Metaverse-based simulation investment game service providing device, method, and recording medium

Abstract

A metaverse-based simulation investment game service providing device according to the present invention comprises: a communication module that collects information for each stock item of a company and transmitting and receiving data to and from a user terminal; a memory that stores a program for providing a simulation investment game service on the basis of a metaverse and an application for operating the simulation investment game service on the user terminal through the program; and a processor. The processor: calculates risk information for each stock item by inputting the information for each stock item into a pre-trained first artificial intelligence algorithm as the program stored in the memory is executed; provides a match-based simulation investment game among a plurality of users as the metaverse-based simulation investment game service is operated on the application; calculates a simulation investment betting amount of users participating in the simulation investment game in response to a result of the simulation investment game; and collects, on the application, information about the activities of the users participating in the simulation investment game via the communication module, and then inputs the collected information about user activities to a pre-trained second artificial intelligence algorithm to generate and provide hyper-personalized stock portfolio recommendation information.

Description

Device, method, and recording medium for providing a metaverse-based simulated investment game service

[0001] The present invention relates to a device, method, and recording medium for providing a metaverse-based simulated investment game service.

[0002] With the recent rise in personal interest in stock investment, many people are installing stock trading programs and jumping into the market. These newcomers, unfamiliar with stock trading programs, often use simulated investment services to avoid potential trading mistakes and gain more investment experience.

[0003] However, conventional mock investment services operated with a uniform structure that relied solely on individual returns and profits, making it difficult to maintain user concentration and interest, which ultimately led to insufficient stock investment practice.

[0004] Furthermore, existing mock investment services failed to provide personalized investment decisions because they did not take into account the individual tendencies of users at all. Furthermore, while users were exposed to a variety of data and information, it was extremely difficult to effectively analyze and apply this information.

[0005] Moreover, conventional mock investment services have limited investment education and decision-making support for users, lack experience and knowledge sharing among users, and have difficulty making investment decisions that reflect diverse perspectives.

[0006] An embodiment of the present invention provides a metaverse-based mock investment game service providing device, method, and recording medium that increases users' participation, experience, interest, and excitement in mock investment by providing a mock investment service based on existing rates of return or profits as a mock investment game based on competition between multiple users, thereby enhancing their understanding of stock investment and making it easier to conduct actual stock investment.

[0007] However, the technical task that this embodiment seeks to achieve is not limited to the technical task described above, and other technical tasks may exist.

[0008] As a technical means for achieving the above-described technical task, a metaverse-based mock investment game service providing device according to a first aspect of the present invention comprises a memory in which a program for providing a metaverse-based, competition-based mock investment game service and an application for operating the mock investment game service on a user terminal through the program are stored, and a program stored in the memory is executed, thereby collecting and storing information on each stock item of a company and inputting it into a first artificial intelligence algorithm that has been learned in advance to calculate risk information on each stock item, and providing a mock investment game between multiple users as the mock investment game service is operated on the application, and calculating and settling the rate of return and the betting amount based on the mock investment betting amount of users who participated in the mock investment game and the stocks selected by the users in accordance with the results of the mock investment game, and inputting user activity information including a competition tendency, a game type, a stock item search history, a number of stock item selections, a user active time on a specific stock item screen, a preference for a specific stock item, and trading information, and the risk level on each stock item into a second artificial intelligence algorithm that has been learned in advance to generate user tendency information, and generating and providing stock portfolio recommendation information based on the similarity with the activity information and tendency information of other users. Includes processor.

[0009] In some embodiments of the present invention, the processor may provide virtual simulated investment funds that can be charged and used to buy and sell stocks to participating users through in-app payment when the simulated investment game first starts, and may match matches between users who have formed a list of competing stocks using stocks traded using the simulated investment funds among the stocks included in the collected stock information, and may settle the simulated investment betting amount from the simulated investment funds in accordance with the result of the simulated investment game when the matched match is completed.

[0010] In some embodiments of the present invention, the processor may provide information on the stock list of other users among the users with whom the match has been completed as the match is completed.

[0011] In some embodiments of the present invention, the processor may provide correlation values ​​and beta values ​​between stocks included in the configured list of stocks based on the risk level of each stock.

[0012] In some embodiments of the present invention, the processor may provide an educational program to a user who has lost a daily mock investment game by having the user's avatar participate in a lecture space configured within the metaverse space.

