CN116611695A - Digital asset risk assessment system based on interval fuzzy comprehensive evaluation - Google Patents
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Abstract
The invention provides a digital asset risk assessment system based on interval fuzzy comprehensive assessment, which comprises a data acquisition module, a data storage module, an interval fuzzy module and a risk assessment module, wherein the data acquisition module is used for acquiring transaction data of digital assets, the data storage module is used for storing the transaction data of the digital assets, the interval fuzzy module is used for analyzing the transaction data to obtain a fuzzy interval, and the risk assessment module is used for assessing the risk of the digital assets based on the fuzzy interval; the system analyzes transaction information of the digital asset from multiple angles through the interval blurring module to finally obtain an interval capable of reflecting risks, and finally evaluates the digital asset based on the interval to obtain an evaluation value capable of reflecting real risk conditions.
Description
Technical Field
The invention relates to the field of electric digital data processing, in particular to a digital asset risk assessment system based on interval fuzzy comprehensive evaluation.
Background
With the development of digital currency, more and more physical assets are converted into digital assets to perform investment or warranty, but the supervision of the digital assets is imperfect, and a larger risk exists in the investment process, so that a risk assessment system for the digital assets is needed to help investors perform the investment of the digital assets better.
The foregoing discussion of the background art is intended to facilitate an understanding of the present invention only. This discussion is not an admission or admission that any of the material referred to was common general knowledge.
A number of digital asset risk assessment systems have now been developed, and through extensive search and reference we have found that existing risk assessment systems have a system as disclosed in publication No. CN115983645a, which generally comprises the steps of: s1, gathering exposed digital assets and track information of enterprises; s2, identifying an influence factor which has influence on each digital asset; setting a weight value of the association influence factor by analyzing the association factor between the influence factor and the asset, and then calculating the risk influence degree of other assets on the appointed asset; and S3, according to the hazard degree of all the association factors of a certain digital asset, the weight value of the influence factor and the value factor of the asset, the risk assessment result of the digital asset can be obtained through assessment and calculation. However, the system adopts specific values when performing risk assessment, and the risk has uncertainty, so that the accuracy of the obtained assessment value needs to be improved.
Disclosure of Invention
The invention aims to provide a digital asset risk assessment system based on interval fuzzy comprehensive assessment aiming at the defects.
The invention adopts the following technical scheme:
a digital asset risk assessment system based on interval fuzzy comprehensive evaluation comprises a data acquisition module, a data storage module, an interval fuzzy module and a risk assessment module;
the data acquisition module is used for acquiring transaction data of the digital asset, the data storage module is used for storing the transaction data of the digital asset, the interval blurring module is used for analyzing the transaction data to obtain a blurring interval, and the risk assessment module is used for assessing the risk of the digital asset based on the blurring interval;
the data acquisition module comprises a data source interface unit, a data acquisition unit, a data cache unit and a data cleaning unit, wherein the data source interface unit is used for establishing communication connection with a trading center or a platform of the digital asset, the data acquisition unit is used for acquiring original data information of a purchase order, a sell order and a deal order from the trading center or the platform, the data cache unit is used for temporarily storing the original data information, and the data cleaning unit is used for analyzing and cleaning the original data information to obtain effective and uniform data;
the interval blurring module comprises a daily order analysis unit, a price analysis unit and a comprehensive blurring unit, wherein the daily order analysis unit is used for analyzing and processing daily order information, the price analysis unit is used for analyzing and processing price fluctuation of digital assets, and the comprehensive blurring unit is used for analyzing and obtaining a blurring interval；
The risk assessment module comprises an assessment information interaction processor and a risk assessment processor, wherein the assessment information interaction processor is used for inputting digital asset information and sending a fuzzy instruction to the interval fuzzy module, and the risk assessment processor calculates a risk value Q of the digital asset according to the following formula:
；
wherein a and b are respectively a first quantization base value and a second quantization base value, and M is a digital asset quantization value to be evaluated;
