CN111915436A

CN111915436A - Digital asset assessment method, device, equipment and storage medium

Info

Publication number: CN111915436A
Application number: CN202010777243.1A
Authority: CN
Inventors: 聂二保; 朱江
Original assignee: Beijing Kingsoft Cloud Network Technology Co Ltd
Current assignee: Beijing Kingsoft Cloud Network Technology Co Ltd
Priority date: 2020-08-05
Filing date: 2020-08-05
Publication date: 2020-11-10
Anticipated expiration: 2040-08-05
Also published as: CN111915436B

Abstract

The embodiment of the application discloses a digital asset evaluation method, a device, equipment and a storage medium, wherein the method comprises the following steps: after each transaction of the target digital asset is finished, acquiring transaction prediction information given by an original holder of the transaction for the target digital asset, taking the transaction prediction information as a transaction prediction information user corresponding to the transaction, and writing the transaction prediction information corresponding to the transaction into a alliance chain; verifying transaction prediction information corresponding to the last transaction of the transaction to obtain a prediction judgment result according to the transaction result of the target digital asset in the transaction, taking the prediction judgment result as the prediction judgment result corresponding to the last transaction, and writing the prediction judgment result corresponding to the last transaction into the alliance chain; and evaluating the target digital assets according to the transaction prediction information and the prediction judgment result which correspond to each transaction of the target digital assets in the alliance chain. The scheme can ensure that the evaluation result of the digital assets has higher reference value and guidance for traders.

Description

Digital asset assessment method, device, equipment and storage medium

Technical Field

The present application relates to the field of internet technologies, and in particular, to a method, an apparatus, a device, and a storage medium for evaluating digital assets.

Background

The original assets are transformed digitally, and the system established based on the alliance chain is adopted to transfer the transaction digital assets, so that the method becomes a common transaction mode in the modern digital financial scene. In the process of trading the digital assets, the digital assets are evaluated, the digital asset evaluation result is provided for a trader, and the trader can know the value and the risk of the digital assets.

At present, a trading platform and a third-party professional organization are mainly relied on, digital assets are evaluated through an existing model based on information of a digital asset holder, digital asset trading information, information of the digital assets and the like, and a digital asset evaluation result is determined.

However, the above implementation has the following drawbacks: first, the digital asset assessment framework is not complete enough, and no matter the trading platform or the third-party professional organization stands at the perspective of a bystander to assess the digital assets, and the factors such as market performance, market risk, trading profit opportunities and the like of the digital assets are difficult to be deeply known and grasped, so that the assessment results of the digital assets are often not deep enough, and the reference value for the trader is not high. Secondly, the trading platform and the third-party professional organization often rely on the generated trading data when evaluating the digital assets, and lack of trading expectation information for the market, which results in poor guidance of the digital asset evaluation result.

Disclosure of Invention

The embodiment of the application provides a digital asset evaluation method, a digital asset evaluation device, digital asset evaluation equipment and a storage medium, which can better evaluate digital assets and ensure that the evaluation result of the digital assets has higher reference value and guidance for traders.

In view of the above, a first aspect of the present application provides a digital asset assessment method, including:

after each transaction of a target digital asset is finished, acquiring transaction prediction information given by an original holder of the transaction aiming at the target digital asset, and taking the transaction prediction information as corresponding transaction prediction information of the transaction, wherein the original holder of the transaction is a user holding the target digital asset before the transaction; writing the transaction prediction information corresponding to the current transaction into a alliance chain;

verifying transaction prediction information corresponding to the last transaction of the current transaction according to the transaction result of the target digital asset in the current transaction to obtain a prediction judgment result of the transaction prediction information corresponding to the last transaction, wherein the prediction judgment result is used as the prediction judgment result corresponding to the last transaction; writing the prediction judgment result corresponding to the last transaction into the alliance chain;

and evaluating the target digital assets according to the transaction prediction information and the prediction judgment result which are respectively corresponding to each transaction of the target digital assets in the alliance chain.

Optionally, the obtaining of the transaction prediction information given by the original holder of the current transaction for the target digital asset includes:

acquiring transaction prediction information given by the original holder of the transaction for the target digital asset through an intelligent contract;

writing the transaction prediction information corresponding to the current transaction into a alliance chain, including:

and encrypting the intelligent contract by using a private key, and writing the encrypted intelligent contract into the alliance chain.

Optionally, the transaction prediction information includes any one of: the target digital asset price is rising, the target digital asset price is falling, and the target digital asset price is flat;

then, the verifying the transaction prediction information corresponding to the last transaction of the current transaction according to the transaction result of the target digital asset in the current transaction to obtain the prediction judgment result of the transaction prediction information corresponding to the last transaction includes:

acquiring the transaction price of the target digital asset in the transaction as a first transaction price; acquiring the transaction price of the target digital asset in the last transaction as a second transaction price;

when the transaction prediction information corresponding to the last transaction is the price rise of the target digital asset, if the first transaction price is higher than the second transaction price, determining that the prediction judgment result of the transaction prediction information corresponding to the last transaction is correct; if the first transaction price is not higher than the second transaction price, determining that the prediction judgment result of the transaction prediction information corresponding to the last transaction is wrong;

when the transaction prediction information corresponding to the last transaction is that the price of the target digital asset falls, if the first transaction price is lower than the second transaction price, determining that the prediction judgment result of the transaction prediction information corresponding to the last transaction is correct; if the first transaction price is not lower than the second transaction price, determining that the prediction judgment result of the transaction prediction information corresponding to the last transaction is wrong;

when the transaction prediction information corresponding to the last transaction is that the price of the target digital asset is flat, if the first transaction price is equal to the second transaction price, determining that the prediction judgment result of the transaction prediction information corresponding to the last transaction is correct; and if the first transaction price is not equal to the second transaction price, determining that the prediction judgment result of the transaction prediction information corresponding to the last transaction is wrong.

