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WO2019004358A1 - Dispositif de génération de conseils, système de présentation de conseils, programme de génération de conseils, système de génération de données de conseil et procédé de génération de données de conseil - Google Patents

Dispositif de génération de conseils, système de présentation de conseils, programme de génération de conseils, système de génération de données de conseil et procédé de génération de données de conseil Download PDF

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Publication number
WO2019004358A1
WO2019004358A1 PCT/JP2018/024591 JP2018024591W WO2019004358A1 WO 2019004358 A1 WO2019004358 A1 WO 2019004358A1 JP 2018024591 W JP2018024591 W JP 2018024591W WO 2019004358 A1 WO2019004358 A1 WO 2019004358A1
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WO
WIPO (PCT)
Prior art keywords
advice
data
brand
purchase
amount
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/JP2018/024591
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English (en)
Japanese (ja)
Inventor
哲也 藤村
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Risingbull Inc
Original Assignee
Risingbull Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from JP2018090956A external-priority patent/JP2019012518A/ja
Application filed by Risingbull Inc filed Critical Risingbull Inc
Publication of WO2019004358A1 publication Critical patent/WO2019004358A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/06—Asset management; Financial planning or analysis

Definitions

  • One aspect of the present invention relates to an advice generation device, an advice presentation system, an advice generation program, an advice data generation system, and an advice data generation method.
  • Patent Document 1 is known as a prior art.
  • Japanese Patent Publication Japanese Patent Application Laid-Open No. 2002-203105 (July 19, 2002)" Japanese Patent Publication "Japanese Patent Application Laid-Open No. 2000-250997 (September 14, 2000)” Japanese Patent Publication "Japanese Patent Application Laid-Open No. 2000-293569 (Oct. 20, 2000)” Japanese Patent Publication "Japanese Patent Application Laid-Open No. 2004-240720 (August 26, 2004)” Japanese Patent Publication "Japanese Patent Application Publication No. 2008-243158 (October 9, 2008)” Japanese Patent Publication "Japanese Patent Application Laid-Open No. 2009-070028 (Apr. 2, 2009)" Japan Published Patent Gazette “Special Table 2014-525062 Gazette (December 6, 2012 International Publication)” Japanese patent publication "patent 6072 357 (January 13, 2017 registration)"
  • Patent Documents 2 to 8 disclose a service that proposes a portfolio of investment products at a certain point in time.
  • An aspect of the present invention aims to provide advice in accordance with the amount of investment with continuity.
  • an advice generation device is an advice generation device that generates a plurality of advices according to an investment amount, and a plurality of advices included in past presented advices.
  • the system includes an advice generation unit that generates the plurality of advices including advices related to at least one of the items of the brand and the cash amount.
  • the advice generation device even if the advice generation unit generates an advice according to the predetermined amount when the evaluation value regarding the owned brand and the cash amount reaches a predetermined amount or more. Good.
  • the advice corresponding to the predetermined amount is generated when the evaluation amount reaches the predetermined amount or more, it is possible to provide useful advice for the user according to the rank of the evaluation amount.
  • the advice generation unit refers to the virtual trading model according to the advice and the actual trading information of the user, and the investment content of the user approaches the virtual trading model. Such advice may be generated.
  • the advice generation unit may generate a plurality of advices according to the investment amount and the investment start time.
  • an advice presentation system is an advice presentation system including the advice generation device and a terminal device, wherein the terminal device is a plurality of advices generated by the advice generation unit. Present at least one of the advices to the user.
  • an advice data generation system for generating a plurality of advices according to a course according to an investment amount, which comprises: advice on buying a brand or a product; An advice generation unit that generates the plurality of advices that are continuous in the above-described course and that change according to buying and selling by repeatedly generating advice on selling is provided.
  • an advice data generation system is an advice data generation system that generates a plurality of advices according to a course according to an investment amount, and remains for buying a brand or a product for each course.
  • Cash ratio data showing the ratio of cash
  • purchase number data showing the number of purchases of brand or product in case of buy of brand or product
  • an amount showing distribution of purchase amount of brand or product in case of buy of brand or product
  • Storage unit for storing distribution data and purchase / selling condition data indicating purchase condition and sale condition of brand or product, cash ratio data, purchase number data, money amount distribution data, and trade condition data according to And an advice generation unit that generates the plurality of advices.
  • the purchase is possible with reference to the steps of storing unregistered brand or product in the storage unit, calculating the purchase available amount, and the storage unit. Generating a buying advice in a range of money, recalculating a purchase price according to the buying advice, and generating a selling advice with reference to the storage unit. Repeat the above steps.
  • FIG. 1 It is a figure which shows the hardware constitutions of the advice presentation system which concerns on Embodiment 1 of this invention. It is a block diagram which shows the structure of the terminal which concerns on Embodiment 1 of this invention, and a server. It is a figure which shows the example of a display of the screen of "to the first time” based on Embodiment 1 of this invention. It is a figure which shows the example of a display of the screen of the "held brand” which concerns on Embodiment 1 of this invention. It is a figure which shows the example of a display of the screen of the "evaluation amount” which concerns on Embodiment 1 of this invention.
  • Embodiment 1 Hereinafter, Embodiment 1 of the present invention will be described in detail.
  • FIG. 1 is a diagram showing a hardware configuration of the advice presentation system 1 according to the present embodiment.
  • the advice presentation system 1 includes a terminal (terminal device) 2 and a server (advice generation device) 3.
  • the terminal 2 and the server 3 are configured to be able to communicate via the network 4.
  • the terminal 2 acquires data by the operation of the user and displays an advice according to the amount of money of the initial setting (the amount of investment), and is, for example, a PC, a tablet terminal, a smartphone or the like.
  • the server 3 generates a plurality of advices according to the investment amount.
  • the network 4 is a network including the Internet.
  • the server 3 may generate separate advice for each individual user, or may group a plurality of users according to investment timing, investment amount, etc., and generate advice for each group.
  • FIG. 2 is a block diagram showing the configuration of the terminal 2 and the server 3 according to the present embodiment.
  • the terminal 2 includes a communication unit 21, a control unit 22, a display unit 23, and an operation reception unit 24.
  • the communication unit 21 is a part that communicates with the server 3.
  • the control unit 22 controls the entire terminal 2 and is, for example, one or more processors.
  • the display unit 23 displays data according to an instruction from the control unit 22.
  • the display unit 23 is, for example, a liquid crystal display.
  • the operation receiving unit 24 receives an operation of the user, and is, for example, a mouse, a touch panel, or the like.
  • the server 3 includes a communication unit 31, a control unit 32, and a storage unit 33.
  • the communication unit 31 is a part that communicates with the terminal 2.
  • the control unit 32 controls the entire server 3 and is, for example, one or more processors.
  • the storage unit 33 stores data according to an instruction from the control unit 22.
  • the storage unit 33 is, for example, a hard disk device, a flash memory, or the like.
  • the control unit 32 includes an advice generation unit 321.
  • the advice generation unit 321 generates a plurality of advices including advices related to at least one of a plurality of brands and items of purchaseable cash balance (cash amount) included in the past presented advice.
  • the past presented advice may be advice already presented to the target user, or may be advice already presented to the user included in the group including the target user.
  • the advice may also be the provision of trading data of the brand.
  • the person who provides the advice presentation system 1 with the trading data of the brand may be an adviser who operates the advice presentation system 1 or may be an individual investor such as another user.
  • the cash balance may not necessarily be constant on the way except when buying and selling stocks, and may be increased or decreased depending on the cash in / out of the user's account.
  • the terminal 2 presents at least one of the plurality of advices generated by the advice generation unit 321 to the user.
  • the control unit 32 also manages a virtual trading model.
  • the hypothetical trading model is a trading model, such as a recommended stock, according to the amount and start date of the default funds.
  • the hypothetical trading model may be a model corresponding to an item including not only the amount of initial setting funds, the start date, but also the adviser and the market (TSE, Mothers, etc.), and changes dynamically.
  • FIG. 10 is a flowchart showing the process of the advice presentation system 1 according to the present embodiment. The process of the advice presentation system 1 will be described according to the flow of FIG. 10 and with reference to FIGS. 3 to 9.
  • Step S1001 As shown in FIG. 10, the terminal 2 acquires the amount of the initial setup funds of the target user, and transmits data indicating the amount to the server 3.
  • FIG. 3 is a view showing a display example of a screen of “For the first time”.
  • the control unit 22 displays on the display unit 23 a screen including the start date (the investment start timing), the initial setting funds, the summary, and the transition of the evaluation value as a screen of “to the first person”.
  • the amount of initial setup funds is the amount of investment set when the user receives advice.
  • the user has previously selected "[S member] 1 million yen course", and the control unit 22 selects "1,000,000 yen" in the initial setup funds column according to the selected investment amount. After being displayed, the amount of the initial setting funds is sent to the server 3.
