
determining the fluctuation rate of the combination strategy according to the gain rate of each unit time period contained in the set time period;
and determining the balance capability of the combination strategy according to the fluctuation rate.
In a possible implementation, the operation data includes a reference gain rate, and the first determining unit is further configured to:
according to the reference gain rate of each unit time period contained in the set time period, sequentially determining the time selection gains of each unit time period to obtain a time selection gain sequence;
determining the time selection benefit rate of the combination strategy according to the time selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the time selection rate of the combination strategy according to the ratio of the number of unit time periods with positive time selection benefit to the total number of the unit time periods contained in the set time period;
and determining the time selection capability of the combination strategy according to the time selection benefit rate and the time selection win rate.
In a possible implementation, the operation data includes a reference gain rate, and the first determining unit is further configured to:
sequentially determining the base selection gain of each unit time period according to the reference gain rate of each unit time period contained in the set time period to obtain a base selection gain sequence;
determining the base selection benefit rate of the combination strategy according to the base selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the base selection rate of the combination strategy according to the ratio of the number of unit time periods with positive base selection benefit to the total number of the unit time periods contained in the set time period;
and determining the base selection capability of the combination strategy according to the base selection benefit rate and the base selection winning rate.
In a possible implementation, the second determining unit is further configured to:
and respectively determining the comprehensive attributes of the combination strategy corresponding to each expected type according to the N capability indexes of the combination strategy and the setting parameters of each expected type.
In a possible implementation, the second determining unit is further configured to:
for each expected type, respectively executing the following operations:
acquiring a setting parameter corresponding to the expected type; the setting parameters comprise weights corresponding to the N capacity indexes respectively;
and determining the comprehensive attribute of the combination strategy corresponding to the expected type according to the N capacity indexes and the corresponding weights.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory and a processor, where the memory stores a computer program that is executable on the processor, and when the computer program is executed by the processor, the steps of the combined policy evaluation method in any one of the first aspects are implemented.
In a fourth aspect, the present application provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the combined policy evaluation method in any one of the first aspects are implemented.
In a fifth aspect, the present application provides a computer program product, which includes computer-executable instructions for causing a computer to perform the steps of any one of the combined policy evaluation methods in the first aspect.
The embodiment of the application provides a combination strategy evaluation method and device, electronic equipment and a storage medium. And determining the comprehensive attributes of the combination strategy through N capability indexes, wherein the capability indexes can comprise benefit capability, withdrawal control capability, balance capability, timing capability and base selection capability. And comprehensively evaluating the quality of the fund combination strategy based on a plurality of capacity indexes, and evaluating the fund combination strategy from the profit alone. And different weights can be assigned to different capability indexes according to different expected types, the comprehensive attributes of a fund combination strategy are considered in multiple aspects from multiple angles, and the most accurate and optimal evaluation is given.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a combined policy evaluation method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a manner of determining a composite attribute according to an embodiment of the present application;
FIG. 3 is a schematic diagram of another way of determining a composite attribute according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a combined policy evaluation device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that references in the specification of the present application to the terms "comprises" and "comprising," and variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Aiming at the problem that the evaluation mode of a combination strategy of funds or stocks is single in the prior art, the embodiment of the application provides a combination strategy evaluation method, the operation data of the combination strategy in a set time period is obtained, the advantages and disadvantages of the combination strategy are judged through N capacity indexes according to the operation data of the combination strategy, the comprehensive attributes of the combination strategy are determined through the N capacity indexes, and the combination strategy can be evaluated more accurately.
Fig. 1 shows that a combination policy evaluation method provided in an embodiment of the present application is applied to an electronic device, and as shown in fig. 1, the combination policy evaluation method provided in the embodiment of the present application includes the following steps:
step S101: and acquiring the operation data of the combination strategy in a set time period.
In one possible embodiment, operational data for a combined strategy for a set period of time may be obtained for a fund or stock. The set time period may be, for example, a trade day of one year or a trade day of one month. The combination policy refers to a combination of several funds or several stocks selected by the user.
Wherein the fund or stock in the portfolio strategy can be selected from Shanghai depth 300 and Zhongliao comprehensive wealth.