Optionally, after verifying the transaction prediction information corresponding to the last transaction of the current transaction according to the transaction result of the target digital asset in the current transaction, and obtaining a prediction judgment result of the transaction prediction information corresponding to the last transaction, the method further includes:

and when the prediction judgment result corresponding to the last transaction represents that the transaction prediction information corresponding to the last transaction is correct, giving an incentive asset to the original holder of the last transaction according to the transaction price of the target digital asset in the current transaction and/or the transaction price of the target digital asset in the last transaction.

then said giving an incentive asset to the original holder of the last transaction according to the transaction price of the target digital asset in the current transaction and/or the transaction price of the target digital asset in the last transaction comprises:

when the transaction prediction information corresponding to the last transaction is that the price of the target digital asset rises, determining the rewarding asset according to a first rewarding proportion and a difference value between the first transaction price and the second transaction price;

when the transaction prediction information corresponding to the last transaction is that the price of the target digital asset falls, determining the rewarding asset according to a second rewarding proportion and a difference value between the second transaction price and the first transaction price;

and when the transaction prediction information corresponding to the last transaction is that the price of the target digital asset is flat, determining the rewarding asset according to a third rewarding proportion and the first transaction price or the second transaction price.

Optionally, the first reward proportion, the second reward proportion and the third reward proportion are set by an original holder of the last transaction or fixedly configured by a transaction platform.

Optionally, the reward asset is paid by the original holder in the current transaction to the original holder of the previous transaction.

Optionally, before the obtaining of the transaction prediction information given by the original holder of the current transaction for the target digital asset, the method further includes:

determining a time difference value between the current time and the time when the transaction is ended;

and judging whether the time difference exceeds a prediction time threshold, if so, not allowing the original holder of the transaction to give transaction prediction information for the target digital asset.

Optionally, the evaluating the target digital asset according to the transaction prediction information and the prediction judgment result corresponding to each transaction of the target digital asset in the alliance chain includes:

generating a transaction prediction information sequence aiming at the target digital asset according to the transaction prediction information respectively corresponding to each transaction aiming at the target digital asset in the alliance chain;

generating a prediction judgment result sequence aiming at the target digital asset according to the prediction judgment result corresponding to each transaction aiming at the target digital asset in the alliance chain;

and evaluating the target digital assets according to the transaction prediction information sequence and the prediction judgment result sequence.

A second aspect of the present application provides a digital asset assessment apparatus, the apparatus comprising:

the system comprises a prediction information storage module, a transaction prediction module and a prediction information processing module, wherein the prediction information storage module is used for acquiring transaction prediction information given by an original holder of the transaction aiming at a target digital asset after each transaction of the target digital asset is finished, and the transaction prediction information is used as transaction prediction information corresponding to the transaction, and the original holder of the transaction is a user holding the target digital asset before the transaction; writing the transaction prediction information corresponding to the current transaction into a alliance chain;

a judgment result storage module, configured to verify, according to the transaction result of the target digital asset in the current transaction, transaction prediction information corresponding to a last transaction of the current transaction, to obtain a prediction judgment result of the transaction prediction information corresponding to the last transaction, where the prediction judgment result is used as a prediction judgment result corresponding to the last transaction; writing the prediction judgment result corresponding to the last transaction into the alliance chain;

and the evaluation module is used for evaluating the target digital asset according to the transaction prediction information and the prediction judgment result which respectively correspond to each transaction of the target digital asset in the alliance chain.

Optionally, the prediction information storage module is specifically configured to:

the judgment result storage module is specifically configured to:

Optionally, the apparatus further comprises:

and the rewarding module is used for giving rewarding assets to the original holder of the last transaction according to the transaction price of the target digital asset in the current transaction and/or the transaction price of the target digital asset in the last transaction when the prediction judgment result corresponding to the last transaction represents that the transaction prediction information corresponding to the last transaction is correct.

the reward module is specifically configured to:

Optionally, the apparatus further comprises:

the prediction time control module is used for determining a time difference value between the current time and the time when the transaction is ended; and judging whether the time difference exceeds a prediction time threshold, if so, not allowing the original holder of the transaction to give transaction prediction information for the target digital asset.

Optionally, the evaluation module is specifically configured to:

A third aspect of the present application provides an apparatus comprising: a processor and a memory:

the memory is used for storing a computer program and transmitting the computer program to the processor;

the processor is configured to execute the digital asset assessment method according to the first aspect, according to the computer program.

A fourth aspect of the present application provides a computer-readable storage medium for storing a computer program for executing the digital asset assessment method of the first aspect.

A fifth aspect of the present application provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the digital asset assessment method of the first aspect described above.

