CN108876059A

CN108876059A - Transaction data processing method, device, electronic equipment and computer storage medium

Info

Publication number: CN108876059A
Application number: CN201810845037.2A
Authority: CN
Inventors: 胡士兴
Original assignee: Alibaba Group Holding Ltd
Current assignee: Advanced New Technologies Co Ltd; Advantageous New Technologies Co Ltd
Priority date: 2018-07-27
Filing date: 2018-07-27
Publication date: 2018-11-23

Abstract

The embodiment of the invention discloses a kind of transaction data processing method, device, electronic equipment and computer storage medium, the method includes：Obtain the first transaction prediction data of default future time；Obtain the market price variation prediction information of default future time；Default second transactional operation is executed according to the first transaction prediction data and market price variation prediction information.The technical solution can fully consider the risk that the preferential and service side provided by client faces, i.e., evade service side's risk as much as possible while providing convenient for client, and then greatly improve the usage experience of user.

Description

Transaction data processing method and device, electronic equipment and computer storage medium

Technical Field

The embodiment of the invention relates to the technical field of data processing, in particular to a transaction data processing method and device, electronic equipment and a computer storage medium.

Background

In the financial field, many transactions have certain market risks, such as interest rate risk, exchange rate risk, stock price risk, commodity price risk, and the like. For example, the conventional foreign exchange service operation scheme provided by the service provider is as follows: the method comprises the following steps of normally accepting a client foreign exchange request, accumulating the open of the foreign exchange, and opening the open of the foreign exchange to a flat plate of a foreign exchange market according to a certain time period, such as every moment and every hour, wherein the open of the foreign exchange refers to the phenomenon that a certain currency is bought too much or sold too much due to non-timely compensation, and the scheme has the following defects: if a time difference exists between the acceptance of the foreign exchange request of the client and the open flat disc and the fluctuation of foreign exchange markets is severe in the time difference, if foreign exchange offers which are as preferential as possible are provided for the client, the risk of fund loss may exist when the service side is flat disc; if a high foreign exchange offer is provided to a customer, the risk of fund loss due to the flat disk can be largely avoided, but the attraction to the customer is reduced, and the amount of the customer is lost. The other scheme is that a client exchange request and a balance foreign exchange opening are synchronized, and the scheme has the problems that when the client exchanges foreign exchanges, the same industry market is not always at a service time point, so that the risk that the opening cannot be leveled in real time still exists, if the client foreign exchange service is carried out in a service time window opened in the same industry market, and other times are not opened, the client foreign exchange requirements cannot be met, and the use experience of the client is greatly reduced. Therefore, how to avoid the risks faced by the service provider as much as possible while providing convenience to the client is an urgent problem to be solved.

Disclosure of Invention

The embodiment of the invention provides a transaction data processing method and device, electronic equipment and a computer-readable storage medium.

In a first aspect, an embodiment of the present invention provides a transaction data processing method.

Specifically, the transaction data processing method includes:

acquiring first transaction prediction data of a preset future time;

acquiring market price change prediction information of preset future time;

and executing preset second transaction operation according to the first transaction prediction data and the market price change prediction information.

With reference to the first aspect, in a first implementation manner of the first aspect, the obtaining first transaction prediction data of a preset future time includes:

obtaining a first transaction data prediction element, wherein the first transaction data prediction element comprises one or more of: presetting first transaction data in a historical time period, the timeliness information of the preset future time, first transaction related data in the historical time period and transaction related data of the preset future time;

and acquiring first transaction prediction data of preset future time according to the first transaction data prediction element.

With reference to the first aspect and the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the obtaining of the market price change prediction information at the preset future time includes:

obtaining a market price change information prediction element, wherein the market price change information prediction element comprises one or more of the following elements: market price data in a preset historical time period, market price change data in the preset historical time period and timeliness information of the preset future time are preset;

and obtaining market price change prediction information of preset future time according to the market price change information prediction element.

With reference to the first aspect, the first implementation manner of the first aspect, and the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the performing a preset second transaction operation according to the first transaction prediction data and the market price change prediction information includes:

executing a second buy operation corresponding to the first trade prediction data when it is determined that the market price change prediction information is elevated;

executing a second selling operation corresponding to the first trade prediction data when it is determined that the market price change prediction information is decreased;

executing a second sell operation corresponding to the first trade prediction data at the preset future time when the market price change prediction information is determined to be elevated;

executing a second buy operation corresponding to the first trade prediction data at the preset future time when the market price change prediction information is determined to be decreasing.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, and the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the performing a preset second transaction operation according to the first transaction prediction data and the market price change prediction information includes:

acquiring a second transaction predicted time of a preset future time;

and executing preset second transaction operation at the second transaction prediction time according to the first transaction prediction data and the market price change prediction information.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, and the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the executing a preset second transaction operation at the second transaction prediction time according to the first transaction prediction data and the market price change prediction information includes:

executing a second buy operation corresponding to the first trade prediction data at the second trade prediction time when it is determined that the market price change prediction information is elevated;

executing a second selling operation corresponding to the first trade prediction data at the second trade prediction time when it is determined that the market price change prediction information is decreased;

when it is determined that the market price change prediction information is rising, performing a second selling operation corresponding to the first trade prediction data at a second trade prediction time of the preset future time;

and when the market price change prediction information is determined to be reduced, executing a second buying operation corresponding to the first transaction prediction data at a second transaction prediction time of the preset future time.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, and the fifth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the embodiment of the present invention further includes:

the first transaction price is adjusted according to the first transaction price, the first transaction data, the second transaction price, and the second transaction data.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, and the sixth implementation manner of the first aspect, in a seventh implementation manner of the first aspect, the adjusting the first transaction price according to the first transaction price, the first transaction data, the second transaction price, and the second transaction data includes:

determining a first trading price, the first trading price being lower than a current market trading price;

acquiring first transaction data, a second transaction price and second transaction data;

calculating a first transaction price adjustment value according to the first transaction price, the first transaction data, the second transaction price and the second transaction data;