Step S102: and respectively determining N capacity indexes of the combined strategy according to the operation data of the combined strategy.
Wherein N is an integer greater than 1.
In one possible embodiment, the N capability indicators include at least two of a benefit capability, a fallback control capability, a balance capability, a timing capability, and a base capability.
In one possible embodiment, the N capability indicators may include five of a benefit capability, a fallback control capability, a balancing capability, a timing capability, and a base selection capability, each determined according to the operational data of the combined policy.
For example, the benefit capability of the combination strategy may be determined according to the benefit rate of the combination strategy in any unit time period and the number of unit time periods in which the benefit rate exists in the set time period.
Taking the combination strategy as the fund as an example, first, the benefit rate of the combination strategy in any unit time period needs to be calculated. The benefit rate in any unit time period is understood as follows: daily profitability of the combined strategy. Wherein the daily profitability of the operating data in the combined strategy can be calculated according to the increase rate of each fund in the combined strategy.
First, the daily profitability of the (N +1) th combination strategy is calculated through a formula.
Σ (percentage of each fund per N-th stage × (1+ net-value growth rate per fund)) — the net value of all the funds in stage N +1 of the combinatorial strategy.
After determining the net worth of all funds at stage N +1 in the combined strategy, the daily profitability at stage N +1 of the combined strategy can be determined.
Secondly, the (N +1) th period proportion is calculated by a formula, wherein the formula is as follows:
the proportion of each fund at stage N +1 ═ h (proportion of each fund at stage N × (1+ net growth rate per fund))/(1 + daily rate of return at stage N +1 of the combinatorial strategy).
And finally, calculating the ratio of each fund in the (N +1) th period through the formula, and calculating the daily yield of the (N + 2) th combination strategy according to the ratio of each fund in the (N +1) th period. The daily yield of each fund per period combination strategy is calculated in the recursion mode.
Alternatively, the rate of return for a set period of time, which may be calculated on a trading day of the year as an example, may be calculated by calculating the daily rate of return for a combined strategy that yields funds per period.
The daily yield of the n (1+ combination strategy) is equal to the yield of the combination strategy in the set time period +1
After the daily rate of return of the combination strategy is determined through a formula, the annual rate of return R in a set time period is calculated, and the calculation formula is as follows:
n is expressed as the number of unit time periods over which the benefit rate is present for a set period of time.
The set time period may be a trade day in one year, specifically 244 days. Therefore, N is expressed as the total number of days in which the daily profitability was not 0 in the previous 244 days.
And determining an annual rate of return R based on the formula, and determining the profitability Score of the combination strategy based on the annual rate of return R. The calculation formula is as follows:
R0＝max (min(R,b),a)
in the above description, a and b are set values, and specifically, a is-20% and b is 20% as an example.
If the calculated R is 10%, the value of min (R, b) is R, and the value of max (R, a) is R, i.e. R can be obtained0Is finally taken as R, so R0＝10％。
Determining R according to the formula0After the value is taken, the Score can be determinedProfits abilityIf R has a value of0Score 10%, thenProfits abilityThe value of (A) was 75%. Note that ScoreProfits abilityThe larger the value of (A), the higher the score, and the stronger the profitability.
Illustratively, the operation data may include a withdrawal influence value, and for each unit time period included in the set time period, according to the withdrawal influence value of each unit time period, the withdrawal capability values of each unit time period are respectively determined to obtain a plurality of withdrawal capability values, and according to a maximum capability value of the obtained plurality of withdrawal capability values, the withdrawal control capability of the combination policy is determined.
The withdrawal impact value may be the net value of the combination strategy as an example, buying the fund is the warehouse building, the net value of the first day of the warehouse building is 1, and the net value estimation is generally displayed on the (T +1) day. And calculating the net value of the combined strategy T day according to the yield of the combined strategy T day and the net value of the combined strategy (T-1) day.
The net value of the T days of binning can be calculated as follows:
combination strategy T-day net worth (T-1) day net worth multiplied by combination strategy T-day yield
And determining the net value of each day of the combined strategy after the bin is built by a formula for calculating the net value. The retraction impact value for each unit time period can be understood as the net value per day of the combined strategy.