[0013] In some embodiments of the present invention, the processor may perform the matchmaking for users participating in the metaverse space and provide marketing information of a securities company to a predetermined area within the metaverse space.

[0014] In addition, a method for providing a metaverse-based mock investment game service according to a second aspect of the present invention includes the steps of collecting and storing information on each stock item of a company; transmitting the collected information on each stock item to a user terminal; inputting the collected information on each stock item into a first artificial intelligence algorithm that has been previously learned to calculate risk information on each stock item; providing a mock investment game between multiple users as a metaverse-based match-based mock investment game service operates on an application of a user terminal; calculating and settling the rate of return and the betting amount based on the mock investment betting amounts of users who participated in the mock investment game and the stocks selected by the users in accordance with the results of the mock investment game; and inputting user activity information including match tendencies, game types, stock search records, number of stock selections, user active time on a specific stock screen, preferences for specific stock items, and trading information, and the risk information on each stock item, into a second artificial intelligence algorithm that has been previously learned to generate user tendency information, and generating and providing stock portfolio recommendation information based on the similarity with the activity information and tendency information of other users.

[0015] In addition, other methods for implementing the present invention, other systems, and computer-readable recording media recording a computer program for executing the above methods may be further provided.

[0016] That is, a computer-readable recording medium storing a computer program including a sequence of commands for execution according to the third aspect of the present invention collects and stores information on each stock item of a company, transmits the collected information on each stock item to a user terminal, inputs the collected information on each stock item into a first artificial intelligence algorithm that has been learned in advance to calculate risk information on each stock item, and as a metaverse-based, competition-based mock investment game service is operated on an application of a user terminal, a mock investment game is provided between multiple users, and, corresponding to the results of the mock investment game, the rate of return and the betting amount are calculated and settled based on the mock investment betting amounts of users who participated in the mock investment game and the stocks selected by the users, and user activity information including competition tendencies, game types, stock search records, number of stock selections, user active time on a specific stock screen, preferences for specific stock items, and trading information, and the risk information on each stock item are input into a second artificial intelligence algorithm that has been learned in advance to generate user tendency information, and stock portfolio recommendation information is generated and provided based on the similarity with the activity information and tendency information of other users.

[0017] According to one embodiment of the present invention described above, a customized investment portfolio can be provided for simulated investment by systematically analyzing a user's stock investment activities and tendencies, thereby enabling investors to develop investment strategies that suit their individual tendencies and goals and make effective investment decisions.

[0018] In particular, by providing a metaverse-based mock investment service, multiple users can participate simultaneously. By forming individuals or teams to play a competitive mock investment game, users can increase and sustain their interest and focus. Furthermore, it can facilitate the sharing of experiences and knowledge among users and support investment decisions that reflect diverse perspectives.

[0019] Additionally, by analyzing various stock-related information through artificial intelligence algorithms and recommending stock portfolios based on user activity, it enables effective analysis and decision-making even in environments where users are exposed to a vast amount of stock-related information and data.

[0020] Moreover, one embodiment of the present invention provides education and training to investors, so that simulated investment does not remain merely a reckless game, but rather users can be encouraged to play simulated investment games and take training courses to improve their knowledge of the capital markets.

[0021] The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0022] FIG. 1 is a diagram illustrating a metaverse-based simulated investment game service provision system according to one embodiment of the present invention.

[0023] FIG. 2 is a block diagram of a metaverse-based simulated investment game service providing device according to one embodiment of the present invention.

[0024] FIG. 3 is a diagram for explaining a first artificial intelligence algorithm according to one embodiment of the present invention.

[0025] FIG. 4 is a diagram for explaining a second artificial intelligence algorithm according to one embodiment of the present invention.

[0026] Figure 5 is a flowchart of a method for providing a metaverse-based simulated investment game service according to one embodiment of the present invention.

[0027] The advantages and features of the present invention, and the methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided solely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the present invention, and the present invention is defined solely by the scope of the claims.

