Resource processing method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a resource processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: displaying a creation interface of a conditional transaction order of a target resource; in response to the input operation, displaying input condition information in the creation interface, the condition information at least comprising a transaction tendency, and the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering the transaction based on a transaction estimation model; and in response to the conditional transaction order creation operation, creating a conditional transaction order about the target resource based on the conditional information, the conditional transaction order being used for executing a transaction on the target resource. By adopting the method, the deviation of a single and subjective conditional transaction decision-making mode can be reduced, the accuracy and reliability of conditional transaction decision-making are improved, and the repeated interaction process of objects is avoided.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a resource processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] With the development of computer and internet technologies, people can now choose to invest and manage their finances online. Various platforms developed for resources provide convenient ways to trade resources such as deposits, stocks, and funds.

[0003] In related technologies, some platforms also support conditional trading functions. Conditional trading refers to allowing the object to specify the basic trading conditions of resources, such as trading shares and trading prices. Once the current trading price of the resource reaches or exceeds the trading price specified by the object, the transaction will be automatically executed on the resource.

[0004] Since the subject cannot obtain real-time information about investment in resources in the trading market, this single, subjective conditional trading decision-making method is relatively passive for the subject, affecting the accuracy and reliability of the subject's decision-making. The subject may even need to intervene manually multiple times, withdraw the conditional trading order, or repeatedly re-create the conditional trading order. The repeated interaction process is time-consuming and cumbersome. Summary of the Invention

[0005] Based on this, it is necessary to provide a resource processing method, device, computer equipment, computer-readable storage medium and computer program product to address the above-mentioned technical problems. The resource processing method can reduce the deviation of the single, subjective conditional trading decision-making method and improve the accuracy and reliability of conditional trading decisions.

[0006] In a first aspect, the present application provides a resource processing method, comprising:

[0007] Displays the interface for creating conditional trading orders for target resources;

[0008] In response to the input operation, the input condition information is displayed in the creation interface, the condition information at least including a transaction tendency, the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model;

[0009] In response to a conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the condition information, where the conditional transaction order is used to execute a transaction on the target resource.

[0010] In a second aspect, the present application further provides a resource processing device, comprising:

[0011] A display module, used to display the creation interface of the conditional transaction order of the target resource;

[0012] an input response module, configured to display input condition information in the creation interface in response to an input operation, wherein the condition information at least includes a transaction propensity, which is at least one of a degree of propensity to trigger a transaction based on the condition information and a degree of propensity to trigger a transaction based on a transaction prediction model;

[0013] An order creation module is configured to create a conditional transaction order for the target resource based on the condition information in response to a conditional transaction order creation operation, wherein the conditional transaction order is used to execute a transaction on the target resource.

[0014] In a third aspect, an embodiment of the present application further provides a resource processing method, including:

[0015] receiving a request to create a conditional transaction order for a target resource, the request carrying condition information, the condition information including at least a transaction tendency, the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model;

[0016] generating a conditional transaction order for the target resource based on the condition information;

[0017] Execute a transaction on the target resource according to the conditional transaction order.

[0018] In a fourth aspect, the present application further provides a resource processing device, comprising:

[0019] a receiving module configured to receive a request for creating a conditional transaction order for a target resource, the creation request carrying condition information, the condition information at least including a transaction tendency, the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model;

[0020] An order generating module, configured to generate a conditional transaction order for the target resource based on the condition information;

[0021] An order execution module is used to execute a transaction on the target resource according to the conditional transaction order.

[0022] In a fifth aspect, the present application also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned resource processing method when executing the computer program.

[0023] In a sixth aspect, the present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned resource processing method are implemented.

[0024] In a seventh aspect, the present application also provides a computer program product, comprising a computer program, which implements the steps of the above-mentioned resource processing method when executed by a processor.

[0025] The resource processing method, apparatus, computer device, computer-readable storage medium, and computer program product described above display a creation interface for a conditional transaction order for a target resource. In response to an input operation, the entered condition information is displayed in the creation interface. The condition information includes at least a transaction propensity, which is at least one of the degree of propensity to trigger a transaction based on the condition information and the degree of propensity to trigger a transaction based on a transaction prediction model. In response to the conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the condition information. The conditional transaction order is used to execute a transaction for the target resource. In this method, the condition information entered by the subject includes a transaction propensity, which is at least one of the degree of propensity to trigger a transaction based on the condition information and the degree of propensity to trigger a transaction based on a transaction prediction model. This method automatically executes the conditional transaction order by combining a transaction strategy based on the subject's entered condition information, a transaction strategy based on a transaction prediction model, and a customized transaction propensity-triggered transaction timing. This reduces the bias of single, subjective conditional transaction decision-making methods, improves the accuracy and reliability of conditional transaction decisions, and avoids repeated interaction between subjects. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 An application environment diagram of a resource processing method in one embodiment;

[0028] Figure 2 1 is a flow chart of a resource processing method in one embodiment;

[0029] Figure 3 A schematic diagram of creating an interface in one embodiment;

[0030] Figure 4 A schematic diagram of creating an interface in another embodiment;

[0031] Figure 5 A schematic diagram of creating an interface in yet another embodiment;

[0032] Figure 6 is a timing diagram of a resource processing method in one embodiment;

[0033] Figure 7 1 is a flow chart of a resource processing method in another embodiment;

[0034] Figure 8 A schematic diagram of a process for executing a transaction on a target resource according to a conditional transaction order in one embodiment;

[0035] Figure 9 is a timing diagram of a resource processing method in another embodiment;

[0036] Figure 10 is a structural block diagram of a resource processing device in one embodiment;

[0037] Figure 11 is a structural block diagram of a resource processing device in another embodiment;

[0038] Figure 12 is a diagram of the internal structure of a computer device in one embodiment;

[0039] Figure 13 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0041] It should be noted that the terms "first", "second", etc. used in this application may be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "including" and "having" used in this application and any variations thereof are intended to cover non-exclusive inclusions. The term "plurality" used in this application refers to two or more. The term "and / or" used in this application refers to one of the solutions or any combination of multiple solutions.

[0042] In order to facilitate understanding of the technical solution of this application, the technical terms involved in this application are explained below.

[0043] Resources: Deposits, stocks, funds, etc. The resource trading platform can conduct and complete resource transactions based on client requests. Typically, a client creates a resource-related order on the client side and submits it to the resource trading server. The resource trading server records the resource-related order and, when the transaction opportunity is right, conducts and completes the resource transaction based on the resource-related order. Resource-related orders can be conditional trade orders.

[0044] Conditional trading order: When creating a trading order, an object can specify the trading conditions of a resource, such as trading shares and trading price. Once the current trading price of the resource reaches or exceeds the trading price specified by the object, the transaction will be automatically executed according to the trading order.

[0045] Trading Propensity: refers to which trading strategy an individual prefers when automatically executing conditional trading orders by combining a trading strategy that triggers trades based on the conditional information with a trading strategy that triggers trades based on a trade prediction model. Combining these two trading strategies can reduce the bias of single, subjective conditional trading decision-making methods, improve the accuracy and reliability of conditional trading decisions, and avoid repeated interactions between individuals. Furthermore, the trading propensity can be used to customize the individual's preferences, avoiding the lack of explainability of the decision-making results of a single trading strategy.

[0046] The transaction tendency can be the tendency degree of triggering a transaction based on the conditional information and the tendency degree of triggering a transaction based on the transaction estimation model. In the embodiment of the present application, the transaction strategy based on the conditional information triggering the transaction and the transaction strategy based on the transaction estimation model are combined to automatically realize the execution of the conditional transaction order, allowing the object to set corresponding transaction tendencies for these two transaction strategies to automatically realize the execution of the conditional transaction order. For example, the object can set the tendency degree of triggering a transaction based on the transaction estimation model to α2, then the tendency degree of triggering a transaction based on the conditional information α1=1-α2 can be automatically determined. Of course, the object can also set the tendency degree of triggering a transaction based on the conditional information α1, then the tendency degree of triggering a transaction based on the transaction estimation model α2=1-α1 can be automatically determined. The object can also set the tendency degree of triggering a transaction based on the transaction estimation model α2 and the tendency degree of triggering a transaction based on the conditional information α1 respectively, and the sum of the tendency degrees of the two transaction strategies can be 1. The higher the tendency degree α1 set by the object for triggering a transaction based on the conditional information, the more inclined the object is to trigger a transaction based on the decision result of the conditional information; the higher the tendency degree α2 set by the object for triggering a transaction based on the transaction prediction model, the more inclined the object is to trigger a transaction based on the decision result of the transaction prediction model.

[0047] Transaction Prediction Model: This is a model based on an artificial intelligence algorithm. It is trained based on sample data and learns the ability to estimate whether a transaction can be executed based on resource and object information. This ability can be quantified through transaction probability. The greater the transaction probability, the more likely the transaction will meet the transaction needs of the object at the current time. The smaller the transaction probability, the less likely the transaction will meet the transaction needs of the object at the current time.