And determining the withdrawal capacity value of the combined strategy on the T day according to the net value of the combined strategy on the T day.
The formula for the withdrawal capability value on day T is as follows:
when the net value of T day is calculated, the T day is the current time period, and the maximum influence value in the candidate withdrawal influence values corresponding to the current time period may be understood as the maximum value from the first day of the warehouse building to the net value of T day. The withdrawal capacity value of the T day can be determined through the formula.
After the withdrawal capacity value of the T day is calculated according to the formula, the withdrawal capacity value of the combination strategy in each day in a set time period can be calculated in the same mode, the maximum capacity value of the plurality of the withdrawal capacity values is obtained, and the maximum withdrawal capacity value can be defined as DmaxAnd determining the withdrawal control capability of the combination strategy according to the maximum withdrawal capability value.
The calculation formula of the withdrawal control capability is as follows:
D0＝max(min(Dmax,b),a)
wherein D ismaxThe maximum withdrawal capability value is represented, and a and b are set values, and specifically, a is 5% and b is 25% as an example.
If with DmaxIf 20% is taken as an example, D020% by weight. Calculated ScoreRetraction control capabilityThe content was 25%. Note that ScoreRetraction control capabilityThe larger the value of (b), the stronger the pullback control capability is.
Illustratively, the balancing capability may be determined by: and determining the fluctuation rate of the combination strategy according to the gain rate of each unit time period contained in the set time period, and determining the balance capability of the combination strategy according to the fluctuation rate. The balance capability can be expressed as a profit risk ratio in a set time period, and specifically expressed as the capability of a combination strategy for balancing risk and profit.
And calculating the standard deviation of the daily rate of return after the daily rate of return in the set time period is obtained according to calculation, and determining the fluctuation rate. The calculation formula of the fluctuation ratio is as follows:
wherein std represents the standard deviation of the daily profitability of the combination strategy in the set time period, and the set time period is the trading day of the fund in one year as an example.
The sharp rate is determined from the fluctuation rate, and assuming that the risk-free annual interest rate is 3%, the risk-free interest rate here indicates the annual benefit rate of buying funds without loss risk.
The formula for calculating the sharp ratio is:
r is expressed as the annual profitability of the combined strategy and SR is expressed as the sharp rate.
After the sharp ratio is determined, the balance ability can be obtained according to the sharp ratio.
The formula for the balance ability is:
SR0＝max(min(SR,b),a)
in the above description, a and b are set values, and specifically, a ═ 1 and b ═ 2 may be taken as examples.
According to the above formula, if SR is 1, SR01. Then Score is determinedBalance ability66.7%. Note that ScoreBalance abilityThe higher the value, the stronger the ability to balance risk with revenue.
For example, the timing capability may be determined by: and sequentially determining the time selection benefit of each unit time period according to the reference benefit rate of each unit time period contained in the set time period to obtain a time selection benefit sequence. Determining the time selection benefit rate of the combination strategy according to the time selection benefit sequence and the number of unit time periods with the benefit rate in the set time period; determining the time selection rate of the combination strategy according to the ratio of the number of unit time periods with positive time selection benefit to the total number of the unit time periods contained in the set time period; and determining the time selection capability of the combination strategy according to the time selection benefit rate and the time selection win rate. The time selection capability represents the profit size of different time periods or different time points selected by the combination strategy and the time selection rate of the combination strategy.
The benchmark benefit rate is determined according to the combination strategy selected by the user, and the benchmark benefit rate is a fixed value after the user selects the combination strategy.
After the reference rate of return is determined, the reference rate of return is adjusted according to the selection of the user, the specific adjustment mode is determined according to the last day of the Shanghai depth 300 and the holding proportion of the Shanghai comprehensive wealth, and if the last day of the Shanghai depth 300 is 80% and the holding proportion of the Shanghai depth 300 is 20%, the calculation formula of the adjusted reference rate of return is as follows:
after the adjusted reference yield is determined as 20% x 300 yield + 80% x medium-debt comprehensive wealth yield, the calculation formula of the time-selective gain sequence is as follows:
Rtimingadjusted baseline profitability-baseline profitability
RtimingDenoted as a time-selective gain sequence.
