System and method for providing investment operation information based on emotion

Abstract

A method for providing sentiment-based investment management information is disclosed. The method for providing sentiment-based investment management information according to the present invention comprises: a step of collecting sentiment information for a plurality of investors; a step of clustering the plurality of investors based on the sentiment information; and a step of generating and providing trader recommendation information for at least one investor among the clustered investors.

Description

Technology Field

[0001] The present invention relates to a system and method for providing sentiment-based investment operation information. Background Technology

[0003] Generally, in the trading market, individual investors lack the time to focus on information gathering and investment-related activities, as well as investment strategies, compared to professional investors; therefore, they receive relevant information to assist with their investments or entrust their asset management to traders.

[0004] In investment, a trader refers to a dealer who manages assets by executing investments using financial investment instruments such as stocks, futures, and options. Traders may receive a certain percentage of the total profits as an incentive.

[0005] Individual investors can choose a trader instead of planning and executing an investment strategy. Generally, quantitative indicators regarding a trader's past investment data, such as returns and risk levels, are provided as relevant indicator information and serve as criteria for selection.

[0006] However, with conventional methods of providing trader information, it is difficult for individual investors to select traders that reflect their own tendencies or psychological characteristics. While it is possible to choose investment styles such as high-risk, high-return or low-risk, low-return, this is a very limited range of choices that makes it difficult to reflect the diverse tendencies of investors. The problem to be solved

[0008] The technical problem that the present invention aims to solve is to provide a sentiment-based investment management information provision system and method capable of providing more personalized and customized investment information by recommending traders and managing investment operations based on the sentiment of a group including investors. means of solving the problem

[0010] To solve the above technical problem, a method for providing sentiment-based investment operation information according to an embodiment of the present invention comprises: a step of collecting sentiment information for a plurality of investors; a step of clustering the plurality of investors based on the sentiment information; and a step of generating and providing trader recommendation information for at least one investor among the clustered investors; wherein the recommendation information may be generated based on association information between the clustered investor group to which the investor to whom the recommendation information is to be provided belongs and the trader.

[0011] To solve the above technical problem, a method for providing sentiment-based investment operation information according to an embodiment of the present invention comprises: a step of collecting sentiment information for a plurality of investors; a step of collecting sentiment information for a plurality of traders; a step of clustering the plurality of investors and the plurality of traders together based on the sentiment information; and a step of generating and providing trader recommendation information for at least one investor among the clustered investors; wherein the recommendation information may include information on at least one trader among the traders belonging to the clustered group to which the investor to whom the recommendation information is to be provided belongs.

[0012] In one embodiment of the present invention, the emotional information may be time-series emotional state information classified into happiness, sadness, surprise, anger, disgust, and fear.

[0013] In one embodiment of the present invention, the emotional information may be information in which any one of heart rate, step count, respiration, body temperature, sleep time, and oxygen saturation is recorded together with the time of viewing investment-related content.

[0014] In one embodiment of the present invention, the sentiment information may be reaction information regarding positive and negative sentiments toward investment-related content.

[0015] In one embodiment of the present invention, the method further comprises an investment management step for at least one of the investor and the trader; wherein the investment management step may include a biometric information collection step for any one of the investor and the trader as a management target; and a step of generating and outputting a warning message information when any one of the biometric information satisfies a preset abnormality criterion.

[0016] In one embodiment of the present invention, the method further comprises an investment management step for at least one of the investor and the trader; wherein the investment management step may include a biometric information collection step for any one of the investor and the trader as a management target; and a step of restricting investment-related decisions of the management target when any one of the biometric information satisfies a preset ideal standard.

[0017] To solve the above technical problem, an emotion-based investment operation information providing system according to an embodiment of the present invention comprises: a storage unit in which emotion information regarding a plurality of investors is collected and recorded; a communication unit; and a control unit that controls the storage unit and the communication unit. The control unit clusters the plurality of investors based on the emotion information and generates trader recommendation information for at least one investor among the clustered investors and transmits it to the investor terminal. The recommendation information may be generated based on association information between the clustered investor group to which the investor to whom the recommendation information is to be provided belongs and the trader.

