Price determination assistance device, price determination assistance method, and price determination assistance program

Abstract

To provide a price determination assistance device, a price determination assistance method, and a price determination assistance program that causes a computer to function as the price determination assistance device, which provide assistance in price determination of a traded item by optimizing a target price coefficient in a target price determination formula.SOLUTION: A price determination assistance device 10 is provided, comprising: an input unit for inputting a market index used in a target price determination formula for determining a price of a traded item based on the market index and one or more constraints a transaction of the traded item must satisfy; and an optimization unit for optimizing a target price coefficient in the target price determination formula such that the constraints are satisfied.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a pricing support device, a pricing support method, and a pricing support program. [Background technology]

[0002] Patent Document 1 describes an "input information receiving unit that receives input of market price information consisting of futures market prices and option market prices for the index good, and contract content information including contract period information indicating the contract period and the price formula for each of the transaction conditions, and stores the information in the storage area" (Claim 1). Patent Document 2 describes an "input information receiving unit that performs calculations using the market model generated by the model formation unit and the calculation period information, contract content information, and purchaser information input from the information input unit, and estimates the buying and selling prices of the target goods by applying the price formula to the market prices of the index good in the market model, and calculates the expected value of the transaction costs for the calculation period from the transaction costs and the realization probability for each buying and selling price when the option right is allowed to be exercised within the exercisable range and the transaction costs for procuring the target goods in excess of the expected demand are minimized" (Claim 1). Patent Document 3 describes that the system is equipped with "a contract content evaluation unit that estimates the market price of the index good during the contract period using the index good market model generated by the model formation unit, estimates the expected buying and selling price of the good to be bought and sold during the contract period using the market price of the index good during the contract period and the price formula, and estimates the expected market price of the comparative good during the contract period using the comparative good market model generated by the model formation unit, and an output unit that outputs the expected buying and selling price and the expected market price estimated by the contract content evaluation unit, or the difference between the expected buying and selling price and the expected market price, as a comparison result" (Claim 1). [Prior art document] [Patent documents] [Patent Document 1] Patent No. 4761969 [Patent Document 2] Patent No. 4804148 [Patent Document 3] Patent No. 4804147 Summary of the Invention

[0003] A first aspect of the present invention provides a price support device. The price support device may include an input unit for inputting a market index used in a target price determination formula that determines the price of a trading target based on a market index, and one or more constraints that trading of the trading target must satisfy. The price determination support device may include an optimization unit that optimizes a target price coefficient included in the target price determination formula so as to satisfy the constraints.

[0004] In the above-mentioned price support device, the input unit may input, as at least part of the constraints, at least one of the conditions for the sales price of the transaction object and the conditions for the expected sales profit that the seller of the transaction object should earn from selling the transaction object.

[0005] In the price support device, the input unit may input a procurement cost determination formula that determines the cost required to procure the transaction target, and the optimization unit may optimize the target price coefficient based on the procurement cost determination formula so that the expected sales profit amount satisfies the constraints.

[0006] In the price support device, the input unit may input a market index for a trading period in which the trading target is expected to be traded, and the optimization unit may perform optimization of the target price coefficient based on price fluctuations of the market index during the trading period.

[0007] The above-mentioned pricing assistance device may further include a simulation unit that generates price movements of market indexes during a trading period.

[0008] In the price support device, the target price determination formula may include a tolerance range for the price of the transaction target. The optimization unit may optimize the target price coefficient when the price determined by the target price determination formula is within the tolerance range.

[0009] In the above price support device, the input unit may input an upper limit and / or a lower limit of the target price coefficient as at least a part of the constraint condition.

[0010] In the price support device, the input unit may further input, as at least a part of the constraints, at least one of a condition for a sales price that a purchaser of the transaction object should obtain by using the transaction object and a condition for an expected utilization profit from the sales price. The optimization unit may optimize the target price coefficient so that the expected utilization profit amount satisfies the constraints.

[0011] In the price support device, the input unit may further input a secondary price determination formula that determines the sales price when the purchaser sells a product using the trading object, or the sales price itself. The optimization unit may optimize the target price coefficient based on the secondary price determination formula so that the expected utilization profit amount satisfies the constraints.

[0012] The above-mentioned price determination support device may further include an access restriction unit that allows only buyers to access the secondary price determination formula and / or the selling price itself, but not sellers, and that allows only sellers to access the procurement cost determination formula, but not buyers.

[0013] In the above price support device, the optimization unit may optimize the target price coefficient by maximizing or minimizing the value of an evaluation function that indicates the degree of satisfaction of the constraint conditions.

[0014] The evaluation function may have a block corresponding to each of the constraints.

[0015] In the above-mentioned price support device, the optimization unit may optimize the target price coefficient for multiple trading objects that have a common target price determination formula but different procurement cost determination formulas, using a weighted evaluation function for each trading object.

[0016] The above-described pricing decision support device may further include an output unit that outputs the degree of satisfaction of the constraints achieved by the optimized target price coefficients.

[0017] In the price support device, the optimization unit may obtain optimized target price coefficients as a set of Pareto solutions for the constraints, and the output unit may output a degree of satisfaction of the target price coefficients corresponding to the Pareto solutions.

[0018] In the price support device, the optimization unit may obtain an optimized target price coefficient by sampling the target price coefficient, and the output unit may output a degree of satisfaction of the constraint condition achieved by the sampled target price coefficients.

[0019] In the above price support device, the output unit may output the degree of satisfaction of the constraint condition realized by the sampled target price coefficients for each divided period.

[0020] In the above price support device, the output unit may output the range of the constraint along with the degree of satisfaction of the constraint.