And after the time selection benefit sequence is determined, determining the time selection benefit rate of the combination strategy according to the time selection benefit sequence and the number of unit time periods with the benefit rate in the set time period. The number of the unit time periods in which the benefit rate exists in the set time period can be understood as the total number of days in which the benefit rate is not 0 in the set time period.
The calculation formula of the time selection benefit rate is as follows:
Rt0＝max(min(Rt,b),a)
wherein N represents the total number of days in which the yield is not 0 within the set time period. a and b are set values, and specifically, a is-10%, and b is 10% as an example.
Firstly determining annual excess income R by the formulatExcess income R according to the agingtAnd determining the time selection benefit rate. If R istIs 5%, then Rt0And 5%, the time selection gain rate is 75%.
Since the time selection capability is determined by the time selection benefit rate and the time selection win rate, the time selection win rate needs to be calculated, and the calculation formula of the time selection win rate is as follows:
wherein, count (R)timing>0) Represents the total number of days, count (R), that the timing benefit is positivetiming) Representing the total number of days to benefit from timing.
After determining the time selection rate and the time selection benefit rate, the time selection capability is calculated according to the following formula:
the specific weight coefficient may be freely set, and may be, for example, 50%. The larger the time selection ability score is, the stronger the time selection ability is.
For example, the determination of the base selection capability may be: sequentially determining the base selection gain of each unit time period according to the reference gain of each unit time period contained in the set time period to obtain a base selection gain sequence, and determining the base selection gain of the combination strategy according to the base selection gain sequence and the number of the unit time periods with the gain in the set time period; determining the base selection rate of the combination strategy according to the ratio of the number of unit time periods with positive base selection benefit to the total number of the unit time periods contained in the set time period; and determining the base selection capability of the combination strategy according to the base selection benefit rate and the base selection win rate.
The number of the unit time periods in which the benefit rate exists in the set time period can be understood as the total number of days in which the benefit rate is not 0 in the set time period.
First, a base selection gain sequence is determined according to the base gain rate and the adjusted base gain rate.
The formula for determining the gain sequence of the basis selection is as follows:
Rfundreference yield-adjusted reference yield
Determining annual excess profit R according to base-selecting benefit sequenceαAnnual excess income RαThe calculation formula of (a) is as follows:
n is expressed as the total number of days in which the profitability is not 0 within the set period of time.
Determine the annual excess income RαThereafter, the earnings R can be increased according to the annual excessαDetermining the gain rate of the basis selection, wherein the calculation formula of the gain rate of the basis selection is as follows:
Rα0＝max(min(Rα,b),a)
in the above description, a and b are set values, and specifically, a is-10% and b is 10% as an example.
If R isαIs 5%, then Rα0At 5%, can be calculated
The content was found to be 75%.
Since the base selection capability is determined by the base selection gain rate and the base selection winning rate, the base selection winning rate needs to be calculated, and the calculation formula of the base selection winning rate is as follows:
wherein, count (R)fund>0) The number of time periods over which the contribution gain is positive is expressed, which can be understood as the total number of days over which the contribution gain is positive, count (R)fund) Can be expressed as the total number of days of the benefit of the selection basis.
After the base selection rate is determined, the base selection capacity can be determined according to the base selection gain rate and the base selection rate, and the calculation formula of the base selection capacity is as follows:
the specific weight coefficient may be freely set, and may be, for example, 50%. The greater the base selection ability score, the stronger the base selection ability.
Specific 5 of the N capability indexes may be determined in the above manner, and after the N capability indexes are determined, step S103 may be performed.
Step S103: and determining the comprehensive attributes of the combination strategy according to the N capability indexes of the combination strategy.
In a possible embodiment, the comprehensive attributes of the combination strategy corresponding to each expected type are respectively determined according to the N capability indexes of the combination strategy and the setting parameters of each expected type.
The desired types may include, among others, robust, balanced, and growing types.
Each expected type refers to a type selected by the user, after the combination strategy is selected, the user can select the expected type by himself, and according to different expected types, the user can distribute the total amount held in the user's hand in different proportions.
