CN112465646A - Security data monitoring method and device, computer equipment and storage medium - Google Patents
Security data monitoring method and device, computer equipment and storage medium Download PDFInfo
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- CN112465646A CN112465646A CN202110078711.0A CN202110078711A CN112465646A CN 112465646 A CN112465646 A CN 112465646A CN 202110078711 A CN202110078711 A CN 202110078711A CN 112465646 A CN112465646 A CN 112465646A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The application relates to a security data monitoring method, a security data monitoring device, computer equipment and a storage medium. The method comprises the following steps: acquiring market data and return data; positioning the market data and the return data to a time axis; determining a current time window according to the time slices of the time axis; determining target market data and target return data of a current time window; determining a traffic ratio according to the target market data and the target return data, and determining the unit value expansion according to the target market data; when the ratio of the volume to the volume is more than or equal to the threshold value of the ratio of the volume to the volume and the unit numerical value amplitude is more than or equal to the threshold value of the unit numerical value amplitude, judging that the unit numerical value is abnormal; and re-determining the current time window when the traffic volume ratio is smaller than the traffic volume ratio threshold and/or the unit value amplitude is smaller than the unit value amplitude threshold, and determining that the unit value is normal until the number of the time slices in the current time window reaches the preset number threshold. The method can improve the identification accuracy of unit numerical values of securities.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a security data monitoring method, apparatus, computer device, and storage medium.
Background
With the continuous development of computer technology, the application of information technology in the securities trade is also deepened, some novel illegal security trade behaviors begin to appear, and the illegal manipulation of the securities trade influences the fairness of the securities trade market. However, illegal manipulation of securities trades necessarily results in abnormal fluctuations in the value of the security units, i.e., the price of the securities. In the traditional technology, a fixed-size time window is usually adopted to monitor the price of the securities, but the fixed-size time window cannot accurately identify the abnormal fluctuation of the price of the securities, so that the identification accuracy rate of the abnormal price of the securities is low.
Disclosure of Invention
In view of the above, it is necessary to provide a security data monitoring method, apparatus, computer device and storage medium capable of improving the accuracy of identifying abnormal security unit values.
A security data monitoring method, the method comprising:
acquiring market data and return data of securities;
positioning the market data and the return data to a pre-constructed time axis;
determining a current time window according to the time slices on the time axis;
determining target market data and target return data in the current time window;
determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data;
when the volume ratio of the securities is greater than or equal to a volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to a unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal;
and when the volume of the securities is smaller than the volume of the securities than the threshold value, and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold value, and judging that the securities unit numerical value is normal.
In one embodiment, the method further comprises:
determining a security data monitoring time interval;
dividing the time interval into corresponding time slices according to a preset time length;
and constructing a time axis according to the time intervals and the time slices.
In one embodiment, the positioning the market data and the reward data on a pre-constructed time axis includes:
respectively extracting time information carried by the market data and the return data;
respectively matching the time information carried by the market data and the return data with a time slice on a pre-constructed time axis to obtain a matching result;
and positioning the market data and the return data to a pre-constructed time axis according to a matching result.
In one embodiment, the determining the current time window according to the time slices on the time axis includes:
determining a target time slice from the time slices on the time axis;
determining the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices;
and determining the current time window according to the starting time and the ending time.
In one embodiment, the determining the ratio of the stock volume to the volume of the stock according to the target market data and the target return data includes:
when the access time of the target market data and the target return data is aligned, determining the security commission quantity in the current time window according to the target market data;
determining the number of securities reported in the current time window according to the target report data;
and determining the ratio of the return quantity of the securities to the entrusted quantity of the securities as the proportion of the volume of trades of the securities.
In one embodiment, the method further comprises:
when the access time of the target market data and the target return data is not aligned, determining an access time difference value between the target market data and the target return data;
and performing supplementary calculation on the target market data and the target return data according to the access time difference so as to obtain the stock volume ratio.
In one embodiment, the determining the increment of the security unit value according to the target market data comprises:
extracting securities unit numerical value fluctuation data from the target market data;
determining security unit values corresponding to two ends of the current time window according to the security unit value fluctuation data;
and determining the increment of the security unit numerical value according to the security unit numerical values corresponding to the two ends of the current time window.