and adjusting the first transaction price according to the first transaction price adjusting value.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, and the seventh implementation manner of the first aspect, in an eighth implementation manner of the first aspect, the embodiment of the present invention further includes:

and compensating the spread price for the first trading party which completes the trading before the first trading price is adjusted.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, the seventh implementation manner of the first aspect, and the eighth implementation manner of the first aspect, in a ninth implementation manner of the first aspect, the performing the spread compensation on the first transaction party who completes the transaction before the first transaction price adjustment includes:

acquiring first transaction data occurring before price adjustment;

calculating a trading fee difference of a first trading user before and after price adjustment according to the first trading price adjustment value, wherein the first trading user is a trading user corresponding to first trading data generated before price adjustment;

returning the transaction fee balance to the first transaction user.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, the seventh implementation manner of the first aspect, the eighth implementation manner of the first aspect, and the ninth implementation manner of the first aspect, an embodiment of the present invention further includes, in a tenth implementation manner of the first aspect:

and repeating the steps of adjusting the first trading price and compensating the difference price for the first trading party until a preset ending condition is met.

In a second aspect, an embodiment of the present invention provides a transaction data processing apparatus.

Specifically, the transaction data processing apparatus includes:

a first obtaining module configured to obtain first transaction prediction data for a preset future time;

a second obtaining module configured to obtain market price change prediction information of a preset future time;

and the execution module is configured to execute preset second transaction operation according to the first transaction prediction data and market price change prediction information.

With reference to the second aspect, in a first implementation manner of the second aspect, the embodiment of the present invention includes:

a first obtaining sub-module configured to obtain a first transaction data prediction element, wherein the first transaction data prediction element comprises one or more of the following elements: presetting first transaction data in a historical time period, the timeliness information of the preset future time, first transaction related data in the historical time period and transaction related data of the preset future time;

a second obtaining sub-module configured to obtain first transaction prediction data for a preset future time according to the first transaction data prediction element.

With reference to the second aspect and the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the embodiment of the present invention includes:

a third obtaining sub-module configured to obtain a market price change information prediction element, wherein the market price change information prediction element includes one or more of the following elements: market price data in a preset historical time period, market price change data in the preset historical time period and timeliness information of the preset future time are preset;

a fourth obtaining sub-module configured to obtain market price change prediction information of a preset future time according to the market price change information prediction element.

With reference to the second aspect, the first implementation manner of the second aspect, and the second implementation manner of the second aspect, in a third implementation manner of the second aspect, the execution module of the embodiment of the present invention includes:

a first execution sub-module configured to execute a second buy operation corresponding to the first trade prediction data when it is determined that the market price change prediction information is elevated;

a second execution sub-module configured to execute a second selling operation corresponding to the first trade prediction data when it is determined that the market price change prediction information is a reduction;

a third execution sub-module configured to execute a second selling operation corresponding to the first trade prediction data at the preset future time when it is determined that the market price change prediction information is elevated;

a fourth execution sub-module configured to execute a second buy operation corresponding to the first trade prediction data at the preset future time when the market price change prediction information is determined to be decreasing.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, and the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the embodiment of the present invention includes:

a fifth obtaining sub-module configured to obtain a second transaction predicted time of a preset future time;

a fifth execution sub-module configured to execute a preset second trading operation at the second trading prediction time according to the first trading prediction data and market price change prediction information.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, and the fourth implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the fifth execution sub-module in the embodiment of the present invention includes:

a sixth execution sub-module configured to, when it is determined that the market price change prediction information is an increase, execute a second buy operation corresponding to the first trade prediction data at the second trade prediction time;

a seventh execution sub-module configured to, when it is determined that the market price change prediction information is a decrease, execute a second sell operation corresponding to the first trade prediction data at the second trade prediction time;

an eighth execution sub-module configured to, when it is determined that the market price change prediction information is elevated, execute a second selling operation corresponding to the first trade prediction data at a second trade prediction time of the preset future time;

a ninth execution sub-module configured to, when it is determined that the market price change prediction information is a decrease, execute a second buy operation corresponding to the first trade prediction data at a second trade prediction time of the preset future time.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, and the fifth implementation manner of the second aspect, in a sixth implementation manner of the second aspect, the embodiment of the present invention further includes:

an adjustment module configured to adjust the first transaction price according to the first transaction price, the first transaction data, the second transaction price, and the second transaction data.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, and the sixth implementation manner of the second aspect, in a seventh implementation manner of the second aspect, the adjusting module includes:

a determination submodule configured to determine a first trading price, the first trading price being lower than a current market trading price;

a sixth obtaining sub-module configured to obtain the first transaction data, the second transaction price, and the second transaction data;

a first calculation submodule configured to calculate a first transaction price adjustment value from the first transaction price, first transaction data, a second transaction price and second transaction data;

an adjustment submodule configured to adjust the first transaction price according to the first transaction price adjustment value.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, and the seventh implementation manner of the second aspect, in an eighth implementation manner of the second aspect, the embodiment of the present invention further includes:

a compensation module configured to compensate for a spread for a first counterparty completing a transaction prior to the first transaction price adjustment.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, the seventh implementation manner of the second aspect, and the eighth implementation manner of the second aspect, in a ninth implementation manner of the second aspect, the compensation module includes:

a seventh obtaining sub-module configured to obtain first transaction data occurring before price adjustment;

a second calculation sub-module configured to calculate a difference between transaction fees of the first transaction user before and after the price adjustment according to the first transaction price adjustment value, wherein the first transaction user is a transaction user corresponding to first transaction data occurring before the price adjustment;

a return submodule configured to return the transaction fee balance to the first transaction user.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, the seventh implementation manner of the second aspect, the eighth implementation manner of the second aspect, and the ninth implementation manner of the second aspect, in a tenth implementation manner of the second aspect, the adjusting module and the compensating module are further configured to:

In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory is used to store one or more computer instructions that support a transaction data processing apparatus to execute the transaction data processing method in the first aspect, and the processor is configured to execute the computer instructions stored in the memory. The transaction data processing apparatus may further comprise a communication interface for the transaction data processing apparatus to communicate with other devices or a communication network.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium for storing computer instructions for a transaction data processing apparatus, which includes computer instructions for executing the transaction data processing method in the first aspect as described above.

