KR101487329B1 - System for computing credit default swap index levels upon consensus of credit derivatives market participants and method therefor - Google Patents

Abstract

The present invention relates to a system for calculating a credit derivative index by a financial market participant, which calculates a credit derivative index accurately reflecting a market situation based on quotation data of a market participant, The present invention is directed to a system and method for publicly notifying a user of a message.
According to an aspect of the present invention, there is provided an information processing system including a call data input unit receiving call data of a market participant for a credit derivation index determined by consultation of market participants from a user terminal of a market participant; A database construction unit for receiving call data from the call input unit and storing the call data; A cleansing unit that receives call data from the database from the database building unit and divides the call data into abnormal call data and abnormal call data; And a credit derivation index calculating unit for calculating a credit derivative index based on the normal call rate data classified through the clearing unit; Wherein the credit derivation index calculator divides the data according to the number of data included in the normal call data and removes a predetermined number of upper and lower data from the divided call data; And a credit derivative index calculating module for calculating a credit derivative index by arithmetically averaging the remaining call data as object data after removal through the data removal module; And a control unit.

Description

[Background Art] [0002] The system for computing the credit derivative index by the financial market participant and the method thereof,

The present invention relates to a system and a method for calculating a credit default swap index, and more particularly, to a credit default swap index calculating system that calculates a credit derivation index accurately reflecting a market situation based on quotation data of market participants, To a customer who needs it, and to a method for publicly notifying the system.

Regarding the listing of derivatives stocks, numerous applications and disclosures have been made in addition to the Korean Registered Patent No. 10-0953209 (hereinafter referred to as "the preceding document").

The apparatus according to the preceding document is an individual derivative stock listing apparatus in a database-based system that classifies and manages a plurality of individual derivative stocks as a unit of a transaction into a plurality of derivatives groups according to derived underlying assets, A derivative product generation unit for generating or modifying information of the derivative groups by receiving at least one of information on an underlying asset, a sales contract rule, and a settlement settlement rule of the derivatives group; Wherein the derivation commodity group initialization unit is configured to initialize a listing price of each of the derivative groups by receiving a reference date and a date information of the group of derivatives from the database and defining a settlement month in which the group of derivatives is newly listed or de- Wherein the information of the derivative group to which the market action of the prohibition of the listing of the new month is added is deleted from the database, Adding the date on which the market action is added to the event date information of the derivative group to which the market action of the trading day change is added and changing the final settlement date information defined based on the latest transaction date information and the final transaction date Payment Month Event Lifetime Father; A derivative item generating unit for generating the next day item information of the individual derivative item belonging to the derivatives group based on the information on the payment month and the event date of the generated derivative goods groups; A derivative item price generating unit for generating the next day price data among the next day item information of the individual derivative item based on price information preliminarily processed for the information of the underlying asset in the system; A futures stock producer for generating second day stock information for a futures item of the individual derivative stocks belonging to the derivative groups and listing the futures stock; And an option item for generating second-day-of-stock information for the option item among the individual derivative items belonging to the derivative groups and calculating the equal price and the exercise price of the option item from the second day's item information, Wherein the option item creator includes an option item generating unit that generates an option item in which if the exercise price of the option item is within the range of the reference value according to the exercise price rule, And further forming a state in which the number of option items up and down by the reference number is listed on the basis of the equal price.

On the other hand, in the case of OTC derivatives that are not standardized, such as Credit Default Swap, traded on the basis of trading partners, unlike listed stocks where market participants can easily find market prices due to multiple traders It is not easy to find real-time market value because trading is done privately in a limited number of stocks.

Therefore, there is a need to disclose various credit derivatives indexes to assist managers who manage various hedge funds or funds / funds that take positions in credit default swaps. In view of this, the International Swap and Derivatives Association (ISDA) And Derivatives Association) and Markit have traded the iTraxx and CDX indexes, which are tradable credit derivatives, on the exchanges such as Markit ICE and Eurex.

However, iTraxx and CDX, which are announced overseas, have a disadvantage in that they can not properly reflect the domestic market because the constituent company is not an domestic company but an index made for European or American companies, and iTraxx ex -Japan Index has a problem that it can not act as an index representing the market because the transaction is not active.