[0048] In the related art, when creating an order, an object only supports inputting basic trading conditions such as the transaction share and transaction price. Without real-time access to relevant investment information about resources in the trading market, this single, subjective conditional trading decision-making method is relatively passive for the object, affecting the accuracy and reliability of the object's decision-making. The object may even need to manually intervene multiple times to withdraw the conditional trading order or repeatedly re-create the conditional trading order. This repeated interaction process is time-consuming and cumbersome. To address this problem in the related art, the present application provides a resource processing method. When creating a conditional trading order, the object can set a combination of two trading strategies to make a trading decision. When inputting conditional information, the object can support inputting a trading tendency, which is at least one of the degree of tendency to trigger a transaction based on the conditional information and the degree of tendency to trigger a transaction based on a transaction prediction model. This method can automatically execute the conditional trading order by combining the trading strategy based on the conditional information input by the object, the trading strategy based on the transaction prediction model, and the object's customized trading tendency to trigger the transaction timing. This reduces the deviation of the single, subjective conditional trading decision-making method, improves the accuracy and reliability of the conditional trading decision, and avoids repeated interaction between the object.

[0049] The resource processing method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104 or placed on the cloud or other network servers.

[0050] In some embodiments, the terminal 102 can display a creation interface for a conditional transaction order for a target resource; in response to an input operation, the input condition information is displayed in the creation interface, the condition information at least including a transaction tendency, and the transaction tendency is at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction estimation model; in response to a conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the condition information, and the conditional transaction order is used to execute a transaction on the target resource.

[0051] In some embodiments, the terminal 102 may send a request to the server 104 to create a conditional transaction order for the target resource, where the creation request carries condition information, where the condition information at least includes a transaction tendency, where the transaction tendency is at least one of a tendency degree to trigger a transaction based on the condition information and a tendency degree to trigger a transaction based on a transaction estimation model; the server 104 receives the request to create a conditional transaction order for the target resource, and the server 104 generates a conditional transaction order for the target resource based on the condition information, and then the server 104 may execute a transaction on the target resource according to the conditional transaction order.

[0052] In some embodiments, the terminal 102 can display a creation interface for a conditional transaction order for the target resource; in response to the input operation of the object, the condition information input by the object is displayed in the creation interface; in response to the conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the condition information, that is, the terminal 102 submits the creation request for the conditional transaction order to the server 104, and the server 104 can generate a conditional transaction order for the target resource and execute a transaction on the target resource according to the conditional transaction order.

[0053] The aforementioned server 104 can be a resource trading server. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The aforementioned terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart car devices, and projectors. Portable wearable devices can include smart watches, smart bracelets, head-mounted devices, and the like. Head-mounted devices can include virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, and the like.

[0054] Next, we will introduce the resource processing method from the perspective of the terminal, taking the terminal as the execution entity.

[0055] In an exemplary embodiment, Figure 2 As shown, a resource processing method is provided, which is applied to Figure 1 The terminal 102 in the example is used as an example to illustrate the process, including the following steps 202 to 206. Among them:

[0056] Step 202: Display a creation interface for a conditional transaction order of the target resource.

[0057] The interface for creating a conditional trading order is used to create a conditional trading order for a specific resource. The interface for creating a conditional trading order for a target resource is used to create a conditional trading order for the target resource. Resources can include deposits, stocks, funds, and so on, while the target resource is any of the multiple tradable resources provided by the trading platform. A conditional trading order is a trading order that can only be executed if the conditions entered by the subject are met. Specifically, when creating a trading order, the subject can specify the trading conditions for the resource, such as the trading volume, trading price, and trading preference. Once the current trading price of the resource reaches or exceeds the subject's specified price, the resource is automatically traded according to the trading order. Conditional trading orders can be either conditional buy orders or conditional sell orders. A conditional buy order is used to buy the target resource for the current account, while a conditional sell order is used to sell the target resource held by the current account.

[0058] In some embodiments, the terminal may display a conditional transaction order creation interface in a browser, or may display the conditional transaction order creation interface in a client for resource transactions.

[0059] In some embodiments, the terminal can display a target resource conditional trading order creation interface in response to an object triggering an operation on the target resource. Taking a client for resource trading as an example, the terminal can display a target resource conditional trading order creation interface on the client in response to an object-triggered client account login operation. In some embodiments, the object can trigger an interface jump operation on another interface of the client. Thus, the terminal can jump to and display the target resource conditional trading order creation interface in response to the object-triggered jump operation, i.e., jump from another interface to display the target resource conditional trading order creation interface. The other interface can be a resource information viewing interface for the target resource.

[0060] In some embodiments, the creation interface includes at least one conditional information input control for supporting the input of conditional information. Conditional information input controls are used to enter conditional information. The number, shape, location, and display of these controls can be customized based on actual needs. In this embodiment, the conditional information input controls can be triggered to execute the conditional information input operation by any of a number of methods, such as mouse clicks, touches, or voice control. It will be understood that different conditional information input controls in the creation interface are used to enter different information, which together constitute the conditional information required to create a conditional trading order.

[0061] In step 204, in response to the input operation, the input condition information is displayed in the creation interface, where the condition information at least includes a transaction tendency, which is at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model.

[0062] In some embodiments, the creation interface provides input controls for the subject to set conditional information. That is, the terminal can respond to the subject's input operations on these input controls by displaying the entered conditional information on the creation interface. The entered conditional information may include resource identification, transaction price, transaction share (or transaction amount), order validity period, etc. Conditional information is a general term for all specific conditions. A transaction for the target resource will only be triggered if the transaction conditions indicated by the conditional information are met.

[0063] In an embodiment of the present application, the input conditional information also includes a transaction tendency, which is at least one of the tendency degree of triggering a transaction based on the conditional information and the tendency degree of triggering a transaction based on a transaction prediction model. The transaction tendency is at least one of the tendency degree of triggering a transaction based on the conditional information and the tendency degree of triggering a transaction based on a transaction prediction model. When combining a trading strategy based on conditional information triggering a transaction and a trading strategy based on a transaction prediction model to automatically implement the execution of a conditional transaction order, the trading strategy to which the subject is more inclined is the trading tendency. In this way, combining these two trading strategies can not only reduce the deviation of a single, subjective conditional transaction decision-making method, improve the accuracy and reliability of conditional transaction decisions, avoid repeated interaction processes of the subject, but also customize the subject's preferences through the trading tendency, avoiding the lack of explainability of the decision results of a single trading strategy.

[0064] Objects are allowed to set corresponding trading preferences for these two trading strategies to automatically execute conditional trade orders. For example, an object can set the preference level for triggering trades based on the trade prediction model to α2, which will automatically determine the preference level for triggering trades based on conditional information to be α1 = 1 - α2. Alternatively, an object can set the preference level for triggering trades based on conditional information to be α1, which will automatically determine the preference level for triggering trades based on the trade prediction model to be α2 = 1 - α1. Objects can also set the preference level for triggering trades based on the trade prediction model and the preference level for triggering trades based on conditional information separately, with the sum of the preference levels for the two strategies being 1. The higher the preference level α1 set for triggering trades based on conditional information, the more likely the object is to trigger trades based on the decision results of conditional information. The higher the preference level α2 set for triggering trades based on the trade prediction model, the more likely the object is to trigger trades based on the decision results of the trade prediction model.

[0065] The transaction prediction model is based on an artificial intelligence algorithm. It is trained using sample data and learns to predict whether a transaction is executable based on resource and object information. This ability is quantified by transaction probability. A higher transaction probability indicates that executing the transaction at the current time is more likely to meet the transaction needs of the subject, while a lower transaction probability indicates that executing the transaction at the current time is less likely to meet the transaction needs of the subject. The transaction prediction model can be used to estimate a second transaction probability based on resource and object information.

[0066] In some embodiments, the conditional information also includes basic transaction information and a probability threshold, wherein the current price of the target resource and the basic transaction information are used to calculate the first transaction probability, the transaction estimation model is used to estimate the second transaction probability, and the conditional transaction order is used to execute a transaction on the target resource when the target transaction probability determined based on the transaction tendency, the first transaction probability and the second transaction probability is greater than the probability threshold.

[0067] Specifically, in this embodiment, the current price of the target resource and the basic transaction information entered by the user can be used to calculate the first transaction probability. The aforementioned transaction propensity, first transaction probability, and second transaction probability can be used to calculate the target transaction probability. In some embodiments, the input conditional information also includes a probability threshold. The probability threshold is a quantitative value that the user sets as the threshold for triggering a transaction. The probability threshold is one of the conditional information entered by the user. Only when the transaction condition indicated by the conditional information is met will the transaction be executed on the target resource. The satisfaction of the transaction condition indicated by the conditional information can be understood as the currently determined target transaction probability being greater than the aforementioned set probability threshold. In other words, in this case, the transaction is executed on the target resource.

[0068] In some embodiments, the basic transaction information includes an expected transaction price range and a transaction willingness range, the expected transaction price range includes a first expected transaction price and a second expected transaction price, and the transaction willingness range includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price, wherein the current price of the target resource, the first expected transaction price and the second expected transaction price, the first transaction willingness and the second transaction willingness are used to calculate the first transaction probability.