[0018] In one embodiment of the present invention, a first biometric device for collecting biometric information of the investor; and a first AI speaker for generating and outputting warning message information when any one of the biometric information satisfies a preset abnormality criterion may be included. Effects of the invention

[0020] The present invention has the effect of providing more personalized and customized investment information by recommending traders and managing investment operations based on the sentiments of a group including investors.

[0021] The present invention has the effect of managing the emotions of investors or traders during the investment management stage to induce them to make rational choices. Brief explanation of the drawing

[0023] FIG. 1 shows an emotion-based investment operation information provision system according to an embodiment of the present invention. FIG. 2 illustrates a method for providing sentiment-based investment operation information according to an embodiment of the present invention. Figure 3 shows in detail a partial configuration of a method for providing sentiment-based investment operation information according to an embodiment of the present invention. Figure 4 shows in detail a partial configuration of a method for providing sentiment-based investment operation information according to an embodiment of the present invention. FIG. 5 illustrates a method for providing sentiment-based investment operation information according to another embodiment of the present invention. Specific details for implementing the invention

[0024] The present invention is capable of various modifications and may have various embodiments, and specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that it includes all modifications, equivalents, and substitutions that fall within the spirit and scope of the invention.

[0025] In describing the present invention, if it is determined that a detailed description of related known technology may obscure the essence of the present invention, such detailed description is omitted.

[0026] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0028] FIG. 1 shows an emotion-based investment operation information provision system (100) (hereinafter also briefly referred to as 'system (100)') according to an embodiment of the present invention.

[0029] Referring to FIG. 1, an emotion-based investment operation information providing system (100) according to one embodiment of the present invention may include a control unit (110), a storage unit (120), a communication unit (130), and an input unit (140).

[0030] The control unit (110) is connected to the storage unit (120), the communication unit (130), and the input unit (140) to transmit and receive information and control them.

[0031] The control unit (110) may include at least one processor for controlling the components and performing operations related to control.

[0032] The processor may include at least one of a Central Processing Unit, a Graphic Processing Unit, a Micro Processor, or a processor dedicated to artificial intelligence, and the type of processor is not limited thereto as long as it performs the functions of the present invention.

[0033] The storage unit (120) is connected to the control unit (110), and modules related to information analysis and processing can be stored in the form of a program.

[0034] The storage unit (120) (memory) can store a program, which is a set of data and executable instructions that can be read or written by the control unit (110).

[0035] The storage unit (120) may include at least one of a storage means having non-volatile properties and a storage means having volatile properties. The storage means may include at least one of flash memory, HDD (hard-disc drive), SSD (solid-state drive), ROM (Read Only Memory), buffer memory, and RAM (Random Access Memory), and is not limited to the above embodiments.

[0036] The storage unit (120) can store personal information regarding investors and traders.

[0037] The storage unit (120) can store sentiment information collected about investors and / or traders.

[0038] The storage unit (120) can store a clustering module in which an algorithm regarding clustering is stored in the form of a program.

[0039] The storage unit (120) may store investment-related information regarding the trader. The investment-related information may include information such as the trader's past investment performance, investment propensity, trading volume, and investor selection ranking.

[0040] The storage unit (120) may store application information that can be installed on an investor terminal (200), a first AI speaker (220), a trader terminal (300), and a second AI speaker (320). The application may include user interface information capable of providing investment-related information or transmitting investment-related selection information. The application may include information regarding a generative artificial intelligence model regarding investment management, or may include a program that accesses the inference or generation information of said model to download information.

[0041] The communication unit (130) is connected to the control unit (110) and can transmit and receive information with an external device according to the control of the control unit (110).

[0042] The communication unit (130) can communicate using at least one of wired / wireless LAN, Wi-Fi, Bluetooth, Zigbee, infrared communication (IrDa, infrared Data Association), NFC (Near Field Communication), Wibro (Wireless Broadband Internet), SQAP (Shared Wireless Access Protocol), and RF communication methods, but the communication method is not limited to the above embodiment.