In addition, as described above, the method of using quotation traded as a market representative index by listing tradable credit derivative indexes representing the domestic market on the derivatives market does not correspond to the reality that there are no exchanges where derivatives can be traded in the domestic market There was a problem.

In addition, the method of using the quotation to be traded is that since the index is calculated using only the contracted data, the number of data used in the calculation is insufficient, the price discovery ability is deteriorated, and the credit spread sharply increases and contracts for a few minutes There is a problem that the risk of the transaction increases because the index does not reflect the market situation at all.

In addition, as the closing price of the trading day is vulnerable to the malicious attack of some market participants as evidenced by the option shock that occurred in November 2010, the base of the second derivatives It is not suitable as an asset.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and it is an object of the present invention to provide a credit derivative index that accurately reflects market conditions based on quotation data of market participants, And to provide a system and method capable of notifying a user of a problem.

According to an aspect of the present invention, there is provided a system for calculating a credit derivative index by a financial market participant, the system including: a system for receiving credit data of a market participant for a credit derivative index determined by negotiation of market participants from a user terminal of a market participant A call data input unit; A database construction unit for receiving call data from the call input unit and storing the call data; A cleansing unit that receives call data from the database from the database building unit and divides the call data into abnormal call data and abnormal call data; And a credit derivation index calculating unit for calculating a credit derivative index based on the normal call rate data classified through the clearing unit; Wherein the credit derivation index calculator divides the data according to the number of data included in the normal call data and removes a predetermined number of upper and lower data from the divided call data; And a credit derivative index calculating module for calculating a credit derivative index by arithmetically averaging the remaining call data as object data after removal through the data removal module; And a control unit.

The data erasure module is characterized in that normal call data is arranged in descending order of data number.

In addition, the credit derivation index calculating module transmits the credit derivation index calculated by the corresponding client terminal or the server, so that the information providing request signal can be publicly noticed when the information providing request signal is received from the customer terminal or the server.

The database construction unit may further include: a data reception module for receiving call data from the call data input unit; And a call data DB for storing call data received through the data reception module; And a control unit.

The cleansing unit may further include a second data receiving module for receiving call data databased by the database building unit; And a clearing module for dividing the call data received through the second data receiving module into normal call data and abnormal call data; And a control unit.

The cleansing module determines the call data having a value of 0 or more by judging the call data as normal call data and extracts the call data less than 0 as the abnormal call data.

According to another aspect of the present invention, there is provided a credit derivation index calculation method using a system comprising a call data input unit, a database construction unit, a cleansing unit, and a credit derivation index calculating unit, A step of receiving a quotation data of a market participant for a credit derivation index determined by consultation of market participants from a user terminal; (b) the database building unit receiving and storing call data from the call data input unit; (c) the cleansing unit receives data of call data databased through the process (b) and divides the data into abnormal call data and abnormal call data; And (d) calculating the credit derivative index based on the normal call rate data classified through the step (c); Wherein the step (d) comprises the steps of: (d-1) separating the credit derivation index calculation unit according to the number of data included in the normal call data, and removing a predetermined number of upper and lower data from each of the divided call data step; And (d-2) calculating a credit derivative index by arithmetically averaging remaining credit data as object data after the credit derivation index calculation unit has removed through the step (d-1); .

Also, in the step (d-1), the credit derivation index calculating unit may sort the normal call rate data in descending order of the number of data.

After the step (d-2), the step (d-3) further comprises: determining whether the credit derivation index calculating unit receives an information provision request signal from a customer terminal or a server; And (d-4) if the information providing request signal is received as a result of the determination in the step (d-3), the credit derivation index calculating unit calculates a credit derivative index ; And further comprising:

The step (b) includes the steps of: (b-1) receiving the call data from the call data input unit; And (b-2) storing the call data received by the database building unit; And a control unit.

In addition, the step (c) may further include: (c-1) receiving the database of call data through the clearing unit; And (c-2) dividing the call data received by the cleansing unit into normal call data and abnormal call data; And a control unit.

In step (c-2), the clearing unit checks the value of each call data received, judges the call data having a value of 0 or more as the normal call data, and extracts the call data having a value less than 0 as the abnormal call data .