further, the daily order analysis unit comprises a daily data processor, a daily total amount processor, a buying demand processor and a selling demand processor, wherein the daily data processor is used for calculating the daily total amount Tv3 of the deals and the daily buying demand ratioSell demand ratio for a single day +.>The transaction total processor analyzes and processes the change condition of the transaction total to obtain a transaction cold-hot index P1, and the transaction total processor buys the transaction cold-hot index P1 at the position of the demandThe processor analyzes and processes the change condition of the buying demand ratio to obtain a buying cold and hot index P2, and the sell demand processor analyzes and processes the change condition of the sell demand ratio to obtain a sell cold and hot index P3;
further, the price analysis unit comprises a price equalizing register and a price processor, wherein the price equalizing register receives and stores daily transaction price equalizing data, and the price processor calculates daily rise and fall amplitude according to the following formula：
；
Wherein day represents a specific date, pu (day) represents a day's average price for the day's transaction;
the price processor calculates a volatility index P4 according to the following formula:
；
wherein RC represents a set of dates, m is the number of days contained in the RC set, d 0 Is the rise and fall threshold;
further, the comprehensive blurring unit calculates a blurring value Vague according to the following formula:
；
wherein,% is the remainder symbol;
when Vague is less than or equal to 5, the Vague sectionIs->；
When Vague is greater than 5, the section is blurredIs->；
Further, the data cleaning unit comprises an order recognition processor, an order transaction processor and a data format processor, wherein the order recognition processor is used for recognizing a buying order and a selling order, when recognizing that the order is obtained by modifying an original order, original order information is deleted, the order transaction processor is used for recognizing a bargain order, buying order and selling order information corresponding to the bargain order are deleted, and the data format processor is used for carrying out format unification processing on all order data in the data caching unit at fixed time.
The beneficial effects obtained by the invention are as follows:
the system analyzes four angles of the trading volume, the buying demand ratio, the selling demand ratio and the trading average price to obtain four indexes, calculates a fuzzy interval based on the four indexes, can reflect the uncertainty of risks and the size of the risks, and finally obtains a final risk value based on the fuzzy interval, so that the risk of the digital asset can be accurately reflected.
For a further understanding of the nature and the technical aspects of the present invention, reference should be made to the following detailed description of the invention and the accompanying drawings, which are provided for purposes of reference only and are not intended to limit the invention.
Drawings
FIG. 1 is a schematic diagram of the overall structural framework of the present invention;
FIG. 2 is a schematic diagram of a data acquisition module according to the present invention;
FIG. 3 is a schematic diagram of the section blurring module according to the present invention;
FIG. 4 is a schematic diagram showing the construction of the daily order analysis unit according to the present invention.
Detailed Description
The following embodiments of the present invention are described in terms of specific examples, and those skilled in the art will appreciate the advantages and effects of the present invention from the disclosure herein. The invention is capable of other and different embodiments and its several details are capable of modification and variation in various respects, all without departing from the spirit of the present invention. The drawings of the present invention are merely schematic illustrations, and are not intended to be drawn to actual dimensions. The following embodiments will further illustrate the related art content of the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
Embodiment one: the embodiment provides a digital asset risk assessment system based on interval fuzzy comprehensive evaluation, which comprises a data acquisition module, a data storage module, an interval fuzzy module and a risk assessment module, and is combined with fig. 1;
the data acquisition module is used for acquiring transaction data of the digital asset, the data storage module is used for storing the transaction data of the digital asset, the interval blurring module is used for analyzing the transaction data to obtain a blurring interval, and the risk assessment module is used for assessing the risk of the digital asset based on the blurring interval;
the data acquisition module comprises a data source interface unit, a data acquisition unit, a data cache unit and a data cleaning unit, wherein the data source interface unit is used for establishing communication connection with a trading center or a platform of the digital asset, the data acquisition unit is used for acquiring original data information of a purchase order, a sell order and a deal order from the trading center or the platform, the data cache unit is used for temporarily storing the original data information, and the data cleaning unit is used for analyzing and cleaning the original data information to obtain effective and uniform data;
the interval blurring module comprises a daily order analysis unit, a price analysis unit and a comprehensive blurring unit, wherein the daily order analysis unit is used for analyzing and processing daily order information, the price analysis unit is used for analyzing and processing price fluctuation of digital assets, and the comprehensive blurring unit is used for analyzing and obtaining a blurring interval；