According to the technical scheme, the embodiment of the application has the following advantages:

the embodiment of the application provides a digital asset evaluation method, in the process of evaluating digital assets, transaction prediction information given by an original holder of the digital assets aiming at the digital assets and a prediction judgment result corresponding to the transaction prediction information are innovatively introduced, and the transaction prediction information given by the original holder of the digital assets has higher reference significance for the evaluation of the digital assets because the original holder of the digital assets generally understands the change situation of the digital assets in the market more deeply; in addition, the prediction judgment result corresponding to the transaction prediction information is introduced into the evaluation of the digital assets, so that the trader can be helped to combine the transaction prediction information and the prediction judgment result corresponding to the transaction prediction information to know the digital assets, and the evaluation result of the digital assets can provide higher reference value and guidance value for the trader.

Drawings

FIG. 1 is an overall framework diagram of a digital asset transaction provided by an embodiment of the present application;

FIG. 2 is a schematic diagram of a transaction preparation layer provided by an embodiment of the present application;

FIG. 3 is a schematic flow chart diagram of a digital asset assessment method provided by an embodiment of the present application;

FIG. 4 is a schematic diagram illustrating an implementation process of a digital asset assessment method according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a digital asset assessment device according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a server according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the 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.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any 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.

In the related technology, a trading platform and a third-party professional organization adopt a specific model to evaluate the digital assets according to historical trading data of the digital assets, and the reference value and the guidance value of the digital asset evaluation result obtained in the way are generally not high. The reason for this is that, on one hand, the trading platform and the third-party professional institution do not deeply recognize the factors such as market performance, market risk, trading profit opportunities and the like of the digital assets, so that the reference value of the obtained digital asset evaluation result is not high; on the other hand, when the trading platform and the third-party professional organization evaluate the digital assets, the historical trading data of the digital assets are used as the basis, and the trading prediction information of the market is lacked, so that the guidance value of the obtained digital asset evaluation result is not high.

In order to solve the problems in the related art, the embodiment of the application provides a digital asset assessment method, in the process of assessing digital assets, transaction prediction information of a trader on the digital assets and a prediction judgment result corresponding to the transaction prediction information are introduced, so that the obtained digital asset assessment result can have higher reference value and guidance value.

Specifically, in the digital asset evaluation method provided in the embodiment of the present application, after each transaction for a target digital asset is completed, transaction prediction information given by an original holder of the transaction (a user holding the target digital asset before the transaction) for the target digital asset is obtained and used as transaction prediction information corresponding to the transaction, and the transaction prediction information corresponding to the transaction is written into a federation chain; in addition, the transaction prediction information corresponding to the last transaction of the current transaction is verified according to the transaction result of the target digital asset in the current transaction, the prediction judgment result of the transaction prediction information corresponding to the last transaction is determined and used as the prediction judgment result corresponding to the last transaction, and the prediction judgment result corresponding to the last transaction is written into the alliance chain; further, the target digital asset may be evaluated based on the transaction prediction information and prediction determination results corresponding to each transaction of the target digital asset in the federation chain.

In the process of evaluating the digital asset, transaction prediction information given by an original holder of the digital asset aiming at the digital asset and a prediction judgment result corresponding to the transaction prediction information are innovatively introduced. Because the original holder of the digital asset generally understands the changing condition of the digital asset in the market more deeply, the transaction prediction information given by the original holder of the digital asset has higher reference significance for the evaluation of the digital asset, and the transaction prediction information corresponding to each transaction is introduced into the digital asset evaluation framework, so that the integrity of the digital asset evaluation framework can be continuously improved. And the prediction judgment result corresponding to the transaction prediction information is introduced into the evaluation of the digital assets, so that the trader can be helped to evaluate the digital assets by combining the transaction prediction information and the corresponding prediction judgment result. In this way, the evaluation result of the digital assets can be guaranteed to provide higher reference value and guidance value for the trader.

It should be understood that the executing subject of the above-described digital asset assessment method may be a device having alliance chain access rights, such as a terminal device or a server. The terminal device can be a smart phone, a computer, a tablet computer, a personal digital assistant and the like; the server may specifically be an application server or a Web server, and in actual deployment, the server may be an independent server or a cluster server.

To facilitate understanding of the digital asset assessment method provided in the embodiments of the present application, an overall framework of digital asset transactions is described below.

Referring to fig. 1, fig. 1 is a schematic diagram of an overall framework of a digital asset transaction provided by an embodiment of the present application. As shown in fig. 1, the overall framework of digital asset transaction is divided into two layers, namely a transaction preparation layer and an asset transaction layer, and in practical application, the implementation of the transaction preparation layer and the asset transaction layer is based on a federation chain system.

The transaction preparation layer is used for providing an implementation basis for the transaction of the digital assets, wherein the implementation basis comprises a digital asset creation stage, a digital asset registration stage, a digital asset pricing stage and a digital asset distribution stage.

To facilitate understanding of the specific implementation of the transaction preparation layer, the following describes an exemplary implementation of the transaction preparation layer with reference to the schematic diagram of the transaction preparation process shown in fig. 2, taking the receivable item as an original asset as an example. As shown in fig. 2, the business a and the business B may form an account receivable C through a transaction form of product sale and purchase based on a real trade background, and the business a may initiate a warranty service with respect to the account C; after the money C enters a digital asset transaction environment, for example, after entering a certain transaction platform P, transaction preparation needs to be completed through multiple links of data submission, joint right confirmation, cross validation, asset registration, asset release and the like, and then the work of a transaction preparation layer in FIG. 1 is completed; in the trading platform P, after the money C is converted into the digital asset D through the series of standardized processes, a hang slip can be issued in the open market of the trading platform P to represent that the digital asset D can enter a subsequent asset trading link.