[0028] The terminology used herein is for the purpose of describing embodiments only and is not intended to limit the present invention. In this specification, the singular also includes the plural unless specifically stated otherwise. As used herein, the terms "comprises" and / or "comprising" do not exclude the presence or addition of one or more other components in addition to the mentioned components. Like reference numerals refer to like components throughout the specification, and "and / or" includes each and any combination of one or more of the mentioned components. Although "first", "second", etc. are used to describe various components, these components are not limited by these terms. These terms are only used to distinguish one component from another. Therefore, it should be understood that a first component mentioned below may also be a second component within the technical spirit of the present invention.

[0029] Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used in their common sense to those skilled in the art to which the present invention pertains. Furthermore, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0030] Hereinafter, with reference to the attached drawings, a metaverse-based simulated investment game service providing device (100) and method according to an embodiment of the present invention will be described in detail.

[0031] FIG. 1 is a diagram illustrating a metaverse-based simulated investment game service provision system (1) according to one embodiment of the present invention.

[0032] As illustrated in FIG. 1, the present invention includes a metaverse-based simulated investment game service providing device (100) and a plurality of user terminals (200) that are entities performing the simulated investment game service.

[0033] At this time, each component constituting the metaverse-based simulated investment game service provision system (1) illustrated in FIG. 1 can be connected via a network. The network refers to a connection structure that enables information exchange between each node, such as terminals and servers (100), and examples of such networks include, but are not limited to, a 3GPP (3rd Generation Partnership Project) network, an LTE (Long Term Evolution) network, a WIMAX (World Interoperability for Microwave Access) network, the Internet, a LAN (Local Area Network), a Wireless LAN (Wireless Local Area Network), a WAN (Wide Area Network), a PAN (Personal Area Network), a Bluetooth network, a satellite broadcasting network, an analog broadcasting network, a DMB (Digital Multimedia Broadcasting) network, and WiFi.

[0034] Multiple user terminals (200) are terminals that install an application provided by a simulated investment game service providing device (100) and perform a simulated investment game service corresponding to the present invention through the application. These user terminals (200) correspond to user terminals (200) that register as members through the application, create avatars, and have the authority to manipulate avatars within the metaverse space.

[0035] The user terminal (200) may be a general PC, a smart terminal, etc., and depending on the user's device status, equipment such as an HMD may be operated together or independently.

[0036] Meanwhile, the metaverse space where the simulated investment game described in the present invention is performed may be provided as a complete component of the metaverse world, or as a partial component. For example, "provided as a complete component" means that the user terminal (200) is configured solely with a space for the simulated investment game service. Conversely, "provided as a partial component" means that the metaverse world is provided with not only a space for the simulated investment game service but also virtual objects such as virtual buildings, schools, and travel destinations.

[0037] In one embodiment of the present invention, the metaverse space is implemented, for example, with a stock market street as the backdrop. Buildings, specific exterior walls, banners, and other elements within the metaverse space can be utilized to market specific products of a company (general or securities firm, etc.) to users. Specifically, one embodiment of the present invention may be implemented in the form of a simulated investment game service provided through a securities firm's application. In this case, the marketing information may include advertising information for opening a securities account or subscribing to financial products.

[0038] Within the metaverse, various game elements can be implemented, such as users acquiring items or completing quests through avatar manipulation. Furthermore, corporate marketing elements can be incorporated, such as users being able to obtain corporate IR materials through avatar manipulation within the metaverse.

[0039] In addition, one embodiment of the present invention can provide a hyper-personalized metaverse space. In one embodiment, the server (100) can calculate area information of the metaverse space and divide the entire space into preset areas according to the provided functions. For example, the preset areas may correspond to an advertisement area, a stock information provision area, a news area, etc. Then, the server (100) can differentially allocate and apply an advertisement area, a stock information provision area, and a news area corresponding to the stock based on the proportion of the stock included in each user's current stock portfolio (the number of displayed information or the size of the displayed information) to the metaverse space.

[0040] In this case, one embodiment of the present invention may set a maximum number of deployable information items and a minimum number of deployable information items for each preset area. For example, in the case of a stock information provision area, the maximum number of deployable information items refers to the maximum number of displayable information items based on their respective weights in the number of stocks included in the user's stock portfolio. Conversely, the minimum number of deployable information items may be set to the number of stocks included in the user's stock portfolio.

[0041] Figure 2 is a block diagram of a metaverse-based simulated investment game service providing device (100) according to one embodiment of the present invention.

[0042] A metaverse-based simulated investment game service providing device (100) according to one embodiment of the present invention includes a communication module (110), a memory (120), and a processor (130).

