Data determination method and device, equipment and medium

Abstract

The invention relates to the technical field of data processing, in particular to a data determination method and device, equipment and a medium, and is used for solving the problem that the option value estimation speed is relatively low. The method comprises the following steps: after an option value acquisition instruction sent by a client is received, acquiring option related parameters corresponding to the automatic knock-out and redemption type structural deposit; obtaining a target estimation model of the automatic knock-out and redemption type structural deposit, including a pre-knock-out part sub-model and a non-knock-out part sub-model, and based on the pre-knock-out part sub-model, according to a knock-out yield, market data and a conditional probability rule, obtaining a target estimation model of the automatic knock-out and redemption type structural deposit; determining a first option value under the condition that a knock-out event occurs on any observation day before the option expires; on the basis of the non-knock-out part sub-model, according to the guaranteed return rate, the market data and the conditional probability rule, determining a second option value under the condition that no knock-out event still occurs after the option expires; and obtaining a target option value based on the first option value and the second option value, and returning the target option value to the client.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and medium for determining data. Background Art

[0002] Structured deposits are financial products with certain risks that are established by banks by embedding financial derivatives (including but not limited to forwards, swaps, options or futures, etc.) on top of ordinary deposits, thereby linking investors' returns to interest rates, exchange rates, stock prices, commodity prices, credit, indices and other financial or non-financial underlying assets.

[0003] Automatic knock-out and redemption structured deposits set a knock-out barrier (such as the initial price of the underlying asset) and a series of discrete observation days. If the price of the underlying asset is higher than the barrier level on a certain observation day, the option is knocked out, the product is terminated or expires early, and the agreed high yield is paid. If no knock-out event occurs on all observation days, the product will pay a guaranteed yield upon maturity.

[0004] In the field of derivatives pricing, the commonly used method for numerical pricing of options is the Monte Carlo simulation method. However, this method requires simulating millions or even tens of millions of paths. For example, for options with a value near 0, the Monte Carlo simulation may require 10 million paths to accurately price, and for exotic options, calculations need to be performed on each path, resulting in a very slow pricing speed for the Monte Carlo simulation.

[0005] In summary, there are problems with the existing method of calculating option value, and it is urgent to propose an option pricing scheme with high accuracy and relatively faster speed. Summary of the invention

[0006] The embodiments of the present application provide a data determination method, device, electronic device, storage medium and computer program product, which are used to solve the problem of relatively slow option value estimation speed in related technologies.

[0007] In a first aspect, the present application provides a method for determining data, comprising:

[0008] After receiving the option value acquisition instruction sent by the client, the option related parameters corresponding to the automatic knock-out redemption type structured deposit are acquired, wherein the option related parameters include the knock-out yield and the guaranteed yield of the automatic knock-out redemption type structured deposit, and the market data related to the observation day of the automatic knock-out redemption type structured deposit;

[0009] Obtaining a target valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the target valuation model includes a pre-knock-out part sub-model and a non-knock-out part sub-model;

[0010] Input the option-related parameters into the target valuation model, and determine the first option value under the condition that a knock-out event occurs on any observation day before option expiration based on the early knock-out part sub-model, according to the knock-out yield, the market data and the conditional probability rule; and determine the second option value under the condition that no knock-out event occurs at option expiration based on the non-knock-out part sub-model, according to the guaranteed yield, the market data and the conditional probability rule;

[0011] Based on the first option value and the second option value, a target option value of the automatic knock-out redemption structured deposit on a preset valuation date is obtained, and the target option value is sent to the client.

[0012] In a second aspect, the present application provides a data determination device, the device comprising:

[0013] A data acquisition module, after receiving an option value acquisition instruction sent by a client, acquires option related parameters corresponding to the automatic knock-out redemption type structured deposit, wherein the option related parameters include the knock-out yield and the guaranteed yield of the automatic knock-out redemption type structured deposit, and market data related to the observation day of the automatic knock-out redemption type structured deposit;

[0014] A model acquisition module, which acquires a target valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the target valuation model includes a pre-knock-out part sub-model and a non-knock-out part sub-model;

[0015] The valuation module inputs the option-related parameters into the target valuation model, and determines the first option value under the condition that a knock-out event occurs on any observation day before option expiration based on the early knock-out part sub-model, according to the knock-out yield, the market data and the conditional probability rule; and determines the second option value under the condition that no knock-out event occurs at option expiration based on the non-knock-out part sub-model, according to the guaranteed yield, the market data and the conditional probability rule;

[0016] The option value sending module obtains the target option value of the automatic knock-out redemption structured deposit on a preset valuation date based on the first option value and the second option value, and sends the target option value to the client.

[0017] Optionally, the model acquisition module is used to:

[0018] Obtaining an initial valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the initial valuation model is used to determine, based on the preset valuation date, the risk-neutral expected value between the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day and the non-knock-out discounted returns under the condition that no knock-out event occurs until the last observation day, and using the risk-neutral expected value as the target option value;

[0019] The initial valuation model is converted into two parts, namely, the early knock-out part sub-model and the non-knock-out part sub-model; the early knock-out part sub-model is used to take the sum of the knock-out discounted benefits as the first option value, and the non-knock-out part sub-model is used to take the non-knock-out discounted benefits as the second option value;

[0020] The target valuation model is obtained by adding the early knock-out part sub-model and the non-knock-out part sub-model and calculating the risk-neutral expectation.

[0021] Optionally, the option-related parameters further include: a risk-free interest rate and a barrier value; the market data includes the value of the underlying asset on the observation date; and the valuation module is used to:

[0022] The risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield are input into the early knock-out part sub-model; based on the early knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield, combined with the conditional probability rule, the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day are determined, and the knock-out discounted returns are accumulated to obtain the first option value;

[0023] The risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return are input into the non-knock-out part sub-model; based on the non-knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return, in combination with the conditional probability rule, determine the non-knock-out discounted return if no knock-out event occurs until the last observation day, and use the non-knock-out discounted return as the second option value.

[0024] Optionally, the option value sending module is used to:

[0025] The first option value and the second option value are added together and the risk-neutral expectation is calculated to obtain the target option value.

[0026] Optionally, the option-related parameters further include: a risk-free interest rate and a barrier value, and the market data includes the value of the underlying asset on the observation date; and the valuation module is further used to:

[0027] The knock-out discounted return under the condition that a knock-out event occurs on any observation day is determined as follows:

[0028] For the i-th observation day, the knock-out discounted income corresponding to the i-th observation day is determined according to the discount factor on the i-th observation day, the annualized time of the interest-bearing interval of the i-th early maturity date, the knock-out yield and the knock-out conditional probability on the i-th observation day;

[0029] Wherein, the discount factor on the i-th observation day is determined based on the risk-free interest rate and the time difference between the i-th early maturity date and the preset valuation date;

[0030] The knock-out conditional probability on the i-th observation day represents the probability that the value of the underlying asset on the i-th observation day is not lower than the barrier value and the value of the underlying asset on any observation day before the i-th observation day is lower than the barrier value.

[0031] Optionally, the option-related parameters further include: a risk-free interest rate and a barrier value, and the market data includes the value of the underlying asset on the observation date; and the valuation module is further used to:

[0032] The un-knocked-out discounted return under the condition that no knock-out event occurs on the last observation day is determined as follows:

[0033] For the last observation day, the un-knocked discounted income corresponding to the last observation day is determined based on the discount factor on the last observation day, the annualized time of the interest-bearing interval of the last early maturity date, the guaranteed yield and the conditional probability of un-knocked out on the last observation day;

[0034] Wherein, the discount factor at the last observation date is determined based on the risk-free interest rate and the time difference between the last early maturity date and the preset valuation date;

[0035] The conditional probability of not knocking out on the last observation day represents the probability that the value of the underlying asset on each observation day is lower than the barrier value.

[0036] Optionally, the probability that the value of the underlying asset on any observation day is lower than the barrier value is determined based on the Black-Scholes option pricing model.