[0069] The basic transaction information includes the above-mentioned transaction price, transaction share (or transaction amount), and may also include the order validity period, etc. In some embodiments, the transaction price can be a specified expected transaction price, such as 3 yuan. In some embodiments, the transaction price is a specified numerical range, which is called the expected transaction price range, that is, the basic transaction information includes the expected transaction price range, and the expected transaction price range includes a first expected transaction price and a second expected transaction price, which can be recorded as N1 and N2. The first expected transaction price and the second expected transaction price are the two boundary values ​​of the expected transaction price range. For example, when a conditional buy order needs to be created, the transaction price of the specified target resource is a closed range of 2 yuan to 4 yuan. For example, when a conditional sell order needs to be created, the transaction price of the specified target resource is a closed range of 4 yuan to 2 yuan.

[0070] In some embodiments, the basic transaction information also includes a transaction willingness interval. The transaction willingness interval includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price, which can be denoted as P1 and P2 respectively. The transaction willingness indicates the user's willingness to trigger a transaction at the set transaction price. The value range of the first transaction willingness and the second transaction willingness is [0,1.0], which are decimals, where 1 indicates that the object fully agrees to trigger the transaction at this transaction price, and 0 indicates that the object completely disagrees to trigger the transaction at this price. Alternatively, the value range of the first transaction willingness and the second transaction willingness is [0,100], which are integers, or the value range of the first transaction willingness and the second transaction willingness is a value between [0,100%], which are percentages.

[0071] In some embodiments, the magnitude relationship between the first transaction willingness and the second transaction willingness can be fixed, for example, the first transaction willingness P1 is fixed to be smaller than the second transaction willingness P2. Then, when a conditional buy order needs to be created, the first expected transaction price N1 set for the first transaction willingness P1 should be higher than the second expected transaction price N2 set for the second transaction willingness P2, that is, a lower transaction willingness P1 corresponds to a higher expected transaction price N1, and a higher transaction willingness P2 corresponds to a lower expected transaction price N2. When a conditional sell order needs to be created, the first expected transaction price N1 set for the first transaction willingness P1 should be lower than the second expected transaction price N2 set for the second transaction willingness P2, that is, a lower transaction willingness P1 corresponds to a lower expected transaction price N1, and a higher transaction willingness P2 corresponds to a higher expected transaction price N2. For example, when creating a conditional buy order, the input transaction willingness range is 0.5 to 1, and the transaction price of the input target resource is a closed range of 2 yuan to 4 yuan. When creating a conditional sell order, the input transaction willingness range is 0.5 to 1, and the transaction price of the specified target resource is a closed range of 4 yuan to 2 yuan.

[0072] In some embodiments, the relationship between the first expected transaction price and the second expected transaction price can also be fixed, for example, the first expected transaction price N1 is fixed to be smaller than the second expected transaction price N2. Then, when a conditional buy order needs to be created, the first transaction willingness P1 corresponding to the first expected transaction price N1 should be greater than the second transaction willingness P2 corresponding to the second expected transaction price N2, that is, a higher transaction willingness P1 corresponds to a smaller expected transaction price N1, and a lower transaction willingness P2 corresponds to a larger expected transaction price N2. When a conditional sell order needs to be created, the first transaction willingness P1 corresponding to the first expected transaction price N1 should be less than the second transaction willingness P2 corresponding to the second expected transaction price N2, that is, a lower transaction willingness P1 corresponds to a smaller expected transaction price N1, and a higher transaction willingness P2 corresponds to a larger expected transaction price N2. For example, when creating a conditional buy order, the transaction price of the target resource entered is a closed range of 2 yuan to 4 yuan, and the transaction willingness entered is a range of 1 to 0.5. When creating a conditional sell order, the transaction price of the target resource entered is a closed range of 2 yuan to 4 yuan, and the transaction willingness entered is a range of 0.5 to 1.

[0073] Step 206 : In response to the conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the condition information. The conditional transaction order is used to execute a transaction on the target resource.

[0074] Specifically, in response to the conditional transaction order creation operation, the terminal creates a conditional transaction order for the target resource based on the condition information.

[0075] In some embodiments, the creation interface includes a creation control, and the terminal creates a conditional transaction order for the target resource based on the input condition information in response to a triggering operation on the creation control.

[0076] In some embodiments, creating a conditional transaction order regarding a target resource based on conditional information includes: generating a creation request based on the conditional information, sending the creation request to a server so that the server creates a conditional transaction order based on the conditional information, and executing a transaction on the target resource based on the conditional transaction order.

[0077] Specifically, in response to the conditional transaction order creation operation, the terminal generates a creation request according to the input condition information, and sends the creation request to the server. The server generates a conditional transaction order for the target resource based on the condition information.

[0078] In some embodiments, the resource processing method further includes: in response to an order query operation, sending a query request to a server, the query request being used to request order information of a conditional transaction order of a target object; receiving order information regarding the conditional transaction order of the target object from the server; and displaying the order information. The server returns the order information to the terminal, and the terminal can display the order transaction status based on the order information regarding the conditional transaction order of the target object returned by the server.

[0079] In some embodiments, the resource processing method further includes: receiving the execution result of a conditional trade order for a target subject, sent by a server; and displaying a prompt message generated based on the execution result. Specifically, upon completion of the trade, the exchange server may return the trade result to the trading server, which may then return it to the terminal, allowing the subject to promptly view the trade result through a client on the terminal. In a specific implementation, the terminal receives the trade result returned by the trading server and then displays a prompt message based on the trade result, allowing the subject to view the trade result.

[0080] Figure 3 A schematic diagram of creating an interface in an exemplary embodiment. Figure 3 The creation interface 300 includes multiple condition information input controls 301, among which input control 301-1 is used to input the expected transaction price range, input control 301-2 is used to input the corresponding transaction willingness range, input control 301-3 is used to input the transaction tendency, which is the tendency degree of triggering a transaction based on the transaction estimation model, input control 301-4 is used to input the probability threshold, input control 301-5 is used to input the order validity period, input control 301-6 is used to input the transaction share (or transaction amount), and input control 301-7 is used to input the source or destination of funds.

[0081] Figure 4A schematic diagram of creating an interface in an exemplary embodiment. Figure 4 The creation interface 300 is used to create a conditional buy order. The creation interface 300 includes multiple condition information input controls 301, among which input control 301-1 is used to input the expected buying price range, input control 301-2 is used to input the corresponding buying willingness range, input control 301-3 is used to input the buying tendency, which is the tendency degree to trigger a buy based on the transaction estimation model, input control 301-4 is used to input the probability threshold, input control 301-5 is used to input the order validity period, input control 301-6 is used to input the purchase share (or purchase amount), and input control 301-7 is used to input the source of funds.

[0082] Figure 5 A schematic diagram of creating an interface in an exemplary embodiment. Figure 5 The creation interface 300 is used to create a conditional sell order. The creation interface 300 includes multiple condition information input controls 301, among which the input control 301-1 is used to input the expected selling price range, the input control 301-2 is used to input the corresponding selling willingness range, the input control 301-3 is used to input the selling tendency, which is the tendency degree of triggering selling based on the transaction estimation model, the input control 301-4 is used to input the probability threshold, the input control 301-5 is used to input the order validity period, the input control 301-6 is used to input the selling shares (or selling amount), and the input control 301-7 is used to input the destination of funds.

[0083] In some embodiments, the aforementioned server may be a trading server provided by the investment platform, which provides trading services for the target. After generating a conditional trading order for the target resource, the trading server, when the trading conditions are met, generates a trade request corresponding to the conditional trading order and reports the trade request to the exchange backend, which then completes the transaction based on the reported trade request.

[0084] In some embodiments, the transaction server may periodically or regularly query whether there are any conditional transaction orders that have not expired and have not been successfully executed. If so, for these conditional transaction orders, based on the corresponding condition information and the current price of the target resource, check whether the transaction conditions are met.

[0085] In some embodiments, the transaction server may calculate a first transaction probability based on the current price of the target resource and basic transaction information in the condition information; query the resource information of the target resource and the object information of the target object, and estimate a second transaction probability based on the resource information and the object information using a transaction prediction model; calculate a target transaction probability based on the first transaction probability, the second transaction probability, and the transaction propensity; and execute a transaction on the target resource when the target transaction probability is greater than a probability threshold. Specifically, when the target transaction probability is greater than the probability threshold, it can be determined that the transaction condition is met, and a transaction request corresponding to the conditional transaction order can be generated and reported to the exchange backend, so that the exchange backend can complete the transaction execution based on the reported transaction request.

[0086] In some embodiments, when calculating the first transaction probability based on the current price of the target resource and the basic transaction information in the condition information, the transaction server may specifically calculate the transaction willingness coefficient based on the expected transaction price range and the transaction willingness range when the current price of the target resource is within the expected transaction price range, and calculate the first transaction probability based on the current price of the target resource and the transaction willingness coefficient. If the current price of the target resource is outside the expected transaction price range, the first transaction probability is determined to be 0.

[0087] In some embodiments, the transaction server calculates the transaction willingness coefficient by: calculating the transaction willingness difference between the second transaction willingness and the first transaction willingness; calculating the price difference between the second expected transaction price and the first expected transaction price; and obtaining the transaction willingness coefficient based on the ratio of the transaction willingness difference to the price difference.