Illustratively, the Hu depth 300 and the Zhongbing comprehensive wealth are taken as examples, since the Hu depth 300 represents benefit-type funds or stocks, and the Zhongbing comprehensive wealth represents stable funds or stocks, the two are taken as examples.
In the case of allocating the amount held in the distributor, if the robust type is selected, the amount of money can be allocated to the Shanghai depth 300 in an amount of 20% and the amount of money can be allocated to the Zhongdebt comprehensive wealth in an amount of 80%.
If the balance type is selected, 50% of money can be allocated to the Shanghai depth 300, and 50% of money can be allocated to the Zhongliao comprehensive wealth.
If the growth type is selected, 80% of the amount can be allocated to the Shanghai depth of 300, and 20% of the amount can be allocated to the Zhongliao comprehensive wealth.
Optionally, according to different expected types, setting parameters corresponding to the expected types are obtained, and then according to the N capability indexes and corresponding weights, the comprehensive attribute of the combination strategy corresponding to the expected types is determined. Wherein each capability index can be given different weight according to actual conditions.
Illustratively, if a robust type is selected, 20%, 30%, 10% are weighted in the order of the profit-ability, the fallback control ability, the balancing ability, the timing ability, and the base-selection ability, respectively. The main bases for the robust type of allocation are: the risk bearing capacity is low, the configuration is dominant, and the excess income is not too large when the selection is less; emphasis is placed on withdrawal control capability and balancing capability.
If the balance type is selected, 30%, 20%, 15% of the weight is given in the order of profit-ability, withdrawal-control-ability, balance-ability, timing-ability, and selection-base-ability. And when the balance type is adopted, all aspects are balanced, the five aspects are comprehensively considered, and the risk level is moderate.
If a growth type is selected, the profit-making ability, the withdrawal control ability, the balance ability, the timing ability, and the base ability are weighted in the order of 40%, 10%, 20%, and 20%, respectively. The growth type mainly focuses on the profit capacity, allows relatively high fluctuation and withdrawal, and focuses on the profit capacity, the timing capacity and the base selection capacity.
The data transmission and calculation flow is shown in fig. 2, and the comprehensive attributes of the combination policy can be obtained.
Alternatively, the comprehensive attribute may be determined in other manners, for example, the N indexes are comprehensively evaluated according to a linear model, and the comprehensive attribute is calculated.
The way to calculate the synthetic properties using the linear model is:
n represents the user purchasing an asset of funds or stocks in the portfolio strategy; t represents time; k represents each different capability index; n is expressed as N capability indexes; r isn(t) represents the total evaluation index of the asset from time t to time t + 1; xn,k(t) represents the exposure of the asset n to the energy index k at time t. bk(t) is expressed as the standard influence of the capability index from time t to time t + 1; u. ofn(t) is a specific influence of the asset n from time t to time t +1, and the specific influence represents the combination strategyThe influence of other factors that have a slight influence.
Specifically, if the profitability index is calculated, the exposure of the asset n to all other capacity indexes is 0, and the exposure of the asset n to the profitability index is 1. The specific influence is not related to the standard influence, and the specific earnings of different stocks are not related to each other.
And calculating the linear value of each capability index in the linear model through the formula, and finally accumulating the linear values of each capability index to obtain a comprehensive evaluation value, namely the comprehensive attribute.
The flow of data transmission and calculation to determine the composite property by the linear model is shown in fig. 3.
Optionally, after the combination policy is evaluated by using the comprehensive attribute, if the user does not allocate the total assets according to the given set allocation proportion in the using process, the score of the comprehensive attribute may be deducted according to a set rule, or the comprehensive attribute may be reduced.
It can be understood that: when the position of the user for asset allocation is greatly different from the set reference equity position, the comprehensive attribute is inaccurate due to the large difference between the risk level and the target, so that the comprehensive attribute obtained by calculation needs to be punished, namely, deducted.
For example, if the desired type selected by the user is balance, the user should make 50% proportions of each asset allocation for the Shanghai depth 300 and the mid-debt portfolio, respectively. However, the user can deduct the assets allocated according to the total amount of the debt in 300% of the Shanghai depth and 80% of the Zhongbao when allocating the assets according to the set rules.