[0043] The communication unit (130) can transmit and receive information by communicating with at least one of the investor terminal (200), the first AI speaker (220), the trader terminal (300), and the second AI speaker (320).

[0044] The input unit (140) may include an input interface for inputting control commands or information for the system (100).

[0045] The input unit (140) may include a keyboard or a touchscreen.

[0046] The system (100) may receive information through the input unit (140), but may also receive control commands or information through the administrator terminal and the communication unit (130).

[0047] Although not illustrated in the drawing, the investor terminal (200) may include a control unit, a communication unit, a storage unit, and an input unit.

[0048] The control unit is connected to the communication unit, storage unit, and input unit and can control them.

[0049] The communication unit can transmit and receive information with the system (100).

[0050] The storage unit can store necessary information to provide convenience in information processing. The storage unit can store an application that can be installed on an investor terminal (200).

[0051] The input section may be configured as a keyboard or a touchscreen as an input interface for controlling the investor terminal (200).

[0052] The investor terminal (200) configured in this manner may be, for example, any one of a smartphone, tablet PC, notebook, and desktop PC, and is not limited to the above embodiment as long as it is capable of performing the above functions.

[0053] The person who owns and uses the investor terminal (200) may be an individual investor. Of course, a trader may also be an individual investor.

[0054] The investor terminal (200) communicates with the first bio-device (210) and the first AI speaker (220) and can transmit some or all of the information received from the first bio-device (210) to the first AI speaker (220).

[0055] The first bio-device (210) can monitor the investor's bio-information and generate sensing information and transmit it to the investor terminal (200).

[0056] The first bio-device (210) may be a wearable device that generates, records, and transmits wearable data.

[0057] Biometric information can detect and generate information regarding, for example, heart rate, step count, respiration, body temperature, sleep duration, oxygen saturation, etc., and may include additional obtainable information in addition to the examples described above.

[0058] Information generated by the first bio-device (210) may be provided to at least one of the investor terminal (200) and the first AI speaker (220).

[0059] Although not illustrated in the drawing, the first AI speaker (220) may include a processor, memory, a communication module, and a speaker.

[0060] The first AI speaker (220) can record and execute a generative artificial intelligence model regarding investment management in memory.

[0061] Generative AI models for investment management can provide investment-related information, recommend traders, and generate advice information by analyzing the user's emotional state.

[0062] The first AI speaker (220) can provide advice information to the user at an appropriate time by outputting advice information through the speaker.

[0063] For example, the first AI speaker (220) can recognize the investor's emotions and provide feedback based on them. For example, it can output a praise message when the investor makes a positive investment decision, or output an advice message in a negative situation.

[0064] The first AI speaker (220) can recommend traders or investment products based on the investor's sentiment.

[0065] The first AI speaker (220) can interact with the user by providing information through free question and answer with the investor.

[0066] The first AI speaker (220) can monitor the user's emotional state and output a notification message if excessive stress or anxiety is detected.

[0067] The first AI speaker (220) can evaluate the risk regarding investment decisions based on the user's emotional state and advise to avoid excessive risk.

[0068] The first AI speaker (220) can analyze the investor's biosignal and output a message advising to take appropriate rest if the stress level or fatigue level is above a preset threshold.

[0069] The specific operation of the first AI speaker (220) other than that described above will be described later.

[0070] Although not illustrated in the drawing, the trader terminal (300) may include a control unit, a communication unit, a storage unit, and an input unit.

[0071] The control unit is connected to the communication unit, storage unit, and input unit and can control them.

[0072] The communication unit can transmit and receive information with the system (100).

[0073] The storage unit can store necessary information to provide convenience in information processing. The storage unit can store an application that can be installed on the trader terminal (300).

[0074] The input section may be configured as an input interface for controlling the trader terminal (300), such as a keyboard or a touchscreen.

[0075] The trader terminal (300) configured in this manner may be, for example, any one of a smartphone, tablet PC, notebook, and desktop PC, and is not limited to the above embodiment as long as it is capable of performing the above functions.