[0088] In some embodiments, when the conditional trading order is a conditional buy order, the second expected trading price is less than the first expected trading price; when the conditional trading order is a conditional sell order, the second expected trading price is greater than the first expected trading price.

[0089] In some embodiments, the first transaction probability is calculated based on the current price of the target resource and the transaction willingness coefficient, including: calculating the difference between the current price of the target resource and the first expected transaction price; and obtaining the first transaction probability based on the product of the difference and the transaction willingness coefficient.

[0090] In some embodiments, the transaction propensity is the degree of tendency to trigger a transaction based on a transaction prediction model, and the target transaction probability is calculated based on the first transaction probability, the second transaction probability and the transaction propensity, including: calculating the degree of tendency to trigger a transaction based on conditional information based on the degree of tendency to trigger a transaction based on the transaction prediction model; weighting the first transaction probability according to the degree of tendency to trigger a transaction based on the conditional information to obtain a first weighted transaction probability; weighting the second transaction probability according to the degree of tendency to trigger a transaction based on the transaction prediction model to obtain a second weighted transaction probability; and obtaining the target transaction probability based on the sum of the first weighted transaction probability and the second weighted transaction probability.

[0091] In some embodiments, the conditional information also includes a transaction share. When the target transaction probability is greater than a probability threshold, a transaction is executed on the target resource, including: when the conditional transaction order is a conditional buy order and the target transaction probability is greater than the probability threshold, a buy operation is performed on the target resource according to the transaction share and the current price of the target resource; when the conditional transaction order is a conditional sell order and the target transaction probability is greater than the probability threshold, a sell operation is performed on the target resource according to the transaction share and the current price of the target resource.

[0092] Figure 6 FIG. 1 is a timing diagram of a resource processing method in an embodiment. Figure 6 The technical architecture used in this sequence diagram includes a client 602 and a transaction server 604. First, the client displays a creation interface based on the object's operation to create a conditional transaction order. When creating a conditional transaction order, the client receives relevant condition information input by the object, including resource identification, expected transaction price range, transaction tendency, transaction willingness range, validity period, etc. Next, the object confirms the creation and sends a creation request carrying this condition information to the server. The server generates and creates the conditional transaction order for the object based on the condition information and returns information indicating the success (or failure) of the creation.

[0093] In the above-mentioned resource processing method, a creation interface for a conditional transaction order for a target resource is displayed. In response to an input operation, the input conditional information is displayed in the creation interface. The conditional information includes at least a transaction propensity, which is at least one of the degree of propensity to trigger a transaction based on the conditional information and the degree of propensity to trigger a transaction based on a transaction prediction model. In response to the conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the conditional information. The conditional transaction order is used to execute a transaction for the target resource. In this method, the conditional information input by the subject includes a transaction propensity, which is at least one of the degree of propensity to trigger a transaction based on the conditional information and the degree of propensity to trigger a transaction based on a transaction prediction model. This method automatically executes the conditional transaction order by combining a transaction strategy based on the subject's input conditional information, a transaction strategy based on the transaction prediction model, and the subject's customized transaction propensity-triggered transaction timing. This reduces the bias of single, subjective conditional transaction decision-making methods, improves the accuracy and reliability of conditional transaction decisions, and avoids repeated interaction between subjects.

[0094] The preceding description primarily describes the terminal's response object operation, requesting the server to create a conditional trade order. The server then checks the trade conditions and, if the conditions are met, reports the corresponding trade request to the exchange backend. It will be appreciated that in some embodiments, depending on actual needs, the terminal may also create a conditional trade order based on the conditional information and execute a trade on the target resource based on the conditional trade order. Specifically, the terminal checks the locally created conditional trade order and, at a trading opportunity when the trade conditions are met, generates a trade request corresponding to the conditional trade order and reports the trade request to the exchange backend, allowing the exchange backend to complete the trade based on the reported trade request. For example, the terminal may periodically or periodically query whether there are any conditional trade orders that have not expired and have not yet been successfully executed. If so, the terminal checks whether the trade conditions are met for these conditional trade orders based on the corresponding conditional information and the current price of the target resource. Most embodiments of this application primarily illustrate the server performing the trade condition check.

[0095] Next, we will introduce the resource processing method from the perspective of the server, with the server as the execution entity.

[0096] In an exemplary embodiment, Figure 7 As shown, a resource processing method is provided, which is applied to Figure 1 The server 104 in the example is used for illustration, and the steps include the following steps 702 to 706. Among them:

[0097] Step 702: Receive a request to create a conditional transaction order for a target resource. The creation request carries condition information. The condition information at least includes a transaction tendency. The transaction tendency is at least one of a tendency degree to trigger a transaction based on the condition information and a tendency degree to trigger a transaction based on a transaction estimation model.

[0098] Conditional trade orders are orders where a trade can only be executed if the conditions entered by the trader are met. Specifically, when creating a trade order, the trader can specify the trading conditions for a resource, such as the trading volume, price, and trading preference. Once the current trading price of the resource reaches or exceeds the specified price, the trade is automatically executed according to the trade order. Conditional trade orders can be either conditional buy orders or conditional sell orders. A conditional buy order is used to buy the target resource for the current account, while a conditional sell order is used to sell the target resource held by the current account.

[0099] In some embodiments, a terminal can display a creation interface for a conditional trading order for a target resource in response to an object triggering an operation on the target resource. Taking a client for resource trading as an example, the terminal can display a creation interface for a conditional trading order for the target resource in response to a client account login operation triggered by an object. In response to an input operation, the terminal can display the entered conditional information in the creation interface. Then, in response to the conditional trading order creation operation, the terminal can generate a creation request for a conditional trading order for the target resource based on the entered conditional information and send the creation request to a server. The server can then receive the creation request for the conditional trading order for the target resource sent by the terminal.

[0100] Condition information can include resource identification, transaction price, transaction share (or transaction amount), order validity period, etc. Condition information is a general term for all specific conditions. Only when the transaction conditions indicated by the condition information are met will the transaction be triggered for the target resource.

[0101] In an embodiment of the present application, the input conditional information also includes a transaction tendency, which is at least one of the tendency degree of triggering a transaction based on the conditional information and the tendency degree of triggering a transaction based on a transaction prediction model. The transaction tendency is the tendency degree of triggering a transaction based on the conditional information and the tendency degree of triggering a transaction based on a transaction prediction model. When combining the transaction strategy based on conditional information triggering transactions and the transaction strategy based on the transaction prediction model to automatically realize the execution of conditional transaction orders, which transaction strategy the object is more inclined to is the transaction tendency. In this way, combining these two transaction strategies can not only reduce the deviation of the single, subjective conditional transaction decision-making method, improve the accuracy and reliability of the conditional transaction decision, avoid the repeated interaction process of the object, but also customize the object's preferences through the transaction tendency, and avoid the lack of explainability of the decision results of a single transaction strategy.

[0102] Objects are allowed to set corresponding trading preferences for these two trading strategies to automatically execute conditional trade orders. For example, an object can set the preference level for triggering trades based on the trade prediction model to α2, which will automatically determine the preference level for triggering trades based on conditional information to be α1 = 1 - α2. Alternatively, an object can set the preference level for triggering trades based on conditional information to be α1, which will automatically determine the preference level for triggering trades based on the trade prediction model to be α2 = 1 - α1. Objects can also set the preference level for triggering trades based on the trade prediction model and the preference level for triggering trades based on conditional information separately, with the sum of the preference levels for the two strategies being 1. The higher the preference level α1 set for triggering trades based on conditional information, the more likely the object is to trigger trades based on the decision results of conditional information. The higher the preference level α2 set for triggering trades based on the trade prediction model, the more likely the object is to trigger trades based on the decision results of the trade prediction model.

[0103] The transaction prediction model is based on an artificial intelligence algorithm. It is trained using sample data and learns to predict whether a transaction is executable based on resource and object information. This ability is quantified by transaction probability. A higher transaction probability indicates that executing the transaction at the current time is more likely to meet the transaction needs of the subject, while a lower transaction probability indicates that executing the transaction at the current time is less likely to meet the transaction needs of the subject. The transaction prediction model can be used to estimate a second transaction probability based on resource and object information.

[0104] In some embodiments, the input conditional information also includes a probability threshold. The probability threshold is a quantified value that the user sets as the threshold for triggering a transaction. The probability threshold is one of the conditional information input by the user. A transaction will only be executed on the target resource if the transaction condition indicated by the conditional information is met. Satisfaction of the transaction condition indicated by the conditional information can be understood as meaning that the currently determined target transaction probability is greater than the set probability threshold. In this case, the transaction will be executed on the target resource.

[0105] Step 704: Generate a conditional transaction order for the target resource based on the condition information.

[0106] The server can obtain condition information from the creation request, generate a conditional transaction order for the target resource based on the condition information, and record the conditional transaction order in a storage system.

[0107] Step 706: Execute the transaction on the target resource according to the conditional transaction order.

[0108] In some embodiments, the server may periodically or regularly check whether there are any conditional trade orders that have not expired and have not been successfully executed. If so, the server will check whether the trade conditions of these conditional trade orders are met based on the corresponding condition information and the current price of the target resource. Only when the trade conditions are met will the trade be executed on the target resource.