According to the present invention, it is possible to more accurately reflect the market situation by calculating the market representative credit derivative index reflecting the opinions of the market participants in a market with a small effective transaction amount.

Further, according to the present invention, not only the call data is used as it is, but also the credibility of the credit derivation index can be enhanced through the data verification operation and the cleansing operation.

According to the present invention, the system can be applied without any change even in a situation where the credit derivative index is calculated in real time by adopting a scalable structure.

FIG. 1 is an overall schematic diagram illustrating a system for calculating a credit derivative index by a financial market participant according to the present invention. FIG.
FIG. 2 is an overall flowchart of a method for calculating a credit derivative index by a financial market participant according to the present invention. FIG.

Specific features and advantages of the present invention will become more apparent from the following detailed description based on the accompanying drawings. It is to be noted that the detailed description of known functions and constructions related to the present invention is omitted when it is determined that the gist of the present invention may be unnecessarily blurred.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will now be described in detail with reference to the accompanying drawings.

The system for calculating the credit derivative index by a financial market participant according to the present invention will be described with reference to FIG.

FIG. 1 is a block diagram conceptually illustrating a credit derivation index calculation system S by a financial market participant according to the present invention. As shown in FIG. 1, a credit value data input unit 100, a database building unit 200, (300) and a credit derivation index calculation unit (400).

The call data input unit 100 receives call data of a market participant for a credit derivation index determined by consultation of market participants from a user terminal 10 of a market participant.

At this time, the call data input unit 100 may perform a verification operation to confirm data in order to prevent input data of the call data from being input error of the user or distortion and error of data that may occur during the data transmission process.

Data verification is performed through a total of five steps.

In step 1, the call data input unit 100 confirms whether the fluctuation range of the received call data from the previous day is smaller than a certain multiple of the recent 3-month average. At this stage, the default value of a certain multiple is two times, but a specific value can be specified in consideration of the market situation.

In step 2, the call data input unit 100 confirms whether the received call data has a discrete value that is different from the average value of the received call data by 20% or more. At this time, the 20% value is set as the default value, but the verification range can be adjusted for operational purposes.

In step 3, the call data input unit 100 verifies whether the received call data has a buy call number and a sell call price reversed. In general, the selling price is larger than the buying price.

In step 4, the call data input unit 100 verifies the values of the buy / sell spread value, which is the difference between the buy and sell prices, to a predetermined level or more.

In step 5, the call data input unit 100 confirms whether the received call price of the received individual call data is smaller than the average value of the remaining call orders, or the received call price of the individual call data is larger than the average value of the remaining call orders. This finds out when the received individual call data is received with the remaining calls differing from the buy or sell price of the data.

The query data of the market participants filtered through the data verification is sent back to the participants who entered the query data, and the process of confirming the abnormality is performed.

1, the first data reception module 210 and the second data reception module 200 are connected to the data building unit 200. The first data reception module 210 and the data DB 220).

Specifically, the first data receiving module 210 receives the call data from the call data input unit 100. At this time, the data reception module 210 and the call data input unit 100 use the SFTP (Secure File Transfer Protocol) method for call data transmission and reception. That is, unlike the general FTP method, the first data receiving module 210 and the call data input unit 100 perform data encryption using the SFTP method, thereby preventing hacking and solving security problems.

The call data DB 220 stores call data received through the data receiving module 210.

Meanwhile, the database building unit 200 may be a database built in a remote place.

The cleansing unit 300 receives call data from the database 200 and divides the call data into abnormal call data and abnormal call data. As shown in FIG. 1, Module 310 and a cleansing module 320.

Specifically, the second data receiving module 310 receives call data from the database constructed by the database construction unit 200.

At this time, the second data receiving module 310 may perform a verification operation for checking data in order to prevent data distortion and error that may occur during the data transmission process.

That is, the second data receiving module 310 adds a header and a tail to the transmission file in order to prevent data distortion and error that may occur in the data transmission process, .

The header includes the number of data items included in the transmission file and checks whether the number of finally received data matches the number of data items displayed in the header. , The average value of the received call data is calculated and compared with the average value displayed on the tail to check whether there is a change in the data. In this manner, data transmission errors that may occur in the computational environment are identified, thereby verifying data deformation and errors.