The asset trading layer supports multiple trades of issued digital assets, and the digital asset evaluation method provided by the embodiment of the application is applied to the asset trading layer. In the process of multiple transactions of digital assets, transaction prediction information given by a user holding the digital assets before the transaction for the digital assets by the digital asset evaluation method provided by the embodiment of the application for the digital assets is obtained as transaction prediction information corresponding to the transaction for the digital assets after each transaction for the digital assets is finished, and the transaction prediction information is written into a alliance chain; meanwhile, the transaction prediction information corresponding to the last transaction can be verified according to the transaction result of the digital assets in the transaction to obtain the prediction judgment result of the transaction prediction information corresponding to the last transaction, and the prediction judgment result is used as the prediction judgment result corresponding to the transaction and is also written into the alliance chain; furthermore, transaction prediction information and prediction judgment results which are recorded in a alliance chain and correspond to each transaction of the digital assets can be provided for the trader, transaction reference information for the digital assets is provided for the trader, and the trader is helped to evaluate the digital assets better.

The digital asset assessment method provided by the present application is described below by way of example.

Referring to fig. 3, fig. 3 is a schematic flow chart of a digital asset assessment method according to an embodiment of the present application. For convenience of description, the following embodiments are described taking a server as an execution subject. As shown in fig. 3, the digital asset assessment method includes:

step 301: after each transaction of a target digital asset is finished, acquiring transaction prediction information given by an original holder of the transaction aiming at the target digital asset, and taking the transaction prediction information as corresponding transaction prediction information of the transaction, wherein the original holder of the transaction is a user holding the target digital asset before the transaction; and writing the transaction prediction information corresponding to the transaction into a alliance chain.

The user holding the target digital asset sells the target digital asset to other users, and the transfer of the target digital asset is completed, so that the target digital asset can be regarded as the end of one transaction aiming at the target digital asset. In this transaction, the user who originally holds the target digital asset (i.e., the seller of the target digital asset) is regarded as the original holder of this transaction in this application.

After one transaction for the target digital asset is finished, the transaction platform can prompt the original holder of the transaction to give out transaction prediction information for the target digital asset, namely prompt the original holder of the transaction to predict the transaction result of the target digital asset in the next transaction. Accordingly, the original holder of the transaction can give the transaction prediction information for the target digital asset based on the knowledge of the original holder of the transaction about the variation situation of the target digital asset in the market.

In specific implementation, the server can acquire transaction prediction information given by the original holder of the transaction through the intelligent contract. The transaction platform can set several transaction prediction options in advance through the intelligent contract, such as UP for target digital asset price, down for target digital asset price and HOLD for target digital asset price, and when the original holder of the transaction predicts the transaction result of the target digital asset in the next transaction, one option which is in accordance with the expectation of the original holder of the transaction can be selected as the transaction prediction information provided by the original holder of the transaction.

Of course, in some cases, the transaction prediction option may not be given to the original holder of the current transaction, but the original holder of the current transaction directly gives the transaction prediction information, and the method for giving the transaction prediction information to the original holder of the current transaction is not limited in this application.

And after acquiring the transaction prediction information given by the original holder of the transaction, the server takes the transaction prediction information as the transaction prediction information corresponding to the transaction, and writes the transaction prediction information into the alliance chain. Specifically, after acquiring the transaction prediction information given by the original holder of the transaction through the intelligent contract, the server may encrypt the intelligent contract by using the private key, write the encrypted intelligent contract into the alliance chain, and broadcast the message to the whole network.

In some embodiments, in order to encourage the original holder of the transaction to give a prediction about the price change direction of the target digital asset, and at the same time, to ensure the accuracy of the prediction, the method provided in the embodiments of the present application further provides a reward mechanism. The original holder of the transaction is allowed to set an incentive proportion through an intelligent contract, such as 5% of the whole transaction price of the target digital asset, 10% of the transaction spread of the target digital asset and the like, and if the transaction prediction information given by the original holder of the transaction is verified to be correct according to the next transaction result of the target digital asset, the transaction platform can endow the original holder of the transaction with the incentive asset according to the incentive proportion.

It should be noted that, in consideration of the compliance problem of financial asset trading, an upper limit is usually set for the above reward rate, such as 10% of the total trading price of the target digital asset, 20% of the trading spread of the target digital asset, etc. In practical application, the reward proportion can be set by the first holder of the target digital asset, subsequent transactions reward the original holder of the last transaction according to the reward proportion, a fixed reward proportion can be set by the transaction platform, and the method for setting the reward proportion is not limited in any way.

In some embodiments, the transaction platform and the first holder of the target digital asset may further set a predictive time threshold, and the original holder of the current transaction is required to give out transaction prediction information within the predictive time threshold, so as to ensure that the transaction prediction information can be obtained in time. Specifically, after one transaction for the target digital asset is finished, the server may continuously determine a time difference between the current time and the time when the transaction is finished before obtaining the transaction prediction information given by the original holder of the transaction, and determine whether the time difference exceeds a predicted time threshold, and if so, the original holder of the transaction is not allowed to give the transaction prediction information for the target digital asset.

For example, if the predicted time threshold is one hour, the server allows the original holder of the current transaction to give the transaction prediction information within one hour after the current transaction is ended, and if the predicted time threshold exceeds the hour, the server does not receive the transaction prediction information given by the original holder of the current transaction any more.