[0021] The price support device may further include an access restriction unit that permits only users who have permission to view the degree of satisfaction of the constraints to access the degree of satisfaction of the constraints.

[0022] A second aspect of the present invention provides a price decision support method. The price decision support method may be executed by the above-described price decision support device. The price decision support method may include executing a step of inputting a market indicator used in a target price determination formula that determines the price of a trading object based on a market indicator, and one or more constraints that trading of the trading object must satisfy. The price support method may include executing an optimization step of optimizing a target price coefficient included in the target price determination formula so as to satisfy the constraints.

[0023] In a third aspect of the present invention, there is provided a pricing support program executed by a computer, which may cause a computer to function as the above-described pricing support device.

[0024] The above summary of the invention does not list all of the features of the present invention, and subcombinations of these features may also be inventions. [Brief explanation of the drawings]

[0025] [Figure 1] 1 shows the configuration of a price decision support device 10 according to this embodiment. [Figure 2] 1 shows a flow of a price determination support method according to this embodiment. [Figure 3] 10 shows an example of an input screen according to the present embodiment. [Figure 4A] An example of the evaluation function is shown below. [Figure 4B] An example of the evaluation function is shown below. [Figure 4C] An example of the evaluation function is shown below. [Figure 5] 10 shows an example of a display screen of an optimization result according to the present embodiment. [Figure 6] 10 shows another example of a display screen of an optimization result according to the present embodiment. [Figure 7] 10 shows another example of a display screen of an optimization result according to the present embodiment. [Figure 8] 10 shows an example of a display screen of an optimization result according to the present embodiment. [Figure 9] 10 shows another example of a display screen of an optimization result according to the present embodiment. [Figure 10] 10 shows a flow of a price determination support method according to a modified example of the present embodiment. [Figure 11] 22 illustrates an example computer 2200 in which aspects of the present invention may be embodied, in whole or in part. DETAILED DESCRIPTION OF THE INVENTION

[0026] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0027] Figure 1 shows the configuration of a price determination support device 10 according to this embodiment. In a typical transaction, a seller sells a trading object to a buyer and receives payment according to the price. Here, in this embodiment, it is assumed that the price of the trading object is determined in conjunction with market indices such as crude oil, product prices, and raw material prices.

[0028] The price determination support device 10 supports price determination of such market-linked trading targets. For example, the price of the trading target is determined by a target price determination formula based on market indicators. The price determination support device supports price determination of the trading target by optimizing the target price coefficient included in the target price determination formula.

[0029] The trading object may be any product or service, but is not limited to it, and examples thereof include chemical products such as synthetic resins. Chemical products often use raw materials derived from crude oil, and sometimes fuel derived from crude oil is also used in the manufacturing process. For this reason, a large portion of the manufacturing cost of chemical products depends on the price of crude oil. Therefore, the trading price of chemical products is determined using a target price determination formula that uses the market price of crude oil (e.g., the WTI crude oil futures price) as a variable. In addition to crude oil and chemical products, the pricing support device 10 may also be used to support price determination in transactions that use market indicators when determining the trading price of a certain product (i.e., trading object).

[0030] Pricing support device 10 includes an input unit 110, an optimization unit 120, a simulation unit 130, and an output unit 140. Pricing support device 10 may be a computer such as a personal computer (PC), a tablet computer, a smartphone, a workstation, a server computer, or a general-purpose computer, or may be a computer system in which multiple computers are connected.

[0031] Alternatively, the pricing support device 10 may be a dedicated computer designed for information processing for pricing support, or may be dedicated hardware implemented using dedicated circuits. The pricing support device 10 may be implemented by a single device (computer), or may be implemented by multiple devices with different roles. Although not specifically described below, the pricing support device 10 is equipped with a memory / hard disk, etc., which stores information required for processing as appropriate and transmits information between processing modules such as the optimization unit 120 and the simulation unit 130.

[0032] The pricing support device 10 may access the seller's terminal 20 and / or the buyer's terminal 30 and obtain necessary information from these terminals. The seller's terminal 20 and the buyer's terminal 30 may communicate with each other and perform transaction / payment processing for the transaction object.

[0033] The input unit 110 inputs market indicators used in the target price determination formula and one or more constraints. Information may be input directly to the input unit 110 by a person via a keyboard or a storage medium, or information may be input from an external source such as a website via the Internet.

[0034] The market index may be a security price, a stock price, a bond price, a commodity price, a national currency exchange rate, a cryptocurrency price, or a spot price or futures price of another financial product / real-demand commodity traded on a stock exchange, a private exchange, a commodity exchange, a spot market, a foreign exchange market, a cryptocurrency exchange, and / or other exchange. The market index may also be an option price (e.g., a call option price or a put option price) and / or an index (e.g., the Tokyo Stock Price Index) on these prices. The market price may also be a price index of a specific commodity published by a government agency (e.g., the domestic price index for ethylene) or an energy price (e.g., an electricity price or a gasoline price). As an example, the input unit 110 may input a WTI crude oil futures price as the market index.

[0035] The input unit 110 may input a market index for a trading period in which the trading target is expected to be traded. For example, the input unit 110 may input WTI crude oil futures prices every other week for the past year (for 52 weeks).

[0036] The input unit 110 may periodically access the website of an exchange or the like and automatically collect information on market indexes. Additionally or alternatively, the input unit 110 may receive market indexes directly from an operator.

[0037] Constraints are conditions that should be or are desirable to be met in a transaction involving a transaction object. Here, the constraints are input by the seller of the transaction object. Therefore, the constraints are desirable / necessary matters from the seller's perspective. On the other hand, as will be described later, the buyer may also input other desirable / necessary matters as constraints. For example, the input unit 110 may input, as at least part of the constraints, at least one of a condition regarding the sales price of the transaction object and a condition regarding the expected utilization profit that the seller of the transaction object should obtain by selling the transaction object.