The technical scheme provided by the embodiment of the invention has the following beneficial effects:

according to the technical scheme, whether pre-trading operation is needed or what pre-trading operation is needed is determined by predicting the trading data facing customers in the future and the market price change information. The technical scheme can fully consider the preferential offer provided for the client and the risk faced by the service provider, namely, the service provider risk is avoided as much as possible while providing convenience for the client, and further the use experience of the user is greatly improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the invention.

Drawings

Other features, objects and advantages of embodiments of the invention will become more apparent from the following detailed description of non-limiting embodiments thereof, when taken in conjunction with the accompanying drawings. In the drawings:

FIG. 1 shows a flow diagram of a transaction data processing method according to an embodiment of the invention;

FIG. 2 shows a flow chart of step S101 of a transaction data processing method according to the embodiment shown in FIG. 1;

FIG. 3 shows a flow chart of step S102 of a transaction data processing method according to the embodiment shown in FIG. 1;

FIG. 4 shows a flow chart of step S103 of a transaction data processing method according to the embodiment shown in FIG. 1;

fig. 5 shows a flowchart of step S103 of a transaction data processing method according to another embodiment of the present invention;

FIG. 6 shows a flow chart of step S502 of the transaction data processing method according to the embodiment shown in FIG. 5;

FIG. 7 shows a flow diagram of a transaction data processing method according to another embodiment of the invention;

FIG. 8 shows a flowchart of step S704 of the transaction data processing method according to the embodiment shown in FIG. 7;

FIG. 9 shows a flowchart of step S804 of the transaction data processing method according to the embodiment shown in FIG. 8;

FIG. 10 shows a flow diagram of a transaction data processing method according to another embodiment of the invention;

fig. 11 shows a flowchart of step S1005 of the transaction data processing method according to the embodiment shown in fig. 10;

fig. 12 is a block diagram showing the construction of a transaction data processing apparatus according to an embodiment of the present invention;

fig. 13 is a block diagram showing a configuration of a first obtaining module 1201 of the transaction data processing apparatus according to the embodiment shown in fig. 12;

fig. 14 shows a block diagram of the second acquisition module 1202 of the transaction data processing apparatus according to the embodiment shown in fig. 12;

fig. 15 is a block diagram showing the structure of an execution module 1203 of the transaction data processing apparatus according to the embodiment shown in fig. 12;

fig. 16 is a block diagram showing the structure of an execution module 1203 of the transaction data processing apparatus according to another embodiment of the present invention;

fig. 17 is a block diagram showing a fifth execution sub-module 1602 of the transaction data processing apparatus according to the embodiment shown in fig. 16;

fig. 18 is a block diagram showing the construction of a transaction data processing apparatus according to another embodiment of the present invention;

FIG. 19 is a block diagram illustrating the configuration of the adjustment module 1804 of the transaction data processing apparatus according to the embodiment shown in FIG. 18;

fig. 20 is a block diagram showing the structure of an adjustment submodule 1904 of the transaction data processing apparatus according to the embodiment shown in fig. 19;

fig. 21 is a block diagram showing the construction of a transaction data processing apparatus according to another embodiment of the present invention;

FIG. 22 illustrates a block diagram of a compensation module 2105 of the transaction data processing apparatus according to the embodiment illustrated in FIG. 21;

FIG. 23 shows a block diagram of an electronic device according to an embodiment of the invention;

fig. 24 is a schematic block diagram of a computer system suitable for implementing a transaction data processing method according to an embodiment of the present invention.

Detailed Description

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.

In the embodiments of the present invention, it is to be understood that terms such as "including" or "having", etc., are intended to indicate the presence of the features, numbers, steps, actions, components, parts, or combinations thereof disclosed in the present specification, and are not intended to exclude the possibility that one or more other features, numbers, steps, actions, components, parts, or combinations thereof may be present or added.

It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. Embodiments of the present invention will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

The technical scheme provided by the embodiment of the invention determines whether or not pre-trading operation is needed or what pre-trading operation is needed by predicting the customer-oriented trading data and market price change information at the future time, wherein the pre-trading operation refers to pre-executed trading operation, such as pre-buying or pre-selling. The technical scheme can fully consider the preferential offer provided for the client and the risk faced by the service provider, namely, the service provider risk is avoided as much as possible while providing convenience for the client, and further the use experience of the user is greatly improved.

Fig. 1 shows a flowchart of a transaction data processing method according to an embodiment of the present invention, which, as shown in fig. 1, includes the following steps S101-S103:

in step S101, first transaction prediction data of a preset future time is acquired;

in step S102, market price change prediction information at a preset future time is acquired;

in step S103, a preset second trading operation is performed according to the first trading prediction data and market price change prediction information.

As mentioned above, in the financial field, many transactions have certain market risks, such as interest rate risk, exchange rate risk, stock price risk, commodity price risk, and so on. For foreign exchange trading, balancing the convenience offered to customers against the risk faced by the service provider is a difficult problem to deal with.

In view of the above problem, in this embodiment, a transaction data processing method is proposed, which first acquires prediction data of first transaction data of a preset future time, that is, first transaction prediction data; then obtaining market price change prediction information of preset future time; and finally, executing preset second transaction operation according to the first transaction prediction data and the market price change prediction information. The technical scheme can fully consider the preferential offer provided for the client and the risk faced by the service provider, namely, the service provider risk is avoided as much as possible while providing convenience for the client, and further the use experience of the user is greatly improved.

The preset future time refers to a future time relative to the current time, such as tomorrow, afterday, etc., of course, if necessary, the future time may be set to a more recent time, such as the next time, or a more distant time, such as the next week, the next month, etc., and the setting of the specific future time may be determined according to the needs of the actual application, which is not specifically limited by the present invention.

The first transaction data refers to transaction data between a service party and a client, the first transaction prediction data is data obtained by predicting the first transaction data, and the first transaction data at least comprises a first transaction quantity; the service party refers to a party that provides a transaction to a customer and is not a marketplace party.