[0043] The communication module (110) collects information on each stock item of a company, transmits and receives data with multiple user terminals (200), and provides an application for operating a mock investment game service with multiple user terminals (200).

[0044] In the memory (120), a program for providing a simulated investment game service based on the metaverse and an application for operating the simulated investment game service on a user terminal (200) through the program are stored.

[0045] The processor (130) operates a simulated investment game service based on multiple artificial intelligence algorithms by executing a program stored in the memory (120). At this time, the processor (130) may functionally include a collection module and a settlement module.

[0046] Specifically, the processor (130) collects information on a company's stock items via a collection module via the communication module (110) and stores it in memory. The processor (130) can collect information on various stocks listed on the stock market, and preferably, information on stocks targeted for the simulated investment game service rather than all stocks. The company's stock-specific information collected here may include financial statements, high-frequency transaction information, bonds, notes, and news data.

[0047] Information on a company's stock items can be collected by utilizing data provided by data providing entities such as Dart (Korea Electronic Disclosure System), KRX (Korea Exchange), and KIND (Korea Financial Investment Association) in Korea, for example. Various methods can be applied for data collection, such as web crawling and extraction through API.

[0048] For example, in the case of financial statements, which are the most crucial data, the processor (130) monitors the site for public disclosure data based on market measures at a predetermined interval (from as short as 1 minute to as long as 5 minutes) so that all relevant information can be collected immediately when new public disclosure data is updated. In this case, financial statements can be collected through an international standard computer language based on XBRL (eXtensible Business Reporting Language).

[0049] Meanwhile, not all listed stocks submit reports on a single date and time. To achieve this, the processor (130) can collect reports for a specific company for a specific month, tailored to each company's fiscal year. Furthermore, the processor (130) can collect non-numerical data, such as footnotes, as information for each stock.

[0050] The processor (130) can simultaneously collect and refine information on a company's stocks, and extract data for artificial intelligence algorithm learning and judgment. In other words, the processor (130) can verify the validity of the data and process the information on each stock into an analyzable form.

[0051] Next, the processor (130) can input stock-specific information into a pre-trained first artificial intelligence algorithm to produce risk information for each stock. Figure 3 is a diagram illustrating the first artificial intelligence algorithm according to one embodiment of the present invention. While the present invention is described for convenience as one first artificial intelligence algorithm outputting risk information for each stock, this is not necessarily limited to this. Preferably, the first artificial intelligence algorithm may be configured as a combination of artificial neural networks that output each of the five risk levels described below, excluding the final risk level.

[0052] As an example, risk information for each stock may include risks related to financial statements, risks related to high-frequency transactions, risks related to corporate bonds, risks based on corporate unstructured data, risks based on news and social media, and a final risk calculated by ensembling these.

[0053] Here, the financial statement risk is a numerical value that analyzes the financial statement data of a listed company and quantifies the company's financial health and stability. Financial statements may include the company's financial status, income statement, and cash flow statement, and the financial statement risk can reflect the company's financial risk.

[0054] The risk associated with high-frequency trading is a value that evaluates the trading pattern and volatility of a stock by analyzing high-frequency trading data. High-frequency trading here means rapid trading in the stock market.

[0055] Bond risk is a value that evaluates the risk of a stock in the bond market, and can be calculated by analyzing data related to credit ratings and interest rates in the bond market, for example.

[0056] Risk based on unstructured data is a value that analyzes unstructured data, such as a company's publicly disclosed annotation data, to detect and evaluate special information or events related to the stock. Annotation data provides detailed information related to financial statements, allowing for the identification of potential risk factors.

[0057] Risk indexes, such as news and social media, are values ​​that analyze news and social media data to detect and evaluate news, issues, and sentiment related to a stock. They can be used to assess risks based on market sentiment and external factors.

[0058] The final risk is calculated by ensembling the five risk levels described above. The processor (130) can calculate the final risk by averaging (so-called "Soft Voting") or weighting (so-called "Weighted Voting") the determined risks. Furthermore, rather than ensembling all five risk levels, the processor (130) can ensemble only the risks corresponding to the items selected by each user and provide the final risk level. This can be a crucial element in constructing a hyper-personalized portfolio.