[0038] The input unit 110 may further input the procurement costs of materials (raw materials, media, fuel, packaging materials, and / or other supplies) required for manufacturing the transaction target, so that the amount obtained by deducting the procurement costs from the sales price of the transaction target can be estimated as profit.

[0039] When the procurement cost is determined based on a market index, like the trading object, the input unit 110 may further input a procurement cost determination formula that determines the cost required to procure the trading object, in addition to or instead of directly inputting the procurement cost. The procurement cost determination formula may have a market index as a variable and a procurement cost coefficient, like the object price determination formula.

[0040] The optimization unit 120 optimizes the target price coefficients included in the target price determination formula so as to satisfy the constraints input to the input unit 110. The target price determination formula F1 may be, for example, as shown in the following formula 1. F1=a1×X1+a2×X2+a0+c… (Formula 1) Here, X1 and X2 are market indices. For example, X1 may be the WTI crude oil futures price, and X2 may be the ethylene market price. a0, a1, and a2 are target price coefficients. c is a constant. The optimization unit 120 determines optimal a0, a1, and a2 that satisfy the constraints.

[0041] This allows the price decision support device 10 to generate a target price determination formula F1 that satisfies the input constraints. The optimization unit 120 may further optimize the target price coefficient based on the procurement cost and / or the procurement cost determination formula so that the expected sales profit amount satisfies the constraints.

[0042] The optimization unit 120 may perform optimization of the target price coefficient based on the price fluctuation of the market index during the trading period. That is, the optimization unit 120 may perform optimization so as to satisfy the constraint conditions in the price fluctuation of the market index input / expected during the trading period. Details of the optimization will be described later.

[0043] The simulation unit 130 generates price movements of market indexes during a trading period by performing a simulation. The optimization unit 120 may perform optimization based on the price movements generated by the simulation unit 130.

[0044] The output unit 140 outputs the results of optimization by the optimization unit 120. The output unit 140 may further output the degree to which the constraint conditions are satisfied by the optimized target price coefficients, thereby enabling the operator to confirm whether the optimization results sufficiently satisfy the constraint conditions.

[0045] The access restriction unit 150 allows only users with access rights to access the information handled by the pricing support device 10. For example, the access restriction unit 150 allows only users with access rights to view the degree of satisfaction of constraint conditions. As an example, the access restriction unit 150 may perform authentication such as requesting the operator to enter a password.

[0046] In this way, the price determination support device 10 optimizes the target price coefficients included in the target price determination formula so as to satisfy the received constraints, thereby enabling the seller to obtain a reasonable target price determination formula with minimal computational resources.

[0047] FIG. 2 shows the flow of the price decision support method according to this embodiment. The price decision support device 10 may optimize the target price coefficient included in the target price determination formula and output the results by, for example, executing the processes of S100 to S600. The flow of FIG. 2 assumes a case where constraints are input only by the seller of the transaction target, but this is not limited to this. If the buyer has the right to determine the price, the following explanation may also be applied to a form in which constraints are input only by the buyer of the transaction target.

[0048] First, in S100, the input unit 110 inputs the expected sales volume of the transaction object from the seller's terminal. If multiple grades are set for the transaction object, the input unit 110 may input the sales volume for each grade. A grade is a classification of the same transaction object according to quality or specifications.

[0049] The input unit 110 may input only the total sales quantity of all grades, rather than the sales quantity for each grade. In this case, the input unit 110 may treat the total sales quantity divided by the number of grades as the sales quantity for each grade.

[0050] The input unit 110 may further input a weight for each grade. The weight indicates which grade should be prioritized in subsequent optimization. For example, if the weight of grade 1 for a certain trading object is greater than the weight of grade 2, optimization is performed so that grade 1 satisfies the constraints more than grade 2.

[0051] Next, in S200, the input unit 110 acquires the target price determination formula from the seller's terminal. For example, the input unit 110 inputs the structure of the target price determination formula, that is, a combination of target price coefficients, variables, constants, and operators. The input unit 110 inputs a specification of which variables correspond to which market indexes.

[0052] As an example, the input unit 110 inputs the following Equation 1. F1=a1×X1+a2×X2+a0+c… (Formula 1) In this example, the input unit 110 inputs variables X1 to X2, target price coefficients a0 to a2, a constant c, and operators x and +. Furthermore, the input unit 110 inputs a specification that X1 corresponds to the WTI crude oil futures price and X2 corresponds to the ethylene market price. The input unit 110 inputs the value of the constant c from a seller's terminal or assigns a predetermined value. The target price coefficients a0 to a2 are optimized later.

[0053] When multiple grades are set for the trading object, the input unit 110 may input a target price determination formula for each grade. The target price determination formula may be different among the multiple grades, or at least part or all of the formula may be common.

[0054] The price specified by the target price formula is the unit amount of the traded item (e.g., 1g, 1kg, 1 ton, 1cc, 1 liter, or 1m 3 Alternatively, the price specified by the target price determination formula may be the unit price per transaction unit (one item, one package, one can, one bottle, one case, one carton, or one container).

[0055] The input unit 110 may convert the currency of the price specified by the target price determination formula in response to input from an operator. For example, if the target price determination formula outputs a price in yen by default, the input unit 110 may output a price in another currency in response to input from an operator. For example, the input unit 110 may add an exchange rate coefficient (e.g., 1 dollar / 150 yen) to the target price determination formula to output a price in dollars instead of yen.

[0056] Next, in S300, the input unit 110 acquires one or more constraints from the seller's terminal. As described above, the input unit 110 inputs desirable / necessary items of the seller as constraints.