The risk assessment module comprises an assessment information interaction processor and a risk assessment processor, wherein the assessment information interaction processor is used for inputting digital asset information and sending a fuzzy instruction to the interval fuzzy module, and the risk assessment processor calculates a risk value Q of the digital asset according to the following formula:
；
wherein a and b are respectively a first quantization base value and a second quantization base value, and M is a digital asset quantization value to be evaluated;
the daily order analysis unit comprises a daily data processor, a daily total amount processor, a buying demand processor and a selling demand processor, wherein the daily data processor is used for calculating the daily total amount Tv3 of the deals and the daily buying demand ratioSell demand ratio for a single day +.>The transaction total amount processor analyzes and processes the change condition of the transaction total amount to obtain a transaction cold and hot index P1, the purchase demand processor analyzes and processes the change condition of the purchase demand ratio to obtain a purchase cold and hot index P2, and the sell demand processor analyzes and processes the change condition of the sell demand ratio to obtain a sell cold and hot index P3;
the price analysis unit comprises a price equalizing register and a price processor, wherein the price equalizing register receives and stores daily transaction price equalizing data, and the price processor calculates daily rise and fall amplitude values according to the following formula：
；
Wherein day represents a specific date, pu (day) represents a day's average price for the day's transaction;
the price processor calculates a volatility index P4 according to the following formula:
；
wherein RC represents a set of dates, m is the number of days contained in the RC set, d 0 Is the rise and fall threshold;
the comprehensive blurring unit calculates a blurring value Vague according to the following formula:
；
wherein,% is the remainder symbol;
when Vague is less than or equal to 5, the Vague sectionIs->；
When Vague is greater than 5, the section is blurredIs->；
The data cleaning unit comprises an order identification processor, an order transaction processor and a data format processor, wherein the order identification processor is used for carrying out identification processing on a buying order and a selling order, when the fact that the order is obtained by modification of an original order is identified, original order information is deleted, the order transaction processor is used for carrying out identification processing on a closing order, buying order and selling order information corresponding to the closing order are deleted, and the data format processor is used for carrying out format unification processing on all order data in the data caching unit at fixed time.
Embodiment two: the embodiment comprises the whole content in the first embodiment, and provides a digital asset risk assessment system based on interval fuzzy comprehensive evaluation, which comprises a data acquisition module, a data storage module, an interval fuzzy module and a risk assessment module;
the data acquisition module is used for acquiring transaction data of the digital asset, the data storage module is used for storing the transaction data of the digital asset, the interval blurring module is used for analyzing the transaction data to obtain a blurring interval, and the risk assessment module is used for assessing the risk of the digital asset based on the blurring interval;
referring to fig. 2, the data acquisition module includes a data source interface unit, a data acquisition unit, a data buffer unit and a data cleaning unit, wherein the data source interface unit is used for establishing communication connection with a trading center or a platform of a digital asset, the data acquisition unit is used for acquiring raw data information of a purchase order, a sell order and a deal order from the trading center or the platform, the data buffer unit is used for temporarily storing the raw data information, and the data cleaning unit is used for analyzing and cleaning the raw data information to obtain effective and uniform data;
the purchase order refers to the number of digital assets which the buyer wants to buy at a fixed price, and comprises three pieces of information including purchase price, purchase quantity and purchase user, the sales order refers to the number of digital assets which the seller wants to sell at a fixed price, and comprises three pieces of information including sales price, sales quantity and sales user, and the deal order refers to the purchase order and the sell order which are matched, and comprises four pieces of information including deal price, deal quantity and deal party user;
the data cleaning unit comprises an order identification processor, an order transaction processor and a data format processor, wherein the order identification processor is used for carrying out identification processing on a buying order and a selling order, when the fact that the order is obtained by modification of an original order is identified, original order information is deleted, the order transaction processor is used for carrying out identification processing on a meeting order, buying order and selling order information corresponding to the meeting order is deleted, and the data format processor is used for carrying out format unification processing on all order data in the data cache unit at fixed time;
the process of the order recognition processor for recognizing the order comprises the following steps:
s1, detecting new order information;
s2, identifying user information and order types of the orders;
s3, searching whether a previous order with the same user information and order type exists in the data caching unit, if not, ending the processing procedure, and if so, entering a step S4;
s4, all the order information of the user is sent to the data source interface unit, and the data source interface order feeds back target order information which does not exist in the exchange or the platform;
s5, deleting the target order information in the data caching unit;
the data storage module divides a storage submodule for each type of digital asset, each storage submodule comprises an order information storage unit, a user information storage unit and a retrieval unit, the order information storage unit stores daily order information according to date, the user information storage unit is used for storing accumulated transaction amount of each user, and the retrieval unit is used for retrieving order information and user information;
referring to fig. 3, the interval ambiguity module includes a daily order analysis unit, a price analysis unit and a comprehensive ambiguity unit, wherein the daily order analysis unit is used for analyzing and processing daily order information, the price analysis unit is used for analyzing and processing price fluctuation of a digital asset, and the comprehensive ambiguity unit is used for analyzing and obtaining a final ambiguity interval;
referring to fig. 4, the daily order analysis unit includes a single day data processor that calculates the following data from daily order information:
；
；
；
；
；
wherein Tv1 is the total purchase amount, tv2 is the total sell amount, tv3 is the total deal amount, N1 is the number of purchase orders, N2 is the number of sell orders, N3 is the number of deal orders, am1 (i) is the purchase price of the ith purchase order, N1 (i) is the purchase number of the ith purchase order, am2 (i) is the sell price of the ith sell order, N2 (i) is the sell number of the ith sell order, am3 (i) is the deal price of the ith deal order, N3 (i) is the deal number of the ith deal order,for buying demand ratio, < >>For the sell demand ratio, i is the order number;
the single day data processor also calculates daily average price of the bargain and sends the average price to the price analysis unit;
referring to fig. 4, the daily order analysis unit includes a total amount of deals processor, a buying demand processor, and a selling demand processor, where the total amount of deals processor obtains a total amount of deals per day and analyzes and processes a change condition of the total amount of deals, the buying demand processor obtains a buying demand ratio per day and analyzes and processes a change condition of the buying demand ratio, and the selling demand processor obtains a selling demand ratio per day and analyzes and processes a change condition of the selling demand ratio;
the total transaction amount processor calculates a transaction cold and hot index P1 according to the following steps:
；
wherein, day represents a specific date, tv3 (day) represents the total amount of the day of day, RC represents a recent date set, PC represents a past date set, and the set judgment rules of RC and PC are set by the staff themselves, but the number of days contained in the two sets needs to be the same;
the buying demand processor calculates a buying cold and heat index P2 according to the following formula:
；
wherein, the liquid crystal display device comprises a liquid crystal display device,for the buying demand ratio average in RC aggregate period, +.>The standard deviation is compared with the buying demand in the RC set period;
the buying demand processor calculates the selling cold and hot index P3 according to the following:
；
wherein, the liquid crystal display device comprises a liquid crystal display device,for the selling demand ratio average in RC aggregate period, +.>The standard deviation is compared for the sell demand during the RC aggregate period;
the price analysis unit comprises a price equalizing register and a price processor, wherein the price equalizing register receives and stores daily transaction price equalizing data, and the price processor calculates daily rise and fall amplitude values according to the following formula：
；
Wherein Pu (day) represents the average price of the day's deals;
the price processor calculates a volatility index P4 according to the following formula:
；
wherein m is the number of days contained in the RC set, d 0 Is the rise and fall threshold;
the comprehensive fuzzy unit comprises a fuzzy processor and a data interaction processor, and the fuzzy processor calculates a final fuzzy value Vague according to the following formula:
；
when Vague is less than or equal to 5, the Vague sectionIs->；
When Vague is greater than 5, the section is blurredIs->；
The data interaction processor is used for outputting a fuzzy interval to the risk assessment module;
the risk assessment module comprises an assessment information interaction processor and a risk assessment processor, wherein the assessment information interaction processor is used for inputting digital asset information and sending a fuzzy instruction to the interval fuzzy module, and the risk assessment processor calculates a risk value Q of the digital asset according to the following formula:
；
wherein a and b are a first quantization base value and a second quantization base value respectively, which are set by a person skilled in the art, and M is a digital asset quantization value to be evaluated;
the larger the risk value, the greater the corresponding digital asset devaluation probability.