[0059] Meanwhile, the processor (130) can provide additional information along with risk information for each stock item. This information may include the stock code and name, which are unique identifiers for each stock, as well as six risk information items, along with scores, rankings, and grades for each stock calculated based on these information. Furthermore, a loan availability value calculated using a preset threshold value to determine the riskiness of the stock may be provided. Furthermore, various corporate information (such as corporate information related to the stock, management status, stock price trends, and economic environment) may be provided as well.

[0060] Thereafter, as the metaverse-based mock investment game service is operated through an application on the user terminal (200), the processor (130) provides a mock investment game based on competition between multiple users. In addition, the processor (130) transmits the mock investment betting amounts and the user's selected stocks of the users who participated in the mock investment game corresponding to the results of the mock investment game to the collection module and stores them in memory, and calculates the rate of return and the betting amount through the settlement module based on the mock investment betting amounts and the user's selected stocks stored in the memory.

[0061] Traditionally, simulated investment systems operated by individuals independently accessing a simulated investment server and simulating investments using stock market data. Each individual investor logged in with their own account and managed their own investment decisions and portfolio. Typically, data and screens similar to those found in the real stock market were provided, allowing users to simulate stock trading and test investment strategies. This traditional approach allowed individual investors to gain experience with the stock market and improve their investment skills.

[0062] In contrast, one embodiment of the present invention differs significantly from existing mock investments in that it conducts mock investments through a metaverse-based mock investment game. Unlike existing mock investments, one embodiment of the present invention allows multiple users to gather in a virtual metaverse space to engage in mock investments. Users can engage in stock trading games with other investors within the metaverse space. For example, the metaverse space could simulate an environment similar to a stock exchange.

[0063] Furthermore, unlike existing simulated investment models, one embodiment of the present invention allows for multi-participation, enabling multiple users to select stocks and engage in simulated investment not only in 1:1 ratios but also in 1:2, 2:2, and even N:M ratios (where N and M are natural numbers). This enables cooperative and competitive investment, allowing users to select stocks together, share the results, and enjoy making and competing investment decisions together.

[0064] In this way, while existing mock investments primarily focus on individual learning and training, one embodiment of the present invention is provided as a metaverse-based mock investment game, thereby providing an experience in which multiple users can participate and enjoy together as a cooperative and competitive investment game.

[0065] To provide this simulated investment game, the processor (130) provides virtual simulated investment funds to participating users upon the game's initial launch. For example, the simulated investment funds may be paid in the form of virtual cyber money (or coins) worth approximately KRW 100 million. The simulated investment funds can be recharged through In&Pay, and users can buy and sell stocks using the funds. This stock trading takes place within the simulated investment game, allowing users to select stocks and trade them using the simulated investment funds.

[0066] Users who receive simulated investment funds can participate in simulated investment games through matchmaking with other users. Users can use the simulated investment funds to buy and sell stocks within a given stock category, creating a list of competing stocks. "Predetermined stocks" here refer to stocks included in the stock-specific information collected by the processor (130).

[0067] The processor (130) matches users who have created a list of competing stocks for the simulated investment game. Users who have been matched can wager a certain amount of money in the match and compete against other users (or teams) for profitability. Upon completion of the match, the processor (130) calculates the simulated investment betting amount from the simulated investment fund, corresponding to the outcome of the simulated investment game. In other words, in the simulated investment game, a user can win the betting amount of another user. This is reflected in the user's simulated investment fund, allowing the user to trade stocks for the next match with the updated simulated investment fund.

[0068] At this time, matched matches can be played over a specified time period. An example of a specified time period is the daily stock trading hours, but this is not necessarily limited to this. If a match is matched over a shorter sub-time period, the betting amount may be automatically set in proportion to the sub-time period.

[0069] When a match is completed after a unit time or a detailed unit time, the processor (130) may recommend a stock portfolio for the next unit time based on the match results. Specifically, the processor may recommend a stock portfolio for the next unit time based on the stock portfolio information applied in the match, the user's activity information (trading, stop-loss, search history, etc.) during the match, and risk information for each stock item corresponding to the stock portfolio information. At this time, the processor (130) may recommend a stock portfolio for the next unit time if the result of the simulated investment betting amount settlement based on the match results in the previous unit time is lower than the result of reflecting the average settlement amount for all users in the unit time.