[0057] Constraints may be conditions that must be met in a transaction of a trading object during a predetermined trading period. Constraints may include one or more of absolute conditions, desired conditions, and search policies. Absolute conditions may be conditions that must be met absolutely. Desired conditions may be conditions that are preferable to meet but are not absolutely necessary. Search policies indicate search policies aimed at achieving a goal, such as maximizing or minimizing a specific numerical value. For example, constraints may include one or more search policies and one or more absolute conditions and / or desired conditions.

[0058] The constraint may be an amount that must be satisfied by a transaction of transaction objects (for example, the sales price of one transaction object, the profit amount of one transaction object, the cost amount of one transaction object, the total sales price of all transactions of transaction objects during the transaction period (i.e., total sales), the profit amount of all transactions of transaction objects during the transaction period (i.e., gross profit), the cost amount, the profit rate, and / or the cost rate), or another amount or indicator. The constraint may be a statistical value of these amounts (for example, the raw value, absolute value, average value, median value, standard deviation, +σ value, and / or −σ value). The constraint may specify some value for the statistical value of the amount (for example, matching a set value, keeping it within a set range, keeping it within an upper or lower limit, minimizing or maximizing it, or specifying it using a mathematical formula).

[0059] Specific examples of constraints include "total sales in transactions from year x month to year x month will be xx dollars or more," "the average profit amount per unit of the trading object in transactions from year x month to year x month will be xx dollars or more," and "the average sales price per unit of the trading object in transactions from year x month to year x month will be xx dollars or more." These conditions may be either absolute conditions or desired conditions. A specific example of a constraint (search policy) is "minimize the standard deviation of the sales price per unit of the trading object in transactions from year x month to year x month."

[0060] The input unit 110 may include a search range as a constraint. As the search range, a constraint related to the target price determination formula F1 itself may be input. For example, the input unit 110 may input a constraint related to a target price coefficient as at least a part of the constraint. As one example, the input unit 110 may input a range (e.g., an upper limit and / or a lower limit) of the target price coefficient as at least a part of the constraint. As another example, the input unit 110 may input a constraint related to the relationship between at least some of the target price coefficients as at least a part of the constraint. The above constraints may be input in the form of a mathematical expression (e.g., 500≧a1≧300, a0+a1=800, a0+a1≧a2).

[0061] The input unit 110 may input a logical expression that combines multiple constraints as a constraint condition. For example, assuming that there are constraints A, B, C, and D, which are described above as specific examples of constraint conditions, a condition such as (constraint A or constraint B) and (constraint C or constraint D) may be input as one constraint condition.

[0062] Next, in S400, the input unit 110 acquires a procurement cost determination formula from the seller's terminal. For example, the input unit 110 inputs the structure of the procurement cost determination formula, that is, a combination of procurement cost coefficients, variables, and operators. The procurement cost determination formula may be a formula that depends on market indicators, similar to the target price determination formula. The input unit 110 inputs a specification of which variables correspond to which market indicators.

[0063] As an example, the input unit 110 inputs the following formula 2 as a procurement cost determination formula C1. C1=b1×X1+b2×X2+b0… (Equation 2) In this example, the input unit 110 inputs variables X1 to X2, procurement cost coefficients b0 to b2, and operators x and +. Furthermore, the input unit 110 inputs a specification that X1 corresponds to the WTI crude oil futures price and X2 corresponds to the ethylene market price. The input unit 110 inputs the values ​​of the procurement cost coefficients b0 to b2 from a seller's terminal, or assigns predetermined values ​​to the procurement cost coefficients b0 to b2.

[0064] The procurement cost coefficients b0 to b2 are predetermined and are not subject to optimization. Alternatively, the procurement cost coefficients b0 to b2 may be subject to optimization together with the target price coefficients a0 to a2. If the procurement cost is a fixed amount and is not determined by a procurement cost determination formula, the processing of S300 may be omitted.

[0065] When multiple grades are set for the trading object, the input unit 110 may input a procurement cost determination formula for each grade. The procurement cost determination formula may be different among the multiple grades, or at least a part of the formula may be common. For example, the target price determination formula may be common among multiple grades, but the procurement cost determination formula may be different.

[0066] If the procurement cost is not linked to a market index and can be treated as a substantially fixed amount, the input unit 110 may acquire the amount of the procurement cost itself from the seller's terminal instead of the procurement cost determination formula.

[0067] The order of S100 to S400 may be as described above, or may be different from that described above. Also, some of S100 to S400 may be omitted as necessary.

[0068] Fig. 3 shows an example of an input screen according to this embodiment. The input unit 110 may display the input screen shown in Fig. 3 on the seller's terminal, and input various pieces of information relating to S100 to S400 via the input screen.

[0069] For example, in the example of Figure 3, the name of the purchaser of the trading target is selected or directly entered from the seller's terminal in input field 310. The target price determination formula is selected or directly entered from the seller's terminal in input field 320. Here, "xx$ (WTI)" and "xx$ (ethylene price)" correspond to variables indicating market indicators, and a1 and a2 correspond to target price coefficients.

[0070] A procurement cost determination formula is selected or directly entered from the seller's terminal in the input field 330. Here, "xx$ (WTI)" and "xx$ (ethylene price)" correspond to variables indicating market indicators, and b1 and b2 correspond to procurement cost coefficients.

[0071] For the sake of convenience, only one target price determination formula and one procurement price determination formula are shown in the example of Figure 3. Alternatively, different target price determination formulas and procurement price determination formulas may be input for each grade.