In practical application, after the holder of the transaction completes the setting of parameters such as transaction prediction information and reward proportion through an intelligent contract, the server can generate a quintuple < target digital asset encryption information, an original holder account, the transaction prediction information, the reward proportion and a prediction time threshold > based on the intelligent contract, wherein the target digital asset encryption information is information obtained by encrypting information related to the transaction of the target digital asset; and further, generating a plaintext abstract 'target digital asset type, reward proportion and prediction time threshold' based on the quintuple, and broadcasting the message to the whole network after carrying out private key signature by the server.

Step 302: after each transaction of a target digital asset is finished, verifying transaction prediction information corresponding to the last transaction of the current transaction according to the transaction result of the target digital asset in the current transaction to obtain a prediction judgment result of the transaction prediction information corresponding to the last transaction, wherein the prediction judgment result is used as the prediction judgment result corresponding to the last transaction; and writing the prediction judgment result corresponding to the last transaction into the alliance chain.

After one transaction of the target digital asset is finished, the server can verify the transaction prediction information corresponding to the last transaction according to the transaction result of the target digital asset in the transaction, namely verify the transaction prediction information given by the original holder of the last transaction, so that a prediction judgment result of the transaction prediction information corresponding to the last transaction is obtained, and the prediction judgment result can represent whether the transaction prediction information corresponding to the last transaction is correct or not. And correspondingly writing the prediction judgment result into the alliance chain as the prediction judgment result corresponding to the last transaction.

During specific implementation, after determining that one transaction for the target digital asset is finished, the server can start an intelligent contract, and judges transaction prediction information corresponding to the last transaction according to the transaction result of the target digital asset in the current transaction so as to determine the prediction judgment result of the transaction prediction information corresponding to the last transaction.

In some embodiments, the transaction prediction information may include any of: UP for a target digital asset price, DOWN for a target digital asset price, and HOLD for a target digital asset price. When the server verifies the transaction prediction information corresponding to the last transaction, the transaction price of the target digital asset in the current transaction can be acquired as a first transaction price, and the transaction price of the target digital asset in the last transaction is acquired as a second transaction price.

Under the condition that the transaction prediction information corresponding to the last transaction is the UP of the price of the target digital asset, if the first transaction price is higher than the second transaction price, the prediction judgment result of the transaction prediction information corresponding to the last transaction can be determined to be correct; on the contrary, if the first transaction price is not higher than the second transaction price, the prediction judgment result of the transaction prediction information corresponding to the last transaction can be determined to be wrong.

Under the condition that the transaction prediction information corresponding to the last transaction is that the price of the target digital asset falls DOWN, if the first transaction price is lower than the second transaction price, the prediction judgment result of the transaction prediction information corresponding to the last transaction can be determined to be correct; on the contrary, if the first transaction price is not lower than the second transaction price, the prediction judgment result of the transaction prediction information corresponding to the last transaction can be determined to be wrong.

Under the condition that the transaction prediction information corresponding to the last transaction is the target digital asset price balance HOLD, if the first transaction price is equal to the second transaction price, the prediction judgment result of the transaction prediction information corresponding to the last transaction can be determined to be correct; otherwise, if the first transaction price is not equal to the second transaction price, the prediction judgment result of the transaction prediction information corresponding to the last transaction can be determined to be wrong.

As introduced above, to encourage the owner of each transaction to give a prediction of the direction of change of the price of the target digital asset, while ensuring the accuracy of the prediction, the method provided by the embodiments of the present application further supports awarding the right owner of the prediction. Specifically, when the prediction judgment result corresponding to the previous transaction represents that the transaction prediction information corresponding to the previous transaction is correct, the server may give the incentive asset to the original holder of the previous transaction according to the transaction price of the target digital asset in the current transaction and/or the transaction price of the target digital asset in the previous transaction.

In a possible implementation manner, when the transaction prediction information corresponding to the last transaction is UP of the price of the target digital asset, and the prediction judgment result of the transaction prediction information indicates that the transaction prediction information is correct, the server may determine, according to the first reward proportion and the difference between the first transaction price and the second transaction price, the reward asset that needs to be given to the original holder of the last transaction. That is, the product of the first reward rate and the difference between the first transaction price and the second transaction price is calculated as the reward asset.

When the transaction prediction information corresponding to the last transaction is that the price of the target digital asset drops DOWN and the prediction judgment result of the transaction prediction information indicates that the transaction prediction information is correct, the server can determine the rewarding asset required to be given to the original holder of the last transaction according to the second rewarding proportion and the difference value between the second transaction price and the first transaction price. That is, the product of the second award proportion and the difference between the second transaction price and the first transaction price is calculated as the award asset.

When the transaction prediction information corresponding to the last transaction is the target digital asset price balance HOLD and the prediction judgment result of the transaction prediction information represents that the transaction prediction information is correct, the server can determine the rewarding asset required to be given to the original holder of the last transaction according to the third rewarding proportion and the first transaction price or the second transaction price. That is, the product of the third award proportion and the first transaction price is calculated as the bonus asset, or the product of the third award proportion and the second transaction price is calculated as the bonus asset.

In practical applications, the first award ratio, the second award ratio and the third award ratio may be the same or different, and specific values of the first award ratio, the second award ratio and the third award ratio are not limited in any way herein. In addition, as described above, the first reward proportion, the second reward proportion, and the third reward proportion may be set by the original holder of the last transaction or the first holder of the target digital asset through the smart contract, or may be fixedly configured by the transaction platform.