[0037] Optionally, the device further comprises:

[0038] The application module is configured to, after the valuation module obtains the target option value of the automatic knock-out redemption structured deposit on a preset valuation date, perform at least one of the following operations according to the target option value:

[0039] According to the target option value, combined with the historical behavior information and / or product preference information of the data requester, recommend products to the data requester;

[0040] Conduct risk analysis on the related products of the automatic knock-out redemption structured deposit according to the target option value and in combination with corresponding sensitivity indicators;

[0041] Obtaining the target option value of the automatic knock-out redemption structured deposit on each preset valuation date, and recording accounts according to each of the obtained target option values;

[0042] Based on the target option value and the issuance scale of the automatic knock-out redemption structured deposits, the potential risk exposure caused by market fluctuations is quantified.

[0043] In a third aspect, the present application provides an electronic device, including:

[0044] A memory for storing program instructions;

[0045] The processor is used to call the program instructions stored in the memory, and execute the steps included in the data determination method described in any one of the first aspects according to the obtained program instructions.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method for determining data described in any one of the first aspects.

[0047] In a fifth aspect, the present application provides a computer program product, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method for determining data described in any one of the first aspects.

[0048] The beneficial effects of this application are as follows:

[0049] The embodiments of the present application provide a method, device, equipment and medium for determining data. By obtaining the option-related parameters of the automatic knock-out redemption structured deposit and combining the target valuation model, the target valuation of the deposit product can be accurately calculated, helping the data requester (such as investor users, customers, etc.) to understand the actual value of their investment products, so as to make more informed decisions. Specifically, by obtaining the knock-out yield, the guaranteed yield and the market data related to the observation day, the accuracy and real-time performance of the option value calculation are ensured, laying a solid foundation for the subsequent valuation process. In addition, the present application adopts an analytical solution to represent the target valuation model of the automatic knock-out redemption structured deposit, and simplifies the complex option value calculation process into an analytical solution, which not only improves the accuracy of the valuation, but also significantly speeds up the calculation speed, overcoming the problem of low calculation efficiency caused by the need to simulate a large number of paths in the traditional Monte Carlo simulation method. Finally, the data requester can obtain the target option value of the product in a timely manner, understand the performance of its investment products in real time, enhance the ability to respond to market changes, and greatly improve the scientificity and effectiveness of decision-making.

[0050] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of an application scenario of a method for determining data provided in an embodiment of the present application;

[0052] Figure 2 An example diagram of a data requester interface of a method for determining data provided in an embodiment of the present application;

[0053] Figure 3 A flowchart of a method for determining data provided in an embodiment of the present application;

[0054] Figure 4 A flowchart of the target valuation model conversion process provided in an embodiment of the present application;

[0055] Figure 5 A schematic diagram of the observation date and the early maturity date of the method for determining data provided in the embodiment of the present application;

[0056] Figure 6 A diagram of a data determination device provided in an embodiment of the present application;

[0057] Figure 7 A schematic diagram of the composition structure of a computer electronic device for a method for determining data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0059] The terms "first" and "second" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any of their variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. "Multiple" in the present application can mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.

[0060] The following is an introduction to some concepts involved in the embodiments of the present application.

[0061] Knock-out yield: refers to the yield that can be obtained by early termination and redemption of structured deposit products when the underlying assets reach or exceed the set barrier value on a certain observation day. The knock-out yield reflects the investor's return level under the early termination conditions.

[0062] Barrier value: also known as barrier price, refers to the price threshold of the underlying asset set in the structured deposit product. When the value of the underlying asset reaches or exceeds the threshold on the observation day, the knock-out event is triggered. Barrier value is the key parameter that determines whether the knock-out event occurs or not. Similarly, other values ​​in this article can also be called prices, which will not be elaborated here.

[0063] Underlying asset value: refers to the market price of the asset used as the benchmark in structured deposit products. This value determines whether a knock-out event is triggered and affects the valuation and profit calculation of options.

[0064] Guaranteed rate of return: refers to the minimum rate of return that investors can obtain when a structured deposit product matures, provided that no knock-out event occurs. The guaranteed rate of return provides investors with a risk protection, ensuring that they can still obtain a certain return in the most unfavorable circumstances.

[0065] Options: A financial derivative that gives the holder the right to buy or sell an asset at a specific price at a specific time or time period in the future, but does not impose the obligation to buy or sell. Options include call options and put options, which correspond to the right to buy and the right to sell, respectively.

[0066] Automatic knock-out structured deposit: It is a financial product embedded with an option structure, which is characterized by the ability to automatically trigger a knock-out event and early redemption under certain conditions. This product combines the characteristics of deposits and options, providing investors with the opportunity to obtain higher returns when certain conditions are met, while providing a guaranteed return when the conditions are not met.

[0067] Knock-out: refers to an early termination event triggered when the price of the underlying asset reaches or exceeds the pre-set barrier price on a certain observation day. After a knock-out event occurs, the structured deposit product will be terminated early and redeemed according to the knock-out yield.

[0068] Observation day: refers to the date pre-set during the life of the structured deposit product to monitor whether the price of the underlying asset reaches the barrier price. On each observation day, if the price of the underlying asset reaches or exceeds the barrier price, a knock-out event is triggered.

[0069] Early maturity date: refers to the date on which the structured deposit product is terminated early after a knock-out event occurs. This date is usually set in advance within a period of time after the observation date. If a knock-out event is triggered on a certain observation date, the product will be terminated and redeemed early on the corresponding early maturity date.

[0070] Risk Neutrality: Risk neutrality is the assumption that investors have a neutral attitude toward risk.

[0071] Discounted return: refers to the value of future cash flows discounted to the current time point at a certain discount rate. Discounted return reflects the present value of cash flows obtained at different time points and is used to evaluate the actual value of financial products.

[0072] Closing: The last trading price of an underlying asset at the end of a financial market trading day. Closing prices are often used to calculate trigger conditions for knock-out events and to evaluate the performance of the underlying asset.

[0073] Risk exposure: Risk exposure refers to the potential loss or risk that a financial institution or investor faces due to market fluctuations. It reflects the potential impact of a portfolio or financial product when market conditions change. Risk exposure can involve various risk types, including market risk, credit risk, liquidity risk, etc.

[0074] Risk hedging: Risk hedging is an investment strategy that aims to reduce or eliminate the risk in an existing portfolio by taking opposite investment actions. For example, investors can hedge against potential losses from market fluctuations by purchasing derivatives (such as options and futures) or diversifying their investments. Risk hedging strategies help investors protect the value of their assets under adverse market conditions.

[0075] The solution provided in the embodiment of the present application mainly involves the application of data determination methods in the financial field, and specifically involves the option value assessment scenario for automatic knock-out redemption type structured deposits. For example, the structured deposit products purchased by investors are embedded with financial derivatives such as options. By setting a knock-out barrier and a series of observation days, when the price of the underlying asset on the observation day is higher than the preset barrier value, the option is knocked out, the product is terminated early and a high yield is paid; if no knock-out event occurs on all observation days, the product will pay a guaranteed yield at maturity. In this scenario, by obtaining the option-related parameters of the automatic knock-out redemption type structured deposits and combining them with the target valuation model, the target valuation of the deposit product can be accurately calculated, which helps investors understand the actual value of their investment products and make corresponding decisions.

[0076] The following is a brief introduction to the design concept of the embodiment of the present application:

[0077] As an efficient and accurate technical means, data determination methods are widely used in many fields such as financial product pricing, investment decision support, and asset management of financial institutions due to their advantages of fast calculation and high precision.

[0078] For example, in the field of financial product pricing, data determination methods are used to obtain and process relevant parameters, such as option yields, market data, etc., so as to accurately calculate the value of financial products, help investors understand the actual value of their investment products and make wise decisions. In the field of investment decision support, data determination methods are used to obtain and calculate the target value of investment products in real time, and provide timely feedback to the client, so that investors can understand the performance of their investment products in real time, enhance their ability to respond to market changes, and improve the scientificity and effectiveness of decision-making. In the field of asset management of financial institutions, data determination methods are used to accurately assess the value of various financial products, help financial institutions identify and control potential market risks, provide efficient and accurate valuation methods, and achieve more effective asset allocation and risk management.

[0079] Calculating the value of financial products requires efficient and accurate valuation methods. In addition, traditional valuation methods such as Monte Carlo simulation methods are difficult to meet the requirements of real-time and high precision due to their low computational efficiency. Therefore, an efficient method is needed to achieve rapid pricing and risk assessment of complex financial products.