[0072] The sales quantity of the transaction subject is selected or directly entered from the seller's terminal in input field 335. In the example of FIG. 3, there is only one sales quantity input field 335. In such a case, it may be treated as if the same quantity (100 tons / 3 = 33.3 tons) is being sold for each grade. Alternatively, the sales quantity for each grade may be entered.

[0073] The weights for each grade of the transaction object are selected or directly entered from the seller's terminal in input field 340. In the example of Fig. 3, 0.1 is entered as the weight for grade 1, 0.3 is entered as the weight for grade 2, and 0.6 is entered as the weight for grade 3.

[0074] In input field 350, the transaction period is selected or directly input from the seller's terminal. In input field 360, the constraints are selected or directly input from the seller's terminal. The constraints may be such that the object of the constraint (e.g., which of the selling price and profit amount is to be constrained) and the content of the constraint (e.g., to be equal to or greater than a certain numerical value, or to be minimized) are selected independently. Alternatively, the constraints may be directly input from the seller's terminal using logical or mathematical expressions.

[0075] Constraints may be added and / or deleted as appropriate using the delete button 370 and / or the add button 390. After all necessary information has been entered, the operator may click the optimize button 380, which causes the pricing decision support device 10 to start the optimization in S500, which will be described later.

[0076] Next, in S500, the optimization unit 120 optimizes the target price coefficient of the target price determination formula acquired in S200 so as to satisfy the constraint conditions input in S300. The optimization unit 120 may perform the optimization using an evaluation function. For example, the optimization unit 120 may optimize the target price coefficient by maximizing or minimizing the numerical value of the evaluation function that indicates the degree of satisfaction of the constraint conditions.

[0077] For example, the optimization unit 120 sets an evaluation function corresponding to each constraint condition. For example, if the constraint condition is to maximize a certain amount (e.g., a selling price), the optimization unit 120 may set an evaluation function that increases the output evaluation value in proportion to an increase in the selling price.

[0078] Figure 4A shows an example of an evaluation function in which the output evaluation value increases in proportion to an increase in the selling price. The bold line in the graph indicates the output of the evaluation function. As shown in the figure, the selling price and the output value (evaluation value) of the evaluation function are proportional.

[0079] Such an evaluation function may be used when the constraint is a search policy. For example, if the constraint is to minimize the standard deviation of a certain amount (e.g., profit amount), an evaluation function may be set in which the evaluation value decreases in inverse proportion to an increase in the standard deviation of the profit amount. In this case, the optimization unit 120 may set an evaluation function that is a straight line that slopes downward rather than a straight line that slopes upward as shown in FIG. 4A.

[0080] When setting an evaluation function such as that shown in Fig. 4A, the optimization unit 120 may use the target price determination formula itself, or the target price determination formula to which additional coefficients have been added, as the evaluation function. This is because the selling price (i.e., the price of the transaction object) itself is directly linked to the evaluation.

[0081] 4A is set using profit amount instead of sales price, the optimization unit 120 may use as the evaluation function the result of subtracting the procurement cost determination formula from the target price determination formula, or may perform an operation such as adding an additional coefficient to this. This is because the profit amount from the transaction of the transaction target is calculated by subtracting the procurement cost determination formula from the target price determination formula, and the profit amount itself is directly linked to the evaluation.

[0082] When setting the evaluation function based on the profit amount, other transactions may be taken into consideration in addition to the transactions entered in S100 to S400. For example, in S100 to S400, the sales quantity and target price determination formula are entered assuming a specific purchaser (e.g., Company A), but it is possible that the same transaction object has already been sold to another purchaser (e.g., Company B).

[0083] In such a case, the profit of the entire transaction with the trading partner, including not only Company A but also Company B, may be taken in as a constraint. For example, the input unit 110 may input the sales volume (for Company B) and the target price determination formula (for Company B) in the transaction with Company B, and based on these, may incorporate the profit based on the transaction with Company B (for example, {[Target price determination formula (for Company B)] - [Procurement cost determination formula])} × [Sales volume (for Company B)]) into the profit, and perform optimization.

[0084] For example, if a constraint is that a certain amount (e.g., selling price) must be within a set value or set range, an evaluation function may be set such that the evaluation value increases when the selling price matches the set value (or set range), and decreases when the selling price deviates from the set value (or set range) depending on the degree of deviation. In this case, the output value of the evaluation function is an upward convex function when the selling price is taken as the horizontal axis.

[0085] 4B shows an example of an evaluation function that is a convex function when the horizontal axis is the selling price. As shown in the figure, as the selling price deviates from the set value 400, the output value of the evaluation function decreases according to the degree of deviation.

[0086] Such an evaluation function may be used when the constraint condition is a desired condition. When setting an evaluation function such as that shown in FIG. 4B, the optimization unit 120 may use, as the evaluation target, the output of the target price determination formula F1 or its statistics (for example, the average value, standard deviation, etc. of the output of F1) input into a convex function. For example, [constant] - ([setting value] - evaluation target) 2 The optimization unit 120 may use the formula expressed by the following formula or an appropriately modified formula as the evaluation function.

[0087] If the constraint is an absolute condition, the output value of the evaluation function will be a predetermined positive constant when it matches the set value or falls within the set range, and otherwise the output value of the evaluation function may be a very low value (for example, a large negative value).

[0088] 4C shows another example of an evaluation function that is an upwardly convex function when the selling price is plotted on the horizontal axis. In the example of Fig. 4C, when the selling price is within the set selling price range 410, the output value of the evaluation function becomes high, and when the selling price deviates even slightly from the set selling price range 410, the output value suddenly decreases discontinuously, and the further the selling price deviates from the set selling price range 410, the lower the output value of the evaluation function becomes.