It should be noted that the above implementation manner of calculating the bonus asset is only an example, in practical applications, the trading platform may also provide for calculating the bonus asset according to the bonus proportion or the trading price of the target digital asset in the current trading, or provide for calculating the bonus asset according to the bonus proportion or the trading price of the target digital asset in the last trading, or directly provide a fixed asset as the bonus asset, and the present application does not limit the determination manner of the bonus asset.

It should be appreciated that if the prediction result corresponding to the previous transaction indicates that the transaction prediction information corresponding to the previous transaction is incorrect, the original holder of the previous transaction does not need to be given the bonus asset.

In practice, the reward asset may be paid by the original holder in the transaction up to the original holder of the previous transaction. That is, if it is determined through the above operation that the transaction prediction information corresponding to the previous transaction is correct, the original holder of the current transaction needs to pay the reward asset to the original holder of the previous transaction. Of course, the aforementioned rewarding asset may also be paid by the first holder of the target digital asset, for example, the first holder of the target digital asset may specify the rewarding asset in advance, and if it is determined that the transaction prediction information corresponding to the previous transaction is correct, part or all of the rewarding asset may be paid to the original holder of the previous transaction.

Optionally, the bonus results may also be written by the server into the federation chain.

Step 303: and evaluating the target digital assets according to the transaction prediction information and the prediction judgment result which are respectively corresponding to each transaction of the target digital assets in the alliance chain.

Through

steps

301 and 302, when each transaction for the target digital asset is finished, the server obtains transaction prediction information given by the original holder of the current transaction through the intelligent contract, and judges the transaction prediction information given by the original holder of the last transaction through the intelligent contract to obtain a corresponding prediction judgment result, so that transaction prediction information and a prediction judgment result corresponding to each transaction for the target digital asset are obtained. For potential traders of the target digital asset, the server can correspondingly evaluate the target digital asset according to the trading prediction information and the prediction judgment result which are recorded in the alliance chain and respectively correspond to each trade of the target digital asset.

In some embodiments, the server may generate a transaction prediction information sequence for the target digital asset according to the transaction prediction information recorded in the alliance chain and corresponding to each transaction for the target digital asset; generating a prediction judgment result sequence aiming at the target digital asset according to the prediction judgment result which is recorded in the alliance chain and respectively corresponds to each transaction aiming at the target digital asset; and evaluating the target digital assets according to the transaction prediction information sequence and the prediction judgment result sequence.

In a possible implementation manner, the server may directly provide the trader who pays attention to the target digital asset with a trading prediction information sequence and a prediction judgment result sequence corresponding to the target digital asset, so that the trader can measure the value of the target digital asset according to the trading prediction information sequence and the prediction judgment result sequence corresponding to the target digital asset.

In another possible implementation manner, the server may use a specific asset evaluation model to evaluate the target digital asset according to the transaction prediction information sequence and the prediction judgment result sequence corresponding to the target digital asset, generate a corresponding digital asset evaluation result, and provide the digital asset evaluation result corresponding to the target digital asset to the trader who pays attention to the target digital asset.

In practical application, the server may also evaluate the target digital asset in other manners according to the transaction prediction information sequence and the prediction judgment result sequence corresponding to the target digital asset, and the specific implementation manner of evaluating the target digital asset by the server is not limited in this application.

According to the digital asset evaluation method provided by the embodiment of the application, in the process of evaluating the digital asset, transaction prediction information given by an original holder of the digital asset aiming at the digital asset and a prediction judgment result corresponding to the transaction prediction information are innovatively introduced. Because the original holder of the digital asset generally understands the changing condition of the digital asset in the market more deeply, the transaction prediction information given by the original holder of the digital asset has higher reference significance for the evaluation of the digital asset, and the transaction prediction information corresponding to each transaction is introduced into the digital asset evaluation framework, so that the integrity of the digital asset evaluation framework can be continuously improved. And the prediction judgment result corresponding to the transaction prediction information is introduced into the evaluation of the digital assets, so that the trader can be helped to evaluate the digital assets by combining the transaction prediction information and the corresponding prediction judgment result. In this way, the evaluation result of the digital assets can be guaranteed to provide higher reference value and guidance value for the trader.

In order to further understand the digital asset assessment method provided by the embodiments of the present application, an implementation process of the digital asset assessment method is exemplarily described below with reference to fig. 4.

After the target digital asset D enters a transaction link, a seller of the target digital asset D in each transaction can be defined as a front-hand (namely the original holder of the transaction), a buyer of the target digital asset D in each transaction is defined as a back-hand, the back-hand of the last transaction is actually the front-hand of the transaction, and after each transaction of the target digital asset D is finished, the front-hand of the transaction predicts the transaction of the target digital asset D.

In the implementation process shown in fig. 4, a transaction for a target digital asset D is represented by e, n represents the number of transactions, and a plurality of transactions constitute a transaction sequence consisting of e1, e2, … … and en; representing the trader of the target digital asset D by s, wherein a plurality of trades form a trader sequence consisting of s1, s2, … … and sn; the trade prediction information given by the trader is represented by f, the trade prediction information given by the trader s1 is represented by f1, the trade prediction information given by the trader s2 is represented by f2, and the like, a plurality of trades form a trade prediction information sequence consisting of f1, f2, … … and fn-1.