[0109] In some embodiments, the aforementioned server may be a trading server provided by the investment platform, which provides trading services for the target. After generating a conditional trading order for the target resource, the trading server, when the trading conditions are met, generates a trade request corresponding to the conditional trading order and reports the trade request to the exchange backend, which then completes the transaction based on the reported trade request.

[0110] In some embodiments, the server may also receive a query request, where the query request is used to request order information of a conditional transaction order of a target object, and the order information of the conditional transaction order of the target object may be fed back to the terminal based on the query request.

[0111] In some embodiments, the server may also send the execution result of the conditional transaction order of the target object to the terminal so that the terminal can display corresponding prompt information according to the execution result.

[0112] The resource processing method described above receives a request to create a conditional transaction order for a target resource, the creation request carrying conditional information, the conditional information including at least a transaction tendency, which is at least one of the degree of tendency to trigger a transaction based on the conditional information and the degree of tendency to trigger a transaction based on a transaction prediction model; generates a conditional transaction order for the target resource based on the conditional information; and executes a transaction on the target resource according to the conditional transaction order. In this method, the creation request carries conditional information input by an object, the conditional information including a transaction tendency, which is at least one of the degree of tendency to trigger a transaction based on the conditional information and the degree of tendency to trigger a transaction based on a transaction prediction model. This method automatically executes the conditional transaction order by combining a transaction strategy based on the conditional information input by the object, a transaction strategy based on the transaction prediction model, and a transaction timing triggered by a customized transaction tendency. This reduces the bias of single, subjective conditional transaction decision-making methods, improves the accuracy and reliability of conditional transaction decisions, and avoids repeated interaction between objects.

[0113] In some embodiments, as Figure 8 As shown, transactions are executed on target resources according to conditional transaction orders, including:

[0114] Step 802 : Calculate a first transaction probability based on the current price of the target resource and basic transaction information in the condition information.

[0115] The server can periodically check whether conditional trade orders meet the trading conditions, such as at intervals of one hour, 30 minutes, or 10 minutes. It is understood that the trading price of the target resource fluctuates over time, and the current price is the most recent trading price of the target resource. The server can query the current price of the target resource and calculate a first transaction probability M1 based on the current price of the target resource and the basic transaction information in the conditional information. The first transaction probability M1 reflects the probability of triggering a trade based on the conditional information. Since the conditional information is manually set, it also reflects the manual transaction decision. Basic transaction information includes the transaction price, transaction share (or transaction amount), and may also include the order validity period.

[0116] Step 804 : query the resource information of the target resource and the object information of the target object, and estimate the second transaction probability based on the resource information and the object information using a transaction estimation model.

[0117] The target resource's resource information includes, but is not limited to, the target resource's resource identifier, current price, shareholder information, financial indicator information, expected profitability information, and trading market trend information. The target object's object information includes, but is not limited to, the target object's object identifier, risk level, holding cost, holding return, holding duration, holding ratio, transaction fee rate, total holding cost, and deposit and withdrawal plans.

[0118] The server can input the retrieved target resource information and target object information into the transaction prediction model, which then outputs an estimated second transaction probability M2. This second transaction probability M2 reflects the likelihood of triggering a transaction based on the transaction prediction model, thus reflecting the transaction decision made at the intelligent algorithm level.

[0119] Step 806: Calculate the target transaction probability based on the first transaction probability, the second transaction probability, and the transaction tendency.

[0120] After calculating the first and second transaction probabilities, the server can combine them based on the transaction propensity in the conditional information to obtain a target transaction probability. The target transaction probability reflects the likelihood of triggering a transaction. As can be seen, since the target transaction probability is determined by combining a trading strategy based on the conditional information input by the subject, a trading strategy based on a transaction prediction model, and a customized transaction propensity for the subject, it can improve the accuracy and reliability of conditional transaction decisions and avoid the bias of single, subjective conditional transaction decision-making methods.

[0121] Step 808: When the target transaction probability is greater than the probability threshold, execute the transaction on the target resource.

[0122] Specifically, the server may execute a transaction on the target resource when the calculated target transaction probability M0 is greater than or equal to a set probability threshold Mth.

[0123] In some embodiments, the basic transaction information includes an expected transaction price range and a transaction willingness range, and the first transaction probability is calculated based on the current price of the target resource and the basic transaction information, including: when the current price of the target resource is within the expected transaction price range, calculating the transaction willingness coefficient based on the expected transaction price range and the transaction willingness range, and calculating the first transaction probability based on the current price of the target resource and the transaction willingness coefficient.

[0124] In some embodiments, the transaction price in the basic transaction information can be a specified expected transaction price, such as 3 yuan. In this embodiment, the transaction price is a specified numerical range, which is called the expected transaction price range, that is, the basic transaction information includes the expected transaction price range, and the expected transaction price range includes the first expected transaction price and the second expected transaction price, which can be recorded as N1 and N2. The first expected transaction price and the second expected transaction price are the two boundary values ​​of the expected transaction price range. For example, when a conditional buy order needs to be created, the transaction price of the specified target resource is a closed range of 2 yuan to 4 yuan. For example, when a conditional sell order needs to be created, the transaction price of the specified target resource is a closed range of 4 yuan to 2 yuan.

[0125] In this embodiment, the basic transaction information also includes a transaction willingness interval. The transaction willingness interval corresponds to the expected transaction price interval, and the transaction willingness interval includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price, which can be denoted as P1 and P2 respectively. The transaction willingness indicates the user's willingness to trigger a transaction at the set transaction price. The value range of the first transaction willingness and the second transaction willingness is [0,1.0], which are decimals, where 1 indicates that the object fully agrees to trigger the transaction at this transaction price, and 0 indicates that the object completely disagrees to trigger the transaction at this price. Alternatively, the value range of the first transaction willingness and the second transaction willingness is [0,100], which are integers, or the value range of the first transaction willingness and the second transaction willingness is a value between [0,100%], which are percentages.

[0126] In some embodiments, the magnitude relationship between the first transaction willingness and the second transaction willingness can be fixed, for example, the first transaction willingness P1 is fixed to be smaller than the second transaction willingness P2. Then, when a conditional buy order needs to be created, the first expected transaction price N1 set for the first transaction willingness P1 should be higher than the second expected transaction price N2 set for the second transaction willingness P2, that is, a lower transaction willingness P1 corresponds to a higher expected transaction price N1, and a higher transaction willingness P2 corresponds to a lower expected transaction price N2. When a conditional sell order needs to be created, the first expected transaction price N1 set for the first transaction willingness P1 should be lower than the second expected transaction price N2 set for the second transaction willingness P2, that is, a lower transaction willingness P1 corresponds to a lower expected transaction price N1, and a higher transaction willingness P2 corresponds to a higher expected transaction price N2. For example, when creating a conditional buy order, the input transaction willingness range is 0.5 to 1, and the transaction price of the input target resource is a closed range of 2 yuan to 4 yuan. When creating a conditional sell order, the input transaction willingness range is 0.5 to 1, and the transaction price of the specified target resource is a closed range of 4 yuan to 2 yuan.

[0127] In some embodiments, the relationship between the first expected transaction price and the second expected transaction price can also be fixed, for example, the first expected transaction price N1 is fixed to be smaller than the second expected transaction price N2. Then, when a conditional buy order needs to be created, the first transaction willingness P1 corresponding to the first expected transaction price N1 should be greater than the second transaction willingness P2 corresponding to the second expected transaction price N2, that is, a higher transaction willingness P1 corresponds to a smaller expected transaction price N1, and a lower transaction willingness P2 corresponds to a larger expected transaction price N2. When a conditional sell order needs to be created, the first transaction willingness P1 corresponding to the first expected transaction price N1 should be less than the second transaction willingness P2 corresponding to the second expected transaction price N2, that is, a lower transaction willingness P1 corresponds to a smaller expected transaction price N1, and a higher transaction willingness P2 corresponds to a larger expected transaction price N2. For example, when creating a conditional buy order, the transaction price of the target resource entered is a closed range of 2 yuan to 4 yuan, and the transaction willingness entered is a range of 1 to 0.5. When creating a conditional sell order, the transaction price of the target resource entered is a closed range of 2 yuan to 4 yuan, and the transaction willingness entered is a range of 0.5 to 1.

[0128] In some embodiments, calculating a transaction willingness coefficient based on the expected transaction price range and the transaction willingness range includes: calculating the transaction willingness difference between the second transaction willingness and the first transaction willingness; calculating the price difference between the second expected transaction price and the first expected transaction price; and obtaining the transaction willingness coefficient based on the ratio of the transaction willingness difference to the price difference. The transaction willingness coefficient reflects the degree of change in the transaction willingness per unit change in the expected transaction price. For example, the transaction willingness coefficient b can be calculated using the following formula:

[0129] b=(P2-P1) / (N2-N1).

[0130] In some embodiments, when the conditional trading order is a conditional buy order, the second expected trading price is less than the first expected trading price; when the conditional trading order is a conditional sell order, the second expected trading price is greater than the first expected trading price.

[0131] In some embodiments, the first transaction probability is calculated based on the current price of the target resource and the transaction willingness coefficient, including: calculating the difference between the current price of the target resource and the first expected transaction price; and obtaining the first transaction probability based on the product of the difference and the transaction willingness coefficient.