  • Step S1002 The server 3 receives, from the terminal 2, data indicating the amount of initial setting funds.
  • the advice generation unit 321 generates a plurality of advices according to the amount of the initial setting funds indicated by the received data and the start date that is the date.
  • the advice includes buying and selling multiple stocks and the available cash balance after buying and selling.
  • the server 3 determines the name and number of shares of the recommended recommended purchase as the advice, and transmits data indicating the name and number of shares of the recommended recommended purchase to the terminal 2.
  • the server 3 performs the process of step S1002 irregularly according to the daily stock price fluctuation.
  • the advice generation unit 321 of the control unit 32 generates an advice related to at least one of buying and selling of a plurality of stocks and at least one of the purchaseable cash balances after buying and selling included in the advice presented in the past. .
  • the advice generation unit 321 when the user has bought the stock of company A in the past and has received advice on the stock of company A generated by the advice generation unit 321, the current stock price is higher than the stock price at the time of buying. Is higher than a predetermined value, the advice generation unit 321 generates an advice that promotes the sale of the stock of company A.
  • the advice generation unit 321 is configured to purchase a cash balance that can be purchased after trading included in advice that has been presented in the past, in other words, stocks of stocks that are expected to increase in the future. Generate advice to buy.
  • Step S1003 As shown in FIG. 10, the terminal 2 indicates, from the server 3, advice related to at least one of buying and selling of a plurality of stocks and at least one of the purchaseable cash balances after buying and selling included in the advice presented in the past.
  • data data indicating the name and number of stocks of the recommended stock is received, and the name and number of stocks of the recommended stock indicated by the received data are displayed on the display unit 23.
  • FIG. 4 is a view showing a display example of a screen of “held stock”.
  • the "held stock” screen is a screen showing advice related to buying and selling of multiple stocks and / or purchase available cash balances after buying and selling included in the advice presented in the past, and more specifically Is a screen for displaying information on purchase recommended stocks as advice to the user.
  • the control unit 22 causes the display unit 23 to display a screen including a brand name (code), recommended date, number of shares, recommended stock price, recommended price as a screen of “held stock”. . Then, the control unit 22 causes the display unit 23 to display an advice of “ ⁇ If this course is adopted, please purchase the following brand.”
  • the advice presentation system 1 As shown in FIG. 3, it is the principle that the user starts using the advice presentation system 1 after specifying the initial setting funds and the start date. However, the user may start using the advice presentation system 1 after adjusting his own stock to the recommended stock shown in FIG. 4 and follow the advice thereafter. As described above, the advice presentation system 1 is a system that the user can use in the middle.
  • the display unit 23 dynamically changes and displays the advice which is changed and performed in an easy-to-understand manner.
  • the display unit 23 displays the name and the number of stock holdings in an easy-to-understand manner.
  • the display unit 23 extracts and displays only the products for which the opposite trading has not been completed among the updated trading data. That is, the display unit 23 calculates and displays a brand or a product for which sale advice has not yet been generated, or a remaining quantity among brands or products for which the purchase advice has been generated.
  • the user can easily participate halfway.
  • the information that is important for joining is not the information in the past, but the information on what stocks to buy and what to buy and how much it should buy. Therefore, it is possible to join halfway by combining the current stock holdings, and this indication is important in the sense that users who receive the offer also confirm the current stock holdings. If the stocks are aligned according to this display, it will be possible to join halfway, and then follow the trading advice. Even for users who have already started the course, it is possible to confirm whether or not the advice is given by comparing it with the actual holding situation.
  • Step S1004 As shown in FIG. 10, the server 3 calculates an evaluation amount of the virtual trading model, and transmits data indicating the evaluation amount to the terminal 2.
  • the hypothetical trading model is a trading model, such as a recommended stock, according to the amount and start date of the default funds.
  • the virtual trading model may be a model according to items including not only the amount of initial setting funds, the start date, but also the adviser and the market (TSE, Mothers etc.), which changes dynamically It is.
  • Step S1005 As shown in FIG. 10, the terminal 2 receives data indicating the evaluation price of the virtual trading model from the server 3 and causes the display unit 23 to display the evaluation price of the virtual trading model indicated by the received data.
  • FIG. 5 is a diagram showing a display example of a screen of “evaluation amount”. As shown in FIG. 5, the control unit 22 causes the display unit 23 to display a screen including an evaluation summary and an evaluation for each owned stock as a screen of “evaluation amount”.
  • the valuation summary includes current portfolio investments, current portfolio valuations, current unrealized gains, past realized gains and losses, total gains and losses, available cash balances, and credit values.
  • the valuation per stock held includes the brand name (code), date of recommendation, number of shares, stock price and amount at the time of buy recommendation, current stock price and amount, rate of return and valuation loss.
  • a portfolio refers to the state of a hypothetical trading model at that point in time.
  • Step S1006 As shown in FIG. 10, the server 3 calculates the trading history of the virtual trading model, and transmits data indicating the trading history to the terminal 2.
  • Step S1007 As shown in FIG. 10, the terminal 2 receives data indicating the trading history of the virtual trading model from the server 3 and causes the display unit 23 to display the trading history of the virtual trading model indicated by the received data.
  • FIG. 6 is a view showing a display example of a screen of “trading history”. As shown in FIG. 6, the control unit 22 displays the name of the brand, the number of shares, the date of purchase recommendation, the stock price and the amount, the date of sale, the stock price and the amount, the rate of return, the trading profit and loss A screen including is displayed on the display unit 23.
  • FIG. 7 is a diagram showing a display example of a screen of “evaluation amount history”. As shown in FIG. 7, the control unit 22 causes the display unit 23 to display a screen including the publication date and time and the article title as a screen of “evaluation amount history”.
  • FIG. 8 is a view showing a display example of a screen of “evaluation amount details”. As shown in FIG. 8, the control unit 22 causes the display unit 23 to display a screen including an evaluation summary and an evaluation for each owned stock as a screen of “evaluation amount details”.
  • the valuation summary includes current portfolio investments, current portfolio valuations, current unrealized gains, past realized gains and losses, total gains and losses, available cash balances, and credit values.
  • the valuation per stock held includes the brand name (code), date of recommendation, number of shares, stock price and amount at the time of buy recommendation, current stock price and amount, rate of return and valuation loss.
  • FIG. 9 is a diagram showing a display example of the “portfolio” screen. As shown in FIG. 9, the control unit 22 causes the display unit 23 to display a screen including the selected portfolio and the association of the portfolio and the article as a “portfolio” screen.
  • the selected portfolio is: ID, brand name, number of shares, recommended date for buying, article ID for buying, recommended stock price, recommended currency, recommended price, recommended date for selling, article ID for selling, stock price for selling, currency for selling, and , Including the sale amount.
  • the buying article ID indicates a unique ID in a report when it is recommended to buy a stock of the brand name.
  • the article ID for sale indicates an ID unique to the report when it is recommended to sell the stock of the brand name. In the association between the portfolio and the article, it is possible to search for a buying related article ID or selling related article ID.
  • the display screen displayed by the terminal 2 may be configured to be generated by the control unit 22 of the terminal 2 based on the information received from the server 3 or data indicating the display screen generated by the server 3 (for example, html format or The xml format data may be transmitted to the terminal 2 and displayed on the terminal 2.
  • the server 3 may generate a part of the display screen, and the terminal 2 may generate the remaining part.
  • an application for generating the display screen in advance or accepting an input from the user is installed in the control unit 22 of the terminal 2 in advance as a part of the control unit 22 You just have to run it.
  • the purchasable balance may be increased or decreased at times other than buying and selling, flexible services can be provided to the user.
  • a plurality of advices may be generated by generating various advices. You can compare, rate, and rank advice.
  • Embodiment 2 of this invention is demonstrated based on FIG. 11 and FIG.
  • symbol is appended and the description is abbreviate
  • FIG. 11 is a view showing a display example of a hypothetical trade model curve according to the present embodiment.
  • FIG. 11A shows a hypothetical trading model curve.
  • FIG. 11B shows a hypothetical trading model curve and trading information input fields.
  • FIG. 11 (c) shows a hypothetical trading model curve and trading performance curve.
  • FIG. 12 is a flowchart showing the process of the advice presentation system 1 according to the present embodiment. The process of the advice presentation system 1 will be described according to the flow of FIG. 12 and with reference to FIG.
  • the virtual trading model curve indicates a plurality of advices including advices related to at least one of a plurality of issues and items of cash amount included in the past presented advice.
  • the difference between the virtual trading model curve and the trading performance curve is generated by referring to the virtual trading model according to the above advice and the actual trading information of the user, such that the user's investment content approaches the virtual trading model It shows the advice.
  • Step S1201 As shown in FIG. 12, the terminal 2 requests the server 3 for data of a virtual trading model. This data request includes the amount of initial setup funds and the start date for the hypothetical trading model.