[0089] 4C, the optimization unit 120 may set a different evaluation function for each range of input values. For example, the optimization unit 120 may use the target price determination formula F1 to use the following evaluation function: (If the selling price is less than or equal to the lower limit) Evaluation function = [Constant A] - ([Lower limit] - F1) 2 (When lower limit < selling price < upper limit) Evaluation function = [constant B] (where constant B > constant A) (If the selling price is greater than or equal to the upper limit) Evaluation function = [Constant A] - ([Upper limit] - F1) 2

[0090] When there are multiple constraints, the optimization unit 120 may set an evaluation function corresponding to each constraint, and then connect the set evaluation functions to generate one integrated evaluation function. For example, consider a case where an evaluation function E1 is set by constraint 1, an evaluation function E2 is set by constraint 2, an evaluation function E3 is set by constraint 3, and an evaluation function E4 is set by constraint 4. In this case, the optimization unit 120 sets E as the integrated evaluation function. T =E1+E2+E3+E4. In this way, the evaluation function has blocks (i.e., E1, E2, E3, and E4) corresponding to each of the multiple constraints. T When generating E1, E2, etc., each evaluation function (E1, E2, etc.) may be weighted as needed.

[0091] An evaluation function may not be set for some of the constraints, and these may simply be treated as the search range. For example, an evaluation function may not be set for the search range of the constraints. Also, for example, an evaluation function may be set only for the search policy among the constraints, and the rest may simply be treated as the search range.

[0092] When there are multiple types or categories of trading objects (for example, product brands, grades, etc.), the optimization unit 120 may optimize the target price coefficient using an evaluation function weighted for each type, etc. For example, the optimization unit 120 may set an evaluation function for each grade, weight the set evaluation functions, and then link them to generate a single integrated evaluation function.

[0093] Here, the evaluation function E T1 is set, and the evaluation function E is set to Grade 2. T2 The evaluation function E is set to Grade 3. T3 Let us assume that the evaluation function E T1 may be a function that integrates evaluation functions related to multiple constraint conditions for Grade 1. In this case, the optimization unit 120 uses E as the integrated evaluation function. TG =w1×E T1 +w2×E T2 +w3×E T3 Here, w1, w2, and w3 are the weights of each grade, and in the example of Figure 3, for example, w1 = 0.10, w2 = 0.30, and w3 = 0.60.

[0094] In the above example, weighting for each type etc. is performed using an evaluation function, but this is not limiting. A weighted average of values ​​(e.g., sales price or profit) related to the transaction object included in the constraints may be calculated, and the evaluation may be performed using the evaluation function using this average value.

[0095] The optimization unit 120 calculates an evaluation function E T or E TG In the above, for the sake of convenience, an example is shown in which the output value of the evaluation function increases as the constraint conditions are satisfied, but this is not limiting, and an evaluation function whose output value decreases as the constraint conditions are satisfied may also be used. In this case, the optimization unit 120 performs optimization to minimize the evaluation function.

[0096] The optimization unit 120 may perform optimization on the assumption that the trading volume will be evenly distributed and trades will be executed during the input trading period / predetermined trading period. For example, if the trading volume is 100 tons and the trading period is 100 days, the optimization unit 120 may perform optimization on the assumption that one ton of the trading object will be traded every day.

[0097] Alternatively, the optimization unit 120 may perform optimization on the assumption that transactions will be executed based on a sales schedule that is predetermined or input from a terminal. In this case, the total sales volume for all days of the sales schedule may match the input sales quantity. The optimization unit 120 may create a sales schedule using an algorithm (e.g., dollar cost method) that decreases the transaction volume as the sales price determined by the target price determination formula increases and increases the transaction volume as the sales price decreases.

[0098] The optimization unit 120 may acquire price movements of market indexes (hereinafter also referred to as "expected price movements") for the input trading period / predetermined trading period in a predetermined manner and perform optimization using the expected price movements. For example, the optimization unit 120 may acquire, as expected price movements, the numerical values ​​of market indexes for a certain past period corresponding to the trading period, either by directly inputting the expected price movements from an operator via the input unit 110 or from an information source such as a website of an exchange or the like via the input unit 110. For example, if the trading period is three months, the optimization unit 120 may acquire, as expected price movements, the WTI crude oil futures prices for every other day for the most recent three months.

[0099] The optimization unit 120 may acquire, as the expected price movement, the price movement of the market index during the trading period generated by the simulation by the simulation unit 130. The simulation unit 130 may simulate the price movement of the market index using a known market price forecasting algorithm or the like. As an example, the simulation unit 130 may generate the expected price movement by executing a simulation in which the market index undergoes Brownian motion.

[0100] The optimization unit 120 may obtain optimized target price coefficients by sampling the target price coefficients. For example, the optimization unit 120 may perform optimization by searching for target price coefficients that maximize (or minimize) the evaluation function, assuming that market indicators follow expected price movements. For example, the optimization unit 120 may search for target price coefficients that maximize (or minimize) the evaluation function based on a tree-structured Parzen estimator (TPE) by randomly sampling the target price coefficients according to a predetermined procedure. For example, the optimization unit 120 may search for target price coefficients that maximize (or minimize) the evaluation function based on multi-objective TPE (MOTPE). Alternatively, the optimization unit 120 may search for target price coefficients using design of experiments (DOE), Markov chain Monte Carlo (MCMC), Gibbs sampling (GS), Metropolis-Hastings (MH), simulated annealing (SA), or other known optimization and / or sampling methods.

[0101] Next, in S600, the output unit 140 outputs the results optimized by the optimization unit 120 in S500. The output unit 140 may output the degree of satisfaction of the constraint conditions realized by the optimized target price coefficients. For example, the output unit 140 may output a plurality of sampled target price coefficients and the degree of satisfaction of the constraint conditions realized thereby. The output unit 140 may output all the sampled results, or alternatively, may output a portion of the sampled results (for example, a portion that highly satisfies the constraint conditions, or a portion randomly extracted).