As shown in fig. 4, the first transaction for target digital asset D corresponds to e1, and s1 is the first trader of the target digital asset, which may be the original holder of the target digital asset D, or the user who purchased the target digital asset D from the original holder after the target digital asset D entered the trading platform. s1 transfers the target digital asset D to s2 through e1, and completes the process of e1, in which s1 is the front hand and s2 is the back hand, and the transaction price of the target digital asset D in the transaction is marked as p 1.

The method comprises the steps that a former needs to give transaction prediction information aiming at a target digital asset D after transaction is finished, the transaction prediction information can be set through an intelligent contract, the method can set UP the price rising UP of the target digital asset, the price falling DOWN of the target digital asset and the HOLD HOLD of the target digital asset, and after the former gives the transaction prediction information through the intelligent contract, the transaction prediction information is written into a message which needs to be broadcasted in a alliance chain.

In order to encourage the forehand to give a prediction for the price change direction of the target digital asset D and ensure the accuracy level of the prediction, the method can be provided with a reward mechanism, and allow the forehand to set a reward proportion r through an intelligent contract.

In e2, s2 transfers the target digital asset D to s 3. And e2, obtaining the transaction price p2 of the target digital asset in the transaction, and the server can start an intelligent contract to judge the transaction prediction information given by s 1.

Specifically, if p2 > p1, the price of the target digital asset D is considered to be increased, and the bonus asset B may be calculated as (p2-p1) × r; if p2 < p1, the price of the target digital asset D is deemed to have dropped and a bonus asset B may be calculated (p1-p2) r; if p2 is p1, the price of the target digital asset D is considered to be equal, and the bonus asset B may be calculated as p1 r.

And if the transaction prediction information given by s1 is determined to be correct according to the relation between p2 and p1, starting the intelligent contract, paying the reward asset B for s1 by s2, and particularly completing the payment of the reward asset B through the intelligent contract in a TOKEN chain in a TOKEN mode. If it is determined that the transaction prediction information given at s1 is erroneous according to the relationship between p2 and p1, then it is not necessary to pay bonus asset B for s 1.

Repeating the above process, the forehand of each transaction gives out transaction prediction information, the intelligent contract judges whether the transaction prediction information is correct according to the transaction result of the next transaction, and the reward asset is paid for the forehand by the backhand under the correct condition. Therefore, a transaction prediction information sequence, a prediction judgment result sequence and an incentive asset sequence corresponding to n transactions are formed, and reference information is provided for other traders when evaluating the target digital asset D. Furthermore, the transaction prediction information sequence, the prediction judgment result sequence and the reward asset sequence can be written into the account book according to a transaction summary mechanism corresponding to the alliance chain, and a block is generated and linked to the main chain.

The embodiment of the application also provides a digital asset evaluation device. Referring to fig. 5, fig. 5 is a schematic structural diagram of a digital asset evaluation device according to an embodiment of the present application, and as shown in fig. 5, the device includes:

a prediction information storage module 501, configured to, after each transaction for a target digital asset is finished, obtain transaction prediction information, which is given by an original holder of the current transaction for the target digital asset and is used as transaction prediction information corresponding to the current transaction, where the original holder of the current transaction is a user holding the target digital asset before the current transaction; writing the transaction prediction information corresponding to the current transaction into a alliance chain;

a judgment result storage module 502, configured to verify, according to the transaction result of the target digital asset in the current transaction, transaction prediction information corresponding to a last transaction of the current transaction, to obtain a prediction judgment result of the transaction prediction information corresponding to the last transaction, where the prediction judgment result is used as a prediction judgment result corresponding to the last transaction; writing the prediction judgment result corresponding to the last transaction into the alliance chain;

an evaluating module 503, configured to evaluate the target digital asset according to the transaction prediction information and the prediction determination result that correspond to each transaction of the target digital asset in the alliance chain.

Optionally, the prediction information storage module 501 is specifically configured to:

the judgment result storage module 502 is specifically configured to:

Optionally, the apparatus further comprises:

the reward module is specifically configured to:

Optionally, the apparatus further comprises:

Optionally, the evaluation module 503 is specifically configured to:

According to the digital asset evaluation device provided by the embodiment of the application, in the process of evaluating the digital asset, transaction prediction information given by an original holder of the digital asset aiming at the digital asset and a prediction judgment result corresponding to the transaction prediction information are innovatively introduced. Because the original holder of the digital asset generally understands the changing condition of the digital asset in the market more deeply, the transaction prediction information given by the original holder of the digital asset has higher reference significance for the evaluation of the digital asset, and the transaction prediction information corresponding to each transaction is introduced into the digital asset evaluation framework, so that the integrity of the digital asset evaluation framework can be continuously improved. And the prediction judgment result corresponding to the transaction prediction information is introduced into the evaluation of the digital assets, so that the trader can be helped to evaluate the digital assets by combining the transaction prediction information and the corresponding prediction judgment result. In this way, the evaluation result of the digital assets can be guaranteed to provide higher reference value and guidance value for the trader.

The embodiment of the present application further provides a device for evaluating a digital asset, where the device may specifically be a server and a terminal device, and the server and the terminal device provided in the embodiment of the present application will be described below from the perspective of hardware materialization.