[0080] In view of this, the embodiments of the present application provide a method, device, electronic device and medium for determining data. First, after receiving the option value acquisition instruction sent by the client, the option-related parameters corresponding to the automatic knock-out redemption type structured deposit are obtained. By obtaining these option-related parameters, the accuracy and real-time performance of the option value calculation are ensured, laying the foundation for the subsequent valuation process. Then, the target valuation model corresponding to the automatic knock-out redemption type structured deposit is obtained, and the model includes an early knock-out part sub-model and a non-knock-out part sub-model. The early knock-out part sub-model determines the first option value under the condition that a knock-out event occurs on any observation day before the option expires according to the knock-out yield; the non-knock-out part sub-model determines the second option value under the condition that no knock-out event occurs at the expiration of the option according to the guaranteed yield. By establishing a target valuation model, the option value calculation under the knock-out and non-knock-out conditions is decomposed and refined by an analytical solution, which improves the accuracy and efficiency of the valuation and overcomes the problem of slow pricing of the Monte Carlo simulation method. Finally, the option-related parameters are input into the target valuation model to obtain the target option value of the automatic knock-out redemption structured deposit on the preset valuation date, and send it to the client. The target option value is determined based on the first option value and the second option value. In this process, the target option value is automatically calculated and fed back to the client in a timely manner, so that investors can understand the value of their investment products in real time and make corresponding investment decisions. This application expresses the target valuation model of the automatic knock-out redemption structured deposit in the form of an analytical solution, which greatly improves the solution efficiency.

[0081] The following is a description of exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present application. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description. It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, which should be considered as exemplary, and their purpose is only to illustrate the feasibility of the implementation of the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0082] In the technical solution of this application, the acquisition, transmission, storage, and use of data are in compliance with the requirements of relevant national laws and regulations.

[0083] Before introducing a method for determining data provided in an embodiment of the present application, in order to facilitate understanding, the technical background of the embodiment of the present application is first introduced in detail below.

[0084] With the continuous development of financial markets, the types and complexity of financial products are increasing, especially structured deposit products embedded with financial derivatives. This type of product embeds financial derivatives such as options, forwards, swaps, etc. on the basis of ordinary deposits, linking investors' returns to interest rates, exchange rates, stock prices, commodity prices, etc. Although this type of structured deposit product can provide high returns, it is also accompanied by certain risks. Automatic knock-out redemption structured deposits are a common structured deposit product, which sets a knock-out barrier (such as the initial price of the underlying asset) and a series of discrete observation days. If the price of the underlying asset is higher than the barrier level on a certain observation day, the option is knocked out, the product is terminated early and the agreed high return is paid; if no knock-out event occurs on all observation days, the product will pay the guaranteed return at maturity. In the field of derivative pricing, the numerical pricing of options usually adopts the Monte Carlo simulation method. However, the Monte Carlo simulation method requires the simulation of a large number of paths (sometimes even millions of paths), especially for options with a value near 0, which requires a very large number of paths to accurately price. At the same time, the Monte Carlo simulation method needs to be calculated on each path, which makes its pricing very slow and difficult to meet the real-time and high-precision requirements of the financial market. In order to solve the problems existing in the existing option value calculation method, the embodiment of the present application provides an efficient and accurate method for determining data.

[0085] The preferred embodiments of the present application are described in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. In addition, the embodiments and features in the embodiments of the present application may be combined with each other if there is no conflict.

[0086] See also Figure 1 , which is a schematic diagram of an application scenario of a data determination method provided in an embodiment of the present application. The application scenario diagram includes a terminal device 110 and a server 120.

[0087] In the embodiment of the present application, the terminal device 110 includes but is not limited to mobile phones, tablet computers, laptop computers, desktop computers, e-book readers, intelligent voice interaction devices, smart home appliances, vehicle-mounted terminals and other devices; the terminal device may be installed with a client related to the determination of option value data, which may be software (such as a browser, editing software, other video object detection related software, etc.), or a web page, a small program, etc. The server 120 is a background server corresponding to the software or web page, small program, etc., or a server specifically used for determining option value data, which is not specifically limited in the present application. The server 120 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0088] It should be noted that the method for determining data in each embodiment of the present application can be executed by an electronic device, which may be a terminal device 110 or a server 120, that is, the method can be executed by the terminal device 110 or the server 120 alone, or can be executed jointly by the terminal device 110 and the server 120.

[0089] For example, when the terminal device 110 and the server 120 jointly execute, the data requester triggers the option value acquisition instruction on the client related to the data determination method installed on the terminal device 110, and sends it to the server 120 through the client. The server 120 analyzes the option-related parameters, obtains the option value, and sends it to the terminal device 110, which is presented to the data requester for viewing. The specific identification process on the server 120 side is as follows:

[0090] First, after receiving the option value acquisition instruction from the data requester, the server 120 starts to acquire option parameters related to the automatic knock-out redemption type structured deposit. These parameters include the knock-out rate, the guaranteed rate of return, and the market data related to the observation date. Then, the server 120 establishes a target valuation model based on these parameters. The target valuation model includes an early knock-out part sub-model and an un-knock-out part sub-model. The early knock-out part sub-model is used to calculate the first option value in the case of a knock-out event on any observation day before the option expires based on the knock-out rate of return; the un-knock-out part sub-model is used to calculate the second option value in the case of no knock-out event when the option expires based on the guaranteed rate of return. Then, the server 120 inputs the acquired option-related parameters into the target valuation model, performs calculations, and obtains the target option value on the preset valuation date. The target option value is determined based on the first option value and the second option value. Finally, the server 120 packages the calculated target option value and sends it back to the terminal device 110 through the network. After receiving the target option value, the terminal device 110 analyzes it and displays it in a visual form to the data requester for viewing, so that the data requester can understand the value of its investment product in real time and make corresponding decisions.

[0091] in, Figure 1 The entire process is shown, from the data requester inputting the option value acquisition instruction on the terminal device 110, to the server 120 obtaining the relevant parameters, analyzing and calculating the option value, and then sending the result back to the terminal device 110, which is displayed to the data requester by the terminal device 110.

[0092] In an optional implementation, the terminal device 110 and the server 120 may communicate with each other via a communication network.

[0093] In an optional implementation, the communication network is a wired network or a wireless network.

[0094] It should be noted that Figure 1 The figure is only an example. In fact, the number of terminal devices and servers is not limited and is not specifically limited in the embodiments of the present application.

[0095] The following describes the data determination method provided by the exemplary embodiment of the present application in combination with the application scenario described above and with reference to the accompanying drawings. It should be noted that the above application scenario is only shown to facilitate understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this regard.

[0096] It should be noted that the execution subject of the data determination method of the embodiment of the present application is an electronic device, for example, it may include the above-mentioned terminal device, server, etc. The data determination method of the embodiment of the present application can be executed by the data determination device of the embodiment of the present application, and the data determination device of the embodiment of the present application can be configured in any electronic device to execute the data determination method of the embodiment of the present disclosure.

[0097] See also Figure 2 As shown, a data requester interface example diagram of a method for determining data provided by an embodiment of the present application is shown, which exemplarily shows the various components and functional modules of the target valuation acquisition interface of the automatic knock-out redemption type structured deposit. In this interface, the data requester can enter and select the specific information of the underlying asset, such as the target code, the target category (such as futures, warrants, and foreign exchange related options). The start date is used to enter the start date of the product, such as 2024-01-01, and the underlying asset value is used to enter the current market price of the underlying asset. The data requester can choose to perform valuation calculations or coupon calculations, and perform corresponding operations through the calculation button on the interface, thereby triggering the option value acquisition instruction. In addition, the data requester can also enter the calculation type in the interface, including the initial pricing or the duration pricing, select the buy or sell direction, and enter the principal amount of the investment. The guaranteed rate of return and the knock-out rate of return are used to enter the annualized rate of return of the product when no knock-out event occurs and the knock-out event is triggered. Expiration date is used to input the expiration date of the product, such as 2025-01-01, knock-out price is used to input the price that triggers the knock-out event, and the knock-out observation date list lists the dates of each observation day. In this process, parameters can be divided into two categories: parameters entered by the data requester and parameters obtained externally. The parameters entered by the data requester include: underlying code, underlying category (such as futures, warrants, and foreign exchange), start date, calculation type (initial pricing or duration pricing), buy or sell direction, investment principal amount, guaranteed rate of return and knock-out rate of return, expiration date, knock-out price, and knock-out observation date list. Externally obtained parameters include: risk-free interest rate, barrier value, and underlying asset value.