Wherein, the prediction of the first transaction data and the market price change can be realized by a prediction model, and the prediction model can be generated by comprehensively considering long-term, medium-term and short-term historical transaction data, wherein the long term can be a 'year' grade, the medium term can be a 'month' grade, and the short term can be a 'day' or 'hour' grade.

In order to adapt to market changes, the preset model can be dynamically adjusted according to market data so as to tend to regression perfection. It should be noted that, the use of the prediction model may be selected according to the needs of practical application and the characteristics of the data to be predicted, and the present invention is not limited to this specific one, but all prediction models capable of effectively predicting the first transaction data and the market price change information fall within the protection scope of the present invention.

Wherein the second transaction refers to a transaction between the service party and the market, and the second transaction operation refers to a transaction operation between the service party and the market.

In an optional implementation manner of this embodiment, as shown in fig. 2, the step S101, that is, the step of obtaining the first transaction prediction data of the preset future time, includes the following steps S201 to S202:

in step S201, a first transaction data prediction element is acquired;

in step S202, first transaction prediction data of a preset future time is obtained according to the first transaction data prediction element.

Wherein the first transactional data prediction element comprises one or more of the following elements: the method comprises the steps of presetting first transaction data in a historical time period, presetting future time timeliness information and presetting first transaction related data in the historical time period.

In this embodiment, the first transaction prediction data at the preset future time is predicted in consideration of the first transaction data within the preset historical period of time, the preset future time timeliness information, and one or more prediction elements in the first transaction-related data within the preset historical period of time to improve the accuracy of the first transaction prediction data.

The preset historical time period refers to a historical time period before the current time, and the length of the historical time period can be determined according to the requirements of actual application; the future time timeliness information refers to information related to a future time and having timeliness that may have an impact on the first transaction, such as for foreign exchange, the future time timeliness information may include: whether the future time is daily time, whether shopping information for strong sales promotion and the like exists, whether the future time is on holidays, whether the future time is in a cold or hot holiday period, whether relevant current news exists and the like; the first transaction related data refers to other related data that may have an impact on the first transaction, such as for foreign exchange, the first transaction related data may include cross-border travel data, global purchase data, overseas purchase data, and the like.

In an optional implementation manner of this embodiment, as shown in fig. 3, the step S102, namely the step of obtaining the market price change prediction information of the preset future time, includes the following steps S301 to S302:

in step S301, a market price change information prediction element is acquired;

in step S302, market price change prediction information of a preset future time is acquired according to the market price change information prediction element.

Wherein the market price change information prediction element comprises one or more of the following elements: market price data in a preset historical time period, market price change data in the preset historical time period and timeliness information of the preset future time.

In this embodiment, the market price change prediction information at the preset future time is predicted in consideration of one or more prediction elements among the market price data at the preset historical time period, the market price change data at the preset historical time period, and the timeliness information at the preset future time, so as to improve the accuracy of the market price change prediction information.

The market price change data may be, for example, a market price change rate in a preset time period, a market price change probability in a preset time period, or the like; the future time timeliness information is similar to that described above and will not be described in detail here.

In an optional implementation manner of this embodiment, as shown in fig. 4, the step S103, namely the step of executing a preset second trading operation according to the first trading prediction data and the market price change prediction information, includes the following steps S401 to S404:

in step S401, when it is determined that the market price change prediction information is an increase, performing a second buy operation corresponding to the first trade prediction data;

in step S402, when it is determined that the market price change prediction information is a decrease, performing a second selling operation corresponding to the first trade prediction data;

in step S403, when it is determined that the market price change prediction information is an increase, performing a second selling operation corresponding to the first trade prediction data at the preset future time;

in step S404, when it is determined that the market price change prediction information is a decrease, a second buying operation corresponding to the first trade prediction data is performed at the preset future time.

In this embodiment, the preset second transaction operation is executed based on the first transaction prediction data and the market price change prediction information, so that the risk caused by price fluctuation of foreign currency can be avoided scientifically and maximally.

Wherein the second transaction operation corresponding to the first transaction prediction data refers to performing the same number or more of second transaction operations as the first transaction prediction data.

In the following description of the present embodiment, with reference to the exchange example, if it is assumed that the future time is tomorrow, then when it is determined that the market price change prediction information is rising, that is, the tomorrow foreign currency market price is higher than today, this means that if the foreign currency is purchased tomorrow, more money is required, and therefore, the same amount or more foreign currencies as the first transaction prediction data need to be purchased today; when it is determined that the market price change prediction information is decreased, that is, the price of the foreign currency is lower than that of the current day, this means that less cost is required if the foreign currency is purchased again in the current day, and therefore, the foreign currency with the same amount or more than the amount of the first transaction prediction data can be purchased again in the current day; similarly, when it is determined that the market price change prediction information is rising, i.e., the tomorrow foreign currency price is higher than today, this means that more fees are received if the foreign currency is sold tomorrow, and therefore, the same amount or more of foreign currency as the first transaction prediction data can be sold tomorrow; when it is determined that the market price change prediction information is decreasing, i.e., the tomorrow foreign currency price is lower than today, this means that less money is received if the foreign currency is sold tomorrow, and therefore, the same amount or more foreign currency as the first trade prediction data needs to be sold today.

In another optional implementation manner of this embodiment, as shown in fig. 5, the step S103 of performing a preset second trading operation according to the first trading prediction data and the market price change prediction information includes the following steps S501 to S502:

in step S501, a second predicted transaction time of a preset future time is obtained;

in step S502, a preset second trading operation is performed at the second trading prediction time according to the first trading prediction data and market price change prediction information.

In order to further improve the accuracy of the second trading operation, in this embodiment, the trading time of the second trading is also predicted, wherein the prediction of the second trading time is similar to the prediction of the first trading data and the market price change, and can also be realized by a prediction model, and the prediction model can also be generated by comprehensively considering the long-term, medium-term and short-term market price change data, for example, the prediction model can obtain the distribution probability of market price low points in each day within a preset historical time period, such as the last 1 year, by counting the change of the historical market price, and then predict that the second trading operation performed at a certain time point of each day or future time is relatively low in cost.