  • Step S1202 the server 3 receives the data request of the virtual trading model from the terminal 2, and receives the data of the virtual trading model according to the amount of initial setting funds included in the received data request and the start date.
  • Send to The data of the virtual trading model includes the transition of the evaluation value of the virtual trading model.
  • Step S1203 As shown in FIG. 12, the terminal 2 receives data of a virtual trading model from the server 3 and causes the display unit 23 to display a virtual trading model curve drawn by the received data. As shown in FIG. 11, the control unit 22 generates a screen including a curve indicating the transition of the evaluation value of the virtual trading model included in the received data, and the generated screen is displayed on the display unit 23 as a virtual trading model curve. Display.
  • Step S1204 As shown in FIG. 12, the terminal 2 acquires trading information from the user. More specifically, as shown in FIG. 11B, when the operation receiving unit 24 detects a date on the time axis on which the cursor is positioned by the user operation, the control unit 22 determines the date A screen including a trading information input field for inputting trading information on a day is generated, and the generated screen is displayed on the display unit 23. The user may use another input screen. Next, when the operation receiving unit 24 detects that trading information such as brand, trading, number of shares, etc. has been input in the trading information input field by the user operation, the control unit 22 inputs the trading information input. get.
  • trading information such as brand, trading, number of shares, etc.
  • Step S1205 the terminal 2 requests the server 3 for data of the evaluation value of the virtual trading model according to the trading information.
  • This data request is to request data of an evaluation value when the virtual trading model is corrected using actual trading information.
  • This data request includes date and time, brand name, buying and selling, and number of shares, which are trading information.
  • Step S1206 the server 3 receives a request for evaluation amount data from the terminal 2, calculates an evaluation amount, and transmits the evaluation amount data. Specifically, the control unit 32 acquires the date, brand, trading, and number of shares included in the received data request. Next, the control unit 32 acquires the date and the unit price of the stock from the storage unit 33. Then, the control unit 32 specifies the transition of the evaluation value by calculating the increase or decrease of the evaluation value based on trading, the number of shares, and the unit price of stock. Furthermore, the control unit 32 transmits data of the evaluation amount transition to the terminal 2.
  • Step S1207 As shown in FIG. 12, the terminal 2 receives evaluation price transition data from the server 3, generates a screen including a trading performance curve drawn by the received data, and causes the display unit 23 to display the generated screen. As shown in FIG. 11C, the control unit 32 causes the display unit 23 to display a trading performance curve having a divergence from the virtual trading model curve.
  • the advice generating unit 321 refers to the virtual trading model according to the advice in step S1202 and the actual trading information of the user in step S1206, and generates an advice such that the user's investment content approaches the virtual trading model.
  • the terminal 2 causes the display unit 23 to display such advice.
  • FIG. 11C shows a display example of such an advice.
  • Step S1208 As shown in FIG. 12, the terminal 2 causes the display unit 23 to display a model performance difference between the virtual trading model curve and the trading performance curve. As shown in FIG. 11C, the control unit 32 causes the display unit 23 to display the model performance difference by the line segments of double arrows.
  • the model performance difference shown in FIG. 11 (c) is the difference between the virtual trading model at the present time and the trading performance, but the virtual trading model, the trading performance, and the trading performance are in the left direction on the time axis from that time. Since it is displayed when they were separated, it displays advice on how to buy and sell.
  • control unit 32 causes the display unit 23 to display an advice that "the model and the performance are separated from here.” This is advice that brings the user's investment content closer to the virtual trading model.
  • the terminal 2 displays a random model indicating what happened if you did not get the recommended sales, so the virtual trading model and the random model You may display the deviation of the
  • the terminal 2 displays the model performance difference between the virtual trading model curve and the trading performance curve on the display unit 23, thereby displaying an advice that brings the user's investment content closer to the virtual trading model. Can provide useful advice.
  • FIG. 13 is a diagram showing an example regarding the continuity of the advice according to the first embodiment of the present invention.
  • the present embodiment shows a specific example of “the advice related to at least one of a plurality of items and items of cash amount included in the past presented advice”.
  • the terminal 2 acquires an initial setting item and transmits the initial setting item to the server 3 by the user's input operation.
  • Initial setting items include initial amount, target stock (Chinese stock, Japanese stock, emerging market stock, etc.), usage start date, type (performance-oriented, large stock-oriented, etc.), name of manager, etc. Is included.
  • the server 3 receives an initial setting item from the terminal 2 and generates an advice according to the initial setting item. As shown in FIG. 13, the advice presentation system 1 operates with an initial amount of 1 million yen.
  • the server 3 advises on purchasing the brand A and the brand B with the initial price of 1,000,000 yen (the purchase price of each brand And the advice is transmitted to the terminal 2.
  • the remaining cash is the sum of 1 million yen minus the purchases of brand A and brand B.
  • the terminal 2 receives the advice after 3 months from the server 3 and displays it.
  • the server 3 After a half year has passed from the use start date of the advice presentation system 1, the server 3 generates an advice on the purchased brand and the remaining cash advised after 3 months, and transmits the advice to the terminal 2.
  • the terminal 2 receives the advice after half a year from the server 3 and displays it.
  • the server 3 After one year has passed from the use start date of the advice presentation system 1, the server 3 generates advice on the purchased brand and cash advised in half a year, and transmits the advice to the terminal 2.
  • the terminal 2 receives the advice one year later from the server 3 and displays it.
  • the advice to sell the brand C As shown in FIG. 13, in the advice after one year, the advice to sell the brand C, the advice to purchase the brand F by cash, the advice to continuously hold the brand B and the brand D, and the brand E to sell Advice to purchase brand G and brand H (including the purchase price of each brand) is included.
  • Cash is the total of the sale amount of the brand E minus the purchase amounts of the brand G and the brand H and the sale amount of the brand C.
  • the valuations at each point in time, trading gains and losses, unrealized gains and losses, and cash balances are as shown in the following formulas.
  • x number of stocks-not sold Unrealized gains and losses of stocks (Current stock-recommended stock to buy) ⁇ Number of shares
  • Cash balance 1 million yen-(Current value of unsold stocks at that time-Unrealized gains and losses of unsold stocks at that time) + Sales up to that point Trading gains and losses of pre-established stocks
  • the present embodiment shows a specific example of “the advice according to the predetermined amount, which is generated when the evaluation value regarding the owned brand and the cash balance which can be purchased becomes equal to or more than the predetermined amount”.
  • the advice generation unit 321 of the server 3 generates an advice according to the predetermined amount of money
  • the advice generation unit 321 initially generates an advice according to 300,000 yen, which is the user's purchasable cash balance. After that, when the above evaluation amount reaches 1 million yen or more, the advice generation unit 321 makes a proposal to the user to use the advice of making the purchaseable cash balance 1 million yen.
  • the advice generation unit 321 of the server 3 generates an advice according to 1 million yen, which is the user's purchasable cash balance, when the user acquires information indicating that the user accepts the above proposal from the terminal 2 by the operation of the user. Do. After that, when the evaluation amount reaches 5 million yen or more, the advice generation unit 321 makes a proposal to the user to use the advice of making the purchaseable cash balance 5 million yen.
  • the advice generation unit 321 proposes to sell the stock held to the user once and use the advice according to the predetermined amount every time the evaluation amount rises and becomes equal to or more than the predetermined amount.
  • the predetermined amount of money to be compared with the evaluation amount has been described as 1 million yen and 5 million yen, without being limited thereto, the predetermined amount of money may be set to one or more arbitrary amounts. Is possible.
  • Embodiment 3 of the present invention, while referring to FIGS.
  • symbol is appended and the description is abbreviate
  • the advice data generation system 10 generates a plurality of advices according to a course corresponding to the investment amount.
  • the advice data generation system 10 has the same configuration as the advice presentation system 1 according to the first and second embodiments.
  • the advice data generation system 10 includes at least an advice generation unit 321, a display unit 23, and a storage unit 33.
  • the advice generation unit 321 generates and outputs advice data.
  • the display unit 23 displays the advice data.
  • the storage unit 33 stores a database storing data on registered investment products.
  • the advice generation unit 321 repeatedly generates advice for buying a brand or a product and advice for selling a brand or a product, so that there is continuity in the course according to the amount of investment, and according to trading. Generate multiple, changing advices.
  • the plurality of advices are continuous in the course selected by the user, and dynamically change in response to various changes such as the market conditions of the brand or the product.
  • the advice data is not static data such as a portfolio at a certain point in time but data corresponding to various changes such as market conditions.
  • FIG. 14 is a diagram showing a series of flows of the advice generation process according to the present embodiment.
  • Step S1401 The advice generating unit 321 calculates the purchase available amount. From the second time onward, the advice generation unit 321 reflects the price of the sale related to the advice generated in step S1403 in the purchase available amount.