The cleansing module 320 divides the call data received through the second data receiving module 310 into normal call data and abnormal call data.

That is, the clearing module 320 determines the call data having a value of 0 or more as the normal call rate data and extracts the call data having a value of 0 or more as the abnormal call rate data by checking each value of the received call data.

The credit derivation index calculating unit 400 calculates the credit derivative index based on the normal call data classified through the clearing unit 300. As shown in FIG. 1, the data deriving module 410 And a credit derivation index calculation module 420. [

Specifically, the data erasure module 410 classifies the normal call data according to the data number of the data, and removes the upper and lower certain number of data from the divided call data. At this time, the data erasure module 410 arranges the normal call data in descending order of the number of data.

delete

The credit derivation index calculation module 420 calculates the credit derivative index by arithmetically averaging the remaining call data as target data after removal through the data cancellation module 410. [

Meanwhile, the credit derivation index calculating module 420 may calculate the credit derivatives index 420 using the credit derivation index, when the information providing request signal is received from the customer terminal or the server 20 requiring the credit derivation index, And the credit derivative index is calculated.

Hereinafter, a method of calculating a credit derivative index by a financial market participant using the above system will be described with reference to FIG.

FIG. 2 is a flowchart illustrating a method of calculating a credit derivative index by a financial market participant according to the present invention. As shown in FIG. 2, a call data input unit 100 receives a call data input from a user terminal 10 of a market participant And receives the quotation data of the market participant for the credit derivation index (S10).

The first data receiving module 210 of the database construction unit 200 receives the call data from the call data input unit 100 in the Secure File Transfer Protocol (SFTP) Stores the call data received through the first data receiving module 210 (S30).

The second data receiving module 310 of the cleansing unit 300 receives the call data databaseed from the database construction unit 200 in step S40 and the cleansing module 320 transmits the call- In order to distinguish between the call data and the abnormal call data, the received call data is checked for each data value (S50), and the call data having a value of 0 or more is determined as normal call data (S60). At this time, the call data less than 0 judges the data as abnormal call data.

Subsequently, the data removal module 410 of the credit derivation index calculating unit 400 divides the data according to the number of data of the normal call data, removes the upper and lower predetermined number of data from the divided call data (S70) The credit derivation index calculating module 420 calculates the credit derivation index by arithmetically averaging the remaining call data as target data after removal through the data cancellation module 410 (S80).

Then, the credit derivation index calculation module 420 determines whether an information provision request signal is received from the customer terminal or the server 20 that requires the credit derivation index (S90).

As a result of the determination in step S90, when the information provision request signal is received, the credit derivation index calculated by the customer terminal or the server 20 is transmitted (S100) so that the information provision request signal can be publicly notified If not, the process is terminated.

While the present invention has been particularly shown and described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. It will be appreciated by those skilled in the art that numerous changes and modifications may be made without departing from the invention. Accordingly, all such appropriate modifications and changes, and equivalents thereof, should be regarded as within the scope of the present invention.

S: Credit Derivative Index Calculation System by Financial Market Participants
100: call data input unit 200: database construction unit
300: cleansing unit 400: credit derivation index calculating unit
210: first data receiving module 220: arc data DB
310: second data receiving module 320: cleansing module
410: data removal module 420: credit derivation index calculation module

Claims (12)

