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CN113592307B - Enterprise profit wind control detection method, device, computer equipment and storage medium - Google Patents

Enterprise profit wind control detection method, device, computer equipment and storage medium Download PDF

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CN113592307B
CN113592307B CN202110879699.3A CN202110879699A CN113592307B CN 113592307 B CN113592307 B CN 113592307B CN 202110879699 A CN202110879699 A CN 202110879699A CN 113592307 B CN113592307 B CN 113592307B
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present value
value
net present
discount rate
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CN113592307A (en
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林才顺
林才国
朱荣超
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Foresight Zhicheng Market Research Consulting Guangdong Co ltd
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Abstract

The application provides an enterprise profit wind control detection method, an enterprise profit wind control detection device, computer equipment and a storage medium. The method includes obtaining a first net present value and a second net present value; performing differential processing on the first net present value and the second net present value to obtain differential values; detecting whether the difference value is matched with a preset difference value; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate. After the first net present value and the second net present value are subjected to different absolute processing, the magnitude relation between the first net present value and the second net present value is obtained, then the different value is matched with the preset different value, after the first net present value and the second net present value are matched, the condition that the net present value is 0 between the first net present value and the second net present value is indicated, the corresponding discount rate in the condition is convenient to know, the wind control safety level of an economic risk level signal is convenient to adjust according to the discount rate, and the wind control detection accuracy is improved.

Description

Enterprise profit wind control detection method, device, computer equipment and storage medium
Technical Field
The invention relates to the technical field of wind control evaluation, in particular to an enterprise income wind control detection method, device, computer equipment and storage medium.
Background
With the growth and development of various enterprises, the fund flow control of the enterprises is an important premise for the healthy development of the enterprises, so that various software for managing the economic risk of the enterprises is derived, and the risk assessment of the enterprise economy is facilitated.
However, in the conventional enterprise economic risk management and control method, historical risk judgment is performed on the fund balance, and when the market is subjected to monetary devaluation or currency expansion, future risks of enterprise economy cannot be evaluated, so that the detection accuracy of enterprise economic wind control is reduced.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an enterprise profit wind control detection method, device, computer equipment and storage medium for improving the accuracy of wind control detection.
The aim of the invention is realized by the following technical scheme:
an enterprise revenue wind control detection method, the method comprising:
acquiring a first net present value and a second net present value;
performing differential processing on the first net present value and the second net present value to obtain differential values;
Detecting whether the difference value is matched with a preset difference value or not;
when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate.
In one embodiment, the obtaining the first net present value and the second net present value includes: sequentially acquiring a first-year current value coefficient and a second-year current value coefficient; and respectively carrying out discount processing on the first annual gold present value coefficient and the second annual gold present value coefficient to obtain the first net present value and the second net present value.
In one embodiment, the sequentially acquiring the first yearly gold current value coefficient and the second yearly gold current value coefficient further includes: detecting whether the first yen present value coefficient is equal to the second yen present value coefficient; and re-acquiring the gold present value coefficient when the first gold present value coefficient is equal to the second gold present value coefficient.
In one embodiment, the discount processing is performed on the first yen present value coefficient and the second yen present value coefficient to obtain the first net present value and the second net present value, respectively, including: according to the first annual gold present value coefficient and the second annual gold present value coefficient, respectively obtaining a first discount rate and a second discount rate; and performing net present processing on the first discount rate and the second discount rate to obtain the first net present value and the second net present value.
In one embodiment, the detecting whether the difference value matches a preset difference value includes: detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate, wherein the method comprises the following steps: when the difference value is matched with the preset difference value, respectively acquiring the discount rate corresponding to the first net present value and the second net present value; acquiring a risk assessment discount rate according to the discount rate corresponding to the first net present value and the second net present value; and controlling the risk management and control level corresponding to the economic risk level signal according to the risk assessment discount rate.
In one embodiment, the detecting whether the difference value matches a preset difference value further includes: and when the difference value is not matched with the preset difference value, the first net present value and the second net present value are acquired again.
In one embodiment, the controlling the risk management level corresponding to the economic risk level signal according to the risk assessment discount rate includes: detecting whether the risk assessment discount rate is greater than or equal to a preset discount rate; and when the risk assessment discount rate is greater than or equal to the preset discount rate, increasing the risk management and control level of the economic risk level signal.
An enterprise revenue wind control detection apparatus, the apparatus comprising:
the sampling module is used for acquiring a first net present value and a second net present value;
the processing module is used for performing differential processing on the first net present value and the second net present value to obtain a differential value;
the wind control detection module is used for detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
acquiring a first net present value and a second net present value;
performing differential processing on the first net present value and the second net present value to obtain differential values;
detecting whether the difference value is matched with a preset difference value or not;
when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring a first net present value and a second net present value;
performing differential processing on the first net present value and the second net present value to obtain differential values;
detecting whether the difference value is matched with a preset difference value or not;
when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate.
Compared with the prior art, the invention has at least the following advantages:
after the first net present value and the second net present value are subjected to different absolute processing, the magnitude relation between the first net present value and the second net present value is obtained, then the different value is matched with the preset different value, after the first net present value and the second net present value are matched, the condition that the net present value is 0 between the first net present value and the second net present value is indicated, the corresponding discount rate in the condition is convenient to know, the wind control safety level of an economic risk level signal is convenient to adjust according to the discount rate, and the wind control detection accuracy is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an enterprise revenue wind control detection method according to one embodiment;
FIG. 2 is an internal block diagram of a computer device in one embodiment.
Detailed Description
In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. The drawings illustrate preferred embodiments of the invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only and are not meant to be the only embodiment.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The invention relates to an enterprise profit wind control detection method. In one embodiment, the enterprise revenue wind control detection method includes obtaining a first net present value and a second net present value; performing differential processing on the first net present value and the second net present value to obtain differential values; detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate. After the first net present value and the second net present value are subjected to different absolute processing, the magnitude relation between the first net present value and the second net present value is obtained, then the different value is matched with the preset different value, after the first net present value and the second net present value are matched, the condition that the net present value is 0 between the first net present value and the second net present value is indicated, the corresponding discount rate in the condition is convenient to know, the wind control safety level of an economic risk level signal is convenient to adjust according to the discount rate, and the wind control detection accuracy is improved.
Referring to fig. 1, a flowchart of an enterprise revenue wind control detection method according to an embodiment of the invention is shown. The enterprise profit wind control detection method comprises part or all of the following steps.