[0076] A person who owns and uses a trader terminal (300) may be a trader. Of course, an individual investor may also be a trader.

[0077] The trader terminal (300) communicates with the second bio-device (310) and the second AI speaker (320) and can transmit some or all of the information received from the second bio-device (310) to the second AI speaker (320).

[0078] The second bio-device (310) can monitor the investor's bio-information and generate sensing information to transmit to the trader terminal (300).

[0079] The second bio-device (310) may be a wearable device that generates, records, and transmits wearable data.

[0080] Biometric information can detect and generate information regarding, for example, heart rate, step count, respiration, body temperature, sleep duration, oxygen saturation, etc., and may include additional obtainable information in addition to the examples described above.

[0081] Information generated by the second bio-device (310) can be provided to at least one of the trader terminal (300) and the second AI speaker (320).

[0082] Although not illustrated in the drawing, the second AI speaker (320) may include a processor, memory, a communication module, and a speaker.

[0083] The second AI speaker (320) can record and execute a generative artificial intelligence model regarding investment management in memory.

[0084] Generative AI models for investment management can provide investment-related information, recommend traders, and generate advice information by analyzing the user's emotional state.

[0085] The second AI speaker (320) can provide advice information to the user at an appropriate time by outputting advice information through the speaker.

[0086] The specific operation of the second AI speaker (320) will be described later.

[0088] Hereinafter, a method for providing sentiment-based investment operation information according to an embodiment of the present invention will be described with the system (100) as the subject. Unless otherwise specified, the method for providing sentiment-based investment operation information according to an embodiment of the present invention may be understood as being performed through the collaboration of the system (100) and its sub-components.

[0089] FIG. 2 illustrates a method for providing sentiment-based investment operation information according to an embodiment of the present invention.

[0090] Referring to FIG. 2, in step S210, the system (100) receives investor information.

[0091] Investor information includes the investor's personal information. Personal information may include investor identification information such as name and ID, and account information. Personal information may be received by being included in membership registration information.

[0092] Investor information can be generated and transmitted by an investor terminal (200), and the communication unit (130) can be controlled to receive it and store it in a storage unit (120).

[0093] Investor information can be collected for multiple investors.

[0094] In step S220, the system (100) collects investor sentiment information.

[0095] Investor sentiment information can be collected from multiple investors.

[0096] Investor sentiment information may include at least one of information regarding the investor's emotions and physical condition.

[0097] Information regarding emotions may be classified into happiness, sadness, surprise, anger, disgust, and fear. However, this classification is not strictly limited to these categories, and the classification criteria and list may be changed within the measurable or measurable range.

[0098] For example, the six emotional parameters of happiness, sadness, surprise, anger, disgust, and fear mentioned above can be analyzed and classified through the detection of face points, definition of facial muscles, and tracking of muscle movements.

[0099] Information regarding physical condition may be classified into immersion, tension, and concentration. However, this classification is not strictly limited to these categories, and the classification criteria and list may be changed within the measurable or measurable range.

[0100] For example, heart rate can be measured, and immersion, tension, and concentration can be classified based on heart rate.

[0101] Additionally, information regarding physical condition may be generated by comprehensively analyzing cardiac responses and facial expressions. This information regarding physical condition may be data on whether or not a state of arousal is analyzable based on cardiac responses.

[0102] In addition, information regarding physical condition may be generated by comprehensively analyzing cardiac responses and facial expressions through video analysis. Based on the video analysis, information regarding physical condition can be classified into normal, focused, and immersive states.

[0103] For example, emotional information can be collected by transmitting emotional information recorded by an investor on an investor terminal (200) to the system (100).

[0104] The investor may record their emotional state directly on the investor terminal (200) at regular or irregular intervals, and the recorded emotional state information may be transmitted to the system (100). Emotional states may include happiness, sadness, surprise, anger, disgust, and fear.