The foregoing disclosure is only a preferred embodiment of the present invention and is not intended to limit the scope of the invention, so that all equivalent technical changes made by applying the description of the present invention and the accompanying drawings are included in the scope of the present invention, and in addition, elements in the present invention can be updated as the technology develops.
Claims (5)
1. The digital asset risk assessment system based on the interval fuzzy comprehensive evaluation is characterized by comprising a data acquisition module, a data storage module, an interval fuzzy module and a risk assessment module;
the data acquisition module is used for acquiring transaction data of the digital asset, the data storage module is used for storing the transaction data of the digital asset, the interval blurring module is used for analyzing the transaction data to obtain a blurring interval, and the risk assessment module is used for assessing the risk of the digital asset based on the blurring interval;
the data acquisition module comprises a data source interface unit, a data acquisition unit, a data cache unit and a data cleaning unit, wherein the data source interface unit is used for establishing communication connection with a trading center or a platform of the digital asset, the data acquisition unit is used for acquiring original data information of a purchase order, a sell order and a deal order from the trading center or the platform, the data cache unit is used for temporarily storing the original data information, and the data cleaning unit is used for analyzing and cleaning the original data information to obtain effective and uniform data;
the interval blurring module comprises a daily order analysis unit, a price analysis unit and a comprehensive blurring unit, wherein the daily order analysis unit is used for analyzing and processing daily order information, the price analysis unit is used for analyzing and processing price fluctuation of digital assets, and the comprehensive blurring unit is used for analyzing and obtaining one piece of informationFuzzy intervals；
The risk assessment module comprises an assessment information interaction processor and a risk assessment processor, wherein the assessment information interaction processor is used for inputting digital asset information and sending a fuzzy instruction to the interval fuzzy module, and the risk assessment processor calculates a risk value Q of the digital asset according to the following formula:
；
wherein a and b are a first quantization base value and a second quantization base value respectively, and M is a digital asset quantization value to be evaluated.
2. The digital asset risk assessment system based on interval fuzzy comprehensive assessment according to claim 1, wherein the daily order analysis unit comprises a single day data processor, a transaction total amount processor, a buying demand processor and a selling demand processor, wherein the single day data processor is used for calculating a transaction total amount Tv3 of a single day and a buying demand ratio of a single daySell demand ratio for a single day +.>The transaction total amount processor analyzes and processes the change condition of the transaction total amount to obtain a transaction cold and hot index P1, the purchase demand processor analyzes and processes the change condition of the purchase demand ratio to obtain a purchase cold and hot index P2, and the sell demand processor analyzes and processes the change condition of the sell demand ratio to obtain a sell cold and hot index P3.
3. The digital asset risk assessment system based on interval fuzzy synthetic valuation of claim 2, wherein the price analysis unit comprisesThe price-equalizing register receives and stores daily transaction price-equalizing data and the price-equalizing processor calculates daily rise and fall values according to the following formula：
；
Wherein day represents a specific date, pu (day) represents a day's average price for the day's transaction;
the price processor calculates a volatility index P4 according to the following formula:
；
wherein RC represents a set of dates, m is the number of days contained in the RC set, d 0 Is the rise and fall threshold.
4. A digital asset risk assessment system based on interval ambiguity synthesis assessment as claimed in claim 3, wherein said synthesis ambiguity unit calculates an ambiguity value Vague according to the following formula:
；
wherein,% is the remainder symbol;
when Vague is less than or equal to 5, the Vague sectionIs->；
When Vague is greater than 5, the section is blurredIs->。
5. The digital asset risk assessment system based on interval fuzzy comprehensive evaluation as claimed in claim 4, wherein the data cleansing unit comprises an order recognition processor, an order transaction processor and a data format processor, wherein the order recognition processor is used for recognizing a buying order and a selling order, when recognizing that the order is obtained by modification of an original order, the order transaction processor is used for recognizing a closing order, deleting buying order and selling order information corresponding to the closing order, and the data format processor is used for carrying out format unification processing on all order data in the data caching unit at fixed time.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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