S100: a first net present value and a second net present value are obtained.
In this embodiment, the first net present value and the second net present value are the differences of the present values in the future funds flow in the economic wind control of the enterprise, the first net present value is used as the first difference between the future funds inflow present value and the future funds outflow present value, the second net present value is used as the second difference between the future funds inflow present value and the future funds outflow present value, and the first net present value and the second net present value are used as the present value differences in two years, can be used as the evaluation reference for the future funds flow of the enterprise, and is convenient for the subsequent knowledge of the profit situation of the future funds flow.
S200: and performing differential processing on the first net present value and the second net present value to obtain a differential value.
In this embodiment, the first net present value is used as a first difference between the future funds inflow present value and the future funds outflow present value, the second net present value is used as a second difference between the future funds inflow present value and the future funds outflow present value, and the first net present value and the second net present value are subjected to differential processing, namely, the difference of the present values in two yearly gold periods is subjected to differential processing, so as to conveniently determine the degree of difference between the first net present value and the second net present value, thereby conveniently determining whether a condition of balance of the net present values exists or not, and further conveniently subsequently determining the economic and wind control security level of an enterprise.
S300: and detecting whether the difference value is matched with a preset difference value.
In this embodiment, the preset differential value is a differential value corresponding to the case that the economic wind control level of the enterprise is safe, and the matching detection is performed on the differential value, which is to perform standard evaluation on the current first net present value and the second net present value, so as to determine whether the current net present value is in a balanced state, that is, whether the current differential value is the situation that the total sum of the detected funds flowing into the present value is equal to the total sum of the funds flowing out of the present value, that is, whether the differential value is a state value corresponding to the case that the net present value is equal to zero is detected, so that the subsequent determination of the safety level in the economic wind control evaluation of the enterprise is facilitated.
S400: when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate.
In this embodiment, the difference value matches the preset difference value, which indicates that the difference value is equivalent to the preset difference value, that is, indicates that the difference value falls within the range of the preset difference value, that is, indicates that there is a net present value with a zero discount rate between the first net present value and the second net present value corresponding to the difference value. At this time, according to the obtained discount rate, the economic risk level of the enterprise is conveniently and accurately judged, so that the accuracy of wind control detection is improved, and the future risk resistance of the enterprise can be timely known, namely whether the economic impact caused by future monetary detraction or currency expansion can be dealt with, and the early warning function of the economic impact in the future economic development process is achieved.
In the above embodiment, after the first net present value and the second net present value are subjected to the different-absolute processing, the magnitude relation between the first net present value and the second net present value is obtained, then the different-difference value is matched with the preset different-difference value, after the first net present value and the second net present value are matched, the condition that the net present value is 0 between the first net present value and the second net present value is indicated, the corresponding discount rate in the condition is convenient to know, and therefore the wind control safety level of the economic risk level signal is convenient to adjust according to the discount rate, and the accuracy of wind control detection is improved.
In one embodiment, the obtaining the first net present value and the second net present value includes: sequentially acquiring a first-year current value coefficient and a second-year current value coefficient; and respectively carrying out discount processing on the first annual gold present value coefficient and the second annual gold present value coefficient to obtain the first net present value and the second net present value. In this embodiment, the first net present value is a first difference between the future funds inflow present value and the future funds outflow present value, and the second net present value is a second difference between the future funds inflow present value and the future funds outflow present value. In the process of collecting the net present value, the first net present value and the second net present value are collected sequentially according to time sequence, that is, the generation time corresponding to the first net present value and the generation time corresponding to the second net present value have time difference. And acquiring two gold-year current value coefficients with chronological gold periods, namely the first gold-year current value coefficient and the second gold-year current value coefficient, wherein the first gold-year current value coefficient corresponds to the first net current value, and the second gold-year current value coefficient corresponds to the second net current value. Thus, after the annual gold present value coefficients in two annual gold periods are acquired, the corresponding net present value is conveniently acquired. In this embodiment, the present annual gold value coefficients are stored in the database, and each present annual gold value coefficient is stored therein, so that the present annual gold value coefficient is convenient to retrieve and use, that is, the present annual gold value coefficient is convenient to calculate the corresponding net present value.
Further, the sequentially obtaining the first year current value coefficient and the second year current value coefficient further includes: detecting whether the first yen present value coefficient is equal to the second yen present value coefficient; and re-acquiring the gold present value coefficient when the first gold present value coefficient is equal to the second gold present value coefficient. In this embodiment, the first yen present value coefficient is used as a reference base of a first net present value, and the second yen present value coefficient is used as a reference base of a second net present value, that is, one of the subparameters in the first yen present value coefficient is used to calculate the first net present value, and one of the subparameters in the second yen present value coefficient is used to calculate the second net present value. In order to find accurate net present value, the difference degree of the first and second annual gold present value coefficients is judged, so that the annual gold present value coefficient corresponding to the found net present value is conveniently determined to be positioned between the first and second annual gold present value coefficients, the collected first and second net present values are conveniently ensured to be different, and the annual gold present value coefficient corresponding to zero net present value is conveniently estimated. In this way, the first yen present value coefficient is equal to the second yen present value coefficient, which indicates that the first net present value and the second net present value remain the same, and the state that the net present value is zero cannot be accurately determined, and at this time, the yen present value coefficient and the corresponding net present value need to be collected again.
Still further, the discount processing is performed on the first yen present value coefficient and the second yen present value coefficient to obtain the first net present value and the second net present value, including: according to the first annual gold present value coefficient and the second annual gold present value coefficient, respectively obtaining a first discount rate and a second discount rate; and performing net present processing on the first discount rate and the second discount rate to obtain the first net present value and the second net present value. In this embodiment, the annual gold present value coefficient includes a discount rate and an annual year, and after the first annual gold present value coefficient and the second annual gold present value coefficient are obtained, the discount rate, that is, the first discount rate and the second discount rate, is collected. The discount rate is used as a correlation parameter between the annuity present value coefficient and the net present value, and the annuity present value coefficient is acquired from the database. The first discount rate and the second discount rate are conveniently determined through data analysis of the first annual gold present value coefficient and the second annual gold present value coefficient, so that the first net present value and the second net present value are conveniently determined. In this way, after the first discount rate is subjected to the net present processing, the first net present value is calculated according to the first discount rate in the first annual gold present value coefficient, and after the first discount rate is subjected to the net present processing, the first net present value is calculated according to the first discount rate in the first annual gold present value coefficient, so that the accurate net present value is conveniently obtained.