[0070] Furthermore, unlike existing simulated investment games, one embodiment of the present invention reflects the combined profits and combined returns earned through users' stock trading activities in the rankings, allowing users to check their performance within the simulated investment game. Furthermore, the amount of virtual simulated investment funds held by users also affects the rankings, as do the number of wins and losses in matches against other users within the simulated investment game. These factors are each assigned a predetermined weighting factor and conversion coefficient to be applied to the rankings.

[0071] In one embodiment, when a match is completed, the processor (130) may provide one of the users with whom the match was successfully completed with information about the other user's stock list. This so-called "peeking" function allows other users to view information related to the stocks they selected within the game. This function is intended to enhance competition and strategy within the simulated investment game. Users can check which stocks other users have selected and achieved, and use this information to adjust their own investment strategies (portfolios) or to reference the experiences of other users.

[0072] Additionally, in one embodiment of the present invention, the processor (130) may provide correlation values ​​and beta values ​​among stocks included in a list of Daejeon stocks constructed by a user based on the risk level of each stock output by the first artificial intelligence algorithm. The correlation value is a numerical representation of the result of interactions between stocks selected by the user, and may provide information on how to combine various stocks when constructing a portfolio. Furthermore, the beta value indicates the relative stock price movement relative to the general market index and is related to the sensitivity of the stock. Therefore, the user may check the beta value and use it as a reference for risk management and portfolio optimization.

[0073] Meanwhile, some users may exhaust their initial simulated investment funds. In this case, the processor (130) may provide an educational program by having a target user participate in a lecture space within the metaverse space using their avatar. The target user may be a user who has lost a daily simulated investment game or has exhausted all of their simulated investment funds. Alternatively, if the processor (130) determines that a user is losing or experiencing difficulties in the return game, the processor may require the user to attend this training. The lectures include learning tools such as problem-solving and quizzes, allowing the user to enhance their understanding of the capital market. In this case, unconditional participation in the training may reduce users' interest in the game. Therefore, users who complete the lectures may be provided with a certain incentive (simulated investment funds, a certificate of completion for financial product investment, etc.).

[0074] Thereafter, the processor (130) collects user activity information on the application of users participating in the mock investment game via the communication module (110), and then inputs the information into a pre-learned second artificial intelligence algorithm to generate hyper-personalized stock portfolio recommendation information and provides it to the user terminal (200). Fig. 4 is a diagram illustrating the second artificial intelligence algorithm according to one embodiment of the present invention.

[0075] Specifically, the processor (130) may collect user activity information including stock search history, number of stock selections, user active time on a specific stock screen, preference and trading information for a specific stock, game tendencies (match tendencies, game types, etc.) related to stock investment risk, betting amount, stock selection and ratio information, etc. In addition, the processor (130) inputs the collected user activity information and the risk level for each stock outputted by the first artificial intelligence algorithm into the second artificial intelligence algorithm. User tendency information is generated as an output corresponding to this input, and the user tendency information may reflect the user's investment tendencies, preferences, behavioral patterns, etc. For example, the user's performance when playing a 1:1, 1:2, 1:3, etc. simulated investment game can be analyzed to determine the user's win / loss rate and tendency. In the case of 1:1, the win / loss rate is 50%, but in the case of 1:2, the win / loss rate is 33.3%, and in the case of 1:3, the win / loss rate gradually decreases to 25%. However, since multiple people are betting, the potential profits can be doubled. Furthermore, a user's risk appetite can be identified through factors such as stock selection frequency, preferences for stock price fluctuations, and stop-loss timing. Thus, one embodiment of the present invention can understand a user's individual tendencies and investment style based on this data and analysis results.

[0076] In one embodiment, a user's propensity information is compared and analyzed with similarity information from other users' activity and propensity information to generate and output stock portfolio recommendations. Collaborative filtering can be applied to analyze similarity with other users. For example, after detecting other users with similar patterns, behaviors, or preferences to the user, recommended stocks can be extracted by comparing investment options between the user and other users.

[0077] Alternatively, other stocks similar to the user's preferred stocks can be recommended. For example, a content-based filtering technique can be applied to determine recommended stocks based on the assumption that if a user likes stock A, they are likely to also like stock B. Similarity measurement techniques, such as the Euclidean distance law and the cosine law, can be utilized to select and present stocks with the closest similarity to the user.