Further, in an optional implementation manner of this embodiment, as shown in fig. 6, the step S502, namely the step of performing a preset second trading operation at the second trading prediction time according to the first trading prediction data and the market price change prediction information, includes the following steps S601-S604:

in step S601, when it is determined that the market price change prediction information is an increase, performing a second buy operation corresponding to the first trade prediction data at the second trade prediction time;

in step S602, when it is determined that the market price change prediction information is a decrease, performing a second selling operation corresponding to the first trade prediction data at the second trade prediction time;

in step S603, when it is determined that the market price change prediction information is an increase, performing a second selling operation corresponding to the first trade prediction data at a second trade prediction time of the preset future time;

in step S604, when it is determined that the market price change prediction information is a decrease, a second buying operation corresponding to the first trading prediction data is performed at a second trading prediction time of the preset future time.

This embodiment is similar to the embodiment shown in fig. 4, except that when the second transaction operation is performed, consideration is added to the predicted time point of the transaction, and the description of the present invention is omitted here.

In an optional implementation manner of this embodiment, the method further includes a step of adjusting the first transaction price, that is, as shown in fig. 7, the method includes the following steps S701 to S704:

in step S701, first transaction prediction data of a preset future time is acquired;

in step S702, market price change prediction information at a preset future time is acquired;

in step S703, a preset second trading operation is executed according to the first trading prediction data and market price change prediction information;

in step S704, an adjustment is made to the first transaction price based on the first transaction price, the first transaction data, the second transaction price, and the second transaction data.

Wherein the second transaction data comprises at least a second transaction amount.

In an optional implementation manner of this embodiment, as shown in fig. 8, the step S704, that is, the step of adjusting the first transaction price according to the first transaction price, the first transaction data, the second transaction price and the second transaction data, includes the following steps S801 to S804:

in step S801, a first trading price is determined, the first trading price being lower than a current market trading price;

in step S802, first transaction data, a second transaction price, and second transaction data are acquired;

in step S803, a first transaction price adjustment value is calculated according to the first transaction price, the first transaction data, the second transaction price and the second transaction data;

in step S804, the first transaction price is adjusted according to the first transaction price adjustment value.

In the above embodiment, a first trading price for the customer is first determined, wherein the first trading price is set to be lower than the current market trading price in order to attract the customer; then acquiring first transaction data which are oriented to the client and have already occurred and second transaction data which are oriented to the market and have already occurred; then, a first transaction price adjusting value is obtained through calculation according to the first transaction price, the first transaction data and the second transaction data; and finally, adjusting the first transaction price according to the first transaction price adjusting value. Since the server is the second transaction performed based on the forecast data, the second transaction price will typically be lower than the current market transaction price, which will also be lower than the first transaction price in order not to lose costs. According to the embodiment, a first preferential transaction price is determined according to the second transaction price, and then the first transaction price is adjusted in real time according to the actually occurring first transaction data, so that the aim of providing the customer with the preferential transaction to the greatest extent is fulfilled.

Wherein, when determining the first trading price, the step S801 may determine the first trading price according to a price difference between the second trading price and the market trading price, for example, the price difference between the second trading price and the market trading price is 6 yuan, that is, the service party performs the buy operation in advance at a price lower than the current market price 6 yuan the day, for the market price, the service party generates a profit of 6 yuan per price on the day, therefore, in order to provide sufficient benefit to the customer, the first trading price may be generated by reducing a value on the basis of the market trading price, the value is less than or equal to the price difference between the second trading price and the market trading price, the specific value may be set according to the actual application requirement, for example, if all profits are to be released, the maximum benefit is created for the customer, the first market price may be set 6 dollars below the market price and may be set 5 dollars or less below the market price if it is desired to retain some price margin.

In an optional implementation manner of this embodiment, as shown in fig. 9, the step S804 of adjusting the first transaction price according to the first transaction price adjustment value includes the following steps S901 to S905:

in step S901, a price difference between the first transaction price and the second transaction price is calculated;

in step S902, calculating a product value between the price difference value and the first transaction amount;

in step S903, a quantity difference between the first transaction quantity and the second transaction quantity is calculated;

in step S904, a quotient value between the product value and the quantity difference value is calculated;

in step S905, the first transaction price adjustment value is generated according to the quotient value.

For example, assuming that a first trading price of a certain trading object is 10 yuan, a market trading price is 12 yuan, a second trading price is 9 yuan, a first trading volume generated by a first trading party is 100 yuan, and a second trading volume is 120 yuan, the service party has previously performed the second trading, and thus has obtained some profits, specifically, the profit generated based on the first trading volume is 100 yuan (10-9) × 100 yuan, and the remaining available volume of the service party is 120 yuan 100-, it is also possible to score only a portion of the generated profit to the remaining available quantity, such as only 50 out of 100 dollars to the remaining available quantity, and then the unit remaining available quantity can be divided equally into 2.5 dollars, i.e., the first trade price can be reduced to 10-2.5 to 7.5 dollars.

In an optional implementation manner of this embodiment, the method further includes a step of compensating for the spread of the first trading party who completes the trading before the first trading price is adjusted, that is, as shown in fig. 10, the method includes the following steps S1001 to S1005:

in step S1001, first transaction prediction data of a preset future time is acquired;

in step S1002, market price change prediction information at a preset future time is acquired;

in step S1003, executing a preset second trading operation according to the first trading prediction data and market price change prediction information;

in step S1004, adjusting the first transaction price according to the first transaction price, the first transaction data, the second transaction price and the second transaction data;

in step S1005, spread compensation is performed for the first transaction part that completes the transaction before the first transaction price adjustment.

Of course, the service party may also choose not to perform the spread compensation operation after the first transaction price adjustment, which may be set according to the needs of the actual application.