It will be appreciated that, in acquiring the corresponding net present value by acquiring the annuity present value coefficient in the annuity present value coefficient table, the manner of acquiring the net present value is selected randomly, and although the first net present value and the second net present value are subjected to difference processing later, this tends to increase the number of comparisons between the net present values, increase the data processing amount of the net present value, and thus result in longer processing difficulty time. In order to reduce the processing duration of the differential processing, thereby reducing the number of differential processing on the first net present value and the second net present value, the acquiring the first net present value and the second net present value includes the steps of:
selecting a modulation discount rate;
obtaining a modulation net present value according to the modulation discount rate;
detecting whether the modulated net present value is equal to 0;
when the modulation net present value is not equal to 0, the modulation discount rate is adjusted so that the modulation net present value is subjected to positive-negative conversion, and two modulation net present values before and after conversion are respectively set as the first net present value and the second net present value.
In this embodiment, the modulation discount rate is a variable discount rate, and at the beginning, the modulation discount rate may be a discount rate selected randomly as an initial discount rate, and the modulation discount rate corresponds to the discount rate in the annual gold value coefficient table. When the modulation discount rate is adjusted, the annuity current value coefficient table in the database is called so as to be convenient for replacing and changing the modulation discount rate, and the modulation discount rate is ensured to have the corresponding annuity current value coefficient. Since the net present value is obtained based on the discount rate, the relationship between the net present value and the discount rate is as follows:
Wherein NPV is a net present value, i is a discount rate, CI is a future funds inflow, CO is a future funds outflow, t is a time interval, and data of the future funds inflow and the future funds outflow are obtained from the enterprise operation activity correspondence table in the database.
Under the condition of the same parameters, that is, the discount rate in the net present value is the same as the discount rate in the annuity present value coefficient, firstly, the annuity present value coefficient in the annuity present value coefficient table is selected, and then the discount rate in the annuity present value coefficient is brought into the net present value formula so as to obtain the corresponding net present value, that is, the modulation net present value. In addition, since the net present value is selected, that is, the first net present value and the second net present value are properly selected, the last selected modulation net present value needs to be detected, which is to detect whether the modulation net present value approaches 0, that is, whether the total sum of the funds inflow and the total sum of the funds outflow are approximately equal.
In different cases, there are different approaches, but eventually they are aligned to 0. When the modulation net present value is not equal to 0, adjusting the modulation discount rate, including the following steps:
And when the modulation net present value is greater than 0, increasing the modulation discount rate.
Or when the modulation net present value is not equal to 0, adjusting the modulation discount rate, and further comprising the following steps:
and when the modulation net present value is smaller than 0, reducing the modulation discount rate.
And correspondingly changing the modulation rate under the condition that the modulation net present values are different, and returning to the step of acquiring the modulation net present value according to the modulation rate. The modulation rate at this time is used as the modulation rate in the next execution step of obtaining the modulation net present value according to the modulation rate, so that the detection of the modulation net present value is convenient to continue on the adjusted modulation rate, and the modulation net present value close to the zero is convenient to find. Since the modulation fold rate is continuously changing, so that the modulation net present value is also changing, and the probability that the modulation net present value is completely equal to 0 is small, when the modulation net present value is judged to be 0, the situation that the modulation net present value passes over 0 often occurs, that is, the modulation net present value can be positive or negative, that is, the modulation net present value is usually changed near 0 when the modulation net present value is close to 0. In this way, at the moment when the positive and negative of the change of the modulated net present value change, the first net present value and the second net present value can be collected, that is, when the positive and negative of the modulated net present value changes, the modulated net present value before and after the change can be used as the first net present value and the second net present value, and the first net present value and the second net present value are ensured to be in the vicinity of 0 net present value, so as to meet the requirement of the sampled net present value, so that the execution times of the step S200 are reduced, the data processing amount of the net present value is reduced, and the detection time of the enterprise profit wind control detection method is reduced.
Further, in order to facilitate the fluctuation measurement of the economic wind control of the enterprise, that is, the fluctuation degree between the possible profit structure and the expected profit, when the modulation net present value is not equal to 0, the modulation discount rate is adjusted so as to make the modulation net present value change positive and negative, and two modulation net present values before and after the change are respectively set as the first net present value and the second net present value, and then the method further includes the following steps:
obtaining the corresponding modulation discount rate when the modulation net present value is subjected to positive and negative transition each time, and dividing the modulation discount rate into a positive discount rate and a reverse discount rate;
carrying out wind separation treatment on the normal-phase discount rate and the reverse discount rate to obtain a risk index;
detecting whether the risk index is smaller than a preset index;
and when the risk index is smaller than the preset index, transmitting a low risk signal to the wind control system.
In this embodiment, the normal-phase discount rate and the reverse discount rate are discount rates corresponding to the first net present value and the second net present value, that is, two discount rates corresponding to each time positive and negative transition occurs to the net present value, that is, discount rates before and after positive and negative transition occurs to the net present value. After the normal discount rate and the reverse discount rate are obtained, performing wind separation treatment on the two groups of discount rates, namely performing risk discrete degree treatment on the normal discount rate and the reverse discount rate so as to know the fluctuation degree of enterprise operation income, wherein the wind separation treatment formula for the two groups of discount rates comprises the following specific steps:
Wherein Var is the risk index, i 1m Is a positive phase discount rate, and the method is characterized in that,k is the expected value of a plurality of normal phase discount rates 1 Is Xiang Quan weight of positive phase discount rate, i 2m Is an inverse discount rate, +.>K is the expected value of a plurality of normal phase discount rates 2 An inverse weight that is an inverse discount rate. The positive Xiang Quan weight and the reverse weight are used for determining the percentage of the positive discount rate and the negative discount rate, namely distinguishing the degree that the net present value corresponding to the positive discount rate and the negative discount rate is close to 0, so that the discount rate corresponding to the net present value which is closer to 0 is conveniently subjected to weight distribution.
Positive Xiang Quan heavy K 1 The specific formula of (2) is as follows:
positive Xiang Quan heavy K 2 The specific formula of (2) is as follows:
wherein, beta is a break-loss adjusting factor for adjusting the loss of the discount rate in the conversion process between the net present value and the yearly present value coefficient, namely for adjusting the error of the discount rate in the conversion process between the net present value and the yearly present value coefficient, log is a logarithmic function based on 10, and the weight distribution accuracy of the normal discount rate and the reverse discount rate is ensured.