[0098] Then, the electronic device obtains these option-related parameters and inputs them into the target valuation model to perform calculations to obtain the target option value of the automatic knock-out redemption structured deposit on the preset valuation date. The calculation results are displayed in the calculation result part of the interface, where the theoretical price (total) shows the total theoretical value of the product, the theoretical price (unit) shows the theoretical value of the unit product, and the valuation (option part) shows the valuation of the option part. Among them, the target option value is determined based on the first option value and the second option value. Through these steps, the electronic device can comprehensively evaluate the value of the automatic knock-out redemption structured deposit, provide accurate financial product pricing, risk management and investment decision support, and ensure that the data requester can obtain detailed product information and accurate valuation results.

[0099] See also Figure 3 As shown, it is an implementation flow chart of a method for determining data provided in an embodiment of the present application. Taking the server as the execution subject as an example, the specific implementation process of the method is as follows S31-S34:

[0100] S31: After receiving the option value acquisition instruction sent by the client, the option related parameters corresponding to the automatic knock-out and redemption type structured deposit are obtained, wherein the option related parameters include the knock-out yield and the guaranteed yield of the automatic knock-out and redemption type structured deposit, and the market data related to the observation day of the automatic knock-out and redemption type structured deposit.

[0101] Among them, the option value acquisition instruction is an instruction used to instruct the server to obtain the valuation of the automatically knocked-out redemption type structured deposit.

[0102] After the data requester inputs the relevant parameters on the client side and triggers the option value acquisition instruction, the server needs to obtain the option-related parameters corresponding to the automatic knock-out and redemption structured deposits. The option-related parameters include but are not limited to some or all of the following: knock-out yield, guaranteed yield, risk-free interest rate, barrier value, and underlying asset value.

[0103] For example:

[0104] Underlying asset value: market data related to the observation day of the automatically-knocked-out structured deposit, specifically indicating the market price of the underlying asset on the observation day, such as the underlying asset price at the close of each observation day, which can be obtained from the outside.

[0105] Barrier value: It is assumed to be 105% of the initial price of the underlying asset, that is, when the price of the underlying asset reaches or exceeds this barrier value, the knock-out event is triggered, which can be obtained externally.

[0106] Knock-out yield: It is assumed to be 10%, that is, when the asset price of the underlying at the close of a certain observation day is greater than or equal to the knock-out price, that is, when a knock-out event occurs, the data requester will obtain a 10% yield, which can be directly entered by the data requester.

[0107] Guaranteed rate of return: Assuming it is 2%, that is, if no knock-out event occurs, this product will mature on the original maturity date and the customer can obtain at least a 2% rate of return, which can be directly entered by the data requester.

[0108] Risk-free rate: Assumed to be 3%, it is the market risk-free investment rate of return used to discount the option value, which can be obtained externally.

[0109] S32: Obtain a target valuation model corresponding to the automatically knocked-out and redeemed structured deposit, where the target valuation model includes a pre-knocked-out part sub-model and a non-knocked-out part sub-model.

[0110] Among them, the early knock-out sub-model is a sub-model in the target valuation model, which is used to calculate the option value of structured deposits when a knock-out event occurs on a certain observation day before the option expires. This part of the model considers all situations that may cause the option to be knocked out early and calculates the option value under these situations.

[0111] The non-knockout part sub-model is another sub-model in the target valuation model, which is used to calculate the option value of structured deposits when no knock-out event occurs at option expiration. That is, if the option does not trigger a knock-out event on the observation day before the expiration date, this sub-model is used to evaluate the value of the option.

[0112] The specific process of the pre-knocked out partial sub-model and the non-knocked out partial sub-model will be introduced below.

[0113] S33: Input option-related parameters into the target valuation model, and based on the early knock-out part sub-model, determine the value of the first option under the condition that a knock-out event occurs on any observation day before the option expires according to the knock-out yield, market data and conditional probability rules; and, based on the non-knock-out part sub-model, determine the value of the second option under the condition that no knock-out event occurs at option expiration according to the guaranteed yield, market data and conditional probability rules.

[0114] Among them, the conditional probability rule is a method for calculating the probability of an event occurring under certain conditions. In the embodiment of the present application, the conditional probability rule is used to calculate the probability of different events occurring in the automatic knock-out redemption structured deposit, such as the knock-out conditional probability and the non-knock-out conditional probability described below.

[0115] The conditional probability of an early knock-out event is to calculate whether the price of the underlying asset will reach or exceed the preset knock-out level based on any observation day before the option expires. Specifically, the probability of a knock-out event occurring on each observation day is evaluated using market data (such as the price of the underlying asset, risk-free interest rate, etc.) and the knock-out yield.

[0116] The conditional probability of a no-knockout event is calculated as the probability that the underlying asset price does not reach the knockout level at option expiration. This probability assesses the likelihood that the underlying asset price will remain below the knockout level over the entire observation period. The calculation uses guaranteed yields, market data, etc., and takes into account asset price changes over the entire observation period.

[0117] When implementing the above steps, the idea of ​​analytical solution can be adopted. An analytical solution refers to a clear expression obtained by mathematical methods, which can directly give the answer to the problem without the need for numerical simulation or iterative calculation. The idea of ​​analytical solution is to simplify complex problems into mathematical expressions that can be directly solved by mathematical modeling of the problem, using formulas, theorems and techniques. In this embodiment, the initial valuation model is first expressed in the form of an analytical solution, and then some items in the initial model are integrated to obtain the target valuation model in the form of an analytical solution.

[0118] An optional implementation is to refer to Figure 4 Implementing the above step S33 includes the following steps S401-S402:

[0119] S401: Obtain the initial valuation model corresponding to the automatic knock-out redemption type structured deposit, wherein the initial valuation model is used to determine the risk-neutral expected value between the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day and the non-knock-out discounted returns under the condition that no knock-out event occurs until the last observation day according to the preset valuation date, and use the risk-neutral expected value as the target option value.

[0120] In the embodiment of the present application, the calculation formula of the initial valuation model can be expressed as:

[0121]

[0122] Where t is the preset valuation date, V(t) is the target option value under the preset valuation date; T0 represents the option start date, which indicates the start time of the option contract; T1 represents the first early expiration date, T2 represents the second early expiration date, and so on. mrepresents the mth early expiration date, indicating the time point when the option may expire early; R1 represents the knock-out yield, which is the yield that the data requester will obtain when a knock-out event occurs on a certain observation day, and is used to calculate the incremental amount of the knock-out yield; R2 represents the guaranteed yield, which is the guaranteed yield that the data requester will obtain when a knock-out event does not occur on a certain observation day, and is used to calculate the incremental amount of the knock-out yield; represents the first observation day, Indicates that on the first observation day The market price of the underlying asset, represents the second observation day, Indicates that on the second observation day The market price of the underlying asset, and so on. represents the mth observation day, Indicates that on the mth observation day The market price of the underlying asset, represents the jth observation day, Indicates that on the jth observation day The market price of the underlying asset; B represents the barrier value.

[0123] Among them, the respective knock-out discounted returns under the condition that a knock-out event occurs on the i-th observation day can be understood as:

[0124] For the i-th observation day, the knock-out discounted yield corresponding to the i-th observation day is determined based on the discount factor on the i-th observation day, the annualized time of the interest-bearing interval of the i-th early maturity date, the knock-out yield, and the knock-out conditional probability on the i-th observation day;

[0125] The discount factor at the i-th observation day is determined based on the risk-free interest rate and the time difference between the i-th early maturity date and the preset valuation date;

[0126] The knock-out conditional probability on the i-th observation day represents the probability that the value of the underlying asset on the i-th observation day is not less than the barrier value and the value of the underlying asset on any observation day before the i-th observation day is less than the barrier value.