In an optional implementation manner of this embodiment, as shown in fig. 11, the step S1005, that is, the step of compensating the spread for the first trading party who completes the trading before the first trading price is adjusted, includes the following steps S1101-S1103:

in step S1101, first transaction data occurring before price adjustment is acquired;

in step S1102, calculating a transaction fee difference between the first transaction user and the second transaction user before and after the price adjustment according to the first transaction price adjustment value, wherein the first transaction user is a transaction user corresponding to the first transaction data occurring before the price adjustment;

in step S1103, the transaction fee balance is returned to the first transaction user.

In this embodiment, in order to maintain the benefit of the customer to the maximum extent, after the first trading price is adjusted downward, spread compensation is also performed for the first trading party who completed the trade before the first trading price is adjusted. As mentioned above, since the second trade price is obtained by executing the second trade under the direction of the forecast data, the second trade price is usually lower than the market trade price, so that the adjustment of the first trade price is usually performed downward, if the first trade price is adjusted upward due to the previous compensation amount or other reasons, no trace back process is performed for the first trade party who completes the trade before the first trade price is adjusted.

In an optional implementation manner of this embodiment, after the spread compensation operation is performed, the first trading price may be adjusted again based on the current first trading price, the current first trading data, the second trading price and the second trading data, and of course, after the price adjustment is performed again, the spread compensation may be performed on the first trading party needing the spread compensation, so that the price adjustment and the spread compensation may be performed repeatedly until a preset ending condition is met, where the preset ending condition may be one or more of a time condition, a cycle number condition, and a profit of the service party lower than a preset profit threshold.

In an optional implementation manner of this embodiment, after the first transaction price is adjusted, the spread compensation is performed, or after price adjustment and spread compensation are performed repeatedly, the method may further include the following steps:

calculating a difference between the first transaction amount and a second transaction amount;

and executing preset second transaction post-operation according to the difference value between the first transaction amount and the second transaction amount.

Wherein the pre-second post-transaction operation comprises one or more of: buyback, return, sell, etc.

In this embodiment, in order to reduce the transaction risk of the service party to the maximum extent, after the first transaction price is adjusted, the spread compensation is performed, or after the price adjustment and the spread compensation are performed for multiple times in a circulating manner, the method further includes the step of performing a preset second post-transaction operation to eliminate the potential risk caused by the difference between the first transaction quantity and the second transaction quantity.

For example, if the foreign exchange quantity purchased by the service side from the market is larger than the foreign exchange quantity purchased by the client from the service side calculated on the same day, namely the service side generates foreign exchange goods, the service side can sell the accumulated foreign exchange quantity to the market; if the calculated foreign exchange amount purchased by the server from the market is less than the foreign exchange amount purchased by the client from the server, namely the server generates foreign exchange backorders, the server can make up for the missing foreign exchange amount from the market.

Of course, the service party may also determine whether the preset second post-transaction operation needs to be performed according to the transaction prediction data, that is, according to the difference between the first transaction amount and the second transaction amount, the step of performing the preset second post-transaction operation is replaced with: and executing preset second trade post-operation according to the difference value between the first trade quantity and the second trade quantity and the market price change prediction information. For example, if the service party produces the foreign exchange accumulated goods on the same day and the price of the foreign exchange is predicted to increase on the next trading day, the service party can reserve the accumulated foreign exchange quantity to the next trading day for trading, and if the price of the foreign exchange is predicted to decrease on the next trading day, the service party can sell the accumulated foreign exchange quantity back to the market on the same day; for another example, if the service party produces a shortage of foreign currencies on the current day and the price of the foreign currencies on the next trading day is predicted to be increased, the service party can make a purchase of the amount of the missing foreign currencies from the market on the current day, and if the price of the foreign currencies on the next trading day is predicted to be decreased, the service party can make a purchase of the foreign currencies on the next trading day.

The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention.

Fig. 12 shows a block diagram of a transaction data processing device according to an embodiment of the present invention, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 12, the transaction data processing apparatus includes:

a first obtaining module 1201 configured to obtain first transaction prediction data for a preset future time;

a second obtaining module 1202 configured to obtain market price change prediction information of a preset future time;

and an executing module 1203 configured to execute a preset second trading operation according to the first trading prediction data and market price change prediction information.

In view of the above problem, in this embodiment, a transaction data processing apparatus is provided, which acquires prediction data of first transaction data of a preset future time, i.e., first transaction prediction data, by a first acquisition module 1201; obtaining market price change prediction information of a preset future time through a second obtaining module 1202; the execution module 1203 executes a preset second transaction operation according to the first transaction prediction data and the market price change prediction information. The technical scheme can fully consider the preferential offer provided for the client and the risk faced by the service provider, namely, the service provider risk is avoided as much as possible while providing convenience for the client, and further the use experience of the user is greatly improved.

In an optional implementation manner of this embodiment, as shown in fig. 13, the first obtaining module 1201 includes:

a first obtaining sub-module 1301 configured to obtain a first transaction data prediction element;

a second obtaining sub-module 1302 configured to obtain the first transaction prediction data of the preset future time according to the first transaction data prediction element.

In an optional implementation manner of this embodiment, as shown in fig. 14, the second obtaining module 1202 includes:

a third obtaining submodule 1401 configured to obtain a market price change information prediction element;

a fourth obtaining sub-module 1402 configured to obtain market price change prediction information of a preset future time according to the market price change information prediction element.

In an optional implementation manner of this embodiment, as shown in fig. 15, the executing module 1203 includes:

a first execution sub-module 1501 configured to execute a second buy operation corresponding to the first trade prediction data when it is determined that the market price change prediction information is elevated;

a second execution sub-module 1502 configured to execute a second sell operation corresponding to the first trade prediction data when the market price change prediction information is determined to be decreasing;

a third execution sub-module 1503 configured to execute, when it is determined that the market price change prediction information is an increase, a second selling operation corresponding to the first trade prediction data at the preset future time;

a fourth execution sub-module 1504 configured to execute a second buy operation corresponding to the first trade prediction data at the preset future time when it is determined that the market price change prediction information is a decrease.

In another optional implementation manner of this embodiment, as shown in fig. 16, the executing module 1203 includes:

a fifth obtaining sub-module 1601 configured to obtain a second predicted transaction time of a preset future time;

a fifth execution sub-module 1602 configured to execute a preset second transaction operation at the second transaction predicted time according to the first transaction predicted data and the market price change predicted information.