[0132] Taking a conditional buy order as an example, the input conditional information includes the second transaction willingness P2 = 1, the first transaction willingness P1 = 0.5, the second expected transaction price N2 = 2, the first expected transaction price N1 = 4, and the current price of the target resource N = 3. Then, the first transaction probability M1 = (N-N1) × b = (N-N1) × (P2-P1) / (N2-N1) = (-1) 0.5 / (-2) = 0.25.

[0133] Taking a conditional sell order as an example, in the input conditional information, the second transaction willingness P2=1, the first transaction willingness P1=0.5, the second expected transaction price N2=4, the first expected transaction price N1=2, and the current price of the target resource N=3, then the first transaction probability M1=(N-N1)×b=(N-N1)×(P2-P1) / (N2-N1)=1×0.5 / (2)=0.25.

[0134] In some embodiments, when the current price of the target resource is outside the expected transaction price range, the first transaction probability is determined to be 0. It will be appreciated that when the current price of the target resource is outside the expected transaction price range, it indicates that the current transaction price is completely outside the expected transaction price of the object. Therefore, the first transaction probability corresponding to the manual transaction decision can be set to 0, or alternatively, a relatively small value.

[0135] In some embodiments, the transaction propensity is the degree of tendency to trigger a transaction based on a transaction prediction model, and the target transaction probability is calculated based on the first transaction probability, the second transaction probability and the transaction propensity, including: calculating the degree of tendency to trigger a transaction based on conditional information based on the degree of tendency to trigger a transaction based on the transaction prediction model; weighting the first transaction probability according to the degree of tendency to trigger a transaction based on the conditional information to obtain a first weighted transaction probability; weighting the second transaction probability according to the degree of tendency to trigger a transaction based on the transaction prediction model to obtain a second weighted transaction probability; and obtaining the target transaction probability based on the sum of the first weighted transaction probability and the second weighted transaction probability.

[0136] For example, if the transaction propensity in the conditional information is the propensity degree α2 for triggering a transaction based on the transaction prediction model, then the propensity degree α1 for triggering a transaction based on the conditional information can be automatically determined to be 1-α2. The final target transaction probability M0 can then be calculated using the following formula:

[0137] M0=α1×M1+α2×M2.

[0138] In the above example, assuming the first transaction probability M1=0.25, M2=0.5, α1=0.3, α2=0.7, and the probability threshold Mth=0.5, the calculated target transaction probability M0=0.25×0.3+0.5×0.7=0.425. Since this probability is less than the set probability threshold, the transaction will not be triggered. In other words, the trading server will not report the transaction request to the exchange backend at this time. It is necessary to wait for the next check opportunity and perform the next check again based on the current price of the target resource.

[0139] In some embodiments, the conditional information also includes a transaction share. When the target transaction probability is greater than a probability threshold, a transaction is executed on the target resource, including: when the conditional transaction order is a conditional buy order and the target transaction probability is greater than the probability threshold, a buy operation is performed on the target resource according to the transaction share and the current price of the target resource; when the conditional transaction order is a conditional sell order and the target transaction probability is greater than the probability threshold, a sell operation is performed on the target resource according to the transaction share and the current price of the target resource.

[0140] In order to make the technical solution of the present application easy to understand, the resource processing method of the embodiment of the present application will be introduced below in combination with specific application scenarios. Figure 8 This is an application scenario diagram of a resource processing method in an embodiment. Figure 8 The user opens the resource transaction client in the terminal 102 and logs into the account. In response to the user operation, the terminal 102 displays the interface for creating a conditional transaction order, for example, Figure 3As shown in Figure 1 , the creation interface includes input controls for conditional information, specifically for entering a desired transaction price range, a corresponding transaction willingness range, and a transaction propensity (which can be the degree of inclination to trigger a transaction based on a transaction prediction model). It also includes input controls for entering a probability threshold, an order validity period, a transaction share (or transaction amount), and a source or destination of funds. The user enters the corresponding conditional information through these input controls and then uses the creation control to request the creation of a conditional transaction order. Terminal 102 then generates a creation request based on the conditional information obtained through these input controls and sends the creation request to transaction server 104. Upon receiving the creation request, transaction server 104 generates a conditional transaction order for the target resource. After generating the conditional transaction order for the target resource, transaction server 104 periodically checks whether there are any conditional transaction orders that have not expired and have not been successfully executed. If so, it checks whether the transaction conditions of these conditional transaction orders are met based on the corresponding conditional information and the current price of the target resource. At the trading opportunity when the trading conditions are met, the trading server 104 generates a trading request corresponding to the conditional trading order and reports the trading request to the exchange backend so that the exchange backend completes the transaction according to the reported trading request.

[0141] Figure 9 FIG. 1 is a timing diagram of a resource processing method in an embodiment. Figure 9 The technical architecture used in this sequence diagram includes a transaction server and an intelligent algorithm server. Figure 9 , the timing diagram includes the following steps:

[0142] Step 902: The scheduled task of the transaction server triggers a check to see whether the transaction conditions of the conditional transaction order are met.

[0143] Step 904: The transaction server queries all executable conditional transaction orders.

[0144] Among them, the executable conditional trading order may be one that has not expired and has not been successfully executed.

[0145] For each conditional transaction order found, the transaction server checks whether the transaction conditions of the conditional transaction order are met according to steps 908 to 916 below.

[0146] Step 906: The transaction server queries the resource information of the target resource and the object information of the target object;

[0147] Step 908: The transaction server calculates a first transaction probability based on the current price and condition information of the target resource;

[0148] Step 910: The transaction server estimates a second transaction probability based on the resource information and the object information by calling the transaction estimation model of the intelligent algorithm server.

[0149] Step 912: The transaction server calculates a target transaction probability based on the first transaction probability, the second transaction probability, and the transaction tendency.

[0150] Step 914: When the target transaction probability is greater than the probability threshold, the transaction server executes the transaction on the target resource.

[0151] Step 916: The transaction server marks the conditional transaction order as successfully executed.

[0152] From the perspective of the terminal and the server, a resource processing method in a specific embodiment is provided below, which specifically includes the following steps:

[0153] 1. The terminal displays the interface for creating a conditional trading order for the target resource.

[0154] In some embodiments, the terminal may display a conditional transaction order creation interface in a browser, or may display the conditional transaction order creation interface in a client for resource transactions.

[0155] In some embodiments, the terminal may display a creation interface for a conditional transaction order of the target resource in response to the triggering operation of the object on the target resource.

[0156] In some embodiments, the creation interface includes at least one condition information input control for supporting the object to input condition information.

[0157] 2. In response to triggering an operation on the condition information input control in the creation interface, the terminal displays the input condition information in the condition information input control.

[0158] In response to the subject's input operations on these input controls, the terminal displays the entered condition information on the creation interface. The entered condition information can include resource identification, transaction price, transaction share (or transaction amount), order validity period, etc. Condition information is a general term for all specific conditions. Only when the transaction conditions indicated by the condition information are met will the transaction be triggered for the target resource.

[0159] In some embodiments, the input conditional information includes trading tendency, which is the degree of tendency to trigger a transaction based on a transaction prediction model; the conditional information also includes an expected transaction price range and a transaction willingness range, the expected transaction price range includes a first expected transaction price and a second expected transaction price, and the transaction willingness range includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price; wherein, when the conditional transaction order is a conditional buy order, the second expected transaction price is less than the first expected transaction price; when the conditional transaction order is a conditional sell order, the second expected transaction price is greater than the first expected transaction price; the input conditional information also includes a probability threshold.

[0160] In some embodiments, the conditional information also includes basic transaction information and a probability threshold, wherein the current price of the target resource and the basic transaction information are used to calculate the first transaction probability, the transaction estimation model is used to estimate the second transaction probability, and the conditional transaction order is used to execute a transaction on the target resource when the target transaction probability determined based on the transaction tendency, the first transaction probability and the second transaction probability is greater than the probability threshold.

[0161] 3. In response to the conditional trading order creation operation, the terminal generates a creation request according to the condition information and sends the creation request to the server, so that the server creates the conditional trading order according to the condition information.

[0162] In some embodiments, the creation interface includes a creation control, and the terminal generates a creation request based on input condition information in response to a triggering operation on the creation control.

[0163] 4. The server checks for conditional transaction orders regarding the target resource that have not expired and have not been executed, and obtains condition information of the conditional transaction orders.

[0164] In some embodiments, the transaction server may periodically or regularly query whether there are conditional transaction orders that have not expired and have not been successfully executed. If so, for these conditional transaction orders, based on the corresponding condition information and the current price of the target resource, check whether the transaction conditions are met.

[0165] 5. When the current price of the target resource is within the expected transaction price range, the server calculates the transaction willingness difference between the second transaction willingness and the first transaction willingness, calculates the price difference between the second expected transaction price and the first expected transaction price, obtains the transaction willingness coefficient based on the ratio of the transaction willingness difference to the price difference, calculates the difference between the current price of the target resource and the first expected transaction price, and obtains the first transaction probability based on the product of the difference and the transaction willingness coefficient.