  • Step S1402 The advice generation unit 321 generates an advice on the purchase of a brand or a product based on the purchasable amount of money calculated in step S1401.
  • Step S1403 The advice generation unit 321 generates an advice on the sale of a brand or a product related to the advice generated in step S1402.
  • Step S1404 The advice generation unit 321 repeats the processing of steps S1401 to S1403. In the processing of steps S1401 to S1403, the subsequent processing is executed inheriting the result of the previous processing.
  • FIG. 15 is a diagram showing a framework of advice generation according to the present embodiment.
  • the terminal 2 transmits data of each item of the constraint condition selected by the user to the server 3.
  • the advice generation unit 321 of the server 3 stores the course in which the constraint condition is set in the storage unit 33. This determines the framework of the advice and prepares to generate a continuous advice. By setting course constraints, various courses with different characters are set, and different types of advice are generated.
  • the advice generation unit 321 generates an advice according to the constraint set in the course according to the investment amount. That is, as shown in FIG. 15, the advice generation unit 321 creates a course with restrictions on trading, which is a large framework of advice including the target product, investment amount, start time, end time, adviser, etc. Generate advice under that course.
  • the advice generation unit 321 generates an advice under a financial constraint of 1 million yen.
  • the advice generation unit 321 generates advice by targeting the TSE portion of the Japanese stock.
  • the advice generation unit 321 gives advice on selling and buying limited to semiconductor related stocks. (4) The advice generation unit 321 generates robot-related advice for 1 million yen for ETFs.
  • the advice generation unit 321 can generate an advice as appropriate as possible under the constraint condition by setting the constraint condition instead of generating the advice completely freely.
  • the constraints include the constraint of the course and the constraint of the advice generation unit 321.
  • the constraint condition of the course is a large framework of what amount of money, who advises, what (target), and (when) advice is given by the advice generation unit 321. Since the constraint does not change until the end of the course, the advice generation unit 321 generates an advice under the constraint.
  • the actual investment amount is specified by the calculated available purchase price and the buying advice within the available purchase price.
  • the brand or product targeted for buying advice is selected from those registered in the database within the scope of the brand or product to be invested.
  • a course manager is assigned to each course.
  • an adviser, a user, a manager, etc. are assigned.
  • the advice generation unit 321 generates an advice according to the investment amount as a constraint condition. For example, the advice generation unit 321 performs different advice even at the same timing between the case where the constraint condition is the investment amount of 300,000 yen and the case where the constraint condition is the investment amount of 10 million yen.
  • the investment amount is limited financially by the initial amount (start amount) at the beginning of the course and during the advice period “initial amount + trading profit + loss amount” and advice is provided within that range. These investment amounts become the upper limit of the purchase amount.
  • the advice generation unit 321 Since the advice generation unit 321 generates an advice in which the number of stocks or products differs depending on the amount of investment and the stocks or products differ depending on the amount of investment, providing advice from the user's perspective according to the amount of investment Can.
  • the advice generation unit 321 by generating advice within the range of the limited investment amount by the advice generation unit 321, it is possible to give rise to a large growth of funds and to give advice to further increase the large growth of funds. . On the other hand, if there is a loss, it is possible to give appropriate advice.
  • the advice generation unit 321 expands the possibility if profit is obtained, and conversely, if the loss is generated, the restriction becomes severe.
  • the advice can be generated dynamically by the increase and decrease of investment funds, such as advice on
  • the advice generation unit 321 In the advice data generation system 10, the advice generation unit 321 generates an advice according to the start time of the course as the constraint condition. Different course start times, different courses, different course managers, and different advice content. The advice generation unit 321 generates different advices, for example, between January 2013 start and January 2018 start.
  • the course advice starts from the start time. If the end time of the course is set, the course advice ends at the end time. In addition, the case where there is no restriction on the end time is also acceptable.
  • the advice generation unit 321 includes advice that changes according to the start time, and the content to be advised from the purchase price of the start time is restricted.
  • the advice according to the start time A and the advice according to the start time B are different.
  • the advice generation unit 321 is also restricted by the end time of the course. If there is an end time of the advice, the advice generation unit 321 generates the advice within a certain time limit. That is, the advice generation unit 321 is determined based on a predetermined standard such as a determined time limit (for example, three years etc.), a time limit to end when the target is reached (for example, when the evaluation amount is doubled etc.) Generate advice under the constraint of "time to end”. If there is no end time of the advice, the advice generation unit 321 generates the advice indefinitely.
  • a predetermined standard such as a determined time limit (for example, three years etc.), a time limit to end when the target is reached (for example, when the evaluation amount is doubled etc.) Generate advice under the constraint of "time to end”. If there is no end time of the advice, the advice generation unit 321 generates the advice indefinitely.
  • the advice generation unit 321 subsequently ends (or shrinks) to rank up with the evaluation amount etc., and moves to another course (a course in which other constraint conditions are set). To be possible.
  • the advice data generation system 10 gives an advice start time
  • the user has to prepare funds in time with the disclosure time.
  • it is a place where they want immediate advice when their investment funds are ready.
  • the interactive advice data generation system 10 allows the user to decide when to start the course. Then, the interactive advice data generation system 10 can meet the needs of the user as described above, and can generate advice data in accordance with the user's desired time.
  • the advice generation unit 321 generates an advice according to an investment target as a constraint condition.
  • the advice generation unit 321 generates different advices when the stock or product to be invested is restricted.
  • the stocks or products to be invested include Japanese stocks, US stocks, Chinese stocks, Hong Kong stocks, futures, FX, ETFs, mutual funds, bonds, etc.
  • the advice generation unit 321 narrows down the population of the course, determines the trading target within the range, and generates the advice according to the restriction of the brand or the product.
  • the brand or product to be advised is a brand or product registered in the database of the storage unit 33 in this population. The registration of the brand or product in the database may be made at any time.
  • the relationship between the investment object as this restriction, the brand or product registered in the database, and the brand or product targeted for buying advice is as follows.
  • Scope of investment target ⁇ ⁇ Scope of database registration ⁇ ⁇ Scope of advice target
  • the advice generation unit 321 registers promising stocks among them in the database and places them under course management. Depending on changes in technical indicators, business performance trends, etc., it will be the subject of buying advice or selling advice.
  • the advice generation unit 321 generates different advices at the same timing even when the investment target is a Japanese share, the investment target is a Chinese share, and the investment target is an ETF. It will be. That is, depending on the investment target, advice is limited.
  • Database registration is required even if there are no restrictions. In this case, whatever brand or product, if it is a brand or product registered in the database, it is the target of buying advice. Moreover, it is also possible to narrow down the population under complex conditions, and it is also possible to narrow down using search condition expressions such as AND and OR.
  • Buy advice stocks or products are eventually registered in the generation process, even if they are not registered from the beginning.
  • the categories include the following examples.
  • the cut of the category is various.
  • ⁇ By type shares, FX, ETF, mutual fund, REIT, bond, etc.
  • Type of share Japanese share, US share, Chinese share, Hong Kong share, Asian share etc.
  • Thematic Robot-related stocks, robot-related ETFs, semiconductor-related stocks, semiconductor-related ETFs
  • Semiconductor-related in general including ETFs, stocks, investment trusts, etc.) -By industry (financial stocks, ETFs consisting of financial stocks, real estate stocks etc.)
  • By ETF type Domestic bond ETF, foreign bond ETF, domestic stock ETF, etc.
  • Chart index minus stock of moving average deviation rate
  • Performance indicators shares with dividends, shares with coupons, shares with increased revenues, etc.
  • Stock index such as stocks less than PER 10 times
  • Market indicators (Trading value of 1 billion yen or more per day, total market value of 100 billion y
  • advice generation unit 321 is subject to the constraint of the investment target of making only robot-related stocks as stock to be purchased.
  • the TSE partial market only for example, the TSE partial market only, overseas ETFs, yen-to-yen exchange, average daily trading value of 1 billion yen or more, etc. There is a cut.
  • TSE partial stocks are divided into different tables and managed in the database according to the difference in classification method such as market table, business type table and the like. Therefore, if the market is limited to TSE partial stocks, the population can be prepared immediately if the market is extracted using TSE partial data.
  • FIG. 16 is a diagram showing a configuration example of the brand or product database DB1 according to the present embodiment.
  • the database DB1 is a database of "stock" as the type of investment target product, and has a configuration in which the theme is added.
  • a theme table for managing themes may be provided separately from the database DB1, and the theme and the brand code may be associated with each other in the theme table.
  • the advice generation unit 321 generates an advice according to the adviser as the constraint condition.
  • the advice generation unit 321 changes the advice according to the adviser, and is restricted by the adviser.
  • the advice generation unit 321 generates, for example, different advices for the advice of the adviser A and the advice of the adviser B.
  • Advisors include individuals, corporations, teams, organizations, etc.