According to different specific proportions, specific deduction can be carried out according to the following table:
| difference in distribution ratio | Comprehensive scoring deduction |
| Less than-50% | L2 |
| [-50％,-30％) | L1 |
| [-30％,20％] | 0 |
| (20％,30％) | L1 |
| [30％,40％) | L2 |
| More than 40 percent | L3 |
The combined strategy evaluation method determines the comprehensive attribute of the combined strategy through a plurality of capacity indexes, the comprehensive attribute can accurately express the capacity of each aspect of the combined strategy to a certain extent, a user can also call the score of each capacity index in the comprehensive attribute, the advantages and the disadvantages of the combined strategy are checked through checking the scores of the N capacity indexes, and the user can also complete the combined strategy through the mode.
The embodiment of the application also provides a combined strategy evaluation device. Fig. 4 is a schematic structural diagram of a combined policy evaluation device according to an embodiment of the present application; as shown in fig. 4, the combination policy evaluation device includes:
an obtaining unit 401, configured to obtain operation data of a combination policy in a set time period;
a first determining unit 402, configured to determine N capability indicators of the combination policy according to the operation data of the combination policy, respectively; wherein N is an integer greater than 1;
a second determining unit 403, configured to determine a comprehensive attribute of the combination policy according to the N capability indicators of the combination policy.
In a possible implementation, N is 5, and the first determining unit 402 is further configured to:
determining the benefit capability of the combination strategy according to the operation data of the combination strategy;
determining the withdrawal control capability of the combined strategy according to the operation data of the combined strategy;
determining the balance capability of the combination strategy according to the operation data of the combination strategy;
determining the time selection capability of the combination strategy according to the operation data of the combination strategy;
and determining the base selection capability of the combination strategy according to the operation data of the combination strategy.
In a possible implementation, the operation data includes a benefit rate, and the first determining unit 402 is further configured to:
and determining the benefit capability of the combination strategy according to the benefit rate of the combination strategy in any unit time period and the number of the unit time periods with the benefit rate in the set time period.
In a possible implementation, the operation data includes a retraction influence value, and the first determining unit 402 is further configured to:
aiming at each unit time period contained in a set time period, respectively determining the withdrawal capability value of each unit time period according to the withdrawal influence value of each unit time period to obtain a plurality of withdrawal capability values;
and determining the withdrawal control capability of the combination strategy according to the maximum capability value in the obtained plurality of withdrawal capability values.
In a possible implementation, the first determining unit 402 is further configured to:
for each unit time period, the following operations are respectively performed:
taking the unit time period as the current time period, and determining the maximum influence value in the candidate withdrawal influence values corresponding to the current time period; the candidate withdrawal influence values corresponding to the current time period comprise the withdrawal influence value of the current time period and the withdrawal influence value of each unit time period before the current time period;
and determining the withdrawal capability value of the current time period according to the maximum influence value and the withdrawal influence value of the current time period.
In a possible implementation, the operation data includes a benefit rate, and the first determining unit 402 is further configured to:
determining the fluctuation rate of the combination strategy according to the gain rate of each unit time period contained in the set time period;
and determining the balance capability of the combination strategy according to the fluctuation rate.
In a possible implementation, the operation data includes a reference gain, and the first determining unit 402 is further configured to:
sequentially determining the time selection benefit of each unit time period according to the reference benefit rate of each unit time period contained in the set time period to obtain a time selection benefit sequence;
determining the time selection benefit rate of the combination strategy according to the time selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the time selection rate of the combination strategy according to the ratio of the number of unit time periods with positive time selection benefit to the total number of the unit time periods contained in the set time period;
and determining the time selection capability of the combination strategy according to the time selection benefit rate and the time selection win rate.
In a possible implementation, the operation data includes a reference gain, and the first determining unit 402 is further configured to:
sequentially determining the base selection gain of each unit time period according to the reference gain rate of each unit time period contained in the set time period to obtain a base selection gain sequence;
determining the base selection benefit rate of the combination strategy according to the base selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the base selection rate of the combination strategy according to the ratio of the number of unit time periods with positive base selection benefit to the total number of the unit time periods contained in the set time period;
and determining the base selection capability of the combination strategy according to the base selection benefit rate and the base selection win rate.