[0166] In some embodiments, when the conditional trading order is a conditional buy order, the second expected trading price is less than the first expected trading price; when the conditional trading order is a conditional sell order, the second expected trading price is greater than the first expected trading price.

[0167] 6. When the current price of the target resource is outside the expected transaction price range, the server determines the first transaction probability to be 0.

[0168] 7. The server queries the resource information of the target resource and the object information of the target object, and estimates the second transaction probability based on the resource information and the object information using a transaction estimation model.

[0169] The target resource's resource information includes, but is not limited to, the target resource's resource identifier, current price, shareholder information, financial indicator information, expected profitability information, and trading market trend information. The target object's object information includes, but is not limited to, the target object's object identifier, risk level, holding cost, holding return, holding duration, holding ratio, transaction fee rate, total holding cost, and deposit and withdrawal plans.

[0170] The server can input the retrieved target resource information and target object information into the transaction prediction model, which then outputs an estimated second transaction probability M2. This second transaction probability M2 reflects the likelihood of triggering a transaction based on the transaction prediction model, thus reflecting the transaction decision made at the intelligent algorithm level.

[0171] The transaction prediction model is a model based on artificial intelligence algorithms. It is trained based on sample data and learns the ability to estimate whether a transaction can be executed based on resource information and object information. This ability can be quantified through transaction probability. The greater the transaction probability, the more likely the transaction can meet the transaction needs of the object at the current time. The smaller the transaction probability, the less likely the transaction can meet the transaction needs of the object at the current time.

[0172] 8. Calculate the propensity for triggering a transaction based on the conditional information based on the propensity for triggering a transaction based on the transaction prediction model.

[0173] For example, if the transaction tendency in the conditional information is a tendency degree α2 for triggering a transaction based on a transaction estimation model, then the tendency degree α1=1-α2 for triggering a transaction based on the conditional information can be automatically determined.

[0174] 9. The first transaction probability is weighted according to the propensity for triggering a transaction based on the conditional information to obtain a first weighted transaction probability. The second transaction probability is weighted according to the propensity for triggering a transaction based on the transaction estimation model to obtain a second weighted transaction probability. The target transaction probability is obtained by summing the first weighted transaction probability and the second weighted transaction probability.

[0175] The target transaction probability M0 can be calculated using the following formula:

[0176] M0=α1×M1+α2×M2.

[0177] Assuming the first transaction probability M1=0.25, M2=0.5, α1=0.3, α2=0.7, and probability threshold Mth=0.5, the calculated target transaction probability M0=0.25×0.3+0.5×0.7=0.425. Since this probability is less than the set probability threshold, the transaction will not be triggered. In other words, the trading server will not report the transaction request to the exchange backend at this time. It is necessary to wait for the next check opportunity and perform the next check based on the current price of the target resource.

[0178] 10. If the conditional transaction order is a conditional buy order and the target transaction probability is greater than the probability threshold, the server will execute a buy operation on the target resource based on the transaction share and the current price of the target resource.

[0179] 11. When the conditional transaction order is a conditional sell order and the target transaction probability is greater than the probability threshold, the server executes a sell operation on the target resource based on the transaction share and the current price of the target resource.

[0180] Specifically, when the target transaction probability is greater than the probability threshold, the server can determine that the transaction conditions are met, and can generate a transaction request corresponding to the conditional transaction order and report the transaction request to the exchange backend so that the exchange backend can complete the transaction execution according to the reported transaction request, that is, perform a buy or sell operation.

[0181] In the above-mentioned resource processing method, the conditional information input by the object includes transaction tendency, and the transaction tendency is at least one of the tendency degree of triggering a transaction based on the conditional information and the tendency degree of triggering a transaction based on the transaction estimation model. In this way, the transaction strategy based on the conditional information input by the object, the transaction strategy based on the transaction estimation model, and the transaction timing triggered by the object's customized transaction tendency can be combined to automatically realize the execution of conditional transaction orders, reduce the deviation of the single and subjective conditional transaction decision-making method, improve the accuracy and reliability of the conditional transaction decision, and avoid the repeated interaction process of the object.

[0182] It should be understood that, although the various steps in the flowcharts involved in the above embodiments are displayed in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless clearly stated herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of the steps or stages in other steps or other steps. It is understandable that the various steps in different embodiments can be freely combined as needed, and the various non-contradictory schemes formed by the combination all fall within the scope of protection of this application.

[0183] Based on the same inventive concept, embodiments of the present application also provide a resource processing device for implementing the resource processing method described above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more resource processing device embodiments provided below can be found in the above-mentioned limitations on the resource processing method and will not be repeated here.

[0184] In an exemplary embodiment, Figure 10 As shown, a resource processing device 1000 is provided, comprising: a display module 1002, an input response module 1004 and an order creation module 1006, wherein:

[0185] Display module 1002, used to display the interface for creating a conditional transaction order for a target resource;

[0186] An input response module 1004 is configured to display the input condition information in the creation interface in response to the input operation, where the condition information includes at least a transaction propensity, which is at least one of a degree of propensity to trigger a transaction based on the condition information and a degree of propensity to trigger a transaction based on a transaction prediction model;

[0187] The order creation module 1006 is configured to create a conditional transaction order for the target resource based on the condition information in response to the conditional transaction order creation operation, wherein the conditional transaction order is used to execute a transaction on the target resource.

[0188] In some embodiments, the conditional information also includes basic transaction information and a probability threshold, wherein the current price of the target resource and the basic transaction information are used to calculate the first transaction probability, the transaction estimation model is used to estimate the second transaction probability, and the conditional transaction order is used to execute a transaction on the target resource when the target transaction probability determined based on the transaction tendency, the first transaction probability and the second transaction probability is greater than the probability threshold.

[0189] In some embodiments, the basic transaction information includes an expected transaction price range and a transaction willingness range, the expected transaction price range includes a first expected transaction price and a second expected transaction price, and the transaction willingness range includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price, wherein the current price of the target resource, the first expected transaction price and the second expected transaction price, the first transaction willingness and the second transaction willingness are used to calculate the first transaction probability.

[0190] In some embodiments, the input response module 1004 is configured to display the input condition information in the condition information input control in response to triggering an operation on the condition information input control in the creation interface.

[0191] In some embodiments, the order creation module 1006 is used to generate a creation request based on the condition information, send the creation request to the server, so that the server creates a conditional transaction order based on the condition information, and executes a transaction on the target resource based on the conditional transaction order.

[0192] In some embodiments, the resource processing device 1000 also includes an order query module, which is used to send a query request to the server in response to an order query operation, and the query request is used to request to query the order information of the conditional transaction order of the target object; receive the order information of the conditional transaction order of the target object fed back by the server; and display the order information.

[0193] In some embodiments, the resource processing device 1000 further includes a prompt module for receiving the execution result of the conditional transaction order regarding the target object sent by the server; and displaying prompt information generated according to the execution result.

[0194] In an exemplary embodiment, Figure 11 As shown, a resource processing device 1100 is provided, comprising: a receiving module 1102, an order generating module 1104 and an order executing module 1106, wherein:

[0195] A receiving module 1102 is configured to receive a request to create a conditional transaction order for a target resource, the request carrying condition information, the condition information including at least a transaction tendency, the transaction tendency being at least one of a tendency to trigger a transaction based on the condition information and a tendency to trigger a transaction based on a transaction prediction model;

[0196] An order generating module 1104 is configured to generate a conditional transaction order for a target resource based on the condition information;

[0197] The order execution module 1106 is used to execute transactions on target resources according to the conditional transaction order.

[0198] In some embodiments, the order execution module 1106 is also used to calculate a first transaction probability based on the current price of the target resource and the basic transaction information in the condition information; query the resource information of the target resource and the object information of the target object, and estimate the second transaction probability based on the resource information and the object information through a transaction prediction model; calculate the target transaction probability based on the first transaction probability, the second transaction probability and the transaction tendency; when the target transaction probability is greater than the probability threshold, execute the transaction on the target resource.

[0199] In some embodiments, the basic transaction information includes an expected transaction price range and a transaction willingness range. The order execution module 1106 is also used to calculate the transaction willingness coefficient based on the expected transaction price range and the transaction willingness range when the current price of the target resource is within the expected transaction price range, and calculate the first transaction probability based on the current price of the target resource and the transaction willingness coefficient.

[0200] In some embodiments, the order execution module 1106 is further configured to determine that the first transaction probability is 0 when the current price of the target resource is outside the expected transaction price range.

[0201] In some embodiments, the expected transaction price range includes a first expected transaction price and a second expected transaction price, and the transaction willingness range includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price; the order execution module 1106 is also used to calculate the transaction willingness difference between the second transaction willingness and the first transaction willingness; calculate the price difference between the second expected transaction price and the first expected transaction price; and obtain the transaction willingness coefficient based on the ratio of the transaction willingness difference to the price difference.

[0202] In some embodiments, when the conditional trading order is a conditional buy order, the second expected trading price is less than the first expected trading price; when the conditional trading order is a conditional sell order, the second expected trading price is greater than the first expected trading price.

[0203] In some embodiments, the order execution module 1106 is further configured to calculate the difference between the current price of the target resource and the first expected transaction price; and obtain the first transaction probability based on the product of the difference and the transaction willingness coefficient.