[0105] Emotional information can be collected by the first bio-device (210). The first bio-device (210) can detect and record the user's bio-signal at set intervals. The recorded bio-signal can be transmitted to the system (100) through the investor terminal (200), analyzed, and stored as emotional information.

[0106] Sentiment information can be collected by a camera (not shown) that can be installed in the investor terminal (200). For example, sentiment information can be generated by analyzing the user's video information acquired by the camera, and facial expression recognition technology can be applied. The subject of the analysis can be provided in various ways, such as software that can be installed in the investor terminal (200), a control unit (110) and a storage unit (120) of the system (100), or a request to an external server.

[0107] Sentiment information can be stored in conjunction with specific situations. For example, sentiment information may be reaction information regarding a certain type of content. For instance, sentiment information may include reactions to investment information, economic news, news about events, articles on market fluctuations, or news regarding corporate earnings announcements. Reaction information may consist of positive and negative responses classified into multiple levels, such as very good, good, neutral, dislike, and very dislike. Reaction information can be stored in conjunction with content information. When reaction information is stored in conjunction with content information, the user's emotional reaction patterns to specific content can be analyzed. Alternatively, the aforementioned emotional state information may be stored in conjunction with content information instead of reaction information.

[0108] Sentiment information can be collected by an investor inputting response information for a pre-prepared question and answer set through an investor terminal (200) and transmitting the response information to a system (100).

[0109] Sentiment information can be collected by analyzing user pattern data. Pattern information can be derived by analyzing daily activities such as exercise, sleep, and leisure, investment trading patterns, clickstream data, and operational activities identified by applications. For example, changes in trading frequency or patterns during periods of high market volatility can indicate a user's emotional response.

[0110] Sentiment information can be stored chronologically and associated with specific information or behaviors. Specific information, for example, could be information regarding changes in investment market conditions. Specific behavior could be information regarding actions such as investment-related decisions. This can be analyzed as emotional responses or patterns.

[0111] As will be described later, sentiment information can be collected from traders as well as investors in the same or similar manner as described above.

[0112] In step S230, the system (100) performs clustering based on sentiment information collected about investors.

[0113] Clustering may involve grouping investors who exhibit similar emotional tendencies or patterns.

[0114] The storage unit (120) can store the clustering model in the form of a program.

[0115] Clustering models can be artificial intelligence models trained through unsupervised learning.

[0116] Any one of K-Means Clustering, Mean Shift, Gaussian Mixture Model, hierarchical clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and Agglomerative Clustering may be applied as a clustering algorithm. However, clustering algorithms are not necessarily limited to the examples described above, and if a more effective or suitable grouping algorithm exists or is developed, it may be applied.

[0117] In step S240, the control unit (110) of the system (100) generates and provides at least one trader recommendation information for at least one investor. The trader may recommend at least one trader among a plurality of traders stored in the storage unit (120). The recommendation information may be transmitted to and provided to the investor terminal (200).

[0118] Recommendation information can be generated based on association information between the trader and the clustered investor group to which the investor to whom the recommendation is provided belongs. For example, the association information may be information about traders that the investor group has frequently selected in the past. For example, the association information may be information about traders preferred by the investor group.

[0119] The system (100) can generate the above recommendation information based on the collected investor sentiment information. Specifically, the system (100) can generate recommendation information based on clustered information clustered based on the sentiment information.

[0120] Trader recommendations can be provided using any one of collaborative filtering, content-based filtering, and hybrid filtering. However, they are not necessarily limited to the above recommendation methods.

[0121] For example, the system (100) can rank and recommend traders that other investors have previously selected or that other investors have selected the most in the clustering group to which the investor belongs.

[0122] Figure 3 shows the S240 step in detail.

[0123] Referring to FIG. 3, in step S241, the system (100) performs sub-classification according to content preference within the clustered groups. For example, within similar sentiment groups, sub-groups that prefer 'electric vehicle' related content, sub-groups that prefer 'pharmaceutical' related content, etc., can be created.

[0124] The system (100) can secure the content preferred by the investor in advance through a survey when receiving the investor's personal information.