In a possible embodiment, the second determination unit 403 is further configured to:
and respectively determining the comprehensive attributes of the combination strategy corresponding to each expected type according to the N capability indexes of the combination strategy and the setting parameters of each expected type.
In a possible implementation, the second determining unit 403 is further configured to:
for each desired type, the following operations are performed:
acquiring a setting parameter corresponding to the expected type; the setting parameters comprise weights corresponding to the N capacity indexes respectively;
and determining the comprehensive attribute of the combination strategy corresponding to the expected type according to the N capacity indexes and the corresponding weights.
The embodiment of the present application further provides an electronic device, where the electronic device at least includes a memory and a processor for storing data, and for the processor for data Processing, when performing Processing, the processor may be implemented by using a microprocessor, a CPU, a GPU (Graphics Processing Unit), a DSP, or an FPGA. For the memory, the memory stores therein operation instructions, which may be computer executable codes, and the operation instructions implement the steps in the flow of the combined policy evaluation method according to the embodiment of the present application.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 5, the electronic device 500 includes a memory 501, a processor 502, a data acquisition module 503, and a bus 504. The memory 501, the processor 502 and the data acquisition module 503 are all connected by a bus 504, and the bus 504 is used for data transmission among the memory 501, the processor 502 and the data acquisition module 503.
The memory 501 may be used to store software programs and modules, and the processor 502 executes various functional applications and data processing of the electronic device 500 by running the software programs and modules stored in the memory 501, such as the combined policy evaluation method provided in the embodiments of the present application. The memory 501 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program of at least one application, and the like; the storage data area may store data created according to the use of the electronic device 500, and the like. Further, the memory 501 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 502 is a control center of the electronic device 500, connects various parts of the entire electronic device 500 using the bus 504 and various interfaces and lines, and performs various functions of the electronic device 500 and processes data by running or executing software programs and/or modules stored in the memory 501 and calling data stored in the memory 501. Alternatively, the processor 502 may include one or more Processing units, such as a CPU, a GPU (Graphics Processing Unit), a digital Processing Unit, and the like.
The embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored, and when executed by a processor, the computer program may be used to implement the combination policy evaluation method described in any embodiment of the present application.
The present application further provides a computer program product, and various aspects of the combination policy evaluation method provided in the present application may also be implemented in the form of a program product, which includes program code for causing a computer device to execute the steps of the combination policy evaluation method according to the various exemplary embodiments of the present application described above in this specification when the program product runs on the computer device, for example, the computer device may execute the flow of the combination policy evaluation method of steps S101 to S103 shown in fig. 1.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (16)
1. A combined policy evaluation method, comprising:
acquiring operation data of a combination strategy in a set time period;
respectively determining N capacity indexes of the combined strategy according to the operation data of the combined strategy; wherein N is an integer greater than 1;
and determining the comprehensive attributes of the combined strategy according to the N capability indexes of the combined strategy.
2. The method of claim 1, wherein the N capability indicators comprise at least two of a benefit capability, a fallback control capability, a balance capability, a timing capability, and a base selection capability.
3. The method according to claim 1 or 2, wherein N is 5, and the determining N capability indicators of the combined strategy according to the operation data of the combined strategy respectively comprises:
determining the benefit capability of the combination strategy according to the operation data of the combination strategy;
determining the withdrawal control capability of the combined strategy according to the operation data of the combined strategy;
determining the balance capability of the combination strategy according to the operation data of the combination strategy;
determining the time selection capability of the combination strategy according to the operation data of the combination strategy;
and determining the base selection capability of the combined strategy according to the operation data of the combined strategy.
4. The method of claim 3, wherein the operational data comprises a gain; the determining the benefit capability of the combination strategy according to the operation data of the combination strategy comprises the following steps:
and determining the benefit capability of the combination strategy according to the benefit rate of the combination strategy in any unit time period and the number of the unit time periods with the benefit rates in the set time period.
5. The method of claim 3, wherein the operational data comprises a rollback impact value; the determining, according to the operation data of the combination policy, a withdrawal control capability of the combination policy includes:
aiming at each unit time period contained in the set time period, respectively determining the withdrawal capability value of each unit time period according to the withdrawal influence value of each unit time period to obtain a plurality of withdrawal capability values;
and determining the withdrawal control capability of the combination strategy according to the maximum capability value in the obtained plurality of withdrawal capability values.