[0127] For example, the discounted knock-out return when a knock-out event occurs on the first observation day is: Among them, DF CNY (t, T1) is the discount factor on the first observation day, △(T0, T1) is the annualized time of the interest-bearing interval on the first early maturity date, and [1+△(T0, T1)*R1] represents the incremental amount of knock-out income, reflecting the incremental amount of yield that the data requester will obtain if a knock-out event occurs on one observation day. is the knock-out conditional probability on the first observation day, that is, the probability that the value of the underlying asset on the first observation day is not less than the barrier value;

[0128] The discounted knock-out return when a knock-out event occurs on the second observation day is: Among them, DF CNY (t, T2) is the discount factor on the second observation day, △(T0, T2) is the annualized time of the interest-bearing interval on the second early maturity date, and [1+△(T0, T2)*R1] represents the incremental amount of knock-out income, reflecting the incremental amount of yield that the data requester will obtain if a knock-out event occurs on the two early maturity dates. is the knock-out conditional probability of a knock-out occurring on the second observation day, where is the probability that the value of the underlying asset on the first observation day is lower than the barrier value, is the probability that the value of the underlying asset on the second observation day is not less than the barrier value;

[0129] Under the condition that a knock-out event occurs on the third observation day, the respective knock-out discounted returns are: Among them, DF CNY (t, T2) is the discount factor on the second observation day, △(T0, T3) is the annualized time of the interest-bearing interval on the third early maturity date, and [1+△(T0, T3)*R1] represents the incremental knock-out yield, reflecting the incremental yield that the data requester will obtain if a knock-out event occurs within 3 observation days. is the knock-out conditional probability of a knock-out on the third observation day, where is the conditional probability that the value of the underlying asset on both the first and second observation days is lower than the barrier value, is the conditional probability that the value of the underlying asset on the third observation day is not less than the barrier value;

[0130] …

[0131] The respective knock-out discounted returns under the condition that a knock-out event occurs on the mth observation day are: Among them, DF CNY (t,T m ) is the discount factor for the mth observation day, △(T0, T m ) is the annualized time of the interest-bearing interval of the mth early maturity date, [1+△(T0, T m )*R1] represents the incremental knock-out income, reflecting the incremental yield that the data requester will obtain if a knock-out event occurs within m observation days. is the knock-out conditional probability of a knock-out on the mth observation day, where is the conditional probability that the value of the underlying asset from the 1st observation day to the m-1th observation day is lower than the barrier value, is the probability that the value of the underlying asset on the mth observation day is not less than the barrier value.

[0132] The un-knocked discounted income under the condition that no knock-out event occurs until the last observation day is: for the last observation day, the un-knocked discounted income corresponding to the last observation day is determined based on the discount factor on the last observation day, the annualized time of the interest-bearing interval of the last early maturity date, the guaranteed rate of return and the conditional probability of un-knocked on the last observation day;

[0133] The discount factor at the last observation date is determined based on the risk-free interest rate and the time difference between the last early maturity date and the preset valuation date;

[0134] The conditional probability of not knocking out on the last observation day represents the probability that the value of the underlying asset is lower than the barrier value on each observation day.

[0135] Specifically, for the last observation day m, if no knock-out event occurs on the last observation day, the unknocked-out discounted return is expressed as Among them, DF CNY (t,T m ) is the discount factor for the mth observation day, △(T0, T m ) is the annualized time of the interest-bearing interval of the mth early maturity date, [1+△(T0, T m )*R1] represents the increment of guaranteed return, which reflects the increment of guaranteed return that the data requester will obtain if no knock-out event occurs within m observation days. It is the probability that a knock-out occurs for m observation days, that is, the value of the underlying asset from the 1st observation day to the mth observation day is lower than the barrier value.

[0136] S402: Convert the initial valuation model into two parts: an early knock-out part sub-model and a non-knock-out part sub-model; the early knock-out part sub-model is used to take the sum of the knock-out discounted benefits as the first option value, and the non-knock-out part sub-model is used to take the non-knock-out discounted benefits as the second option value.

[0137] In an embodiment of the present application, through conversion, the initial valuation model can be represented as two parts: an early knock-out part sub-model and a non-knock-out part sub-model. Specifically, it is obtained by merging some of the terms in the formula listed above, such as merging each knock-out discounted income part and converting it into an early knock-out part sub-model. The early knock-out part sub-model is used to calculate the first option value, specifically the sum of each knock-out discounted income as the first option value, and directly using the non-knock-out discounted income part as the non-knock-out part sub-model, and the non-knock-out part sub-model is used to calculate the second option value.

[0138] An optional implementation is that option-related parameters also include: risk-free interest rate and barrier value, and market data includes underlying asset values ​​related to the observation date.

[0139] Among them, the risk-free interest rate, barrier value and underlying asset value parameters have been introduced above and will not be repeated here.

[0140] Then, the value of the first option and the value of the second option can be calculated as follows:

[0141] The risk-free interest rate, barrier value, and the value of the underlying asset and the knock-out yield on each observation day are input into the early knock-out part sub-model. Based on the early knock-out part sub-model, according to the preset valuation date, risk-free interest rate, barrier value, and the value of the underlying asset and the knock-out yield on each observation day, combined with the conditional probability rule, the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day are determined, and the results are accumulated to obtain the first option value.

[0142] Among them, the partial sub-model knocked out in advance can be expressed as:

[0143]

[0144] In the formula, V(1) represents the first option value, which is the sum of the discounted knock-out returns on each observation day.

[0145] By merging, we can get some sub-models knocked out in advance:

[0146]

[0147] Among them, DF CNY (t,T i ) represents the discount factor from the preset valuation date t to the i-th early maturity date; △(T0, T i ) represents the annualized time of the interest-bearing interval of the ith early maturity date; [1+△(T0, T i)*R1] represents the incremental amount of knock-out income, reflecting the incremental rate of return that the data requester will obtain if a knock-out event occurs on a certain early maturity date; DF CNY (t,T i )*[1+△(T0,T i )*R1] represents the discounted return when the knock-out event occurs on the i-th early maturity date, which is used to discount future returns to the current value according to the discount factor; represents the asset price at the jth observation target The probability of falling below the barrier price B for each observation day from j 1 to i-1; Represents the asset price at the i-th observation target The probability of being higher than or equal to the barrier price B; Represents the asset price at the first i-1 observations The asset price that is below the barrier price B and is the target of the previous i observations The conditional probability of being greater than or equal to the barrier price B.

[0148] In a possible embodiment, the calculation formula of the discount factor is as follows:

[0149]

[0150] Among them, r represents the risk-free interest rate, T i represents the i-th early maturity date.

[0151] See also Figure 5 , which is a schematic diagram of the observation date and the early maturity date of the method for determining data provided in the embodiment of the present application. Exemplary:

[0152] Assuming that the automatic knock-out redemption structured deposit is knocked out on the first observation day, 2024 / 6 / 27, the deposit will mature early on the first early maturity date, 2024 / 7 / 1.

[0153] Assuming that the automatic knock-out redemption structured deposit is knocked out on the second observation day, 2024 / 7 / 26, it means that it was not knocked out on the first observation day, 2024 / 6 / 27. Then the deposit will mature early on the second early maturity date, 2024 / 7 / 30.

[0154] Assuming that the automatic knock-out redemption structured deposit is knocked out on the third observation day 2024 / 8 / 28, it means that it is not knocked out on the first observation day 2024 / 6 / 27 and the second observation day 2024 / 7 / 26. Then the deposit will mature early on the third early maturity date 2024 / 8 / 30.

[0155] And so on, I won’t go into details here…

[0156] Similarly, the risk-free interest rate, barrier value, and the underlying asset value and guaranteed rate of return on the last observation day are input into the non-knock-out part sub-model, so as to determine the non-knock-out discounted return if no knock-out event occurs until the last observation day based on the preset valuation date, risk-free interest rate, barrier value, and the underlying asset value and guaranteed rate of return on the last observation day, combined with the conditional probability rule, and use the non-knock-out discounted return as the second option value.

[0157] Among them, the sub-model of the un-knocked-out part can be expressed as:

[0158]

[0159] In Formula 5, V(2) represents the value of the second option. The parameters have been mentioned and introduced before, so they will not be elaborated here.

[0160] Among them, DF CNY (t,T m ) represents the period from valuation date t to the mth early maturity date T m The discount factor; △(T0, T m ) represents the annualized time of the interest-bearing interval of the mth early maturity date; [1+△(T0, T m )*R2] represents the increment of guaranteed return, reflecting the increment of return that the data requester will obtain if no knock-out event occurs on the final early maturity date; Represents the asset price of all observed targets The conditional probability that both are lower than the barrier price B is calculated. Specifically, the probability of not triggering a knock-out event on each observation day is calculated, and the product is used as the conditional probability.