Further, in an optional implementation manner of this embodiment, as shown in fig. 17, the fifth execution sub-module 1602 includes:

a sixth execution sub-module 1701 configured to, when it is determined that the market price change prediction information is increased, execute a second buy operation corresponding to the first trade prediction data at the second trade prediction time;

a seventh execution submodule 1702 configured to, when it is determined that the market price change prediction information is a reduction, execute a second selling operation corresponding to the first trade prediction data at the second trade prediction time;

an eighth execution submodule 1703 configured to, when it is determined that the market price change prediction information is increased, execute a second selling operation corresponding to the first trade prediction data at a second trade prediction time of the preset future time;

a ninth execution sub-module 1704 configured to, when it is determined that the market price change prediction information is a decrease, execute a second buy operation corresponding to the first trade prediction data at a second trade prediction time of the preset future time.

This embodiment is similar to the embodiment shown in fig. 15, except that each execution submodule takes into account a predicted transaction time point when executing the second transaction operation, and the description of the present invention is omitted here.

In an optional implementation manner of this embodiment, the apparatus further includes a part for adjusting the first transaction price, that is, as shown in fig. 18, the apparatus includes:

a first obtaining module 1801 configured to obtain first transaction prediction data for a preset future time;

a second obtaining module 1802 configured to obtain market price change prediction information of a preset future time;

an execution module 1803 configured to execute a preset second transaction operation according to the first transaction prediction data and market price change prediction information

An adjustment module 1804 configured to adjust the first transaction price based on the first transaction price, the first transaction data, the second transaction price, and the second transaction data.

In an optional implementation manner of this embodiment, as shown in fig. 19, the adjusting module 1804 includes:

a determination submodule 1901 configured to determine a first trading price, the first trading price being lower than a current market trading price;

a sixth obtaining submodule 1902 configured to obtain the first transaction data, the second transaction price, and the second transaction data;

a first calculation submodule 1903 configured to calculate a first transaction price adjustment value from the first transaction price, the first transaction data, the second transaction price and the second transaction data;

an adjustment submodule 1904 configured to adjust the first transaction price according to the first transaction price adjustment value.

In the above embodiment, the determining sub-module 1901 first determines a first trading price facing the customer, wherein the first trading price is set to be lower than the current market trading price in order to attract the customer; the sixth obtaining sub-module 1902 obtains the first transaction data that has occurred for the customer and the second transaction data that has occurred for the market; the first calculation submodule 1903 calculates a first transaction price adjustment value according to the first transaction price, the first transaction data and the second transaction data; the adjustment sub-module 1904 adjusts the first transaction price based on the first transaction price adjustment value. Since the server is the second transaction performed based on the forecast data, the second transaction price will typically be lower than the current market transaction price, which will also be lower than the first transaction price in order not to lose costs. According to the embodiment, a first preferential transaction price is determined according to the second transaction price, and then the first transaction price is adjusted in real time according to the actually occurring first transaction data, so that the aim of providing the customer with the preferential transaction to the greatest extent is fulfilled.

Wherein, when determining the first trading price, the determining sub-module 1901 may determine the first trading price according to a price difference between the second trading price and the market trading price, for example, the price difference between the second trading price and the market trading price is 6 yuan, that is, the service party performs the buy operation in advance at a price lower than the current market price by 6 yuan the day before, and then the service party generates a profit with a price of 6 yuan for the market price on the day, so that, in order to provide sufficient benefit to the customer, the first trading price may be generated by reducing a value on the basis of the market trading price, the value is less than or equal to the price difference between the second trading price and the market trading price, and the specific value may be set according to the needs of practical application, for example, if it is desired to release all profits, create the maximum benefit for the customer, the first market price may be set 6 dollars below the market price and may be set 5 dollars or less below the market price if it is desired to retain some price margin.

In an optional implementation manner of this embodiment, as shown in fig. 20, the adjusting sub-module 1904 includes:

a third calculation submodule 2001 configured to calculate a price difference between the first transaction price and the second transaction price;

a fourth calculation submodule 2002 configured to calculate a product value between the price difference value and the first transaction amount;

a fifth calculation submodule 2003 configured to calculate a quantity difference between the first transaction quantity and the second transaction quantity;

a sixth calculation submodule 2004 configured to calculate a quotient value between the product value and the quantity difference value;

a generating submodule 2005 configured to generate the first transaction price adjustment value in accordance with the quotient value.

In an optional implementation manner of this embodiment, the apparatus further includes a part for compensating the spread for the first trading party who completes the trade before the first trading price is adjusted, that is, as shown in fig. 21, the apparatus includes:

a first obtaining module 2101 configured to obtain first transaction prediction data for a preset future time;

a second obtaining module 2102 configured to obtain market price change prediction information of a preset future time;

an execution module 2103 configured to execute a preset second transaction operation according to the first transaction prediction data and market price change prediction information

An adjustment module 2104 configured to adjust a first transaction price based on the first transaction price, the first transaction data, a second transaction price, and the second transaction data

A compensation module 2105 configured to compensate for a spread for a first counterparty completing the transaction prior to the first transaction price adjustment.

In an optional implementation manner of this embodiment, as shown in fig. 22, the compensation module 2105 includes:

a seventh obtaining submodule 2201 configured to obtain first transaction data occurring before the price adjustment;

a second calculation sub-module 2202 configured to calculate a difference of transaction fees of a first transaction user before and after price adjustment according to the first transaction price adjustment value, wherein the first transaction user is a transaction user corresponding to first transaction data occurring before price adjustment;

a return submodule 2203 configured to return the transaction fee balance to the first transaction user.