In a credit derivation index calculation system by financial market participants,
A call data input unit (100) for receiving call data of a market participant for a credit derivative index determined by consultation of market participants from a user terminal (10) of a market participant;
A database construction unit 200 for receiving and storing call data from the call data input unit 100;
A cleansing unit (300) for receiving call data from the database constructed by the database building unit (200) and distinguishing normal call data and abnormal call data; And
A credit derivation index calculating unit 400 for calculating a credit derivative index based on the normal call rate data classified through the clearing unit 300; , ≪ / RTI &
The call data input unit (100)
For the inputted call data, a verification process is performed to confirm whether the input error of the user or the data that may occur during the data transmission process is error or not, and then the data of the market participants, which are filtered through the data verification, And to encrypt and transmit the verified call data,
The credit derivation index calculating unit 400 calculates a credit derivative index
A data removal module (410) for sorting according to the number of data of the normal call data and removing a predetermined number of upper and lower data from each divided call data; And
A credit derivation index calculation module 420 for calculating a credit derivative index by arithmetically averaging the remaining call data as object data after removal through the data removal module 410; The system comprising: means for calculating a credit derivative index by a financial market participant;
The method according to claim 1,
The data removal module 410,
And the normal call data is sorted in descending order by the number of data.
The method according to claim 1,
The credit derivation index calculating module 420 calculates the credit derivative index
When the information providing request signal is received from the customer terminal or the server (20), transmits the credit derivative index calculated by the corresponding customer terminal or the server (20) so as to be publicly notified Credit Derivation Index Calculation System.
The method according to claim 1,
The database construction unit (200)
A data receiving module 210 for receiving call data from the call input unit 100; And
A call data DB 220 for storing call data received through the data reception module 210; Wherein the credit derivative index is calculated by a financial market participant.
The method according to claim 1,
The cleansing unit (300)
A second data receiving module (310) for receiving call data from the database constructed by the database building unit (200); And
A cleansing module 320 for separating the call data received through the second data receiving module 310 into normal call data and abnormal call data; The system comprising: means for calculating a credit derivative index by a financial market participant;
6. The method of claim 5,
The cleansing module 320,
Wherein the call data is determined as abnormal call rate data by judging that call data having a value of 0 or more is judged as normal call rate data and is extracted when the received call value is checked for each data value, Index calculation system.
A method for calculating a credit derivative index by a financial market participant using a system including a call data input unit (100), a database building unit (200), a cleansing unit (300), and a credit derivation index calculating unit (400)
(a) receiving the call data of the market participant for the credit derivation index determined by consultation of the market participants from the user terminal (10) of the market participant by the call data inputting unit (100);
(b) receiving the call data from the call data input unit (100) and storing the call data;
(c) the cleansing unit 300 receives the database-ordered call data and separates the call data into abnormal call data and abnormal call data through the process (b); And
(d) calculating the credit derivative index based on the normal call rate data classified through the process (c); ≪ / RTI >
In the step (a)
(a-1) performing a verification operation on the input call data to confirm whether the input data is a user's input mistake or a variation and an error of data that may occur in a data transmission process; and
(a-2) confirming whether or not the market participants have abnormalities in the quotation data of market participants who are filtered through data verification,
(a-3) encrypting the verified call data and transmitting the encrypted data to the database building unit 200,
The step (d)
(d-1) separating the credit derivation index calculator 400 according to the number of data included in the normal call data, and removing a predetermined number of upper and lower data from the divided call data; And
(d-2) calculating the credit derivative index by arithmetically averaging the remaining call data as target data after the credit derivation index calculating unit 400 removes the credit value through the step (d-1); The method of calculating the credit derivative index by the financial market participant.
8. The method of claim 7,
In the step (d-1)
Wherein the credit derivation index calculator (400) sorts the normal call rate data in descending order by the number of data.
8. The method of claim 7,
After the step (d-2)
(d-3) determining whether the credit derivation index calculating unit 400 receives an information provision request signal from the customer terminal or the server 20; And
If the information providing request signal is received, the credit derivation index calculating unit 400 calculates the credit derivation index of the corresponding customer terminal or the server 20 so that the information can be publicly noticed as a result of (d-3) A credit derivation index calculated as; And calculating a credit derivative index by a financial market participant.
8. The method of claim 7,
The step (b)
(b-1) receiving the call data from the call data input unit 100 by the database construction unit 200; And
(b-2) storing the call data received by the database building unit 200; And calculating a credit derivative index by a financial market participant.
8. The method of claim 7,
The step (c)
(c-1) the clearing unit 300 receives the database of call data through the process (b); And
(c-2) dividing the call data received by the cleansing unit 300 into normal call data and abnormal call data; And calculating a credit derivative index by a financial market participant.
12. The method of claim 11,
In the step (c-2)
The clearing unit 300 determines the call data having a value of 0 or more as the normal call rate data and extracts the call data having a value of 0 or more as the abnormal call cost data by checking each value of the call data received by the cleansing unit 300 How to calculate credit derivative index by financial market participants.

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