  • the adviser further includes a robot, artificial intelligence (AI), and the like.
  • AI artificial intelligence
  • the robot When the robot is an adviser, there is a configuration in which the robot generates trading data as a trading data provider and presents it to the user by mail distribution or the like.
  • Other constraint settings and changes are automated, and advice can also be automated. Note that there are stages in the level of automation, such as setting and changing constraint conditions manually, and automating advice thereafter.
  • the advice data generation system 10 has a two-way interactive form depending on who decides the constraints of the course. As shown in FIG. 15, the course manager includes an adviser, a user, and a manager.
  • the characteristic of the advice data generation system 10 largely changes depending on who the user, the manager, or the adviser (including the robot) sets the course, and it is possible to have an interactive form.
  • the terminal 2 transmits the data of the constraint condition to the server 3, whereby the server 3 sets the course, thereby providing continuity.
  • An environment in which the advice data generation system 10 operates is established.
  • the manager decides who the course manager is. As the relationship between the course manager and the adviser, the course manager can choose an adviser to give advice.
  • the manager When the manager is the course manager, For example, if the manager decides that the initial amount is 1 million yen, the start time is today, the investment target is Japanese shares, and the adviser is the investment adviser company X, the framework for giving advice is decided, and the course is decided. The investment adviser company X generates advice under this constraint.
  • the manager decides that the initial amount of 1 million yen, the start time is from today, the investment target is ETF, and the adviser is a robot, the ETF is used to generate advice.
  • the ETF is used to generate advice.
  • a course is provided to give a completely different advice from the above-mentioned investment management company X.
  • a robot adviser is assumed, and for example, a course for giving advice on US stocks with an initial amount of 1 million yen will be started next month with the robot as the adviser.
  • Trading conditions are selected by the user from choices. Trading conditions can be automated depending on how far automation is advanced, such as leaving it to a robot or inputting an algorithm by itself.
  • the course management is divided into courses, and the course manager can be changed to generate dynamic advice with different characteristics for each course.
  • the user can try various trading conditions.
  • the user can receive advice under the conditions set by himself. Although various trading conditions were initially set on a dividend yield basis, they were not good, so it is possible to explore other conditions.
  • the advice data generation system 10 manages, evaluates, and displays the advice generated for each course by determining the name and the manager representing the characteristic of the course, and setting the constraint conditions.
  • the advice generation unit 321 generates an advice under various constraints in a course in which certain constraints are set. The results are divided, the display is divided, and the advice is divided. Management also takes place on a course-by-course basis. For example, a course in which the robot advisor generates advice data is set using ETF with a limited investment amount of 1 million yen.
  • a course is stored in the storage unit 33 of the server 3, and advice data is associated with each course.
  • the advice generation unit 321 generates advice data under the constraint conditions of the course.
  • Condition setting who sets the condition, and further determines whether it is public or private.
  • Condition setting is divided into a part determined by the administrator, a part determined by the user, and a part determined by the adviser (including a robot).
  • the course administrator decides whether each item is to be set to the default value, the input value, or the selection system.
  • one-way advice generation in which advice is generated in a one-way way from the manager, the adviser, etc., and interactive advice generation meeting the user's request.
  • the administrator sets most of the conditions on the management screen.
  • the administrator increases or decreases the items that can be selected or input by the user, thereby determining how far the user can become an interactive system tailored to the user.
  • advice data having continuity is generated under each control condition by determining each constraint condition, conditional expression, and table that can be set on the user's my page.
  • the administrator decides the conditions, the user receives the same advice data.
  • the administrator can change a certain condition, and the condition can be set whether it is public or private, and the user can receive a buying advice email or a selling advice email, but the logic is public or non-public. You can change the publication.
  • the administrator manages the course and permits the user to set the conditions, even for the same course, the conditions are different for each user, and various advice data are generated for each user. Since the user can set conditions as desired under the same constraint and the same course, performance competition among the users is also possible. When the user is an administrator and the user himself sets the conditions, various conditions can be put in the test to enable verification.
  • Embodiment 4 The fourth embodiment of the present invention is described below with reference to FIG. In addition, about the member which has the same function as the member demonstrated in Embodiment 1, 2, and 3 for convenience of explanation, the same code
  • the advice data generation system 10 is an advice data generation system that generates a plurality of advices according to a course according to the investment amount, and is a cash ratio data indicating the ratio of cash to be left in case of buying brand or product for each course.
  • Purchase number data indicating the number of purchases of brand or product in the case of brand or product purchase
  • value distribution data indicating distribution of purchase price of brand or product in the case of brand or product purchase
  • brand or product The plurality of advices are generated according to the storage unit 33 storing trading conditions data indicating purchasing conditions and selling conditions, the cash ratio data, the number of purchases data, the amount distribution data, and the trading conditions data.
  • the course manager decides whether to set conditions for generating the advice data. If all of these conditions are set, the advice data generation system 10 is fully automated.
  • the advice generation unit 321 refers to the stock price, minimum unit, and the like of ⁇ ⁇ from the database, and determines 100 million yen buying advice with a total of 200 shares when 100 shares ⁇ 5000 yen is the minimum purchase unit, and sends mail. And store the buying advice data in a database. The same applies to other brands.
  • the advice generation unit 321 If the stock price of ⁇ becomes 6000 yen after 5 stocks are advised and the index of the database falls under the selling condition, the advice generation unit 321 generates 200 stocks of sales advice, and the data of the sales advice In the database.
  • the advice data generation system 10 is not only a full-automatic system, but may be a semi-automatic system that is partially processed by the user, with some user input.
  • Example of partial automation In the case where only the decision conditions of buying advice are not automated, the course manager is presented with the number of products and the amount of money that can be purchased, and by selecting stocks that can be bought within the range, mail delivery of buying advice is performed. After that, if the condition for sale is met, the system delivers a mail of advice for sale, and the available purchase price is automatically calculated again. Thus, there is also a semi-automatic usage, and the range of automation can be adjusted.
  • the buying advice is automated, but a list of stock holdings is generated, and the selling advice mail is delivered by selecting the selling stocks.
  • the repurchase amount is automatically calculated again, and a mail of buying advice is delivered including the number of shares for which the stock meeting the buying condition was found. Then, the renewed stock list is presented again.
  • the degree of automation of advice generation is adjusted.
  • the advice generation unit 321 generates advice data meeting the conditions. If the result is poor, the advice generation unit 321 automates even condition change such as generation of advice data under different conditions in consideration of that.
  • Condition change can control the degree of automation, such as selecting from options.
  • the degree of automation can be divided or tested depending on the subject to be advised. For example, if rebalancing is automated to maintain a certain ratio, stock raising and stock allocation increase, advice on selling stocks and advice on buying bonds will be generated, and the amount allocation of stocks and bonds It is possible to give advice that will be kept constant.
  • the purchaseable amount is calculated and recalculated after buying advice, selling advice and depositing / dispensing according to "initial amount + trading profit + loss amount-stock amount purchased amount", and this amount is restricted. It is restricted by the advice in the inside.
  • This process is always performed when the available money changes not only at the beginning but also at purchase, sale, deposit and withdrawal. This will ensure the continuity of the advice.
  • the advice generation unit 321 receives the trading profit and loss data, the deposit and withdrawal data, the purchase price of the stock, and the initial amount from the aggregation DB, and receives the calculation or the numerical value calculated in the database.
  • the advice generation unit 321 generates a buying advice within this range, and after generating the buying advice, calculates again an increase in the purchase price of the owned stock. It is always constrained by the amount of money that is recalculated and calculated each time buying advice and selling advice.
  • the advice data generation system 10 generates an advice under the limitation of the money while being limited by the series of actions.
  • the advice data generation system 10 is a system for continuously generating advice, but after buying advice, after recalculating the possible purchase price after selling advice, further advice becomes possible, and if profit is obtained, If the range of advice spreads, and conversely loss occurs, it becomes possible to stand in the same view as the user by making the advice more difficult.
  • the repetition of buying advice and selling advice creates continuity in the course and changes the brand.
  • the number-of-purchase data is obtained by correlating the purchase available amount with the purchase number of the purchase available amount, and the advice generation unit 321 performs the purchase when generating the purchase advice.
  • the number of purchases is determined according to the amount of money available for purchase.
  • FIG. 17A is a view showing a configuration example of purchase number data according to the present embodiment.
  • the number-of-purchase data is data in which the range of the purchase available money amount is associated with the number of brands or commodities. For example, when the amount of money that can be purchased is up to 300,000 yen, the number of purchases of a brand or product is one. When the amount of money available for purchase is 300,000 yen to 1,000,000 yen, the number of brands or products purchased is three.
  • the initial amount is 1 million yen and the cash ratio is 10%
  • 900,000 yen will be the purchase limit.
  • the number of purchases is determined to be 3 stocks.