In an optional implementation of this embodiment, after performing the spread compensation operation, the first transaction price may be further adjusted again based on the current first transaction price, the current first transaction data, the second transaction price, and the second transaction data. Of course, the spread compensation can be performed on the first trading party needing spread compensation after the price adjustment is performed again, so that the price adjustment and the spread compensation can be performed for multiple times in a circulating manner until a preset ending condition is met, wherein the preset ending condition can be one or more of a time condition, a circulating time condition and a condition that the profit of the service party is lower than a preset profit threshold value. That is, the adjustment module and the compensation module may be further configured to: and repeating the steps of adjusting the first trading price and compensating the difference price for the first trading party until a preset ending condition is met.

In an optional implementation manner of this embodiment, the apparatus may further include:

a calculation module configured to calculate a difference between the first transaction amount and a second transaction amount;

and the post-operation execution module is configured to execute preset second post-transaction operation according to the difference value between the first transaction quantity and the second transaction quantity.

In this embodiment, in order to reduce the transaction risk of the service party to the maximum extent, after the first transaction price is adjusted, the spread compensation is performed, or after the price adjustment and the spread compensation are performed for multiple times in a circulating manner, a post-operation execution module may be further used to execute a preset second post-transaction operation, so as to eliminate a potential risk caused by a difference between the first transaction quantity and the second transaction quantity.

Of course, the service party may also determine whether the preset second post-transaction operation needs to be performed according to the transaction prediction data, that is, the post-operation execution module is configured to: and executing preset second trade post-operation according to the difference value between the first trade quantity and the second trade quantity and the market price change prediction information. For example, if the service party produces the foreign exchange accumulated goods on the same day and the price of the foreign exchange is predicted to increase on the next trading day, the service party can reserve the accumulated foreign exchange quantity to the next trading day for trading, and if the price of the foreign exchange is predicted to decrease on the next trading day, the service party can sell the accumulated foreign exchange quantity back to the market on the same day; for another example, if the service party produces a shortage of foreign currencies on the current day and the price of the foreign currencies on the next trading day is predicted to be increased, the service party can make a purchase of the amount of the missing foreign currencies from the market on the current day, and if the price of the foreign currencies on the next trading day is predicted to be decreased, the service party can make a purchase of the foreign currencies on the next trading day.

Fig. 23 is a block diagram illustrating a structure of an electronic device according to an embodiment of the present invention, and as shown in fig. 23, the electronic device 2300 includes a memory 2301 and a processor 2302; wherein,

the memory 2301 is used to store one or more computer instructions that are executed by the processor 2302 to implement any of the method steps described above.

As shown in fig. 24, the computer system 2400 includes a Central Processing Unit (CPU)2401, which can execute various processes in the above-described embodiments in accordance with a program stored in a Read Only Memory (ROM)2402 or a program loaded from a storage portion 2408 into a Random Access Memory (RAM) 2403. In the RAM2403, various programs and data necessary for the operation of the system 2400 are also stored. The CPU2401, ROM2402, and RAM2403 are connected to each other through a bus 2404. An input/output (I/O) interface 2405 is also connected to bus 2404.

The following components are connected to I/O interface 2405: an input portion 2406 including a keyboard, a mouse, and the like; an output portion 2407 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 2408 including a hard disk and the like; and a communication section 2409 including a network interface card such as a LAN card, a modem, or the like. The communication section 2409 performs communication processing via a network such as the internet. A driver 2410 is also connected to the I/O interface 2405 as needed. A removable medium 2411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 2410 as necessary, so that a computer program read out therefrom is installed into the storage portion 2408 as necessary.

In particular, the above described method may be implemented as a computer software program according to an embodiment of the present invention. For example, embodiments of the present invention include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the transaction data processing method. In such embodiments, the computer program may be downloaded and installed from a network via communications portion 2409, and/or installed from removable media 2411.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

As another aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium may be a computer-readable storage medium included in the apparatus in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the embodiments of the present invention.

The foregoing description is only exemplary of the preferred embodiments of the invention and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention according to the embodiments of the present invention is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept. For example, the above features and (but not limited to) the features with similar functions disclosed in the embodiments of the present invention are mutually replaced to form the technical solution.

Claims

1. A transaction data processing method, comprising:

acquiring first transaction prediction data of a preset future time;

acquiring market price change prediction information of preset future time;

2. The method of claim 1, wherein obtaining first transaction prediction data for a preset future time comprises:

3. The method according to claim 1 or 2, wherein the obtaining of the market price change prediction information for the preset future time comprises:

4. The method according to any one of claims 1 to 3, wherein said performing a predetermined second transaction operation based on said first transaction prediction data and market price change prediction information comprises:

5. The method according to any one of claims 1 to 3, wherein said performing a predetermined second transaction operation based on said first transaction prediction data and market price change prediction information comprises:

acquiring a second transaction predicted time of a preset future time;

6. The method of claim 5, wherein performing a preset second trade operation at the second trade prediction time based on the first trade prediction data and market price change prediction information comprises:

7. The method of any of claims 1-6, further comprising:

8. The method of claim 7, wherein adjusting the first transaction price based on the first transaction price, the first transaction data, the second transaction price, and the second transaction data comprises:

9. The method of claim 7 or 8, further comprising:

10. The method of claim 9, wherein compensating for the spread for the first counterparty completing the transaction prior to the first transaction price adjustment comprises:

acquiring first transaction data occurring before price adjustment;

returning the transaction fee balance to the first transaction user.

11. The method of claim 9 or 10, further comprising:

12. A transaction data processing apparatus, comprising:

13. The apparatus of claim 12, wherein the first obtaining module comprises:

14. The apparatus of claim 12 or 13, wherein the second obtaining module comprises:

15. The apparatus according to any one of claims 12-14, wherein the execution module comprises:

16. The apparatus according to any one of claims 12-14, wherein the execution module comprises:

17. The apparatus of claim 16, wherein the fifth execution submodule comprises:

18. The apparatus of any of claims 12-17, further comprising:

19. The apparatus of claim 18, wherein the adjustment module comprises:

20. The apparatus of claim 18 or 19, further comprising:

21. The apparatus of claim 20, wherein the compensation module comprises:

22. The apparatus of claim 20 or 21, wherein the adjustment module and compensation module are further configured to:

23. An electronic device comprising a memory and a processor; wherein,

the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of any of claims 1-11.

24. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 1-11.