[0161] In one possible embodiment, the probability that the value of the underlying asset on any observation day is lower than the barrier value is determined based on the Black Scholes option pricing model, and the probability calculation formula is as follows:

[0162] is N(d2) in the Black Scholes formula, where:

[0163]

[0164] In formula 6, is the probability that the value of the underlying asset on the jth observation day is lower than the barrier value, N(d2) is the cumulative distribution function value under the standard normal distribution, indicating that under the risk-neutral assumption, the value of the underlying asset The probability of being below the barrier value B; d2 measures the standardized distance of the current underlying asset price relative to the barrier price, combining the impact of the risk-free rate, the continuous compounding rate of the underlying asset, and volatility. r is the risk-free rate, q is the continuous compounding rate of the underlying asset, σ is the implied volatility on the jth observation day, and other parameters have been introduced before, so I will not go into details here.

[0165] Accordingly, the probability that the value of the underlying asset on any observation day is not less than the barrier value is calculated as follows:

[0166]

[0167] in, is the probability that the value of the underlying asset on the jth observation day is not less than the barrier value. Other parameters have been introduced before and will not be elaborated here.

[0168] S34: Based on the first option value and the second option value, the target option value of the automatic knock-out redemption structured deposit on the preset valuation date is obtained, and the target option value is sent to the client.

[0169] The purpose of combining the first option value and the second option value is to comprehensively evaluate the actual value of the automatic knock-out redemption structured deposit. The first option value represents the return when a knock-out event occurs, while the second option value represents the return when no knock-out event occurs. By considering these two situations, the actual value of the financial product at the preset valuation date in the future can be more accurately evaluated.

[0170] After obtaining the target option value of the automatic knock-out redemption structured deposit on the preset valuation date, the target option value result is sent to the client. This step sends the calculated value result to the client system of the data requester, so that the data requester can perform subsequent analysis, decision-making or other operations.

[0171] In an optional implementation, the early knock-out part sub-model and the non-knock-out part sub-model can be added together and the risk-neutral expectation can be calculated to obtain the target option value on the preset valuation date. Accordingly, the target valuation model is expressed as follows:

[0172]

[0173] Among them, E Q represents risk-neutral expectation.

[0174] In addition, the embodiments of the present application can be applied to various application scenarios, including but not limited to scenarios such as financial product pricing, risk management, and investment decision support, and can be specifically applied to business application scenarios related to the determination of data in these scenarios. Here are a few examples:

[0175] Application 1: Recommend products to the data requester based on the target option value and the historical behavior information and / or product preference information of the data requester;

[0176] The specific implementation method is as follows: through the data determination method in the embodiment of the present application, the browsing history, purchased financial records and fund allocation of the data requester in the bank's mobile banking are utilized, and through the deep learning algorithm, a suitable product structure is intelligently recommended to the data requester, such as setting a suitable barrier price, a suitable observation date, a suitable high yield, etc. The target valuation model can calculate the expected return and risk under different structures according to the data requester's preferences for barrier prices, observation dates and expected returns, so as to accurately recommend product structures that meet the preferences of the data requester. The bank can also reversely calculate the barrier price and structural parameters that meet a specific coupon rate based on the risk preference and return target of the data requester, and tailor structured deposits for the data requester to ensure that the product meets the risk preference of the data requester and provides the expected return.

[0177] Application 2: Based on the target option value and the corresponding sensitivity index, conduct risk analysis on related products of automatic knock-out redemption structured deposits;

[0178] The specific implementation method is as follows: When a bank issues an automatic knock-out structured deposit, it calculates its valuation through the data determination method in the embodiment of this application, conducts scenario analysis and stress testing, and analyzes the impact of changes in market risk factors on the product. The target valuation model is used to calculate the fair value of structured deposits, help banks understand the product's response to market changes, and evaluate product performance in different market environments through scenario analysis and stress testing, thereby effectively managing market risks.

[0179] Application 3: Obtain the target option value of the automatically knocked-out redemption structured deposit on each preset valuation date, and record the account according to each target option value obtained;

[0180] The specific implementation method is as follows: Through the data determination method in the embodiment of the present application, by obtaining the target option value of the automatic knock-out redemption structured deposit on each preset valuation date, the bank can accurately account for these financial products and make regular financial reports based on the obtained target option values. The accurate valuation data provided by the target valuation model can improve the accuracy and transparency of the bank's financial reports.

[0181] Application 4: Based on the target option value and the issuance scale of automatically-knocked-out structured deposits, quantify the potential risk exposure caused by market fluctuations.

[0182] The specific implementation method is as follows: through the data determination method in the embodiment of the present application, based on the target option value, combined with the issuance scale of the automatic knock-out redemption structured deposit, the potential risk exposure caused by market fluctuations is quantified. The target valuation model helps banks quantify the potential impact of market fluctuations on product portfolios, thereby formulating corresponding risk hedging strategies to ensure that the overall risk level of the bank is within a controllable range.

[0183] It should be noted that the above application scenarios are just simple examples. The data determination method in the embodiments of the present application is applicable to any application scenario that can use the data determination function, and will not be described one by one here.

[0184] Based on the same inventive concept, the present application embodiment provides a data determination device, please refer to Figure 6 , which is a schematic diagram of a data determination device 600 in an embodiment of the present application, the device comprising:

[0185] The device includes:

[0186] The data acquisition module 601 is used to acquire option related parameters corresponding to the automatic knock-out redemption structured deposit after receiving the option value acquisition instruction sent by the client, wherein the option related parameters include the knock-out yield and the guaranteed yield of the automatic knock-out redemption structured deposit, and the market data related to the observation day of the automatic knock-out redemption structured deposit;

[0187] Model acquisition module 602, used to acquire the target valuation model corresponding to the automatic knock-out redemption structured deposit, the target valuation model includes a pre-knock-out part sub-model and a non-knock-out part sub-model;

[0188] Valuation module 603, for inputting option-related parameters into a target valuation model, and determining the value of a first option under the condition that a knock-out event occurs on any observation day before option expiration based on the early knock-out part sub-model, according to the knock-out yield, market data and conditional probability rules; and determining the value of a second option under the condition that no knock-out event occurs at option expiration based on the non-knock-out part sub-model, according to the guaranteed yield, market data and conditional probability rules;

[0189] The option value sending module 604 is used to obtain the target option value of the automatic knock-out redemption structured deposit on a preset valuation date based on the first option value and the second option value, and send the target option value to the client.

[0190] This device can accurately obtain the target option value corresponding to the deposit product by obtaining the option-related parameters corresponding to the automatic knock-out redemption structured deposit and combining it with the target valuation model, which helps investors understand the value of their investment portfolio and make corresponding decisions. At the same time, this application uses an analytical solution to express the target valuation model of the automatic knock-out redemption structured deposit, which greatly improves the solution efficiency.

[0191] Optionally, the model acquisition module 602 is specifically used for:

[0192] Obtaining an initial valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the initial valuation model is used to determine, based on the preset valuation date, the risk-neutral expected value between the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day and the non-knock-out discounted returns under the condition that no knock-out event occurs until the last observation day, and using the risk-neutral expected value as the target option value;

[0193] The initial valuation model is converted into two parts, namely, the early knock-out part sub-model and the non-knock-out part sub-model; the early knock-out part sub-model is used to take the sum of the knock-out discounted benefits as the first option value, and the non-knock-out part sub-model is used to take the non-knock-out discounted benefits as the second option value;

[0194] The target valuation model is obtained by adding the early knock-out part sub-model and the non-knock-out part sub-model and calculating the risk-neutral expectation.

[0195] Optionally, the option-related parameters further include: a risk-free interest rate and a barrier value, and the market data includes the value of the underlying asset on the observation date; the valuation module 603 is specifically used for:

[0196] The risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield are input into the early knock-out part sub-model; based on the early knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield, combined with the conditional probability rule, the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day are determined, and the knock-out discounted returns are accumulated to obtain the first option value;

[0197] The risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return are input into the non-knock-out part sub-model; based on the non-knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return, in combination with the conditional probability rule, determine the non-knock-out discounted return if no knock-out event occurs until the last observation day, and use the non-knock-out discounted return as the second option value.

[0198] Optionally, the option value sending module 604 is specifically used for:

[0199] The first option value and the second option value are added together and the risk-neutral expectation is calculated to obtain the target option value.