  • the purchase limit will be 1.08 million yen
  • the range of the available purchase amount will be 1 million yen or more
  • the advice data is generated in which the number of products dynamically changes, such as the possible amount of money to 5 stocks. This allows for the advice that the greater the amount of money, the better the variance.
  • the profit / loss ratio may be above or below the average.
  • the advice data generation system 10 it is possible to control how many stocks are to be bought and advised in this table, and the number of products (or the number of stocks) is specified by collation.
  • the cash ratio is a default value, an adviser decides according to the current market conditions, or a user decides in consideration of risks such as market trends. It is managed so that the fixed cash ratio can be maintained.
  • Initial amount + trading profit and loss amount + purchase amount of stock holdings purchaseable amount
  • Purchaseable amount ⁇ (1-cash ratio) purchase limit amount Under the purchase limit amount and the above restriction conditions, The determined cash ratio can be kept to determine the number.
  • the investment target is not limited, determine the number of products in this phase. For example, if it is determined to be three types, the types will be determined in the later steps, such as ETFs, mutual funds, and bonds.
  • the purchase limit is calculated from the purchase available amount and the cash ratio granted, and the number of purchases of the purchased brand (product) is determined from the purchase limit.
  • This process is followed not only at the beginning but also when the available money changes due to sales or deposits and withdrawals. As a result, continuity is secured, and the profit increases with the progress of diversification, and advice is generated that can perform risk diversification.
  • the number of items (goods) that can usually be bought is determined by the amount of purchase limit. For example, in the case of stocks, if it is 300,000 yen, 1 stock, 1 million yen will be 3 stocks, if it is 10 million yen, 15 stocks, it changes according to the purchase price, and the more profit it is Close to the average.
  • the money amount distribution data is one in which the investment object is associated with the distribution of the purchase amount in the investment object, and the advice generation unit 321 generates the buying advice,
  • the distribution of the purchase price is determined according to the investment target with reference to the money distribution data.
  • the advice generation unit 321 determines the amount distribution for each brand or product. It may be equally distributed, or in the case where a stock is determined based on the ranking, a higher weight may be given. According to the conditions decided here, it is possible to allocate the amount on a certain basis. In the case of no limit, even distribution is performed as a default.
  • FIG. 17B is a view showing a configuration example of money amount distribution data according to the present embodiment.
  • the investment target is ETF
  • the number of purchases of stocks or commodities is 5, for example, 40% domestic stock type, 20% bond type, 20% foreign bond type, foreign stock It becomes 10%, 10% of other money allocation.
  • the investment target is a stock, if there are three stocks or commodities purchased, the first 50%, second 30% and third 20% will be allocated.
  • the second offer advice data when the second offer advice data is provided, it is also possible to change the amount distribution (rebalance) according to the rate of change of the evaluation value. In this case, buying advice etc. is adjusted in order to hold the designated amount distribution.
  • the cash ratio is set to 40% as an emergency measure, and as shown in FIG.
  • the domestic stock type is 50% and the domestic bond type is 50% unconditionally, assuming that the number of brands or products purchased is two. In this way, adjustments can be made to avoid risks.
  • this step determines the amount distribution among brands or products, and the number of purchases of the brand or product and the purchase limit are specified in the above (claim 13), the purchase limit for each brand or product is specified. Be done.
  • the amount limit of the purchase limit is 1 million yen and the amount distribution of the bond type of ETF is 30%, 300,000 yen will be the purchase limit amount of the bond type of ETF.
  • the amount allocation differs for each brand or product.
  • the range of advice can be greatly expanded. For example, it is possible to make an advice such as gradually reducing the amount distribution of the brand, or increasing the amount to a safe asset as the valuation increases.
  • the advice data generation system 10 In the advice data generation system 10, when a new brand or product not registered in the database of the storage unit 33 is bought and advised, prior to that, the database of the brand or product is input. By this input, a new brand or product is registered as a managed brand or managed product and placed under the management of this course. In the case of stocks, by enhancing stock price data, split data, dividend data, minimum purchase unit data, performance data, and the like as necessary, indexes important for the judgment of trading are accumulated. The determination as to whether the conditions for buying, the conditions for selling, etc. apply also is made by referring to these indicators. Database registration is an essential step in the automation of buying advice and selling advice.
  • the advice generation unit 321 may register, or may register a promising brand or product in advance.
  • the advice data generation system 10 it is premised to advise to buy and sell stocks or products registered in the database.
  • the target is managed systematically, with only the registered brand or product being the target of the advice.
  • the trading condition table includes an index relating to the purchase of a brand or a product
  • the advice generation unit 321 determines one brand or one product from the purchaseable amount, the number of purchases, and the distribution of the purchase price. Calculate the per-purchase limit amount, and when generating a buying advice, identify the brand or product to be purchased with reference to the product ranking for the indicator and the purchase limit amount. This is processing of how to decide a specific buying advice issue.
  • the upper limit of how much you can buy for each product is specified for each brand. If the brand name or product name is specifically determined from the brand or product for which the minimum buying unit is determined, the quantity is also automatically determined.
  • the minimum buying unit and the unit price (stock price) are automatically calculated by reading out values from the database for each brand or product, and if the brand name or product name is determined, the quantity that can be purchased is determined automatically.
  • the number of brands or products and the purchase limit amount are determined, and if the even distribution is determined, the purchase limit amount of each brand or product is determined, so the quantity of each brand or product is determined here.
  • the amount is determined if the minimum purchase unit amount can be referred since the upper limit amount is determined.
  • the decision on the brand is crucial to the advice. Automation is possible by determining with reference to data registered in the database.
  • a specific investment target (purchase advice brand or product) within the purchasable range is determined under the purchase limit limited for each brand and the above-mentioned restriction conditions.
  • sifting is further performed under the following conditions from the population stocks extracted by the above constraint conditions.
  • the number of unit shares is determined and the quantity (number of shares) is determined by the purchase limit amount and the minimum purchase amount. It may be determined by a complex conditional expression, or it may be determined from what kind of cut the population is finally selected.
  • the number of stocks or products to be bought and the amount allocation are determined by the processing up to this point, and the quantity (number of shares) is also determined because the respective brand names or product names are determined. There are various conditions, and it may be specified by the adviser even if it does not specify the stock selection criteria. It is also conceivable that the brand is given by input. Therefore, the brand determination process may use another system or the like.
  • conditional expression used in this process for example, various patterns can be assumed, such as determining stocks in the order of the top ranking in the forecast growth yield in this term, etc. It is also possible in the form, and it is also possible that the customer presents.
  • each adviser decides which brand or product is the subject of advice, and it may be decided based on quantitative data alone, or it may be decided taking qualitative factors into consideration, The case is conceivable.
  • management is performed by limiting to brand products registered in the database.
  • the trading condition data includes the purchase timing of the brand or the product, or the purchase price of the brand or the commodity
  • the advice generation unit 321 refers to the trading condition data when generating the buying advice.
  • FIG. 17C is a view showing a configuration example of trading condition data according to the present embodiment.
  • the purchase time index, purchase time, purchase price, and profit determination condition is described.
  • the purchase time may be the same time on the same day as the stock is determined, or may be determined on the day when the stock price meets the conditions, referring to the technical index.
  • the purchase date and the market price are set, and if one is decided, the other is decided.
  • the day when you buy it will be the moment when you decide on what to buy, and the final decision on buying advice.
  • stock prices real-time market prices
  • the contract price is decided, so a reference price such as yesterday's closing price may be displayed. In this case, it is possible to correct the buying advice price later.
  • Registration and distribution of buying advice data Various kinds of processing can be considered by registration in the database, registration in the database, delivery of e-mail to the user, uploading on a member site, uploading in an application, etc. There are various transmission methods, and it is also conceivable that a user or an agent contracted by the user may be delivered.
  • Delivery notification to members' sites, application notifications, etc. addressed to the administrator, addressed to the adviser, addressed to the user, or addressed to the first-class investment adviser contractor (operator) contracted with the user, based on the advice In some cases, it may be possible to outsource operations.
  • the advice data is actually delivered to the user.
  • the generated advice data is recorded in a database, is automatically sent to the display system, is variously calculated, and is sent, notified, and distributed to related parties such as users.
  • the trading condition data includes a condition for determining profits
  • the advice generation unit 321 generates the buying advice with reference to the trading condition data when generating a selling advice. From the target brand or product, the brand or product satisfying the condition for determining the profit is specified, and advice on selling the brand or product is generated.
  • RSI Relative Strength Index
  • target indicators can be matched in a database, and sell advice will be generated if sales conditions apply.
  • the algorithm of the sale advice generation can be determined to be public or private.
  • the purchase limit changes, so that by repeating the generation of the buy advice, the brand or product is also changed, and the continuous advice continues.
  • the sale decision is made by matching various conditions.