A security data monitoring device, the device comprising:
the acquisition module is used for acquiring market data and return data of the securities;
the positioning module is used for positioning the market data and the return data to a pre-constructed time axis;
the determining module is used for determining a current time window according to the time slices on the time axis; determining target market data and target return data in the current time window; determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data;
the judgment module is used for judging that the unit value of the securities is abnormal when the volume ratio of the securities is greater than or equal to a volume ratio threshold value of the securities and the unit value expansion of the securities is greater than or equal to a unit value expansion threshold value of the securities; and when the volume of the securities is smaller than the volume of the securities than the threshold value, and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold value, and judging that the securities unit numerical value is normal.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring market data and return data of securities;
positioning the market data and the return data to a pre-constructed time axis;
determining a current time window according to the time slices on the time axis;
determining target market data and target return data in the current time window;
determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data;
when the volume ratio of the securities is greater than or equal to a volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to a unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal;
and when the volume of the securities is smaller than the volume of the securities than the threshold value, and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold value, and judging that the securities unit numerical value is normal.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring market data and return data of securities;
positioning the market data and the return data to a pre-constructed time axis;
determining a current time window according to the time slices on the time axis;
determining target market data and target return data in the current time window;
determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data;
when the volume ratio of the securities is greater than or equal to a volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to a unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal;
and when the volume of the securities is smaller than the volume of the securities than the threshold value, and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold value, and judging that the securities unit numerical value is normal.
The stock data monitoring method, the stock data monitoring device, the computer equipment and the storage medium acquire market data and return data of the stock; positioning market data and return data to a pre-constructed time axis; determining a current time window according to time slices on a time axis; determining target market data and target return data in a current time window; determining the proportion of the stock traffic according to the target market data and the target return data, and determining the increment of the unit value of the stock according to the target market data; when the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to the unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal; and when the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and judging that the securities unit numerical value is normal. Therefore, the current time window is dynamically determined through the time slices on the time axis, the current time window is dynamically changed, the transaction of the securities is traced back one by one, compared with the traditional mode of monitoring the securities data through the time window with a fixed size, the method for monitoring the securities data through the dynamic change of the time window can more accurately identify the abnormal fluctuation of the security unit numerical value, and the identification accuracy rate of the abnormal security unit numerical value is improved.
Drawings
FIG. 1 is a diagram illustrating an exemplary embodiment of a security data monitoring method;
FIG. 2 is a schematic flow chart diagram illustrating a security data monitoring method according to one embodiment;
FIG. 3 is a schematic diagram of a time axis in one embodiment;
FIG. 4 is a schematic diagram illustrating market data arriving late in one embodiment;
FIG. 5 is a diagram illustrating a calculation of the increase in the security unit value in one embodiment;
FIG. 6 is a schematic view of security data monitoring when the set size of the time window is too large in the conventional art;
FIG. 7 is a schematic view of security data monitoring at a time window set of a size too small in the conventional art;
FIG. 8 is a block diagram showing the construction of a security data monitoring apparatus according to an embodiment;
FIG. 9 is a block diagram showing the construction of a security data monitoring apparatus according to another embodiment;
FIG. 10 is a diagram showing an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The security data monitoring method provided by the application can be applied to the application environment shown in fig. 1. The application environment includes a trading system 102 and a server 104 of a exchange. The transaction system 102 communicates with the server 104 over a network. The server 104 may be implemented as a stand-alone server or a server cluster composed of a plurality of servers. Those skilled in the art will understand that the application environment shown in fig. 1 is only a part of the scenario related to the present application, and does not constitute a limitation to the application environment of the present application.
The server 104 obtains market data and reward data for the securities from the exchange's trading system 102 and locates the market data and reward data onto a pre-constructed timeline. The server 104 determines a current time window according to the time slices on the time axis, and determines target market data and target reward data in the current time window. The server 104 determines the ratio of the stock volume to the volume of the stock according to the target market data and the target return data, and determines the increment of the unit value of the stock according to the target market data. When the volume ratio of securities is greater than or equal to the volume ratio threshold value of securities and the volume value fluctuation of securities units is greater than or equal to the volume value fluctuation threshold value of securities units, the server 104 judges that the security unit value is abnormal. When the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, the server 104 returns to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and the security unit numerical value is judged to be normal.
In one embodiment, as shown in fig. 2, a security data monitoring method is provided, which is illustrated by applying the method to the server 104 in fig. 1, and comprises the following steps:
s202, acquiring market data and return data of the securities.
The market data is all entrusted data of a certain security in the whole market, for example, the market data may be price fluctuation and buying and selling conditions of a certain stock. The reward data is entrusted data confirmed by the exchange, for example, the reward data can be profit and loss data of a certain stock and the like.
Specifically, the exchange system of the exchange stores market data and return data of securities, and the server can acquire the market data and the return data of the securities from the exchange system of the exchange.
S204, positioning the market data and the return data to a pre-constructed time axis.
Specifically, the market data and the return data each carry time information, and the server can position the market data and the return data on a pre-constructed time axis according to the situation data and the return data each carrying the time information.