[0102] In S600, the seller who has received multiple target price coefficients from the output unit 140 may select a target price coefficient to be adopted in the target price determination formula. Furthermore, the seller can start the transaction by presenting the target price determination formula related to the selected target price coefficient to the purchaser of the transaction target.

[0103] In the optimization of S500, if the optimization unit 120 is unable to perform optimization that satisfies all of the constraints, the output unit 140 may output a notification indicating that optimization has not been performed.

[0104] Fig. 5 shows an example of an optimization result display screen 500 according to this embodiment. For example, after clicking the optimization button 380 in Fig. 3, optimization is performed by the optimization unit 120, and then the result screen as shown in Fig. 5 may be displayed by the output unit 140.

[0105] Figure 5 shows the degree of constraint satisfaction achieved by the target price coefficient obtained through optimization. The vertical and horizontal axes of the graph indicate the extent to which the constraints are satisfied. For example, the vertical axis of the graph indicates the standard deviation of the selling price corresponding to constraint 1 in Figure 3, and the horizontal axis of the graph indicates the average selling price corresponding to constraint 2 in Figure 3.

[0106] 5 correspond to trial points attempted in the search of S500. For example, trial point 510 represents a plot of the standard deviation of the sales prices and the average value of the sales prices achieved by the target price coefficients sampled during the search.

[0107] On the assumption that the market index matches the expected price movement for the target price coefficient related to the trial point 510, the optimization unit 120 calculates the selling prices at multiple points during the trading period, calculates their average value and standard deviation as pairs, links them to the target price coefficient, and provides them to the output unit 140. The output unit 140 outputs such pairs obtained as a result of optimization in the form of a graph as a number of points as shown in Figure 5. The degree of satisfaction of the constraint conditions is indicated by plotting the trial point 510 within the range of satisfaction of the constraint conditions indicated by the vertical and horizontal axes of the graph.

[0108] 6 shows another example of a display screen 600 of optimization results according to this embodiment. The output unit 140 may output one or more of the searched target price coefficients that best fit the constraints (e.g., search policy) from among the many searched target price coefficients, distinguishing them from the others. For example, the optimization unit 120 may acquire optimized target price coefficients as a set of Pareto solutions for the search policy, and the output unit 140 may output the degree of satisfaction of the target price coefficients corresponding to the Pareto solutions.

[0109] As shown in Fig. 6, the output unit 140 may display a trial point group 610 (shown as black circles) corresponding to the Pareto solution, distinguishing it from other trial points (shown as white circles). In Figs. 5 and 6, the trial point group 610 located toward the bottom right on the graph (meaning a higher average selling price and a lower standard deviation) is more suitable for the search policy. Therefore, among the many trial points, the trial point group 610 located at the bottom right forms the Pareto boundary.

[0110] In this way, the output unit 140 displays the trial points together with the degree of satisfaction of the search policy obtained as a result of optimization, so that the seller can select trial points (i.e., target price coefficients) that have a high degree of satisfaction of the search policy. In particular, according to this embodiment, useful trial points can be identified from a large number of trial points with fewer computational resources.

[0111] The output unit 140 may output the range of the search policy along with the degree of satisfaction of the search policy. For example, FIG. 6 shows an example in which the search policies are "average selling price is 110$ / Ton or more" and "minimize the standard deviation of the selling prices" as constraint conditions. As shown in FIG. 6, the output unit 140 may make the background color of the range on the graph that satisfies the search policy "average selling price is 110$ / Ton or more" darker than other parts. Furthermore, as shown in FIG. 6, the output unit 140 may make the background color darker as the search policy "minimize the standard deviation of the selling prices" is satisfied (i.e., as you move further down the graph).

[0112] In addition to or instead of the above, the output unit 140 may highlight on the graph the range that satisfies all or part of the search policy by enclosing it with a line segment, etc. This makes it possible to clearly display trial points that satisfy the search policy or that have a high degree of satisfaction.

[0113] 7 shows another example of a display screen 700 of optimization results according to this embodiment. The output unit 140 may further display details of the trial points. For example, when an operator on the seller's terminal places or clicks a cursor 725 on trial point 710, the output unit 140 may open a window 730 on the display screen 700. The output unit 140 outputs, in the window 730, the target price coefficients (a1 = 262.1, a2 = 564.2) corresponding to trial point 710 and the degree of satisfaction of the constraints obtained at the trial point (average selling price = $166.4, standard deviation of selling prices = $43.1).

[0114] The output unit 140 may output the range of the constraint conditions together with the degree of satisfaction of the constraint conditions in a format different from that shown in Figures 5 to 7. For example, when the switching buttons 520 to 720 shown in Figures 5 to 7 are clicked, the output unit 140 may display the display screens shown in Figures 8 and 9.

[0115] Fig. 8 shows an example of a display screen 800 of the optimization results according to this embodiment. Fig. 8 also shows the degree of satisfaction of the constraint conditions realized by the target price coefficients obtained by optimization. On the display screen 800, the output unit 140 indicates the range of the constraint conditions with two vertical lines on the left side and the range of the target price coefficients with two vertical lines on the right side.

[0116] The multiple polygonal lines displayed on the display screen 800 correspond to the trial points tried in the search of S500. For example, polygonal line 810 shows a line connecting the standard deviation (43.1$) and average (166.4$) values ​​of the sales prices realized by a set of target price coefficients (a1=262.1, a2=564.2) sampled during the search.