  • the selling decision can be made by various methods. it can.
  • the advice generation unit 321 registers sales advice data in a database. After that, delivery to a manager site, an adviser, a user, or a first-class investment advisor (contractor) who has contracted with the user is performed, such as updating to a member site, application notification, mail delivery, and the like. There is also a possibility of outsourcing operations based on the advice.
  • advice data generation system 10 (Accumulate, aggregate, and extract trading data etc. in a database)
  • data necessary for determining whether to buy or sell a registered brand or product, buy and sell data, and data needed to display buy and sell data are stored in a database.
  • the possible purchase amount is calculated as the sum of trading gains and losses, the amount of deposit and withdrawal, and the total value of the initial amount minus the total purchase amount of the holdings. This value is recalculated each time it is sold and delivered to the advice generation unit 321.
  • the initial value, the deposit and withdrawal amount, the total of trading profit and loss, the total unrealized gain and loss, and the total evaluation value, which is the total value of cash, become important indicators, and are sequentially calculated used.
  • the calculated values necessary for the condition review are calculated one by one. In particular, when the latest trading profit or loss is negative or unrealized profit or loss is negative, each condition is reviewed. In this way, it is possible to analyze at any time what is wrong and no result.
  • the database stores a stock master table, stock price data of stocks, a series of stock data such as technical data, trading advice data, actual trading data, and the like. Each time, necessary data is read, calculated, and aggregated as needed.
  • advice data generation system 10 information on not only stocks to be traded but also information on stocks or goods that are likely to trade is registered in the stock master table, and various information is accumulated to make changes more dynamic.
  • System that can make precise judgments according to The server 3 is provided with functions such as calculation, display, and recalculation of numeric data.
  • the display unit 23 can display a graph. Further, by accumulating information on past stock prices, market values, etc., the advice generation unit 321 can use the accumulated information to provide a judgment index, calculate the amount of money that can be purchased, and the like.
  • the advice generation unit 321 determines whether the outcome of the course satisfies the rank-up condition.
  • the rank-up condition is a condition serving as a standard for determining whether to increase the investment amount of the course.
  • Indicators included in the rank-up condition include multiple conditions such as asset growth rate by advice, advice profit, evaluation value by advice, actual trading data figures, years of operation, ratio with indicators such as Nikkei average, questionnaire response results, etc. May be included.
  • the advice generation unit 321 sets new constraint conditions, including an investment amount and the like according to the outcome of the course before rank-up, as a new course.
  • the first course was a 1 million yen course targeting a partial listing of Japanese stocks, but the evaluation amount increased to 2 million yen and doubled, so the rank-up condition was satisfied. Therefore, the advice generation unit 321 shifts to a 2 million yen course, broadens the scope to Japanese stocks in general, and includes advice such as Mothers stocks with higher risk as advice, which gives profit more profit. It can be performed. If the evaluation amount exceeds 4 million yen in the 2 million yen course, it will be converted into cash and move to a new course in which the constraint condition in which 4 million yen is the investment amount is set. In addition, the advice generation unit 321 may generate the advice for terminating the course by cashing the original course funds. Also, the user may half cash the original course and newly open a course with the half cashed investment amount as a constraint.
  • the advice generation unit 321 cashes out 1 million yen, launches a new course with 1 million yen course, and uses the safety measures using ETF to make a profit You can secure the remaining 1 million yen worth of conventional advice, and give advice such as cutting off the profit and dividing the course.
  • the advice generation unit 321 converts all or part of the funds into cash, changes the cashed amount into the investment amount, and sets new constraint conditions. Generate advice under the course.
  • the storage unit 33 stores rank-up condition data indicating a rank-up condition.
  • rank-up condition data for example, when the asset growth rate due to advice is doubled, the course is ended, converted into cash, and the process moves to a new course in which a new constraint condition is set. Is included.
  • the advice generation unit 321 repeats the generation of the advice under the course in which the same constraint condition is set until the outcome of the course satisfies the rank-up condition.
  • the advice generation unit 321 changes the advice by increasing the ratio of small stocks with rough prices, changing the method of dispersion, changing the investment target, the amount of money, and the like. Therefore, the mechanism for transitioning to a new course in which new constraint conditions are set contributes to the continuity of advice generation between courses. The ability to move to a new course will allow a wider range of advice. For example, when funding is increased, it can be extended to advise on more risky US stocks and change advisors.
  • the advice generation unit 321 performs the condition change determination if the result of the course does not satisfy the rank-up condition and there is a condition setting relating to trading.
  • This judgment condition follows data such as unrealized gains and losses, trading gains and losses, etc., and serves as a standard for reviewing trading indicators.
  • the determination conditions include, for example, the case where the gain or loss on trading is negative, the case where the unrealized gain or loss exceeds-(minus) 10%, and the asset growth rate becomes negative.
  • the advice generation unit 321 determines whether to buy and sell on the same buying and selling conditions again or to buy and sell by changing the buying and selling conditions. If the criteria of judgment conditions are tightened, each item of trading conditions will be reviewed frequently, and if the criteria of judgment conditions are loosened, the condition of trading advice is controlled such that advice generation under the same trading conditions is continued. Be done.
  • the advice generation unit 321 In the advice data generation system 10, the advice generation unit 321 generates a trading advice, and repeats the advice generation processing from the calculation of the purchase available amount when the purchase available amount changes or there is a deposit or withdrawal.
  • the stock exchange is performed by repeating the advice generation process.
  • the advice generation unit 321 can generate advice with continuity even with the same fund only because there is selling advice, and since there is repetition, it is continuous. Advice is generated.
  • the advice generation unit 321 generates an advice for replacing a brand or a product.
  • the advice generation unit 321 repeats the processing from calculation of the purchase available price every time the available purchase price changes. Specifically, when the generation of the buying advice is completed and registered in the database, the generation of the selling advice is completed and registered in the database, when there is a deposit or withdrawal, when the indicator corresponds to the buying condition, etc. It is.
  • the advice generation unit 321 refers to the generated buying advice and selling advice data, and the actual trading information of the user, and provides advice such that the user's investment content approaches the advice.
  • the advice generating unit 321 When generating the buying advice, the advice generating unit 321 registers the buying advice in the database, and collates the data of the buying advice with the actual trading data. Matching is done with the brand or product and the date. That is, the advice generation unit 321 collates the brand name or product name of the advice data with the brand name or product name included in the actual trading data, compares the same data, and the actual trading date is It is recognized that what has been done later is trading data conducted according to the advice.
  • Trading data and advice data are included in the database, so it is possible to match brand names or product names, and the user becomes an incentive to follow advice by recognizing deviations, and advisers are Further advice can be generated by recognizing the divergence from the advice.
  • the advice data can be compared with the actual trading data, and the difference, deviation can be analyzed to further generate the advice. And we can expect further improvement of advice.
  • the difference between the trading data and the advice data it is possible to set a guideline for the future, such as how the user should behave, how the actual trading and the trading according to the advice differ. it can.
  • the advice data generation system 10 includes an advice generation unit 321 that dynamically generates an advice, a storage unit 33 that stores a course in which the constraint condition of the advice generation unit 321 is set, and a display that displays dynamically changing advice. And a unit 23.
  • the display unit 23 for displaying the trading advice data generated by the advice generation unit 321 includes a stock holding list, a valuation amount transition chart, a valuation amount list, a trading profit / loss list, an unlisted profit / loss list, etc. Display
  • the trading data is consolidated in a database, and the display unit 23 displays a stock holding list, a valuation price transition chart, a valuation price chart, trading, in order to display the trading data in an easy-to-understand manner to the user.
  • Trading data managed for each course is itself a mere collection of data, but stock holdings change and stock prices also fluctuate due to buying and selling of stocks or goods, replacement of stocks or goods, changes in monetary allocation, etc.
  • Etc it is data that changes every moment. It is required to display it accurately and easily. For the user, it is very important how the advice has been generated and how it is now, how it was in the past, and how it deviates from the actual trading data.
  • the advice generation unit 321 sequentially generates trading advice data and registers it in the database.
  • the stored trading advice data is transmitted to the user by e-mail, updating of a member site, etc., but is also output to the display unit 23.
  • trading advice data, deposit and withdrawal data, stock price data, actual trading data, stock split data, and the like are integrated and calculated.
  • the display unit 23 divides the data into functions and displays them in an easy-to-understand manner.
  • the server 3 calculates the trading history of trading advice data, and transmits data indicating the trading history to the terminal 2.
  • the terminal 2 receives data indicating the trading history of trading advice data from the server 3 and causes the display unit 23 to display the trading history of trading advice data indicated by the received data.
  • FIG. 6 is a view showing a display example of a screen of “trading history”. As shown in FIG. 6, the control unit 22 displays the name of the brand, the number of shares, the date of buying advice, the stock price and amount, the date of sale, the stock price and price, the rate of return, the trading profit / loss A screen including is displayed on the display unit 23.