And S206, determining the current time window according to the time slices on the time axis.
A time slice is a time interval with a specific time length, for example, every 1 second is taken as a time slice, or every 1 microsecond is taken as a time slice.
Specifically, the time axis includes a plurality of time slices, and each time slice is sorted according to the time sequence. The server may determine the current time window from the time slices on the time axis.
And S208, determining the target market data and the target return data in the current time window.
The target market data is market data in the current time window, and the target return data is return data in the current time window.
Specifically, the market data and the reward data may exist in the current time window, and the server may determine the market data in the current time window as the target market data and determine the reward data in the current time window as the target reward data.
S210, determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data.
The ratio of the volume of traded securities is the ratio of the number of returned securities to the number of consignments of securities, the unit value of securities refers to the price of securities, and the increase of the unit value of securities is the increase of the unit value of securities.
Specifically, the target market data may include a security commission amount and a security unit value fluctuation data, and the target return data may include a security return amount. The server can determine the proportion of the trading volume of the securities according to the consignment quantity and the return quantity of the securities and determine the increment of the value of the security unit according to the value fluctuation data of the security unit.
S212, when the volume ratio of the securities trades is larger than or equal to the volume ratio threshold value of the securities trades, and the unit value expansion of the securities is larger than or equal to the unit value expansion threshold value of the securities, the unit value of the securities is judged to be abnormal.
Specifically, the server may compare the volume of stock exchange with a threshold of volume of stock exchange, and compare the volume of stock unit value with a threshold of volume of stock unit value. When the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit numerical value expansion of the securities is greater than or equal to the unit numerical value expansion threshold value of the securities, the server can judge that the unit numerical value of the securities is abnormal.
S214, when the volume of the securities trades is smaller than the volume of the securities trades ratio threshold value and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, the step of determining the current time window according to the time slices on the time axis is returned to be continuously executed until the number of the time slices in the current time window reaches the preset number threshold value, and the security unit numerical value is judged to be normal.
Specifically, when the ratio of the volume of securities trades is less than the threshold value of the volume of securities trades, and/or the value spread of security units is less than the threshold value of the value spread of security units, the server may return to the step of determining the current time window according to the time slices on the time axis to continue execution. When the number of the time slices in the current time window reaches a preset number threshold value, the server can judge that the security unit numerical value is normal.
For example, if the server takes every 1 second as a time slice, the server may initially take one time slice as the current time window. The server can acquire all target market data and target return data in the past 1 second, determine the stock volume ratio according to the target market data and the target return data in the past 1 second, and determine the stock unit value expansion according to the target market data. If the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities, and the unit numerical value expansion of the securities is greater than or equal to the unit numerical value expansion threshold value of the securities, the server can judge that the unit numerical value of the securities is abnormal in the past 1 second. If the ratio of the stock volume to the stock volume is smaller than the threshold value of the ratio of the stock volume to the stock volume and/or the value spread of the stock unit is smaller than the value spread threshold value of the stock unit, the result shows that the stock unit value in the past 1 second is normal, at the moment, the server can re-determine the current time window, namely, the server can take two time slices as the current time window, the server can obtain all the target market data and the target return data in the past 2 seconds, determine the ratio of the stock volume to the stock volume according to the target market data and the target return data in the past 2 seconds, and determine the value spread of the stock unit according to the target market data. If the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities, and the unit numerical value expansion of the securities is greater than or equal to the unit numerical value expansion threshold value of the securities, the server can judge that the unit numerical value of the securities is abnormal within the past 2 seconds. If the volume ratio of the securities trades is smaller than the volume ratio threshold value of the securities trades and/or the volume increase of the security unit numerical value is smaller than the volume increase threshold value of the security unit numerical value, it indicates that the security unit numerical value in the past 2 seconds is normal. At this time, the server may re-determine the current time window, that is, the server may use three time slices as the current time window, the server may obtain all the target market data and the target return data in the past 3 seconds, determine the stock and exchange ratio according to the target market data and the target return data in the past 3 seconds, and determine the stock and exchange unit value expansion according to the target market data. If the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities, and the unit numerical value expansion of the securities is greater than or equal to the unit numerical value expansion threshold value of the securities, the server can judge that the unit numerical value of the securities is abnormal in the past 3 seconds. If the volume ratio of the securities trades is smaller than the volume ratio threshold value of the securities trades and/or the volume increase of the security unit numerical value is smaller than the volume increase threshold value of the security unit numerical value, it indicates that the security unit numerical value in the past 3 seconds is normal. And repeating the steps until the number of the time slices in the current time window reaches a preset number threshold, for example, when the number of the time slices in the current time window reaches a preset number threshold 10, judging that the security unit numerical value is normal.