[0125] The system (100) can generate content preferred by investors by analyzing past investment-related transaction history, viewed investment information, etc.

[0126] In step S242, the control unit (110) collects investor selection information within the sub-category.

[0127] Investor selection information may be past trader selection information of investors belonging to the same subcategory.

[0128] In step S243, the control unit (110) generates trader recommendation information based on selection information.

[0129] The trader recommendation at step S240 does not need to be provided only once, and may be provided before or after any subsequent step. This is because investors may change traders depending on their investment situation.

[0130] Referring again to Fig. 2, at step S250, the system (100) performs investment management.

[0131] Investment management can be defined as providing information that assists in investment-related decisions for at least one of the investors and traders, or controlling access rights to investment management applications, etc.

[0132] Investment management may be carried out for at least one of the investors and traders.

[0133] Investment management for investors may include the collection and output of information by the first bio-device (210) and the first AI speaker (220). However, the first bio-device (210) and the first AI speaker (220) are not necessarily required and their roles may be replaced by sensors and processors of the system (100) and the investor terminal (200), and information may be transmitted in a form that can be output visually and / or audibly by the investor terminal (200).

[0134] Investment management for the trader may include the collection and output of information by the second bio-device (310) and the second AI speaker (320). However, the second bio-device (310) and the second AI speaker (320) are not necessarily required and their roles may be replaced by sensors and processors of the system (100) and the trader terminal (300), and information may be transmitted in a form that can be output visually and / or audibly by the trader terminal (300).

[0135] Since investment management for investors and traders is similar in method, differing only in the target of information provision, we will focus primarily on explaining investment management for investors.

[0136] Figure 4 shows the S250 step in detail.

[0137] Step S250 is to be exemplified as being performed by the system (100), but it should be understood that Step S250 can also be performed by the first AI speaker (220).

[0138] Referring to FIG. 4, in step S251, the first bio-device (210) collects bio-information.

[0139] The biometric information may include at least one of heart rate, step count, respiration, body temperature, sleep duration, and oxygen saturation.

[0140] The collected biometric information can be transmitted to an investor terminal (200), which can then be transmitted to the system (100).

[0141] In step S252, the control unit (110) sets an abnormality standard. The abnormality standard may be based on at least one value of the biometric information in a normal state. For example, the abnormality standard may be outside the set range from the investor's average heart rate. For example, if the heart rate of a person with an average heart rate of 75 is 95 or higher, it may be determined as an abnormal value. The abnormality standard may be stored in the storage unit (120) for each investor.

[0142] The setting of the ideal standard may be performed by the first AI speaker (220). In this case, the biometric information collected by the first biometric device (210) may be transmitted to the first AI speaker (220). Alternatively, the collected biometric information may be transmitted to the first AI speaker (220) through the system (100) or the investor terminal (200).

[0143] In step S253, the control unit (110) determines whether the abnormality criteria are satisfied. If satisfied, proceed to step S254; otherwise, this step can be repeated.

[0144] For example, satisfaction of the abnormality criterion may be when a heart rate greater than or less than a preset value is detected from the average heart rate described above.

[0145] This step can also be performed by the first AI speaker (220).

[0146] In step S254, the system (100) can transmit warning message information to an investor terminal (200). The investor terminal (200) can output the warning message information visually and / or audibly so that the investor can recognize it. For example, the warning message may include advice information based on the current emotional state, such as “You are currently in a state of excessive excitement, so it would be advisable to postpone investment-related decisions.”

[0147] The system (100) may lock the functions regarding the selection of some of the application functions of the investor terminal (200). This may be limited to cases where the user has pre-set (or agreed to the action).

[0148] Some selection functions may include decisions related to the direct execution of an investment, such as the trader's decision, detailed settings regarding the scope of the trader's role, and the determination of investment instruments, investment size, and investment funds.

[0149] The system (100) can restrict irrational investment-related decisions by limiting the function for investment-related decisions when the biometric information indicates abnormal values, etc., or when the investor's state analyzed from the biometric information deviates significantly from the concentration state.