Thus, after the risk index is determined, the risk index is compared with the preset index, namely the current risk index is compared with the standard risk index, so that the economic wind control fluctuation condition of the enterprise is determined, and the fluctuation degree between the possible profit structure and the expected profit is compared. The risk index is smaller than the preset index, which indicates that the fluctuation between the current possible profit structure and the expected profit is smaller, namely that the fluctuation between the current possible profit structure and the expected profit is within a safe fluctuation range, namely that the fluctuation between the current possible profit structure and the expected profit is in a low risk state, and at the moment, a low risk signal is sent to the wind control system so as to inform a monitoring background of receiving the current possible risk condition of the enterprise, and effectively and directly numerically displaying the current capability of the enterprise to cope with future economic risks.
In one embodiment, the detecting whether the difference value matches a preset difference value includes: detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate, wherein the method comprises the following steps: when the difference value is matched with the preset difference value, respectively acquiring the discount rate corresponding to the first net present value and the second net present value; acquiring a risk assessment discount rate according to the discount rate corresponding to the first net present value and the second net present value; and controlling the risk management and control level corresponding to the economic risk level signal according to the risk assessment discount rate. In this embodiment, the differential value is a differential module between two net present values currently collected, that is, the differential value is an absolute value of a difference between two net present values currently collected, that is, the differential value is an absolute difference between two net present values currently collected. The preset different number value is also based on the two net present values collected at present, for example, the preset different number value is the sum of the two net present values collected at present, that is, the preset different number value is the sum of the two net present values collected at present after being modulo, that is, the preset different number value is the sum of the absolute values taken by the two net present values collected at present. The difference value is matched with the preset difference value, for example, the difference value is equal to the preset difference value, which indicates that the first net present value and the second net present value are different numbers, that is, the numerical signs of the first net present value and the second net present value are positive and negative. At this time, the first net present value and the second net present value are located on both sides of zero, respectively, and there is a net present value located near zero.
And after the different sign condition of the first net present value and the second net present value is determined, the degree of difference between the first net present value and the second net present value needs to be controlled so as to quickly obtain the corresponding discount rate when the net present value is zero. And at the moment, carrying out matching detection on the difference value and the preset difference absolute value, wherein the preset difference absolute value is a specified difference value, and the preset difference absolute value is a standard difference value between two net present values nearby when the net present value is zero. The difference value is matched with the preset difference absolute value, which indicates that the difference value between the first net present value and the second net present value is within the range of the preset difference absolute value, for example, the preset difference absolute value is 2% to 5%, that is, the difference value between the first net present value and the second net present value is a standard difference value, and at this time, the first net present value and the second net present value are used as the reference value of the obtained net present value, that is, the net present value which is equal to zero is found between the first net present value and the second net present value. In this way, after it is determined that the difference between the first net present value and the second net present value meets the standard, obtaining the discount rate corresponding to the net present value between the first net present value and the second net present value, that is, the risk assessment discount rate, where the net present value corresponding to the risk assessment discount rate is zero, then determining that the risk resistance of the enterprise economy is stronger according to the risk assessment discount rate, and correspondingly improving the risk management level corresponding to the economic risk level signal, so as to determine the risk management level of the enterprise economy assessment.
In another embodiment, the detecting whether the difference value matches a preset difference value further includes: and when the difference value is not matched with the preset difference value, the first net present value and the second net present value are acquired again. In this embodiment, the differential value is a differential module between two net present values currently collected, that is, the differential value is an absolute value of a difference between two net present values currently collected, that is, the differential value is an absolute difference between two net present values currently collected. The preset different number value is also based on the two net present values collected at present, for example, the preset different number value is the sum of the two net present values collected at present, that is, the preset different number value is the sum of the two net present values collected at present after being modulo, that is, the preset different number value is the sum of the absolute values taken by the two net present values collected at present. The difference value is not matched with the preset difference value, for example, the difference value is not equal to the preset difference value, which indicates that the first net present value and the second net present value are the same number, that is, the numerical signs of the first net present value and the second net present value are both positive or negative. In this case, the first and second net present values are located on the same side as zero, respectively, and the net present value located near zero cannot be obtained. Thus, the first net present value and the second net present value need to be retrieved again at this time, so that the net present value corresponding to the case where the total amount of the funds inflow present value is equal to the total amount of the funds outflow present value is newly determined.
Still further, the controlling the risk management level corresponding to the economic risk level signal according to the risk assessment discount rate includes: detecting whether the risk assessment discount rate is greater than or equal to a preset discount rate; and when the risk assessment discount rate is greater than or equal to the preset discount rate, increasing the risk management and control level of the economic risk level signal. In this embodiment, the risk assessment discount rate is a discount rate corresponding to a net present value of zero, that is, the risk assessment discount rate is a discount rate corresponding to a total sum of funds inflow present values and a total sum of funds outflow present values, which indicates that the anti-risk level of enterprise economy is at a security level. Because the risk assessment discount rate is greater than or equal to the preset discount rate at this time, the risk management and control level of the economic risk level signal is correspondingly adjusted to be high, so that the economic risk resistance of the current enterprise is improved by the wind control system, and monitoring personnel can know the economic risk resistance level of the enterprise accurately.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps in fig. 1 may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily sequential, but may be performed in rotation or alternatively with at least a portion of the steps or stages in other steps or other steps.
In one embodiment, an enterprise revenue wind control detection apparatus is provided, which is implemented by using the enterprise revenue wind control detection method described in any one of the embodiments. In one embodiment, the enterprise revenue wind control detection device is provided with a functional module for realizing correspondence of each step of the enterprise revenue wind control detection method. The enterprise income wind control detection device comprises: sampling module, processing module and wind control detection module, wherein:
the sampling module is used for acquiring a first net present value and a second net present value;
the processing module is used for performing differential processing on the first net present value and the second net present value to obtain a differential value;
the wind control detection module is used for detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate.
In this embodiment, the first net present value and the second net present value collected by the sampling module are taken as a present value difference in future funds flow in economic wind control of an enterprise, the first net present value is taken as a first difference between the future funds inflow present value and the future funds outflow present value, the second net present value is taken as a second difference between the future funds inflow present value and the future funds outflow present value, and the first net present value and the second net present value are taken as a present value difference in two annual periods, can be taken as an evaluation reference for the future funds flow of the enterprise, and is convenient for subsequent knowledge of the profit situation of the future funds flow.
