Unlock instant, AI-driven research and patent intelligence for your innovation.
Method for identifying abnormality of customers in futures market
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
An identification method and customer technology, applied in the information field, can solve the problems of high misjudgment, low efficiency, abnormal identification method, etc.
Inactive Publication Date: 2012-06-13
HARBIN INST OF TECH
View PDF3 Cites 2 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
[0006] In order to solve the problem of low efficiency and high degree of misjudgment for futures companies to analyze the credit risk of customers based on manpower, the present invention provides a method for identifying abnormalities of customers in the futures market
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
specific Embodiment approach 1
[0044] Specific implementation mode one: the following combination figure 1 Describe this implementation mode, this implementation mode comprises the following steps:
[0045] Step 1: Obtain the registration information and transaction data of G customers, PF k Indicates the kth customer, G is an integer greater than 600, k=1, 2, 3...G;
[0046] Step 2: According to the registration information and transaction data of G customers, extract the feature quantity F of each customer k (l), wherein l is an integer, l=1,2,3...24;
[0047] Step 3: According to the customer's characteristic quantity F k (l), using p-norm distance to measure customer PF b and customer PF g The similarity distance between Dist(PF b , PF g ):
[0048] Dist ( PF b , PF g ) = ( Σ ...
specific Embodiment approach 2
[0059] Specific implementation mode 2: This implementation mode is a further description of implementation mode 1. In the step 4, the PF of each customer is obtained k The cluster center sample fc to which it belongs k The specific method is:
[0060] Step 41: From the global distance matrix D G×G Get customer PF b and customer PF g The similarity between Sim(b, g), establish a global similarity matrix S G×G :
[0061] S G × G = Sim ( 1,1 ) Sim ( 1,2 ) · · · · · · ...
specific Embodiment approach 3
[0068] Specific embodiment three: this embodiment is a further description of embodiment two, the feedback matrix R after LT times of iterative update is obtained in the step four or three G×G and validity matrix A G×G The specific process is:
[0069] Step 431: The feedback matrix R obtained in step 42 G×G All elements of r(i, j) are updated to r(i.j) * =λr tmp (i,j)+(1-λ)r old (i,j),
[0070] where λ is the update coefficient, r old (i, j) is the r(i, j) obtained from the previous iteration update, r tmp (i, j) is shown in the following formula:
[0071] r tmp ( i , j ) = Sim ( i , j ) - max ...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
PUM
Login to View More
Abstract
The invention discloses a method for identifying the abnormality of customers in a futures market, belongs to the technical field of information, and solves the problems of low efficiency and high mal-judgment degree in manual analysis of the credit risk of the customers. The method comprises the following steps of: acquiring the registration information and transaction data of G customers; according to the registration information and transaction data of the G customers, extracting the characteristic quantity Fk (1) of each customer; according to the characteristic quantity Fk (1) of each customer, establishing a global distance matrix D(G*G); establishing an active matrix A(G*G) and a feedback matrix R(G*G), and acquiring a cluster center sample fck of each customer PFk according to a similar distance Dist (PFb, PFg) between a customer PFb and a customer PFg; and gathering the customers PFk with the same cluster center samples fck into a customer cluster, and determining that the customer cluster having minimum customers is abnormal. The method is applicable to identification of the customers in the futures market.
Description
technical field [0001] The invention relates to a method for identifying abnormalities of customers in a futures market, belonging to the field of information technology. Background technique [0002] The introduction of stock index futures is an objective requirement for the development of my country's capital market to a certain stage. It enables stock holders to transfer the risks of stocks in their hands through stock index futures, thereby increasing the market balance and is conducive to the stability of the entire market. At the same time, stock index futures also contain huge risks. Once stock index futures are used or managed improperly, it may bring huge losses to investors and even disrupt the country's financial order. Therefore, how to effectively prevent and manage the risk of stock index futures is particularly important. [0003] Due to the imperfection of our country's market system, our country's stock index futures have risks brought about by the transact...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to View More 
Login to View More 