  • the display unit 23 displays a table of trading profit and loss tables. That is, the display unit 23 extracts and displays from the database trading data which has been sold and sold, that is, trading data whose profit and loss have been determined due to opposite trading.
  • the display of the trading profit and loss table enables the display of past offered advice that has been traded. For those who receive advice, it is easy to see how past advice has been given.
  • the terminal 2 receives data indicating the evaluation value breakdown table of the trading advice data from the server 3, and causes the display unit 23 to display the evaluation price breakdown table of the trading advice data indicated by the received data.
  • the terminal 2 receives data indicating the evaluation value breakdown table of the trading advice data from the server 3 and causes the display unit 23 to display the evaluation price breakdown table of the trading advice data indicated by the received data.
  • the current valuation consists of unrealized gains and losses, trading gains and losses, in and out amounts, starting amount, current cash balances, unrealized gains and losses are calculated from the unlisted profit and loss list, and trading gains and losses are calculated from the trading loss table, and a summary is displayed Be done.
  • the display of the evaluation value breakdown table of the trading advice data makes it possible to display the breakdown of the current evaluation value, and clears the whole picture of the advice accumulated from the past. For those who receive advice, it is possible to check the current appearance of the advice so far.
  • the evaluation index for each stock includes a brand name or product name, advice date, number of shares, stock price and amount at the time of buying advice, current stock price and amount, rate of return, valuation loss and gain. Portfolio refers to the state of trading advice data at that time.
  • the display unit 23 displays the included profit and loss table.
  • the display unit 23 extracts only the trades that have not traded the trade data, and displays the unrealized profit and loss table by comparing the purchase price of the brand with the current evaluation value.
  • an evaluation amount is calculated as needed, and the database stores the evaluation amount as past data. All data at the past point in time includes data on sales and losses at that time, unrealized gains and losses, and breakdown of valuations.
  • the display unit 23 displays an evaluation value transition table including data at that time.
  • the display unit 23 displays the valuation price summary at that time, a list of unrealized gains and losses, and the like. Since the dates are specified, it becomes possible to read those data from the database, making it easy to follow the progress to the present time. Further, the date on which the transaction was made is in a state where the mark is attached, and when the user moves the cursor to the mark, the display unit 23 displays the breakdown of the transaction on that day.
  • the buying and selling advice data curve (evaluation amount transition table) shows a plurality of advices including advices related to at least one of a plurality of items and items of cash amount included in the past presented advice. is there.
  • the difference between the buying and selling advice data curve (evaluated value transition table) and the buying and selling performance curve is generated by referring to the buying and selling advice data according to the above advice and the actual buying and selling information of the user.
  • Advice Indicates advice that approaches the data.
  • the advice generating unit 321 refers to the trading advice data based on the advice in step S1202 and the actual trading information of the user in step S1206, and generates an advice such that the user's investment content approaches the trading advice data.
  • the terminal 2 causes the display unit 23 to display such advice.
  • the terminal 2 causes the display unit 23 to display a model actual difference between the sales advice data curve (evaluated value transition table) and the sales performance curve.
  • the control unit 32 causes the display unit 23 to display the model performance difference according to the line segments of the double arrows.
  • the model performance difference is the difference between the trading advice data and the trading performance at the present time, but how far did the trading advice data and the trading performance diverge in the left direction along the time axis from that point on? Is displayed, so it displays advice on how to buy and sell.
  • control unit 32 causes the display unit 23 to display an advice that "the model and the performance are separated from here.” This is advice that brings the user's investment content closer to the trading advice data.
  • the terminal 2 displays the random model indicating what happened when the user did not make the recommended sales, thereby obtaining the sales advice data and the random model. You may display the deviation of the
  • the trading data generated in the advice data generation system 10 is normally ordered by a private investor based on it to order a trading order from a securities company to complete the trading.
  • the present invention can also be applied to a business model in which a manager contracts with an investor, the investor provides trading data, and the manager substitutes for an order. It can also be applied to automatic ordering models.
  • the advice data generation method generates a buying advice in the range of the above-mentioned purchase available amount with reference to the step of storing unregistered brand or product in the storage unit, the step of calculating the purchase available amount, and the above storage unit.
  • the above steps are repeated, including the steps of: performing the repurchase amount according to the buying advice; and generating the selling advice with reference to the storage unit.
  • Step of calculating available money Initially, the available price changes when generating the buying advice and when generating the selling advice.
  • the transaction data is calculated each time it is registered, and the amount is output to the advice generation unit 321.
  • the advice generating unit 321 generates a buying advice under the restriction of the available purchase price.
  • Step of registering brand or product if the brand or product is not registered in the database The items or products that may apply to the conditions and which may offer buying advice are registered at any time in the database, but registered if not registered.
  • the brand or product registered in the database can be referred to at the time of advice generation by storing various data as a managed product (brand). It is a condition that stocks of buying advice are registered in the database.
  • Step to generate buying advice In the case of generating the buying advice, the advice data is delivered by mail, updated at the member site, and registered in the database.
  • Step of generating sale advice In the case of generating the selling advice, the advice data is sent by mail, updated at the member site, and registered in the database.
  • Advice each step It is an important step in generating advice data. Advice is not generated at one time, but generated continuously by repeating. It is repeated when the amount of money that can be purchased has changed. Also, since only the stocks registered in the database go through the buying advice step and the amount of money is also restricted, the advice data is generated while being controlled by the system. Advice data on buying and selling is generated within the available purchase price.
  • the advice generation unit 321 buys a stock A buying advice with a fund of 500,000 yen among the purchase possible amounts of 1 million yen. Generate Since the brand A is an unregistered brand in the database, the advice generation unit 321 generates a buying advice after registering the brand A, and generates an advice within this constraint with a purchasable amount of 500,000 yen.
  • the server 3 generates a plurality of advices including the advice related to the items included in the past presented advice, but this is the invention described in the present specification.
  • the above advice may be configured to be generated by the terminal 2.
  • the terminal 2 may include the advice generation unit 321.
  • control block of the terminal 2 and the server 3 may be realized by a logic circuit (hardware) formed in an integrated circuit (IC chip) or the like. It may be realized by software using.
  • the terminal 2 and the server 3 have a CPU that executes an instruction of a program (advice generating program) that is software that implements each function, and the above program and various data are recorded readable by a computer (or CPU).
  • a ROM Read Only Memory
  • a storage device (these are referred to as "recording media")
  • a RAM Random Access Memory
  • the object of the present invention is achieved by the computer (or CPU) reading the program from the recording medium and executing the program.
  • the recording medium a “non-transitory tangible medium”, for example, a tape, a disk, a card, a semiconductor memory, a programmable logic circuit or the like can be used.
  • the program may be supplied to the computer via any transmission medium (communication network, broadcast wave, etc.) capable of transmitting the program.
  • any transmission medium communication network, broadcast wave, etc.
  • one aspect of the present invention can also be realized in the form of a data signal embedded in a carrier wave in which the program is embodied by electronic transmission.
  • advice presentation system 1 advice presentation system 2 terminal (terminal device) 3 Server (advice generator) 4 Network 10 Advice Data Generation System 23 Display Unit 33 Storage Unit 321 Advice Generation Unit

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Abstract

La présente invention fournit de manière continue un conseil selon l'investissement. Un serveur (3), qui génère, en tant que dispositif de génération de conseils, une pluralité d'éléments de conseil selon l'investissement, est équipé d'une unité de génération de conseils (321) qui génère une pluralité d'éléments de conseil incluant un conseil qui comprend un conseil présenté dans le passé et qui est associé à des articles d'une pluralité de marques et/ou à des montants d'argent liquide.
PCT/JP2018/024591 2017-06-30 2018-06-28 Dispositif de génération de conseils, système de présentation de conseils, programme de génération de conseils, système de génération de données de conseil et procédé de génération de données de conseil Ceased WO2019004358A1 (fr)

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JP2017-129759 2017-06-30
JP2018090956A JP2019012518A (ja) 2017-06-30 2018-05-09 アドバイス生成装置、アドバイス提示システム、アドバイス生成プログラム、および、アドバイスデータ生成システム
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JPH11110447A (ja) * 1997-10-06 1999-04-23 Pfps Kenkyukai:Kk 総合ポートフォリオ計画システム
JP2001125964A (ja) * 1999-10-26 2001-05-11 Golden Chrat Sha:Kk 資産運用助言システム及びそのプログラムを収録した記録媒体
JP2006318500A (ja) * 2001-07-31 2006-11-24 American Express Travel Related Services Co Inc ファイナンシャルプランニングおよびアドバイスを提供するシステムおよび方法
JP2003150779A (ja) * 2001-11-14 2003-05-23 Mizuho Trust & Banking Co Ltd パッシブ運用管理システム及びその方法
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