The processing module performs different absolute processing on the first net present value and the second net present value, and performs different number difference processing on the present value difference of two yearly periods, so that the processing module is convenient to determine the difference degree between the first net present value and the second net present value, and is convenient to determine whether the condition of net present value balance exists or not, and further convenient to determine the economic wind control safety level of an enterprise subsequently.
The preset differential value in the wind control detection module is a differential value corresponding to the case that the enterprise economic wind control level is safe, the wind control detection module carries out matching detection on the differential value, and standard evaluation is carried out on the current first net present value and the second net present value to determine whether the net present value in the current net present value is in a balanced state, namely, the current differential value is detected to be the state value corresponding to the case that the total sum of the detected funds inflow present value is equal to the total sum of the funds outflow present value, namely, whether the differential value is the net present value is equal to zero, so that the safety level in the enterprise economic wind control evaluation can be conveniently determined subsequently. And the difference value is matched with the preset difference value, which indicates that the difference value is equivalent to the preset difference value, that is, indicates that the difference value falls within the range of the preset difference value, that is, indicates that a net present value with zero discount rate exists between a first net present value and a second net present value corresponding to the difference value. At this time, the wind control detection module is convenient for accurately judging the economic risk level of the enterprise according to the obtained discount rate, so that the wind control detection accuracy is improved, the future risk resistance of the enterprise can be known in time, namely whether the future monetary detractions or the economic impact caused by the general expansion can be dealt with, and the early warning function of the economic impact in the future economic development process is achieved.
In one embodiment, the sampling module is further configured to sequentially obtain a first yearly gold current value coefficient and a second yearly gold current value coefficient; and respectively carrying out discount processing on the first annual gold present value coefficient and the second annual gold present value coefficient to obtain the first net present value and the second net present value. In this embodiment, the sampling module treats the first net present value as a first difference between a future funds inflow present value and a future funds outflow present value and the second net present value as a second difference between a future funds inflow present value and a future funds outflow present value. In the process of collecting the net present value by the sampling module, the first net present value and the second net present value are collected sequentially according to time sequence, namely, the generation time corresponding to the first net present value and the generation time corresponding to the second net present value have time difference. And acquiring two gold current value coefficients of the gold period with time sequence in the sampling module, namely the first gold current value coefficient and the second gold current value coefficient, wherein the first gold current value coefficient corresponds to the first net current value, and the second gold current value coefficient corresponds to the second net current value. Thus, after the sampling module acquires the annual gold present value coefficients in two annual gold periods, the corresponding net present value is conveniently acquired. In this embodiment, the present annual gold value coefficients are stored in the database, and each present annual gold value coefficient is stored therein, so that the present annual gold value coefficient is convenient to retrieve and use, that is, the present annual gold value coefficient is convenient to calculate the corresponding net present value.
Further, the sampling module is further configured to detect whether the first yearly gold present value coefficient is equal to the second yearly gold present value coefficient; and re-acquiring the gold present value coefficient when the first gold present value coefficient is equal to the second gold present value coefficient. In this embodiment, the first yen present value coefficient is used as a reference base of a first net present value, and the second yen present value coefficient is used as a reference base of a second net present value, that is, one of the subparameters in the first yen present value coefficient is used to calculate the first net present value, and one of the subparameters in the second yen present value coefficient is used to calculate the second net present value. In order to find the accurate net present value, the sampling module judges the difference degree of the first and second annual gold present value coefficients, so as to determine that the annual gold present value coefficient corresponding to the found net present value is located between the first and second annual gold present value coefficients, thereby facilitating the difference between the collected first and second net present values and further facilitating the evaluation of the annual gold present value coefficient corresponding to zero net present value. In this way, the sampling module monitors that the first yen present value coefficient is equal to the second yen present value coefficient, which indicates that the first net present value and the second net present value remain the same, and the state that the net present value is zero cannot be accurately determined, and at this time, the yen present value coefficient and the corresponding net present value need to be collected again.
Still further, the sampling module is further configured to obtain a first discount rate and a second discount rate according to the first annual gold present value coefficient and the second annual gold present value coefficient, respectively; and performing net present processing on the first discount rate and the second discount rate to obtain the first net present value and the second net present value. In this embodiment, the annual gold present value coefficient includes a discount rate and an annual year, and after the sampling module obtains the first annual gold present value coefficient and the second annual gold present value coefficient, the discount rate therein, that is, the first discount rate and the second discount rate, is collected. The discount rate is used as a correlation parameter between the annuity present value coefficient and the net present value, and the annuity present value coefficient is acquired from the database. The sampling module facilitates determining the first discount rate and the second discount rate by analyzing the data of the first yearly cash value coefficient and the second yearly cash value coefficient, thereby facilitating determining the first net cash value and the second net cash value. In this way, after the sampling module performs the net present processing on the first discount rate, the first net present value is calculated according to the first discount rate in the first annual gold present value coefficient, and after the sampling module performs the net present processing on the first discount rate, the first net present value is calculated according to the first discount rate in the first annual gold present value coefficient, so that an accurate net present value is conveniently obtained.
It will be appreciated that, in acquiring the corresponding net present value by acquiring the annuity present value coefficient in the annuity present value coefficient table, the manner of acquiring the net present value is selected randomly, and although the first net present value and the second net present value are subjected to difference processing later, this tends to increase the number of comparisons between the net present values, increase the data processing amount of the net present value, and thus result in longer processing difficulty time. In order to reduce the processing duration of the differential processing, thereby reducing the differential processing times of the first net present value and the second net present value, the sampling module is further used for selecting a modulation discount rate; obtaining a modulation net present value according to the modulation discount rate; detecting whether the modulated net present value is equal to 0; when the modulation net present value is not equal to 0, the modulation discount rate is adjusted so that the modulation net present value is subjected to positive-negative conversion, and two modulation net present values before and after conversion are respectively set as the first net present value and the second net present value.