[0200] Optionally, the option-related parameters further include: a risk-free interest rate and a barrier value, and the market data includes the value of the underlying asset on the observation date; the valuation module 603 is specifically used for:

[0201] The knock-out discounted return under the condition that a knock-out event occurs on any observation day is determined as follows:

[0202] For the i-th observation day, the knock-out discounted income corresponding to the i-th observation day is determined according to the discount factor on the i-th observation day, the annualized time of the interest-bearing interval of the i-th early maturity date, the knock-out yield and the knock-out conditional probability on the i-th observation day;

[0203] Wherein, the discount factor on the i-th observation day is determined based on the risk-free interest rate and the time difference between the i-th early maturity date and the preset valuation date;

[0204] The knock-out conditional probability on the i-th observation day represents the probability that the value of the underlying asset on the i-th observation day is not lower than the barrier value and the value of the underlying asset on any observation day before the i-th observation day is lower than the barrier value.

[0205] Optionally, the option-related parameters further include: a risk-free interest rate and a barrier value, and the market data includes the value of the underlying asset on the observation date; the valuation module 603 is specifically used for:

[0206] The un-knocked-out discounted return under the condition that no knock-out event occurs on the last observation day is determined as follows:

[0207] For the last observation day, the un-knocked discounted income corresponding to the last observation day is determined based on the discount factor on the last observation day, the annualized time of the interest-bearing interval of the last early maturity date, the guaranteed yield and the conditional probability of un-knocked out on the last observation day;

[0208] Wherein, the discount factor at the last observation date is determined based on the risk-free interest rate and the time difference between the last early maturity date and the preset valuation date;

[0209] The conditional probability of not knocking out on the last observation day represents the probability that the value of the underlying asset on each observation day is lower than the barrier value.

[0210] Optionally, the probability that the value of the underlying asset on any observation day is lower than the barrier value is determined based on the Black-Scholes option pricing model.

[0211] Optionally, the device 600 further includes:

[0212] The application module 605 is configured to perform at least one of the following operations according to the target option value of the automatic knock-out redemption structured deposit on a preset valuation date after the valuation module obtains the target option value of the automatic knock-out redemption structured deposit on a preset valuation date:

[0213] According to the target option value, combined with the historical behavior information and / or product preference information of the data requester, recommend products to the data requester;

[0214] Conduct risk analysis on the related products of the automatic knock-out redemption structured deposit according to the target option value and in combination with corresponding sensitivity indicators;

[0215] Obtaining the target option value of the automatic knock-out redemption structured deposit on each preset valuation date, and recording accounts according to each of the obtained target option values;

[0216] Based on the target option value and the issuance scale of the automatic knock-out redemption structured deposits, the potential risk exposure caused by market fluctuations is quantified.

[0217] Based on the same inventive concept, an embodiment of the present application provides an electronic device, which can implement the function of the data determination device discussed above. In one embodiment, the electronic device can be a server, such as Figure 1 In this embodiment, the structure of the electronic device can be as follows: Figure 7 As shown, it includes a memory 701 , a communication module 703 and one or more processors 702 .

[0218] The memory 701 is used to store computer programs executed by the processor 702. The memory 701 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and programs required for running the instant messaging function, etc.; the data storage area may store various instant messaging information and operation instruction sets, etc.

[0219] The memory 701 may be a volatile memory, such as a random-access memory (RAM); the memory 701 may also be a non-volatile memory, such as a read-only memory, a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); or the memory 701 may be any other medium that can be used to carry or store a desired computer program in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 701 may be a combination of the above memories.

[0220] The processor 702 may include one or more central processing units (CPU) or a digital processing unit, etc. The processor 702 is used to implement the above data determination method when calling the computer program stored in the memory 701.

[0221] The communication module 703 is used to communicate with terminal devices and other servers.

[0222] The specific connection medium between the memory 701, the communication module 703 and the processor 702 is not limited in the embodiment of the present application. Figure 7 In the embodiment, the memory 701 and the processor 702 are connected via a bus 704. The bus 704 is connected to the processor 702 via a bus 704. Figure 7 The connections between the other components are only for illustration and are not intended to be limiting. The bus 704 can be divided into an address bus, a data bus, a control bus, etc. For ease of description, Figure 7 The diagram shows that only one thick line is used, but this does not mean that there is only one bus or only one type of bus.

[0223] The memory 701 stores a computer storage medium, and the computer storage medium stores computer executable instructions, and the computer executable instructions are used to implement a video object detection method in an embodiment of the present application. The processor 702 is used to execute the above-mentioned data determination method, such as Figure 3 shown.

[0224] Based on the same inventive concept, the embodiment of the present application provides a computer-readable storage medium, and the computer program product includes: computer program code, when the computer program code is run on a computer, the computer executes any of the data determination methods discussed above. Since the principle of solving the problem by the above-mentioned computer-readable storage medium is similar to the data determination method, the implementation of the above-mentioned computer-readable storage medium can refer to the implementation of the method, and the repeated parts will not be repeated.

[0225] Based on the same inventive concept, the embodiment of the present application also provides a computer program product, which includes: computer program code, when the computer program code is run on a computer, the computer executes any of the data determination methods discussed above. Since the principle of solving the problem by the above computer program product is similar to the determination of page data, the implementation of the above computer program product can refer to the implementation of the method, and the repeated parts will not be repeated.

[0226] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0227] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0228] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0229] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of data requester operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0230] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for determining data, characterized in that: The method comprises: After receiving the option value acquisition instruction sent by the client, the option related parameters corresponding to the automatic knock-out redemption type structured deposit are acquired, wherein the option related parameters include the knock-out yield and the guaranteed yield of the automatic knock-out redemption type structured deposit, and the market data related to the observation day of the automatic knock-out redemption type structured deposit; Obtaining a target valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the target valuation model includes a pre-knock-out part sub-model and a non-knock-out part sub-model; Input the option-related parameters into the target valuation model, and determine the first option value under the condition that a knock-out event occurs on any observation day before option expiration based on the early knock-out part sub-model, according to the knock-out yield, the market data and the conditional probability rule; and determine the second option value under the condition that no knock-out event occurs at option expiration based on the non-knock-out part sub-model, according to the guaranteed yield, the market data and the conditional probability rule; Based on the first option value and the second option value, a target option value of the automatic knock-out redemption structured deposit on a preset valuation date is obtained, and the target option value is sent to the client.

2. The method according to claim 1, characterized in that The step of obtaining the target valuation model corresponding to the automatic knock-out redemption structured deposit includes: Obtaining an initial valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the initial valuation model is used to determine, based on the preset valuation date, the risk-neutral expected value between the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day and the non-knock-out discounted returns under the condition that no knock-out event occurs until the last observation day, and using the risk-neutral expected value as the target option value; The initial valuation model is converted into two parts, namely, the early knock-out part sub-model and the non-knock-out part sub-model; the early knock-out part sub-model is used to take the sum of the knock-out discounted benefits as the first option value, and the non-knock-out part sub-model is used to take the non-knock-out discounted benefits as the second option value; The target valuation model is obtained by adding the early knock-out part sub-model and the non-knock-out part sub-model and calculating the risk-neutral expectation.

3. The method according to claim 1, characterized in that The option-related parameters also include: risk-free interest rate and barrier value, and the market data includes the underlying asset value related to the observation date; The inputting of the option-related parameters into the target valuation model, determining the first option value under the condition that a knock-out event occurs on any observation day before option expiration based on the early knock-out part sub-model, according to the knock-out yield, the market data and the conditional probability rule; and determining the second option value under the condition that no knock-out event occurs at option expiration based on the non-knock-out part sub-model, according to the guaranteed yield, the market data and the conditional probability rule, including: The risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield are input into the early knock-out part sub-model; based on the early knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield, combined with the conditional probability rule, the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day are determined, and the knock-out discounted returns are accumulated to obtain the first option value; The risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return are input into the non-knock-out part sub-model; based on the non-knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return, in combination with the conditional probability rule, determine the non-knock-out discounted return if no knock-out event occurs until the last observation day, and use the non-knock-out discounted return as the second option value.

4. The method according to any one of claims 1 to 3, characterized in that: The step of obtaining the target option value of the automatic knock-out redemption structured deposit on a preset valuation date based on the first option value and the second option value includes: The first option value and the second option value are added together and the risk-neutral expectation is calculated to obtain the target option value.