In the security data monitoring method, market data and return data of the security are acquired; positioning market data and return data to a pre-constructed time axis; determining a current time window according to time slices on a time axis; determining target market data and target return data in a current time window; determining the proportion of the stock traffic according to the target market data and the target return data, and determining the increment of the unit value of the stock according to the target market data; when the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to the unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal; and when the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and judging that the securities unit numerical value is normal. Therefore, the current time window is dynamically determined through the time slices on the time axis, the current time window is dynamically changed, the transaction of the securities is traced back one by one, compared with the traditional mode of monitoring the securities data through the time window with a fixed size, the method for monitoring the securities data through the dynamic change of the time window can more accurately identify the abnormal fluctuation of the security unit numerical value, and the identification accuracy rate of the abnormal security unit numerical value is improved.
In one embodiment, the security data monitoring method further comprises: determining a security data monitoring time interval; dividing the time interval into corresponding time slices according to a preset time length; a timeline is constructed from the time intervals and the time slices.
For example, the server may convert 9: 30-15: 00, determining a time interval for monitoring security data, the server can convert the time interval 9: 30-15: 00, divided into corresponding time slices according to a preset time length, such as 1 second. Further, the server may, according to time interval 9: 30-15: 00 and time slices constitute a time axis. As shown in fig. 3, fig. 3 is a portion of a time line, each time slice being 1 second.
In the embodiment, the time axis consisting of one time slice is constructed, so that securities can be traced back one by one, and the identification accuracy of unit numerical values of abnormal securities is improved.
In an embodiment, the step S204, that is, the step of locating the market data and the reward data on a pre-constructed time axis, specifically includes: respectively extracting time information carried by market data and return data; respectively matching time information carried by the market data and the return data with a time slice on a pre-constructed time axis to obtain a matching result; and positioning the market data and the return data to a pre-constructed time axis according to the matching result.
Specifically, the market data and the return data each carry time information, and the server can extract the time information carried by the market data and the return data respectively. The time slices on the time axis also include corresponding time information. The server can respectively match the time information carried by the market data and the return data with the time information in the time slice on the pre-constructed time axis to obtain a matching result, and then the server can position the market data and the return data on the pre-constructed time axis according to the matching result.
In the embodiment, the market data and the return data are positioned on the pre-constructed time axis, and the market data and the return data do not need to be additionally sequenced, so that the securities can be directly traced back one by one on the basis of the time axis, and the problem of low calculation efficiency caused by data disorder is solved.
In an embodiment, the step S206, that is, the step of determining the current time window according to the time slice on the time axis, specifically includes: determining a target time slice from time slices on a time axis; determining the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices; a current time window is determined from the start time and the end time.
Wherein the target time slice is a time slice used for determining the current time window.
Specifically, the time axis may include a plurality of time slices, and the server may determine target time slices from the time slices on the time axis, where each target time slice carries corresponding time information. The server can determine the time sequence of the target time slices according to the time information carried by each target time slice. The server can determine the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices, and determine the current time window according to the starting time and the ending time.
In one embodiment, as shown in FIG. 3, if the server determines the target time slices to be 10:00:02, 10:00:03, 10:00:04, and 10:00:05 from the time slices on the time axis. The server can determine that the starting time and the ending time of the four target time slices are 10:00:02 and 10:00:05 respectively, and then the current time window is 10:00:02-10:00: 05.
In the embodiment, the target time slice is determined in a stroke-by-stroke backtracking mode, so that the current time window is dynamically determined, the security data is monitored through dynamic change of the time window, and compared with the traditional monitoring mode of the time window with a fixed size, the abnormal fluctuation of the unit value of the security can be more accurately identified.
In one embodiment, the step of determining the ratio of the stock volume to the stock volume according to the target market data and the target return data in step S210 specifically includes: when the access time of the target market data and the target return data is aligned, determining the security commission quantity in the current time window according to the target market data; determining the number of securities reported in the current time window according to the target report data; and determining the ratio of the return quantity of the securities to the entrusted quantity of the securities as the proportion of the volume of trades of the securities.
The access time refers to the time when the target market data and the target return data are accessed to the server.
Specifically, the exchange transaction system accesses the target market data and the target return data to the server through two different data transmission channels, where the different data transmission channels may correspond to different network transmission rates, and the data volumes of the target market data and the target return data may be different, so that the access times of the target market data and the target return data may be aligned or misaligned. When the access time of the target market data and the target return data is aligned, the server can determine the security commission quantity in the current time window according to the target market data and determine the security return quantity in the current time window according to the target return data. Further, the server may determine a ratio of the amount of the securities returned to the amount of the securities committed as a proportion of the amount of the securities traded.