[0078] The stock portfolio recommendation information generated in this way suggests stocks and weightings tailored to the user's preferences, helping them construct a portfolio that meets their specific needs and goals.

[0079] In a series of processes, the processor (130) can collect data of each and every user, store the result values ​​output through each artificial intelligence algorithm, and transmit the original data to the company or output it in a report format of a predetermined format.

[0080] Meanwhile, the processor (130) can count the user's active time on the aforementioned specific stock item screen through the output screen on the application of the user terminal (200). Furthermore, for more specific counting of the active time, one embodiment of the present invention can count based on the time the user gazes at the user terminal (200).

[0081] Specifically, the processor (130) can acquire the user's gaze information by operating the camera at preset intervals through the application of the user terminal (200) and count the active time based on this. In this case, it is preferable to apply when information on a single item is displayed on the screen of the user terminal (200). If multiple items are displayed simultaneously, the processor (130) can acquire gaze coordinate information corresponding to the location where the user is looking through the application. In addition, the processor (130) can accurately determine whether the user is looking at a specific item among the entire area (item and other areas) displayed on the screen through the gaze coordinate information and count the active time for this.

[0082] In this case, if the user's attention span is too short, it can be judged as a coincidental user action. Therefore, a minimum attention span that the user must observe for a certain period of time can be set, and this minimum attention span can be set variably. The minimum attention span can be set to a time corresponding to a predetermined lower grade after attention span is graded based on the average attention span of all users.

[0083] Hereinafter, a method performed by a metaverse-based simulated investment game service providing device (100) according to one embodiment of the present invention will be described with reference to FIG. 5.

[0084] Figure 5 is a flowchart of a method for providing a metaverse-based simulated investment game service according to one embodiment of the present invention.

[0085] First, when information on each stock item of a company is collected (S110), the collected information on each stock item is transmitted to the user terminal (S120).

[0086] Next, the collected stock price information is input into the pre-learned first artificial intelligence algorithm to produce risk information for each stock item (S130).

[0087] Next, as the metaverse-based mock investment game service operates on the application of the user terminal (200), a mock investment game based on competition between multiple users is provided (S140), and the mock investment betting amount of users who participated in the mock investment game and the items selected by the users are transmitted to the collection module and stored in the memory in accordance with the result of the mock investment game (S150).

[0088] Next, the settlement module calculates the rate of return and betting amount based on the simulated investment betting amount stored in the memory and the user's selected stock (S160).

[0089] Next, user activity information on the application of users who participated in the mock investment game is collected (S170), and the collected user activity information is input into a pre-learned second artificial intelligence algorithm to generate and provide hyper-personalized stock portfolio recommendation information (S180).

[0090] Meanwhile, in the above description, steps S110 to S180 may be further divided into additional steps or combined into fewer steps, depending on the implementation of the present invention. Furthermore, some steps may be omitted as needed, and the order of steps may be changed. Furthermore, even if other details are omitted, the contents of FIGS. 1 to 4 may also be applied to the method for providing a metaverse-based simulated investment game service of FIG. 5.

[0091] The method for providing a metaverse-based simulation investment game service according to one embodiment of the present invention described above can be implemented as a program (or application) to be executed in combination with a computer as hardware and stored in a medium.

[0092] The above-described program may include codes coded in a computer language, such as C, C++, JAVA, JavaScript, Ruby, Python, or machine language, that can be read by the processor (CPU) of the computer through the device interface of the computer, so that the computer reads the program and executes the methods implemented as a program. Such codes may include functional codes related to functions that define functions necessary to execute the methods, and may include control codes related to execution procedures necessary for the processor of the computer to execute the functions according to a predetermined procedure. In addition, such codes may further include memory reference-related codes regarding which location (address address) of the internal or external memory of the computer should reference additional information or media necessary for the processor of the computer to execute the functions. In addition, if the processor of the computer needs to communicate with any other computer or server located remotely in order to execute the functions, the code may further include communication-related code regarding how to communicate with any other computer or server located remotely using the communication module of the computer, and what information or media to send and receive during communication.

[0093] The above storage medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specifically, examples of the storage medium include, but are not limited to, ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage device. That is, the program can be stored in various recording media on various servers that the computer can access or in various recording media on the user's computer. In addition, the medium can be distributed across network-connected computer systems, so that computer-readable code can be stored in a distributed manner.