[0150] According to an embodiment, the system (100) may lock the functions regarding the selection of some application functions when the first bio-device (210) is a wearable device and is not worn, regardless of whether the abnormality criteria are satisfied. This is because in this case, it is difficult to determine the user's emotional state as bio-signals cannot be collected.

[0151] Step S254 can also be performed by the first AI speaker (220).

[0152] In step S255, the control unit (110) determines whether at least one of the values ​​of the bio-information has returned to a normal standard. If it has returned to a normal standard, the process proceeds to step S256, and otherwise, step S255 can be repeated.

[0153] In step S256, the control unit (110) can transmit guidance message information to the investor terminal (200). The investor terminal (200) can output the guidance message information visually and / or audibly so that the investor can recognize it. For example, the guidance message may include guidance information based on the current emotional state, such as “You are currently in a stable state, so it would be good to make investment-related decisions.”

[0154] If the system (100) locks the functions regarding some selections in step S254, it can unlock them in step S256.

[0155] The investment management step (S250) can be applied in the same way to traders. Applying the investment management step (S250) to traders has the effect of suppressing irrational judgments to some extent during investment management for traders as well.

[0156] Although not illustrated in the drawing, the system (100) can evaluate the trader's acceptance. The acceptance may be, for example, a score quantified by accumulating points when the trader does not make investment-related decisions based on the advice output of the second AI speaker (320) when any one of the biometric data values ​​is within an abnormal standard range.

[0157] Acceptance can serve as a criterion for filtering or determining recommendation priorities when recommending traders to investors in the future.

[0159] FIG. 5 illustrates a method for providing sentiment-based investment operation information according to another embodiment of the present invention.

[0160] Since steps S310 and S320 in Fig. 5 correspond to steps S210 and S220, respectively, the same explanation is not repeated and is replaced by the explanation above.

[0161] In step S330, the system (100) receives trader information.

[0162] Trader information includes the trader's personal information and investment-related information. Personal information may include investor identification information such as name and ID, and account information. Personal information may be received by being included in membership registration information. Investment-related information may include investment performance, investment propensity, and investment strategy.

[0163] Trader information can be generated and transmitted by a trader terminal (300), and the communication unit (130) can be controlled to receive it and store it in a storage unit (120).

[0164] In step S340, the system (100) collects trader sentiment information.

[0165] Since the collection of trader sentiment information can be carried out by the same method as the collection of investor sentiment information described above, the explanation regarding this will be replaced by the explanation provided above.

[0166] In step S350, the system (100) performs clustering on multiple investors and multiple traders based on sentiment information collected on the investors and traders.

[0167] Step S350 is distinguished from Step S230 in that the clustering targets include not only investors but also traders. However, since the clustering method can be performed using the same method as described in Step S230, the explanation regarding this will be replaced by the description above.

[0168] In step S360, the system (100) recommends a trader to at least one investor.

[0169] Trader recommendations may use the recommendation method described in step S240, but step S360 may further include a method of recommending traders belonging to the same group among the clustered groups. This method has the effect of recommending traders with successful investment records who have sentiment patterns similar to those of investors.

[0170] In step S370, the system (100) performs investment management.

[0171] Since Step S370 is identical to the explanation provided in Step S250 above, the same explanation will not be repeated and will be replaced by the explanation provided above.

[0173] The terms used in this application are used merely to describe specific embodiments and are not intended to limit the invention. In this application, terms such as “comprising” or “having” are intended to indicate the presence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. Explanation of the symbols

[0175] 100: Sentiment-based investment operation information provision system 110: Control unit 120: Storage section 130: Communications Department 140: Input section 200: Investor Terminal 210: 1st bio-device 220: The 1st AI Speaker 300: Trader Terminal 310: Second bio-device 320: The 2nd AI Speaker