In the above embodiment, when the access times of the target market data and the target return data are aligned, the ratio of the number of securities returns in the current time window to the number of securities orders is directly determined as the proportion of the volume of securities trades, so that the computation efficiency of the proportion of the volume of securities trades is improved.
In one embodiment, the security data monitoring method further comprises: when the access time of the target market data and the target return data is not aligned, determining an access time difference value between the target market data and the target return data; and performing supplementary calculation on the target market data and the target return data according to the access time difference to obtain the ratio of the stock volume to the volume of the stock.
Specifically, when the access times of the target market data and the target reward data are not aligned, it indicates that the target market data may be early or late compared to the target reward data. The target market data is earlier or later than the target return data, there may be an access time difference between the target market data and the target return data, the server may determine an access time difference between the target market data and the target return data, and according to the access time difference, performing supplementary calculation on the target market data and the target return data to obtain the ratio of the stock volume to the volume, it can be understood that, when the target market data is earlier or later than the target return data, the share ratio of the stock trades calculated before the access time of the target market data and the target return data are aligned is not accurate enough, and at this time, the server can determine the share ratio of the stock trades calculated before the access time difference between the target market data and the target return data is aligned, and performing supplementary calculation on the target market data and the target return data to obtain the ratio of the stock traffic volume when the access time of the final target market data and the access time of the target return data are aligned.
In one embodiment, as shown in fig. 4, when the time slice is 10:00:02, the access time of the target market data and the target return data are aligned, and in this case, the server may determine the ratio of the number of securities returns to the number of securities consignments in the time slice 10:00:02 as the final ratio of the volume of securities trades. When the time slices are 10:00:03, 10:00:04 and 10:00:05, the target market data are late relative to the access time of the target return data, and at the moment, the server can perform supplementary calculation on the target market data and the target return data in the time slices of 10:00:03, 10:00:04 and 10:00:05 respectively to obtain the stock traffic ratio when the access times of the final target market data and the target return data are aligned.
In the embodiment, when the access time of the target market data and the target return data are not aligned, the stock exchange volume ratio is obtained by performing supplementary calculation on the target market data and the target return data, and the accuracy of the stock exchange volume ratio is improved.
In one embodiment, the step of determining the increment of the security unit value according to the target market data in step S210 specifically includes: extracting securities unit numerical value fluctuation data from the target market data; determining security unit values corresponding to two ends of a current time window according to the security unit value fluctuation data; and determining the increment of the security unit value according to the security unit values corresponding to the two ends of the current time window.
Specifically, the target market data may include securities unit value fluctuation data, and the server may extract the securities unit value fluctuation data from the target market data, and determine the securities unit values corresponding to both ends of the current time window according to the securities unit value fluctuation data. The server can determine the increment of the security unit numerical value according to the ratio of the security unit numerical value corresponding to the end with the later time in the current time window to the security unit numerical value corresponding to the end with the earlier time in the current time window.
In one embodiment, as shown in FIG. 5, P1 represents the security unit value corresponding to the end of the current time window that is earlier in time, and P2 represents the security unit value corresponding to the end of the current time window that is later in time. The server can determine the ratio of P1 to P2 as the value spread of the security units.
In the above embodiment, the security unit value expansion is determined by the security unit values corresponding to the two ends of the current time window, so that the accuracy of the security unit value expansion can be improved.
In the conventional technology, security data is monitored through a time window with a fixed size, however, if the set size of the time window is too large, as shown in fig. 6, the set size of the time window is too large, the volume of the securities trades in the first time window 601 is 30%, which is equal to the volume of the securities trades accounting for 30%, the volume of the securities units increases by 1.5%, which is less than the volume of the securities units increasing by 5%. The volume of stock trades in the second time window 602 is 10%, which is less than the threshold 30%, the value spread in units of stock is 7.62%, which is greater than the threshold 5%. However, in the abnormal curve portion with black dots in fig. 6, the stock volume percentage is 99.85%, which is greater than the stock volume percentage threshold value of 30%, the stock unit value fluctuation is 7.62%, which is greater than the stock unit value fluctuation threshold value of 5%, and the stock unit value is abnormal. However, neither the first time window 601 nor the second time window 602 can accurately identify the abnormal security unit value, the portion of the abnormal curve with black dots in fig. 6 is masked, the portion of the abnormal security unit value, i.e., the security price, cannot be accurately identified, and the portion of the abnormal curve with black dots in fig. 6 is masked. If the set size of the time window is too small, as shown in fig. 7, the increase of the unit value of the securities in the first time window 701 is lower than the increase threshold of the unit value by 5%, the volume of the securities in the second time window 702 is lower than 30%, and the abnormal curve portion with black dots in fig. 7 is missed, and the abnormal unit value of the securities, i.e. the price of the securities, cannot be accurately identified. The current time window is dynamically determined through the time slices on the time axis, so that the current time window is dynamically changed, the transaction of the securities is traced back one by one, compared with the traditional mode of monitoring the security data through the time window with a fixed size, the security data is monitored through the dynamic change of the time window, the abnormal fluctuation of the security unit numerical value can be more accurately identified, and the identification accuracy of the abnormal security unit numerical value is improved.