[0094] The foregoing description of the present invention is for illustrative purposes only, and those skilled in the art will readily appreciate that the present invention can be readily modified into other specific forms without altering the technical spirit or essential characteristics of the present invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single entity may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined manner.

[0095] The scope of the present invention is indicated by the claims described below rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention.

Claims

1. A program for providing a simulation investment game service based on the metaverse and a memory in which an application for operating the simulation investment game service on a user terminal through the program is stored. By executing the program stored in the above memory, information on each stock item of the company is collected and stored and input into the first artificial intelligence algorithm that has been learned in advance to produce information on the risk level of each stock item. As the above-mentioned mock investment game service operates on the application, it provides a mock investment game between multiple users, and calculates and settles the rate of return and betting amount based on the mock investment betting amount of users who participated in the mock investment game and the items selected by the users in accordance with the results of the mock investment game. A processor that inputs user activity information including game tendencies, game types, stock search history, number of stock selections, user active time on a specific stock screen, preferences for specific stocks, and trading information, and the risk level for each stock into a pre-learned second artificial intelligence algorithm to generate user tendency information and generate and provide stock portfolio recommendation information based on the similarity with activity information and tendency information of other users. A device that provides a metaverse-based simulated investment game service.

2. In paragraph 1, The above processor provides virtual mock investment funds that can be charged and used to trade stocks through in-app payments to participating users when the mock investment game first starts. A match is made between users who have created a list of stocks to be traded using the simulated investment funds among the stocks included in the collected stock information, and when the match is completed, the simulated investment betting amount is settled from the simulated investment funds to correspond to the result of the simulated investment game. A device that provides a metaverse-based simulated investment game service.

3. In paragraph 2, The above processor provides information on the stock list of other users among the users whose match was completed upon completion of the match. A device that provides a metaverse-based simulated investment game service.

4. In paragraph 2, The above processor provides correlation values ​​and beta values ​​between stocks included in the above-constructed Daejeon stock list based on the risk level of each stock. A device that provides a metaverse-based simulated investment game service.

5. In paragraph 2, The above processor provides an educational program by having the user's avatar participate in a lecture space configured within the metaverse space for users who have lost in the daily mock investment game. A device that provides a metaverse-based simulated investment game service.

6. In paragraph 2, The above processor is configured to match users participating in the metaverse space with each other and to provide marketing information of securities companies to a specific area within the metaverse space. A device that provides a metaverse-based simulated investment game service.

7. In a method performed by a computer, A step of collecting and storing information on each stock item of a company; A step of transmitting the collected stock information to a user terminal; A step of inputting the collected stock information into a pre-learned first artificial intelligence algorithm to produce risk information for each stock; A step of providing a mock investment game between multiple users by operating a metaverse-based, battle-based mock investment game service on an application of a user terminal; A step of calculating and settling the rate of return and betting amount based on the simulated investment betting amount of users who participated in the simulated investment game and the items selected by the users in accordance with the results of the simulated investment game; and A step of inputting user activity information including competition tendency, game type, stock search history, number of stock selections, user active time on a specific stock screen, preference and trading information for a specific stock, and risk information for each stock into a pre-learned second artificial intelligence algorithm to generate user tendency information and generating and providing stock portfolio recommendation information based on the similarity with activity information and tendency information of other users. Method for providing a metaverse-based simulated investment game service.

8. A computer-readable recording medium storing a computer program including a sequence of commands for execution, Collects and stores information on each stock item of a company, transmits the collected information on each stock item to a user terminal, and inputs the collected information on each stock item into a first artificial intelligence algorithm that has been learned in advance to calculate risk information on each stock item. As the metaverse-based battle-based mock investment game service operates on the user terminal application, it provides a mock investment game between multiple users, and calculates and settles the rate of return and the betting amount based on the mock investment betting amount of the users who participated in the mock investment game and the items selected by the users in accordance with the results of the mock investment game. User activity information including competition tendency, game type, stock search history, number of stock selections, user active time on a specific stock screen, preference for a specific stock and trading information, and risk information for each stock are input into a pre-learned second artificial intelligence algorithm to generate user tendency information and generate and provide stock portfolio recommendation information based on the similarity with activity information and tendency information of other users. A computer-readable recording medium on which a computer program is stored.

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