In this embodiment, the modulation discount rate is a variable discount rate, and at the beginning, the modulation discount rate may be a discount rate selected randomly as an initial discount rate, and the modulation discount rate corresponds to the discount rate in the annual gold value coefficient table. When the modulation discount rate is adjusted, the annuity current value coefficient table in the database is called so as to be convenient for replacing and changing the modulation discount rate, and the modulation discount rate is ensured to have the corresponding annuity current value coefficient. Since the net present value is obtained based on the discount rate, the relationship between the net present value and the discount rate is as follows:
Wherein NPV is a net present value, i is a discount rate, CI is a future funds inflow, CO is a future funds outflow, t is a time interval, and data of the future funds inflow and the future funds outflow are obtained from the enterprise operation activity correspondence table in the database.
Under the condition of the same parameters, that is, the discount rate in the net present value is the same as the discount rate in the annuity present value coefficient, firstly, the annuity present value coefficient in the annuity present value coefficient table is selected, and then the discount rate in the annuity present value coefficient is brought into the net present value formula so as to obtain the corresponding net present value, that is, the modulation net present value. In addition, since the net present value is selected, that is, the first net present value and the second net present value are properly selected, the last selected modulation net present value needs to be detected, which is to detect whether the modulation net present value approaches 0, that is, whether the total sum of the funds inflow and the total sum of the funds outflow are approximately equal.
In different cases, there are different approaches, but eventually they are aligned to 0. The sampling module is further configured to increase the modulation fold rate when the modulation net present value is greater than 0. Or, the sampling module is further configured to reduce the modulation fold rate when the modulation net present value is less than 0.
And correspondingly changing the modulation rate under the condition that the modulation net present values are different, and returning to the step of acquiring the modulation net present value according to the modulation rate. The modulation rate at this time is used as the modulation rate in the next execution step of obtaining the modulation net present value according to the modulation rate, so that the detection of the modulation net present value is convenient to continue on the adjusted modulation rate, and the modulation net present value close to the zero is convenient to find. Since the modulation fold rate is continuously changing, so that the modulation net present value is also changing, and the probability that the modulation net present value is completely equal to 0 is small, when the modulation net present value is judged to be 0, the situation that the modulation net present value passes over 0 often occurs, that is, the modulation net present value can be positive or negative, that is, the modulation net present value is usually changed near 0 when the modulation net present value is close to 0. In this way, at the moment when the positive and negative of the change of the modulated net present value change, the first net present value and the second net present value can be collected, that is, when the positive and negative of the modulated net present value changes, the modulated net present value before and after the change can be used as the first net present value and the second net present value, and the first net present value and the second net present value are ensured to be in the vicinity of 0 net present value, so as to meet the requirement of the sampled net present value, so that the execution times of the step S200 are reduced, the data processing amount of the net present value is reduced, and the detection time of the enterprise profit wind control detection method is reduced.
Further, in order to facilitate the fluctuation measurement of the economic wind control of the enterprise, that is, the fluctuation degree between the possible profit structure and the expected profit, the sampling module is further configured to obtain the modulation discount rate corresponding to each positive and negative transition of the modulation net present value, and divide the modulation discount rate into a normal discount rate and a reverse discount rate; carrying out wind separation treatment on the normal-phase discount rate and the reverse discount rate to obtain a risk index; detecting whether the risk index is smaller than a preset index; and when the risk index is smaller than the preset index, transmitting a low risk signal to the wind control system.
In this embodiment, the normal-phase discount rate and the reverse discount rate are discount rates corresponding to the first net present value and the second net present value, that is, two discount rates corresponding to each time positive and negative transition occurs to the net present value, that is, discount rates before and after positive and negative transition occurs to the net present value. After the normal discount rate and the reverse discount rate are obtained, performing wind separation treatment on the two groups of discount rates, namely performing risk discrete degree treatment on the normal discount rate and the reverse discount rate so as to know the fluctuation degree of enterprise operation income, wherein the wind separation treatment formula for the two groups of discount rates comprises the following specific steps:
Wherein Var is the risk index, i 1m Is a positive phase discount rate, and the method is characterized in that,k is the expected value of a plurality of normal phase discount rates 1 Is Xiang Quan weight of positive phase discount rate, i 2m Is an inverse discount rate, +.>K is the expected value of a plurality of normal phase discount rates 2 An inverse weight that is an inverse discount rate. The positive Xiang Quan weight and the reverse weight are used for determining the percentage of the positive discount rate and the negative discount rate, namely distinguishing the degree that the net present value corresponding to the positive discount rate and the negative discount rate is close to 0, so that the discount rate corresponding to the net present value which is closer to 0 is conveniently subjected to weight distribution.
Positive Xiang Quan heavy K 1 The specific formula of (2) is as follows:
positive Xiang Quan heavy K 2 The specific formula of (2) is as follows:
wherein, beta is a break-loss adjusting factor for adjusting the loss of the discount rate in the conversion process between the net present value and the yearly present value coefficient, namely for adjusting the error of the discount rate in the conversion process between the net present value and the yearly present value coefficient, log is a logarithmic function based on 10, and the weight distribution accuracy of the normal discount rate and the reverse discount rate is ensured.
Thus, after the risk index is determined, the risk index is compared with the preset index, namely the current risk index is compared with the standard risk index, so that the economic wind control fluctuation condition of the enterprise is determined, and the fluctuation degree between the possible profit structure and the expected profit is compared. The risk index is smaller than the preset index, which indicates that the fluctuation between the current possible profit structure and the expected profit is smaller, namely that the fluctuation between the current possible profit structure and the expected profit is within a safe fluctuation range, namely that the fluctuation between the current possible profit structure and the expected profit is in a low risk state, and at the moment, a low risk signal is sent to the wind control system so as to inform a monitoring background of receiving the current possible risk condition of the enterprise, and effectively and directly numerically displaying the current capability of the enterprise to cope with future economic risks.
In one embodiment, the wind control detection module is further configured to detect whether the difference value is matched with a preset difference value; when the difference value is matched with the preset difference value, detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate, wherein the method comprises the following steps: when the difference value is matched with the preset difference value, respectively acquiring the discount rate corresponding to the first net present value and the second net present value; acquiring a risk assessment discount rate according to the discount rate corresponding to the first net present value and the second net present value; and controlling the risk management and control level corresponding to the economic risk level signal according to the risk assessment discount rate. In this embodiment, the differential value obtained by the wind control detection module is a differential module between two currently collected net present values, that is, the differential value is an absolute value of a difference between two currently collected net present values, that is, the differential value is an absolute difference between two currently collected net present values. The preset different number value is also based on the two net present values collected at present, for example, the preset different number value is the sum of the two net present values collected at present, that is, the preset different number value is the sum of the two net present values collected at present after being modulo, that is, the preset different number value is the sum of the absolute values taken by the two net present values collected at present. The difference value is matched with the preset difference value, for example, the difference value is equal to the preset difference value, which indicates that the first net present value and the second net present value are different numbers, that is, the numerical signs of the first net present value and the second net present value are positive and negative. At this time, the first net present value and the second net present value are located on both sides of zero, respectively, and there is a net present value located near zero.