It should be understood that although the various steps of fig. 2 are shown in order, the steps are not necessarily performed in order. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in FIG. 8, there is provided a security data monitoring device 800 comprising: an obtaining module 801, a positioning module 802, a determining module 803, and a determining module 804, wherein:
an obtaining module 801, configured to obtain market data and reward data of the securities.
The positioning module 802 is configured to position the market data and the report data on a pre-constructed time axis.
A determining module 803, configured to determine a current time window according to a time slice on a time axis; determining target market data and target return data in a current time window; and determining the ratio of the stock traffic volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data.
The judging module 804 is used for judging that the unit value of the securities is abnormal when the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit value expansion of the securities is greater than or equal to the unit value expansion threshold value of the securities; and when the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and judging that the securities unit numerical value is normal.
In one embodiment, the positioning module 802 is further configured to extract time information carried by the market data and the return data respectively; respectively matching time information carried by the market data and the return data with a time slice on a pre-constructed time axis to obtain a matching result; and positioning the market data and the return data to a pre-constructed time axis according to the matching result.
In one embodiment, the determining module 803 is further configured to determine a target time slice from the time slices on the time axis; determining the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices; a current time window is determined from the start time and the end time.
In one embodiment, the determining module 803 is further configured to determine the security commission amount in the current time window according to the target market data when the access time of the target market data and the target return data are aligned; determining the number of securities reported in the current time window according to the target report data; and determining the ratio of the return quantity of the securities to the entrusted quantity of the securities as the proportion of the volume of trades of the securities.
In one embodiment, the determining module 803 is further configured to determine an access time difference between the target market data and the target reward data when the access times of the target market data and the target reward data are not aligned; and performing supplementary calculation on the target market data and the target return data according to the access time difference to obtain the ratio of the stock volume to the volume of the stock.
In one embodiment, the determining module 803 is further configured to extract the securities unit value fluctuation data from the target market data; determining security unit values corresponding to two ends of a current time window according to the security unit value fluctuation data; and determining the increment of the security unit value according to the security unit values corresponding to the two ends of the current time window.
Referring to FIG. 9, in one embodiment, the security data monitoring device 800 further comprises: building block 805, wherein:
a construction module 805 configured to determine a time interval for security data monitoring; dividing the time interval into corresponding time slices according to a preset time length; a timeline is constructed from the time intervals and the time slices.
The security data monitoring device acquires market data and return data of the security; positioning market data and return data to a pre-constructed time axis; determining a current time window according to time slices on a time axis; determining target market data and target return data in a current time window; determining the proportion of the stock traffic according to the target market data and the target return data, and determining the increment of the unit value of the stock according to the target market data; when the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to the unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal; and when the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and judging that the securities unit numerical value is normal. Therefore, the current time window is dynamically determined through the time slices on the time axis, the current time window is dynamically changed, the transaction of the securities is traced back one by one, compared with the traditional mode of monitoring the securities data through the time window with a fixed size, the method for monitoring the securities data through the dynamic change of the time window can more accurately identify the abnormal fluctuation of the security unit numerical value, and the identification accuracy rate of the abnormal security unit numerical value is improved.
For specific limitations of the security data monitoring device, reference may be made to the above limitations of the security data monitoring method, which are not described herein again. The modules in the security data monitoring device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be the server 104 in fig. 1 described above, and its internal structure diagram may be as shown in fig. 10. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing security data monitoring data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a security data monitoring method.
Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring market data and return data of securities;
positioning market data and return data to a pre-constructed time axis;
determining a current time window according to time slices on a time axis;
determining target market data and target return data in a current time window;
determining the proportion of the stock traffic according to the target market data and the target return data, and determining the increment of the unit value of the stock according to the target market data;
when the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to the unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal;
and when the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and judging that the securities unit numerical value is normal.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
determining a security data monitoring time interval;
dividing the time interval into corresponding time slices according to a preset time length;
a timeline is constructed from the time intervals and the time slices.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
respectively extracting time information carried by market data and return data;
respectively matching time information carried by the market data and the return data with a time slice on a pre-constructed time axis to obtain a matching result;
and positioning the market data and the return data to a pre-constructed time axis according to the matching result.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
determining a target time slice from time slices on a time axis;
determining the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices;
a current time window is determined from the start time and the end time.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
when the access time of the target market data and the target return data is aligned, determining the security commission quantity in the current time window according to the target market data;
determining the number of securities reported in the current time window according to the target report data;
and determining the ratio of the return quantity of the securities to the entrusted quantity of the securities as the proportion of the volume of trades of the securities.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
when the access time of the target market data and the target return data is not aligned, determining an access time difference value between the target market data and the target return data;
and performing supplementary calculation on the target market data and the target return data according to the access time difference to obtain the ratio of the stock volume to the volume of the stock.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
extracting securities unit numerical value fluctuation data from the target market data;
determining security unit values corresponding to two ends of a current time window according to the security unit value fluctuation data;
and determining the increment of the security unit value according to the security unit values corresponding to the two ends of the current time window.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring market data and return data of securities;
positioning market data and return data to a pre-constructed time axis;
determining a current time window according to time slices on a time axis;
determining target market data and target return data in a current time window;
determining the proportion of the stock traffic according to the target market data and the target return data, and determining the increment of the unit value of the stock according to the target market data;
when the volume ratio of the securities is greater than or equal to the volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to the unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal;
and when the volume of the securities is smaller than the volume of the securities and/or the volume of the securities unit numerical value increases smaller than the volume of the securities unit numerical value increase threshold, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold, and judging that the securities unit numerical value is normal.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a security data monitoring time interval;
dividing the time interval into corresponding time slices according to a preset time length;
a timeline is constructed from the time intervals and the time slices.
In one embodiment, the computer program when executed by the processor further performs the steps of:
respectively extracting time information carried by market data and return data;
respectively matching time information carried by the market data and the return data with a time slice on a pre-constructed time axis to obtain a matching result;
and positioning the market data and the return data to a pre-constructed time axis according to the matching result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a target time slice from time slices on a time axis;
determining the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices;
a current time window is determined from the start time and the end time.
In one embodiment, the computer program when executed by the processor further performs the steps of:
when the access time of the target market data and the target return data is aligned, determining the security commission quantity in the current time window according to the target market data;
determining the number of securities reported in the current time window according to the target report data;
and determining the ratio of the return quantity of the securities to the entrusted quantity of the securities as the proportion of the volume of trades of the securities.
In one embodiment, the computer program when executed by the processor further performs the steps of:
when the access time of the target market data and the target return data is not aligned, determining an access time difference value between the target market data and the target return data;
and performing supplementary calculation on the target market data and the target return data according to the access time difference to obtain the ratio of the stock volume to the volume of the stock.
In one embodiment, the computer program when executed by the processor further performs the steps of:
extracting securities unit numerical value fluctuation data from the target market data;
determining security unit values corresponding to two ends of a current time window according to the security unit value fluctuation data;
and determining the increment of the security unit value according to the security unit values corresponding to the two ends of the current time window.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A security data monitoring method, the method comprising:
acquiring market data and return data of securities;
positioning the market data and the return data to a pre-constructed time axis;
determining a current time window according to the time slices on the time axis;
determining target market data and target return data in the current time window;
determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data;
when the volume ratio of the securities is greater than or equal to a volume ratio threshold value of the securities and the unit numerical value fluctuation of the securities is greater than or equal to a unit numerical value fluctuation threshold value of the securities, judging that the unit numerical value of the securities is abnormal;
and when the volume of the securities is smaller than the volume of the securities than the threshold value, and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold value, and judging that the securities unit numerical value is normal.
2. The method of claim 1, further comprising:
determining a security data monitoring time interval;
dividing the time interval into corresponding time slices according to a preset time length;
and constructing a time axis according to the time intervals and the time slices.
3. The method of claim 1, wherein the locating the market data and the reward data onto a pre-constructed timeline comprises:
respectively extracting time information carried by the market data and the return data;
respectively matching the time information carried by the market data and the return data with a time slice on a pre-constructed time axis to obtain a matching result;
and positioning the market data and the return data to a pre-constructed time axis according to a matching result.
4. The method of claim 1, wherein determining a current time window from time slices on the time axis comprises:
determining a target time slice from the time slices on the time axis;
determining the starting time and the ending time corresponding to the target time slices according to the time sequence of the target time slices;
and determining the current time window according to the starting time and the ending time.