[0204] In some embodiments, the transaction tendency is the tendency degree of triggering a transaction based on a transaction prediction model. The order execution module 1106 is also used to calculate the tendency degree of triggering a transaction based on conditional information based on the tendency degree of triggering a transaction based on the transaction prediction model; according to the tendency degree of triggering a transaction based on the conditional information, the first transaction probability is weighted to obtain a first weighted transaction probability; according to the tendency degree of triggering a transaction based on the transaction prediction model, the second transaction probability is weighted to obtain a second weighted transaction probability; and the target transaction probability is obtained according to the sum of the first weighted transaction probability and the second weighted transaction probability.

[0205] In some embodiments, the conditional information also includes transaction shares, and the order execution module 1106 is further used to perform a buy operation on the target resource according to the transaction share and the current price of the target resource when the conditional transaction order is a conditional buy order and the target transaction probability is greater than the probability threshold; and to perform a sell operation on the target resource according to the transaction share and the current price of the target resource when the conditional transaction order is a conditional sell order and the target transaction probability is greater than the probability threshold.

[0206] Each module in the resource processing device described above may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in hardware form, or may be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0207] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 12 As shown. The computer device includes a processor, memory, an input / output interface (I / O), and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile 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 the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store generated conditional trading orders. The I / O interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a resource processing method.

[0208] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 13As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When the computer program is executed by the processor, a resource processing method is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0209] Those skilled in the art will understand that Figure 12 、 Figure 13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0210] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of the resource processing method when executing the computer program.

[0211] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the resource processing method are implemented.

[0212] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps of the resource processing method when executed by a processor.

[0213] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0214] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processors (GPUs), digital signal processors (DSPs), programmable logic units (PLCs), data processing logic units (DPLs), artificial intelligence (AI) processors, and the like.

[0215] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0216] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A resource processing method, characterized in that: The method comprises: Displays the interface for creating conditional trading orders for target resources; In response to the input operation, the input condition information is displayed in the creation interface, the condition information at least including a transaction tendency, the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model; In response to a conditional transaction order creation operation, a conditional transaction order for the target resource is created based on the condition information, where the conditional transaction order is used to execute a transaction on the target resource.

2. The method according to claim 1, characterized in that The step of displaying the input condition information in the creation interface in response to the input operation includes: In response to triggering an operation on the condition information input control in the creation interface, the input condition information is displayed in the condition information input control.

3. The method according to claim 1, characterized in that The creating a conditional transaction order for the target resource based on the condition information includes: A creation request is generated according to the condition information, and the creation request is sent to a server, so that the server creates a conditional transaction order according to the condition information and executes a transaction on the target resource based on the conditional transaction order.

4. The method according to claim 3, characterized in that The executing a transaction on the target resource based on the conditional transaction order includes: Calculating a first transaction probability based on the current price of the target resource and the basic transaction information in the condition information; querying resource information of the target resource and object information of the target object, and estimating a second transaction probability based on the resource information and the object information using the transaction estimation model; Calculating a target transaction probability based on the first transaction probability, the second transaction probability, and the transaction tendency; When the target transaction probability is greater than the probability threshold, executing a transaction on the target resource.

5. The method according to claim 4, characterized in that The basic transaction information includes an expected transaction price range and a transaction willingness range, and calculating a first transaction probability based on the current price of the target resource and the basic transaction information includes: When the current price of the target resource is within the expected transaction price range, the transaction willingness coefficient is calculated based on the expected transaction price range and the transaction willingness range, and the first transaction probability is calculated based on the current price of the target resource and the transaction willingness coefficient.

6. The method according to claim 4, characterized in that The transaction propensity is the degree of tendency to trigger a transaction based on the transaction prediction model. The target transaction probability is calculated based on the first transaction probability, the second transaction probability, and the transaction propensity, including: Calculating the degree of tendency to trigger a transaction based on the conditional information according to the degree of tendency to trigger a transaction based on the transaction prediction model; weighting the first transaction probability according to the tendency of triggering a transaction based on the condition information to obtain a first weighted transaction probability; weighting the second transaction probability according to the degree of propensity to trigger a transaction based on the transaction prediction model to obtain a second weighted transaction probability; A target transaction probability is obtained according to the sum of the first weighted transaction probability and the second weighted transaction probability.

7. The method according to claim 1, characterized in that The method further comprises: In response to the order query operation, a query request is sent to the server, wherein the query request is used to request order information of the conditional transaction order of the target object; Receiving order information of the conditional transaction order of the target object fed back by the server; The order information is displayed.

8. The method according to any one of claims 1 to 7, characterized in that The method further comprises: receiving an execution result of the conditional transaction order regarding the target object sent by the server; Display prompt information generated according to the execution result.

9. A resource processing method, characterized in that: The method comprises: receiving a request to create a conditional transaction order for a target resource, the request carrying condition information, the condition information including at least a transaction tendency, the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model; generating a conditional transaction order for the target resource based on the condition information; Execute a transaction on the target resource according to the conditional transaction order.

10. The method according to claim 9, characterized in that The executing a transaction on the target resource according to the conditional transaction order includes: Calculating a first transaction probability based on the current price of the target resource and the basic transaction information in the condition information; querying resource information of the target resource and object information of the target object, and estimating a second transaction probability based on the resource information and the object information using the transaction estimation model; Calculating a target transaction probability based on the first transaction probability, the second transaction probability, and the transaction tendency; When the target transaction probability is greater than the probability threshold, executing a transaction on the target resource.

11. The method according to claim 10, characterized in that The basic transaction information includes an expected transaction price range and a transaction willingness range, and calculating a first transaction probability based on the current price of the target resource and the basic transaction information includes: When the current price of the target resource is within the expected transaction price range, the transaction willingness coefficient is calculated based on the expected transaction price range and the transaction willingness range, and the first transaction probability is calculated based on the current price of the target resource and the transaction willingness coefficient.

12. The method according to claim 10, characterized in that The method further comprises: When the current price of the target resource is outside the expected transaction price range, the first transaction probability is determined to be 0.

13. The method according to claim 10, characterized in that The expected transaction price range includes a first expected transaction price and a second expected transaction price, and the transaction willingness range includes a first transaction willingness corresponding to the first expected transaction price and a second transaction willingness corresponding to the second expected transaction price; The calculating of the transaction willingness coefficient according to the expected transaction price range and the transaction willingness range includes: Calculating a transaction willingness difference between the second transaction willingness and the first transaction willingness; calculating a price difference between the second expected transaction price and the first expected transaction price; A transaction willingness coefficient is obtained according to the ratio of the transaction willingness difference to the price difference.

14. The method according to claim 11, characterized in that The calculating a first transaction probability according to the current price of the target resource and the transaction willingness coefficient includes: Calculating the difference between the current price of the target resource and the first expected transaction price; The first transaction probability is obtained according to the product of the difference and the transaction willingness coefficient.

15. The method according to claim 10, characterized in that The transaction propensity is the degree of tendency to trigger a transaction based on the transaction prediction model. The target transaction probability is calculated based on the first transaction probability, the second transaction probability, and the transaction propensity, including: Calculating the degree of tendency to trigger a transaction based on the conditional information according to the degree of tendency to trigger a transaction based on the transaction prediction model; weighting the first transaction probability according to the tendency of triggering a transaction based on the condition information to obtain a first weighted transaction probability; weighting the second transaction probability according to the degree of propensity to trigger a transaction based on the transaction prediction model to obtain a second weighted transaction probability; A target transaction probability is obtained according to the sum of the first weighted transaction probability and the second weighted transaction probability.

16. The method according to any one of claims 10 to 15, characterized in that The condition information further includes a transaction share. When the target transaction probability is greater than the probability threshold, executing the transaction on the target resource includes: When the conditional transaction order is a conditional buy order and the target transaction probability is greater than the probability threshold, performing a buy operation on the target resource according to the transaction share and the current price of the target resource; When the conditional transaction order is a conditional sell order and the target transaction probability is greater than the probability threshold, a sell operation is performed on the target resource according to the transaction share and the current price of the target resource.

17. A resource processing device, characterized in that: The device comprises: A display module, used to display the creation interface of the conditional transaction order of the target resource; an input response module, configured to display input condition information in the creation interface in response to an input operation, wherein the condition information at least includes a transaction propensity, which is at least one of a degree of propensity to trigger a transaction based on the condition information and a degree of propensity to trigger a transaction based on a transaction prediction model; An order creation module is configured to create a conditional transaction order for the target resource based on the condition information in response to a conditional transaction order creation operation, wherein the conditional transaction order is used to execute a transaction on the target resource.

18. A resource processing device, characterized in that: The device comprises: a receiving module configured to receive a request for creating a conditional transaction order for a target resource, the creation request carrying condition information, the condition information at least including a transaction tendency, the transaction tendency being at least one of a tendency degree of triggering a transaction based on the condition information and a tendency degree of triggering a transaction based on a transaction prediction model; An order generating module, configured to generate a conditional transaction order for the target resource based on the condition information; An order execution module is used to execute a transaction on the target resource according to the conditional transaction order.

19. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 16 are implemented.

20. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are implemented.

21. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are implemented.

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