And after the wind control detection module determines the different number condition of the first net present value and the second net present value, the difference degree between the first net present value and the second net present value needs to be controlled, so that the wind control detection module can quickly calculate the corresponding discount rate when the net present value is zero. At this time, the wind control detection module performs matching detection on the difference value and the preset difference absolute value, wherein the preset difference absolute value is a specified difference value, and the preset difference absolute value is a standard difference value between two net present values nearby when the net present value is zero. The difference value is matched with the preset difference absolute value, which indicates that the difference value between the first net present value and the second net present value is within the range of the preset difference absolute value, for example, the preset difference absolute value is 2% to 5%, that is, the difference value between the first net present value and the second net present value is a standard difference value, and at this time, the first net present value and the second net present value are used as the reference value of the obtained net present value, that is, the net present value which is equal to zero is found between the first net present value and the second net present value. In this way, after the wind control detection module determines that the difference between the first net present value and the second net present value meets the standard, obtaining the discount rate corresponding to the net present value between the first net present value and the second net present value, namely the risk assessment discount rate, at this time, the net present value corresponding to the risk assessment discount rate is zero, and then the wind control detection module can determine that the risk resistance of the enterprise economy is stronger according to the risk assessment discount rate, and correspondingly improves the risk management and control level corresponding to the economic risk level signal so as to determine the risk management and control level of the enterprise economy assessment.
In another embodiment, the wind control detection module is further configured to re-acquire the first net present value and the second net present value when the difference value does not match the preset difference value. In this embodiment, the differential value is a differential module between two net present values currently collected, that is, the differential value is an absolute value of a difference between two net present values currently collected, that is, the differential value is an absolute difference between two net present values currently collected. The preset different number value is also based on the two net present values collected at present, for example, the preset different number value is the sum of the two net present values collected at present, that is, the preset different number value is the sum of the two net present values collected at present after being modulo, that is, the preset different number value is the sum of the absolute values taken by the two net present values collected at present. The wind control detection module detects that the difference value is not matched with the preset difference value, for example, the difference value is not equal to the preset difference value, which indicates that the first net present value and the second net present value are the same number, that is, the numerical signs of the first net present value and the second net present value are positive or negative. In this case, the first and second net present values are located on the same side as zero, respectively, and the net present value located near zero cannot be obtained. Thus, the first net present value and the second net present value need to be retrieved again at this time, so that the net present value corresponding to the case where the total amount of the funds inflow present value is equal to the total amount of the funds outflow present value is newly determined.
Still further, the wind control detection module is further configured to detect whether the risk assessment discount rate is greater than or equal to a preset discount rate; and when the risk assessment discount rate is greater than or equal to the preset discount rate, increasing the risk management and control level of the economic risk level signal. In this embodiment, the risk assessment discount rate detected by the wind control detection module is a discount rate corresponding to a net present value of zero, that is, the risk assessment discount rate is a discount rate corresponding to a total sum of funds inflow present values and a total sum of funds outflow present values, which indicates that the anti-risk level of enterprise economy is in a security level. Because the risk assessment discount rate is greater than or equal to the preset discount rate at this time, the risk management and control level of the economic risk level signal is correspondingly adjusted to be high, so that the economic risk resistance of the current enterprise is improved by the wind control system, and monitoring personnel can know the economic risk resistance level of the enterprise accurately.
For specific limitation of the enterprise revenue wind control detection apparatus, reference may be made to the limitation of the enterprise revenue wind control detection method hereinabove, and no further description is given here. The modules in the enterprise revenue wind control detection apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in FIG. 2. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing discount rate, annual gold present value coefficient and corresponding net present value data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements an enterprise revenue wind control detection method.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 2 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor executes the computer program to implement the steps in the method embodiments described above.
In one embodiment, the present application further provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method embodiments described above.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims (10)

1. The enterprise profit wind control detection method is characterized by comprising the following steps:
obtaining a first net present value as a first difference between a future funds inflow present value and a future funds outflow present value and a second net present value as a second difference between the future funds inflow present value and the future funds outflow present value, the first net present value and the second net present value being present value differences over two years, and the first net present value and the second net present value being collected in chronological order;
Performing differential processing on the first net present value and the second net present value to obtain differential values, wherein the differential processing is to perform differential number difference processing on the present value differences of two yearly gold periods to determine the degree of difference between the first net present value and the second net present value, and the differential value is a differential model between the two net present values acquired currently;
detecting whether the difference value is matched with a preset difference value or not;
when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate; the risk indexes are obtained by carrying out risk discrete degree treatment on the normal-phase discount rate and the reverse-phase discount rate, and the formulas for carrying out wind separation treatment on the two groups of discount rates are specifically as follows:
wherein Var is the risk index, i 1m Is a positive phase discount rate, and the method is characterized in that,k is the expected value of a plurality of normal phase discount rates 1 Is Xiang Quan weight of positive phase discount rate, i 2m Is an inverse discount rate, +.>K is the expected value of a plurality of normal phase discount rates 2 An inverse weight that is an inverse discount rate;
positive Xiang Quan heavy K 1 The specific formula of (2) is as follows:
inverse weight K 2 The specific formula of (2) is as follows:
wherein, beta is a break-loss adjusting factor for adjusting the loss of the break rate in the conversion process between the net present value and the yearly present value coefficient, namely for adjusting the error of the break rate in the conversion process between the net present value and the yearly present value coefficient, and log is a logarithmic function based on 10.
2. The method of claim 1, wherein the obtaining the first net present value and the second net present value comprises:
sequentially acquiring a first-year current value coefficient and a second-year current value coefficient;
and respectively carrying out discount processing on the first annual gold present value coefficient and the second annual gold present value coefficient to obtain the first net present value and the second net present value.