5. The method according to claim 2 or 3, characterized in that: The option-related parameters also include: risk-free interest rate and barrier value, and the market data includes the value of the underlying asset on the observation day; the knock-out discounted return under the condition that a knock-out event occurs on any observation day is determined by the following method: For the i-th observation day, the knock-out discounted income corresponding to the i-th observation day is determined according to the discount factor on the i-th observation day, the annualized time of the interest-bearing interval of the i-th early maturity date, the knock-out yield and the knock-out conditional probability on the i-th observation day; Wherein, the discount factor on the i-th observation day is determined based on the risk-free interest rate and the time difference between the i-th early maturity date and the preset valuation date; The knock-out conditional probability on the i-th observation day represents the probability that the value of the underlying asset on the i-th observation day is not lower than the barrier value and the value of the underlying asset on any observation day before the i-th observation day is lower than the barrier value.

6. The method according to claim 2 or 3, characterized in that: The option-related parameters also include: risk-free interest rate and barrier value, and the market data includes the value of the underlying asset on the observation date; the un-knocked-out discounted return under the condition that no knock-out event occurs on the last observation date is determined by the following method: For the last observation day, the un-knocked discounted income corresponding to the last observation day is determined based on the discount factor on the last observation day, the annualized time of the interest-bearing interval of the last early maturity date, the guaranteed yield and the conditional probability of un-knocked out on the last observation day; Wherein, the discount factor at the last observation date is determined based on the risk-free interest rate and the time difference between the last early maturity date and the preset valuation date; The conditional probability of not knocking out on the last observation day represents the probability that the value of the underlying asset on each observation day is lower than the barrier value.

7. The method according to claim 6, characterized in that The probability that the value of the underlying asset on any observation day is lower than the barrier value is determined based on the Black-Scholes option pricing model.

8. The method according to any one of claims 1 to 3, characterized in that: After obtaining the target option value of the automatic knock-out redemption structured deposit on a preset valuation date, the method further includes: According to the target option value, at least one of the following operations is performed: According to the target option value, combined with the historical behavior information and / or product preference information of the data requester, recommend products to the data requester; Conduct risk analysis on the related products of the automatic knock-out redemption structured deposit according to the target option value and in combination with corresponding sensitivity indicators; Obtaining the target option value of the automatic knock-out redemption structured deposit on each preset valuation date, and recording accounts according to each of the obtained target option values; Based on the target option value and the issuance scale of the automatic knock-out redemption structured deposits, the potential risk exposure caused by market fluctuations is quantified.

9. A data determination device, characterized in that: The device comprises: A data acquisition module, after receiving an option value acquisition instruction sent by a client, acquires option related parameters corresponding to the automatic knock-out redemption type structured deposit, wherein the option related parameters include the knock-out yield and the guaranteed yield of the automatic knock-out redemption type structured deposit, and market data related to the observation day of the automatic knock-out redemption type structured deposit; A model acquisition module, which acquires a target valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the target valuation model includes a pre-knock-out part sub-model and a non-knock-out part sub-model; The valuation module inputs the option-related parameters into the target valuation model, and determines the first option value under the condition that a knock-out event occurs on any observation day before option expiration based on the early knock-out part sub-model, according to the knock-out yield, the market data and the conditional probability rule; and determines the second option value under the condition that no knock-out event occurs at option expiration based on the non-knock-out part sub-model, according to the guaranteed yield, the market data and the conditional probability rule; The option value sending module obtains the target option value of the automatic knock-out redemption structured deposit on a preset valuation date based on the first option value and the second option value, and sends the target option value to the client.

10. The device according to claim 9, characterized in that The model acquisition module is used for: Obtaining an initial valuation model corresponding to the automatic knock-out redemption structured deposit, wherein the initial valuation model is used to determine, based on the preset valuation date, the risk-neutral expected value between the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day and the non-knock-out discounted returns under the condition that no knock-out event occurs until the last observation day, and using the risk-neutral expected value as the target option value; The initial valuation model is converted into two parts, namely, the early knock-out part sub-model and the non-knock-out part sub-model; the early knock-out part sub-model is used to take the sum of the knock-out discounted benefits as the first option value, and the non-knock-out part sub-model is used to take the non-knock-out discounted benefits as the second option value; The target valuation model is obtained by adding the early knock-out part sub-model and the non-knock-out part sub-model and calculating the risk-neutral expectation.

11. The device according to claim 9, characterized in that The option-related parameters also include: risk-free interest rate and barrier value; the market data includes the value of the underlying asset on the observation date; the valuation module is used to: The risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield are input into the early knock-out part sub-model; based on the early knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on each observation day, and the knock-out yield, combined with the conditional probability rule, the respective knock-out discounted returns under the condition that a knock-out event occurs on each observation day are determined, and the knock-out discounted returns are accumulated to obtain the first option value; The risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return are input into the non-knock-out part sub-model; based on the non-knock-out part sub-model, according to the risk-free rate, the barrier value, the value of the underlying asset on the last observation day and the guaranteed rate of return, in combination with the conditional probability rule, determine the non-knock-out discounted return if no knock-out event occurs until the last observation day, and use the non-knock-out discounted return as the second option value.

12. The device according to any one of claims 9 to 11, characterized in that: The option value sending module is used for: The first option value and the second option value are added together and the risk-neutral expectation is calculated to obtain the target option value.

13. The device according to claim 10 or 11, characterized in that The option-related parameters also include: risk-free interest rate and barrier value, and the market data includes the value of the underlying asset related to the observation date; the valuation module is also used to determine the knock-out discounted return under the condition that a knock-out event occurs on any observation date in the following manner: For the i-th observation day, the knock-out discounted income corresponding to the i-th observation day is determined according to the discount factor on the i-th observation day, the annualized time of the interest-bearing interval of the i-th early maturity date, the knock-out yield and the knock-out conditional probability on the i-th observation day; Wherein, the discount factor on the i-th observation day is determined based on the risk-free interest rate and the time difference between the i-th early maturity date and the preset valuation date; The knock-out conditional probability on the i-th observation day represents the probability that the value of the underlying asset on the i-th observation day is not lower than the barrier value and the value of the underlying asset on any observation day before the i-th observation day is lower than the barrier value.

14. The device according to claim 10 or 11, characterized in that The option-related parameters also include: risk-free interest rate and barrier value, and the market data includes the value of the underlying asset related to the observation date; the valuation module is also used to determine the un-knocked-out discounted return under the condition that no knock-out event occurs on the last observation date by the following method: For the last observation day, the un-knocked discounted income corresponding to the last observation day is determined based on the discount factor on the last observation day, the annualized time of the interest-bearing interval of the last early maturity date, the guaranteed yield and the conditional probability of un-knocked out on the last observation day; Wherein, the discount factor at the last observation date is determined based on the risk-free interest rate and the time difference between the last early maturity date and the preset valuation date; The conditional probability of not knocking out on the last observation day represents the probability that the value of the underlying asset on each observation day is lower than the barrier value.

15. The device according to claim 14, characterized in that The probability that the value of the underlying asset on any observation day is lower than the barrier value is determined based on the Black-Scholes option pricing model.

16. The device according to any one of claims 9 to 11, characterized in that: The device also includes: The application module is configured to, after the valuation module obtains the target option value of the automatic knock-out redemption structured deposit on a preset valuation date, perform at least one of the following operations according to the target option value: According to the target option value, combined with the historical behavior information and / or product preference information of the data requester, recommend products to the data requester; Conduct risk analysis on the related products of the automatic knock-out redemption structured deposit according to the target option value and in combination with corresponding sensitivity indicators; Obtaining the target option value of the automatic knock-out redemption structured deposit on each preset valuation date, and recording accounts according to each of the obtained target option values; Based on the target option value and the issuance scale of the automatic knock-out redemption structured deposits, the potential risk exposure caused by market fluctuations is quantified.

17. An electronic device, characterized in that: include: A memory for storing program instructions; A processor is used to call the program instructions stored in the memory, and execute the steps included in any one of the methods of claims 1-8 according to the obtained program instructions.

18. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method according to any one of claims 1 to 8.

19. A computer program product, characterized in that The computer program product comprises: a computer program code, and when the computer program code is run on a computer, the computer is enabled to execute the method according to any one of claims 1 to 8.

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