6. The method according to claim 5, wherein the determining, for each unit time period included in the set time period, the withdrawal capability value for each unit time period based on the withdrawal influence value for each unit time period comprises:
for each unit time period, respectively performing the following operations:
taking the unit time period as a current time period, and determining the maximum influence value in the candidate withdrawal influence values corresponding to the current time period; the candidate withdrawal influence values corresponding to the current time period comprise the withdrawal influence value of the current time period and the withdrawal influence value of each unit time period before the current time period;
and determining the withdrawal capability value of the current time period according to the maximum influence value and the withdrawal influence value of the current time period.
7. The method of claim 3, wherein the operational data comprises a gain; determining the balancing capability of the combination strategy according to the operation data of the combination strategy comprises the following steps:
determining the fluctuation rate of the combination strategy according to the gain rate of each unit time period contained in the set time period;
and determining the balance capability of the combination strategy according to the fluctuation rate.
8. The method of claim 3, wherein the operational data comprises a baseline benefit rate; the determining the time selection capability of the combination strategy according to the operation data of the combination strategy comprises the following steps:
according to the reference gain rate of each unit time period contained in the set time period, sequentially determining the time selection gains of each unit time period to obtain a time selection gain sequence;
determining the time selection benefit rate of the combination strategy according to the time selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the time selection rate of the combination strategy according to the ratio of the number of unit time periods with positive time selection benefit to the total number of the unit time periods contained in the set time period;
and determining the time selection capability of the combination strategy according to the time selection benefit rate and the time selection win rate.
9. The method of claim 3, wherein the operational data comprises a baseline benefit rate; the determining the base selection capability of the combined strategy according to the operation data of the combined strategy comprises the following steps:
sequentially determining the base selection gain of each unit time period according to the reference gain rate of each unit time period contained in the set time period to obtain a base selection gain sequence;
determining the base selection benefit rate of the combination strategy according to the base selection benefit sequence and the number of unit time periods with the benefit rate in the set time period;
determining the base selection rate of the combination strategy according to the ratio of the number of unit time periods with positive base selection benefit to the total number of the unit time periods contained in the set time period;
and determining the base selection capability of the combination strategy according to the base selection benefit rate and the base selection winning rate.
10. The method according to any one of claims 1 to 9, wherein the determining the comprehensive attributes of the combination policy according to the N capability indicators of the combination policy comprises:
and respectively determining the comprehensive attributes of the combination strategy corresponding to each expected type according to the N capability indexes of the combination strategy and the setting parameters of each expected type.
11. The method according to claim 10, wherein the determining, according to the N capability indicators of the combination policy and the setting parameters of each desired type, the comprehensive attribute of the combination policy corresponding to each desired type respectively comprises:
for each expected type, respectively executing the following operations:
acquiring a setting parameter corresponding to the expected type; the setting parameters comprise weights corresponding to the N capacity indexes respectively;
and determining the comprehensive attribute of the combination strategy corresponding to the expected type according to the N capacity indexes and the corresponding weights.
12. A combination policy evaluation apparatus, characterized in that the apparatus comprises:
the acquisition unit is used for acquiring the operation data of the combination strategy in a set time period;
the first determining unit is used for respectively determining N capacity indexes of the combined strategy according to the operation data of the combined strategy; wherein N is an integer greater than 1;
and the second determining unit is used for determining the comprehensive attribute of the combined strategy according to the N capacity indexes of the combined strategy.
13. The apparatus of claim 12, wherein the second determining unit is further configured to:
and respectively determining the comprehensive attributes of the combination strategy corresponding to each expected type according to the N capability indexes of the combination strategy and the setting parameters of each expected type.
14. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program operable on the processor, the computer program, when executed by the processor, implementing the method of any of claims 1-11.
15. A computer-readable storage medium having a computer program stored therein, the computer program characterized by: the computer program, when executed by a processor, implements the method of any of claims 1-11.
16. A computer program product comprising computer executable instructions for causing a computer to perform the method of any one of claims 1 to 11.
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