3. The method for detecting the wind control of the enterprise profit according to claim 2, wherein the sequentially obtaining the first yearly gold present value coefficient and the second yearly gold present value coefficient further comprises:
detecting whether the first yen present value coefficient is equal to the second yen present value coefficient;
And re-acquiring the gold present value coefficient when the first gold present value coefficient is equal to the second gold present value coefficient.
4. The method for detecting the wind control of the enterprise revenue according to claim 2, wherein the discounting the first yearly gold present value coefficient and the second yearly gold present value coefficient to obtain the first net present value and the second net present value includes:
according to the first annual gold present value coefficient and the second annual gold present value coefficient, respectively obtaining a first discount rate and a second discount rate;
and performing net present processing on the first discount rate and the second discount rate to obtain the first net present value and the second net present value.
5. The method for detecting the wind control of the enterprise revenue according to claim 1, wherein the detecting whether the difference value matches a preset difference value comprises:
detecting whether the difference value is matched with a preset difference value or not;
when the difference value is matched with the preset difference value, detecting whether the difference value is matched with a preset difference value or not;
when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate, wherein the method comprises the following steps:
When the difference value is matched with the preset difference value, respectively acquiring the discount rate corresponding to the first net present value and the second net present value;
acquiring a risk assessment discount rate according to the discount rate corresponding to the first net present value and the second net present value;
and controlling the risk management and control level corresponding to the economic risk level signal according to the risk assessment discount rate.
6. The method for detecting the wind control of the enterprise revenue according to claim 5, wherein the detecting whether the difference value matches a preset difference value further comprises:
and when the difference value is not matched with the preset difference value, the first net present value and the second net present value are acquired again.
7. The method for detecting the wind control of the enterprise revenue according to claim 5, wherein the controlling the risk management level corresponding to the economic risk level signal according to the risk assessment discount rate comprises:
detecting whether the risk assessment discount rate is greater than or equal to a preset discount rate;
and when the risk assessment discount rate is greater than or equal to the preset discount rate, increasing the risk management and control level of the economic risk level signal.
8. An enterprise revenue wind control detection apparatus, the apparatus comprising:
A sampling module for obtaining a first net present value as a first difference between a future funds inflow present value and a future funds outflow present value and a second net present value as a second difference between the future funds inflow present value and the future funds outflow present value, the first net present value and the second net present value being present as a present value difference over two yearly periods, and the first net present value and the second net present value being collected in chronological order;
the processing module is used for performing differential processing on the first net present value and the second net present value to obtain differential values, wherein the differential processing is to perform differential number difference processing on the present value differences of two yearly time to determine the degree of difference between the first net present value and the second net present value, and the differential value is a differential model between the two currently acquired net present values;
the wind control detection module is used for detecting whether the difference value is matched with a preset difference value or not; when the difference value is matched with the preset difference value, obtaining a discount rate corresponding to the difference value, and adjusting an economic risk level signal sent to the wind control system according to the discount rate; the risk indexes are obtained by carrying out risk discrete degree treatment on the normal-phase discount rate and the reverse-phase discount rate, and the formulas for carrying out wind separation treatment on the two groups of discount rates are specifically as follows:
Wherein Var is the risk index, i 1m Is a positive phase discount rate, and the method is characterized in that,k is the expected value of a plurality of normal phase discount rates 1 Is Xiang Quan weight of positive phase discount rate, i 2m Is an inverse discount rate, +.>K is the expected value of a plurality of normal phase discount rates 2 An inverse weight that is an inverse discount rate;
positive Xiang Quan heavy K 1 The specific formula of (2) is as follows:
inverse weight K 2 The specific formula of (2) is as follows:
wherein, beta is a break-loss adjusting factor for adjusting the loss of the break rate in the conversion process between the net present value and the yearly present value coefficient, namely for adjusting the error of the break rate in the conversion process between the net present value and the yearly present value coefficient, and log is a logarithmic function based on 10.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009087219A (en) * 2007-10-02 2009-04-23 Doshisha Corporate value evaluation device, corporate value evaluation method, and computer program
CN102339452A (en) * 2011-11-09 2012-02-01 曾祥洪 Quantitative trading method and system for financial derivatives
CN107392773A (en) * 2017-03-28 2017-11-24 阿里巴巴集团控股有限公司 Calculate the method and device of combination investment synthesis net value rate of change
CN107451919A (en) * 2017-08-08 2017-12-08 智道金融服务（深圳）有限公司 For working out the method and its system of fund index
CN109978342A (en) * 2019-03-01 2019-07-05 平安科技（深圳）有限公司 Electronic device, methods of risk assessment and computer readable storage medium
CN110689197A (en) * 2019-09-27 2020-01-14 国网上海市电力公司 An Incremental Distribution Network Investment Decision-Making Method
CN111738865A (en) * 2020-08-25 2020-10-02 北京口袋财富信息科技有限公司 Net value curve generation method and device, readable storage medium and computing equipment
CN112446578A (en) * 2019-09-04 2021-03-05 京东数字科技控股有限公司 Risk monitoring method and device

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8126746B2 (en) * 2006-03-02 2012-02-28 Hartford Fire Insurance Company System and method for processing and administering flexible guaranteed income payments
US20130290219A1 (en) * 2008-08-04 2013-10-31 Donald DuBois Method and apparatus for computing the relative risk of financial assets using risk-return profiles

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009087219A (en) * 2007-10-02 2009-04-23 Doshisha Corporate value evaluation device, corporate value evaluation method, and computer program
CN102339452A (en) * 2011-11-09 2012-02-01 曾祥洪 Quantitative trading method and system for financial derivatives
CN107392773A (en) * 2017-03-28 2017-11-24 阿里巴巴集团控股有限公司 Calculate the method and device of combination investment synthesis net value rate of change
CN107451919A (en) * 2017-08-08 2017-12-08 智道金融服务（深圳）有限公司 For working out the method and its system of fund index
CN109978342A (en) * 2019-03-01 2019-07-05 平安科技（深圳）有限公司 Electronic device, methods of risk assessment and computer readable storage medium
CN112446578A (en) * 2019-09-04 2021-03-05 京东数字科技控股有限公司 Risk monitoring method and device
CN110689197A (en) * 2019-09-27 2020-01-14 国网上海市电力公司 An Incremental Distribution Network Investment Decision-Making Method
CN111738865A (en) * 2020-08-25 2020-10-02 北京口袋财富信息科技有限公司 Net value curve generation method and device, readable storage medium and computing equipment

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