5. The method of claim 1, wherein said determining a stock volume ratio based on said target market data and said target reward data comprises:
when the access time of the target market data and the target return data is aligned, determining the security commission quantity in the current time window according to the target market data;
determining the number of securities reported in the current time window according to the target report data;
and determining the ratio of the return quantity of the securities to the entrusted quantity of the securities as the proportion of the volume of trades of the securities.
6. The method of claim 5, further comprising:
when the access time of the target market data and the target return data is not aligned, determining an access time difference value between the target market data and the target return data;
and performing supplementary calculation on the target market data and the target return data according to the access time difference so as to obtain the stock volume ratio.
7. The method according to any one of claims 1 to 6, wherein said determining securities unit value fluctuations from said target market data comprises:
extracting securities unit numerical value fluctuation data from the target market data;
determining security unit values corresponding to two ends of the current time window according to the security unit value fluctuation data;
and determining the increment of the security unit numerical value according to the security unit numerical values corresponding to the two ends of the current time window.
8. A security data monitoring device, said device comprising:
the acquisition module is used for acquiring market data and return data of the securities;
the positioning module is used for positioning the market data and the return data to a pre-constructed time axis;
the determining module is used for determining a current time window according to the time slices on the time axis; determining target market data and target return data in the current time window; determining the proportion of the stock volume according to the target market data and the target return data, and determining the unit value expansion of the stock according to the target market data;
the judgment module is used for judging that the unit value of the securities is abnormal when the volume ratio of the securities is greater than or equal to a volume ratio threshold value of the securities and the unit value expansion of the securities is greater than or equal to a unit value expansion threshold value of the securities; and when the volume of the securities is smaller than the volume of the securities than the threshold value, and/or the volume of the securities unit numerical value is smaller than the volume of the securities unit numerical value volume threshold value, returning to the step of determining the current time window according to the time slices on the time axis to continue to execute until the number of the time slices in the current time window reaches the preset number threshold value, and judging that the securities unit numerical value is normal.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented by the processor when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113612567A (en) * | 2021-10-11 | 2021-11-05 | 树根互联股份有限公司 | Alignment method and device for data collected by multiple sensors of equipment and electronic equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019070589A1 (en) * | 2017-10-02 | 2019-04-11 | Imperative Execution Inc. | Systems and methods for optimizing trade execution |
| CN110032670A (en) * | 2019-04-17 | 2019-07-19 | 腾讯科技（深圳）有限公司 | Method for detecting abnormality, device, equipment and the storage medium of time series data |
| CN111027745A (en) * | 2019-11-08 | 2020-04-17 | 广东财经大学 | Stock index prediction method based on self-adaptive feature extraction |
| CN112150162A (en) * | 2020-11-24 | 2020-12-29 | 深圳华锐金融技术股份有限公司 | Transaction account supervision method and device, computer equipment and storage medium |
-
2021
- 2021-01-21 CN CN202110078711.0A patent/CN112465646B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019070589A1 (en) * | 2017-10-02 | 2019-04-11 | Imperative Execution Inc. | Systems and methods for optimizing trade execution |
| CN110032670A (en) * | 2019-04-17 | 2019-07-19 | 腾讯科技（深圳）有限公司 | Method for detecting abnormality, device, equipment and the storage medium of time series data |
| CN111027745A (en) * | 2019-11-08 | 2020-04-17 | 广东财经大学 | Stock index prediction method based on self-adaptive feature extraction |
| CN112150162A (en) * | 2020-11-24 | 2020-12-29 | 深圳华锐金融技术股份有限公司 | Transaction account supervision method and device, computer equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 翁小清等: ""基于滑动窗口的多变量时间序列异常数据的挖掘"", 《计算机工程》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113612567A (en) * | 2021-10-11 | 2021-11-05 | 树根互联股份有限公司 | Alignment method and device for data collected by multiple sensors of equipment and electronic equipment |
| CN113612567B (en) * | 2021-10-11 | 2021-12-14 | 树根互联股份有限公司 | Alignment method and device for data collected by multiple sensors of equipment and electronic equipment |
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Address after: Room 2301, building 5, Shenzhen new generation industrial park, 136 Zhongkang Road, Meidu community, Meilin street, Futian District, Shenzhen City, Guangdong Province Patentee after: Shenzhen Huarui Distributed Technology Co.,Ltd. Address before: Room 2301, building 5, Shenzhen new generation industrial park, 136 Zhongkang Road, Meidu community, Meilin street, Futian District, Shenzhen City, Guangdong Province Patentee before: SHENZHEN ARCHFORCE FINANCIAL TECHNOLOGY Co.,Ltd. |