Referring to fig. 6, fig. 6 is a schematic structural diagram of a server 600 according to an embodiment of the present disclosure. The server 600 may vary significantly due to configuration or performance, and may include one or more Central Processing Units (CPUs) 622 (e.g., one or more processors) and memory 632, one or more storage media 630 (e.g., one or more mass storage devices) storing applications 642 or data 644. Memory 632 and storage medium 630 may be, among other things, transient or persistent storage. The program stored in the storage medium 630 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Still further, the central processor 622 may be configured to communicate with the storage medium 630 and execute a series of instruction operations in the storage medium 630 on the server 600.

The server 600 may also include one or more power supplies 626, one or more wired or wireless network interfaces 650, one or more input-output interfaces 658, and/or one or more operating systems 641, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so forth.

The steps performed by the server in the above embodiments may be based on the server structure shown in fig. 6.

The CPU 622 is configured to execute the following steps:

Optionally, the CPU 622 can also be used to execute the steps of any implementation manner of the digital asset assessment method provided by the embodiment of the present application.

Referring to fig. 7, fig. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present application. For convenience of explanation, only the parts related to the embodiments of the present application are shown, and details of the specific technology are not disclosed. The terminal may be any terminal device including a computer, a tablet computer, a Personal Digital Assistant (PDA), and the like, taking the terminal as the computer as an example:

fig. 7 is a block diagram illustrating a partial structure of a computer related to a terminal provided in an embodiment of the present application. Referring to fig. 7, the computer includes: radio Frequency (RF) circuit 710, memory 720, input unit 730, display unit 740, sensor 750, audio circuit 760, wireless fidelity (WiFi) module 770, processor 780, and power supply 790. Those skilled in the art will appreciate that the computer architecture shown in FIG. 7 is not intended to be limiting of computers, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.

The memory 720 may be used to store software programs and modules, and the processor 780 performs various functional applications of the computer and data processing by operating the software programs and modules stored in the memory 720. The memory 720 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the computer, etc. Further, the memory 720 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 780 is a control center of the computer, connects various parts of the entire computer using various interfaces and lines, performs various functions of the computer and processes data by operating or executing software programs and/or modules stored in the memory 720 and calling data stored in the memory 720, thereby monitoring the entire computer. Optionally, processor 780 may include one or more processing units; preferably, the processor 780 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 780.

In the embodiment of the present application, the processor 780 included in the terminal further has the following functions:

Optionally, the processor 780 is further configured to perform the steps of any implementation of the digital asset evaluation provided in the embodiments of the present application.

The embodiment of the present application further provides a computer-readable storage medium for storing a computer program, where the computer program is used to execute any one implementation of the digital asset assessment method described in the foregoing embodiments.

The present application further provides a computer program product including instructions, which when run on a computer, causes the computer to execute any one of the embodiments of a digital asset assessment method described in the foregoing embodiments.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing computer programs.

The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims

1. A digital asset assessment method, said method comprising:

2. The method of claim 1, wherein the obtaining of the transaction prediction information given by the original holder of the current transaction for the target digital asset comprises:

3. The method of claim 1, wherein the transaction prediction information comprises any one of: the target digital asset price is rising, the target digital asset price is falling, and the target digital asset price is flat;

4. The method according to claim 1, wherein after the verifying the transaction prediction information corresponding to the last transaction of the current transaction according to the transaction result of the target digital asset in the current transaction to obtain the prediction judgment result of the transaction prediction information corresponding to the last transaction, the method further comprises:

5. The method of claim 4, wherein the transaction prediction information comprises any one of: the target digital asset price is rising, the target digital asset price is falling, and the target digital asset price is flat;

6. The method of claim 5, wherein the first reward rate, the second reward rate, and the third reward rate are set by an original holder of the last transaction or are fixedly configured by a transaction platform.

7. The method of claim 4, wherein the reward asset is paid by the archangel in the current transaction to the archangel of the previous transaction.

8. The method of claim 1, wherein prior to said obtaining transaction prediction information given by the owner of the current transaction for the target digital asset, the method further comprises:

9. The method of claim 1, wherein evaluating the target digital asset according to the transaction prediction information and prediction determination result corresponding to each transaction of the target digital asset in the federation chain comprises:

10. A digital asset assessment device, said device comprising:

11. The apparatus of claim 10, wherein the prediction information storage module is specifically configured to:

12. The apparatus of claim 10, wherein the transaction prediction information comprises any one of: the target digital asset price is rising, the target digital asset price is falling, and the target digital asset price is flat;

the judgment result storage module is specifically configured to:

13. The apparatus of claim 10, further comprising:

14. The apparatus of claim 13, wherein the transaction prediction information comprises any one of: the target digital asset price is rising, the target digital asset price is falling, and the target digital asset price is flat;

the reward module is specifically configured to:

15. The apparatus of claim 14, wherein the first award ratio, the second award ratio and the third award ratio are set by an original holder of the last transaction or fixedly configured by a transaction platform.

16. The apparatus of claim 13, wherein the reward asset is paid by the archangel in the current transaction to the archangel of the previous transaction.

17. The apparatus of claim 10, further comprising:

18. The apparatus of claim 10, wherein the evaluation module is specifically configured to:

19. An apparatus, characterized in that the apparatus comprises: a processor and a memory:

the processor is configured to execute the digital asset assessment method of any one of claims 1 to 9 in accordance with the computer program.

20. A computer-readable storage medium for storing a computer program for executing the digital asset assessment method of any one of claims 1 to 9.