Claims

Claim 1 A method of operation of a sentiment-based investment management information provision system comprising: a step of collecting biometric information and image information, including heart rate, step count, respiration, body temperature, sleep time, and oxygen saturation, from a plurality of investors through a biometric device and a camera; a step of generating sentiment information based on the biometric information and image information for the plurality of investors; a step of clustering the plurality of investors based on the sentiment information; and a step of generating and providing trader recommendation information for at least one investor among the clustered investors; wherein the recommendation information is generated based on association information between the clustered investor group to which the investor to whom the recommendation information is to be provided belongs and the trader, and the sentiment information includes reaction information classified into very good, good, average, bad, and very bad based on the biometric information and image information, regarding the reaction shown by the plurality of investors to each type when they encounter a first type of economic news, a second type of article on sharp fluctuations in the market, a third type of news on specific events, and a fourth type of news on corporate earnings announcements. Claim 2 A method of operation of an emotion-based investment management information provision system comprising: a step of collecting biometric information and image information, including heart rate, step count, respiration, body temperature, sleep time, and oxygen saturation, from a plurality of investors and a plurality of traders through a biometric device and a camera; a step of generating sentiment information based on the biometric information and image information for the plurality of investors and the plurality of traders; a step of clustering the plurality of investors and the plurality of traders together based on the sentiment information; and a step of generating and providing trader recommendation information for at least one investor among the clustered investors, wherein the recommendation information includes information on at least one trader among the traders belonging to the clustered group to which the investor to whom the recommendation information is to be provided belongs, and the sentiment information for the plurality of investors and the plurality of traders includes reaction information classified into very good, good, average, bad, and very bad based on the biometric information and image information, regarding the reaction shown by the plurality of investors and the plurality of traders to each type when they encounter a first type of economic news, a second type of article on sharp fluctuations in the market, a third type of news on a specific event, and a fourth type of news on corporate earnings announcements. Claim 3 A method of operation of an emotion-based investment operation information provision system, characterized in that, in either one of claims 1 and 2, the emotion information is time-series emotion state information classified into happiness, sadness, surprise, anger, disgust, and fear. Claim 4 A method of operation of a sentiment-based investment operation information provision system, characterized in that, in either one of paragraphs 1 and 2, the sentiment information is information recorded together with the time of viewing of investment-related content. Claim 5 delete Claim 6 A method of operation of an emotion-based investment operation information providing system, characterized in that, in either claim 1 or 2, it further comprises an investment management step for at least one of the plurality of investors and the plurality of traders, wherein the investment management step comprises a step of managing any one of the plurality of investors and the plurality of traders, and generating and outputting a warning message information when any one of the biometric information satisfies a preset abnormality standard. Claim 7 A method of operation of an emotion-based investment operation information provision system, characterized in that, in either claim 1 or 2, it further comprises an investment management step for at least one of the plurality of investors and the plurality of traders, wherein the investment management step comprises a step of restricting investment-related decisions of the managed subject when any one of the plurality of investors and the plurality of traders satisfies a preset ideal standard for any one of the biometric information. Claim 8 A bio-device; a camera; a storage unit for recording bio-information and image information, including heart rate, step count, respiration, body temperature, sleep time, and oxygen saturation of a plurality of investors, collected through the bio-device and the camera; and a communication unit. A system for providing sentiment-based investment management information, comprising: a control unit that controls the storage unit and the communication unit; wherein the control unit generates sentiment information for the plurality of investors based on the biometric information and the image information, clusters the plurality of investors based on the sentiment information, generates trader recommendation information for at least one investor among the clustered investors, and transmits it to an investor terminal, wherein the recommendation information is generated based on association information between the clustered investor group to which the investor to whom the recommendation information is to be provided belongs and the trader, and wherein the sentiment information includes reaction information classified into very good, good, average, bad, and very bad based on the biometric information and the image information, regarding the reaction that the plurality of investors show to each type when encountering a first type of economic news, a second type of article on sharp fluctuations in the market, a third type of news on a specific event, and a fourth type of news on a company's earnings announcement. Claim 9 An emotion-based investment operation information providing system characterized by including, in claim 8, a first AI speaker that generates and outputs warning message information when any one of the above biometric information satisfies a preset abnormality standard.

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