[0117] 9 shows another example of a display screen 900 of optimization results according to this embodiment. The output unit 140 may further display details of the trial points. For example, when an operator on the seller's terminal places or clicks a cursor 930 on the broken line 910, the output unit 140 may open a window 940 on the display screen 900. The output unit 140 outputs, in the window 940, the target price coefficients (a1 = 262.1, a2 = 564.2) corresponding to the broken line 910 and the degree of satisfaction of the constraints obtained at the trial points (average selling price = 166.4$, standard deviation of selling prices = 43.1$).

[0118] 8 to 9, the output unit 140 displays lines together with the degree of satisfaction of the constraint conditions obtained as a result of optimization, allowing the operator to select a line (i.e., a set of target price coefficients) with a high degree of satisfaction of the constraint conditions. When the switching buttons 820 to 920 shown in Figures 8 to 9 are clicked, the output unit 140 may switch to the displays shown in Figures 5 to 7.

[0119] As explained using Figures 2 to 9, according to this embodiment, target price coefficients that satisfy constraint conditions can be presented to a seller's terminal using the price decision support device 10. This allows the seller to obtain a reasonable target price determination formula with limited computational resources.

[0120] 5 to 9 above show an example in which the optimization unit 120 displays a large number of search results (i.e., a large number of trial points and broken lines) and the operator can select from them. Alternatively, the optimization unit 120 may automatically select some samples that best satisfy the constraints (for example, the top or top three sets of target price coefficients of the evaluation function), and the output unit 140 may present only these to the operator. This eliminates the need for the operator to make a decision.

[0121] 5 to 9 show results for the entire trading period, but the output unit 140 may divide the trading period into multiple periods and display results for each period. For example, the optimization unit 120 may perform sampling for each divided period. The output unit 140 may output the degree of satisfaction of the constraints achieved by the sampled target price coefficients for each divided period. The length of the period may be a predetermined time such as one year, one month, two months, three months, one week, two weeks, three weeks, one day, two days, or three days.

[0122] In the above example, only the trial points sampled in the optimization are displayed, and points related to the current and / or past target pricing formulas are not displayed. Alternatively, in addition to / instead of the sampled trial points, the optimizer 120 may also perform trials on the target price coefficients related to the current (and / or past) target pricing formulas, and the output unit 140 may display the results.

[0123] In the above example, there is no limit on the price of the trading counterpart determined by the target price determination formula. Alternatively, a limit may be imposed on the price of the trading counterpart determined by the target price determination formula. For example, an allowable range of the trading counterpart price may be set for the target price determination formula. Furthermore, the allowable range may be a predetermined upper and / or lower limit, or an amount determined by a formula other than the target price determination formula. This prevents the price of the linked trading counterpart from being capped at an upper limit and reaching an extreme amount, even if a market index (for example, the WTI crude oil futures price) rises extremely high.

[0124] In such a case, the optimization unit 120 may optimize the target price coefficient when the price determined by the target price determination formula is within the allowable range. In other words, since there is no practical benefit in optimizing the target price coefficient by taking into account market conditions in which market indicators do not affect the target price determination formula, the optimization unit 120 may optimize the target price coefficient based only on market conditions in which market indicators affect the target price determination formula without taking such market conditions into account. For example, the optimization unit 120 may extract only market conditions in which market indicators affect the target price determination formula from the expected price movements, and perform optimization under the assumption that trading will occur only in such market conditions.

[0125] In the above example, the optimization unit 120 optimizes only the target price coefficient from the target price determination formula, but this is not limiting. For example, the optimization unit 120 may optimize not only the target price coefficient, but also the structure of the entire target price determination formula, including the determination of the variables and / or constants to be used and / or the structure of the formula (the structure of terms such as linear expressions, quadratic expressions, and exponents, and the method of connecting them). Alternatively, the optimization unit 120 may perform optimization by determining the most suitable formula from multiple formulas prepared in advance and then determining the target price coefficient included in that formula.

[0126] Fig. 10 shows the flow of a price determination support method according to a modification of this embodiment. In this modification, unlike the example in Fig. 2, constraints are input not only from the seller of the transaction target but also from the buyer of the transaction target, and optimization is performed.

[0127] For example, if a buyer wants to make a certain profit using the trading object he or she has purchased, the buyer's profit can be incorporated into the constraints to obtain a target price coefficient that adjusts the interests of the seller and the buyer. In this modification, the price decision support device 10 executes the processes of S1100 to S1600.

[0128] First, in S1100, the input unit 110 inputs the sales quantity of the transaction object that is expected to be sold. S1100 may be executed in the same manner as S100. The input entity may be the seller or the buyer. That is, the input unit 110 inputs the sales quantity of the transaction object from the seller's terminal or the buyer's terminal.

[0129] In S1200, the input unit 110 acquires the target price determination formula from the seller's terminal. S1200 may be executed in the same manner as S200. The input entity is usually the seller. That is, the input unit 110 inputs the target price determination formula for the transaction object from the seller's terminal.

[0130] Next, in S1300, the input unit 110 acquires one or more constraints from the operator on the seller side and the terminal on the buyer side. The input unit 110 inputs desired / necessary items from the seller side in the same manner as in S300.

[0131] Furthermore, the input unit 110 inputs desirable / necessary items from the purchaser side as constraints. For example, the input unit 110 may input, as at least a part of the constraints, at least one of a condition on the sales amount that the purchaser of the transaction object should obtain by using the transaction object and a condition on the expected utilization profit from the sales amount.

[0132] Specific examples of constraints include "the average expected utilization profit amount that can be obtained from the utilization of the transaction object purchased by the purchaser in transactions from year x month to year x month will be xx dollars or more," "the standard deviation of the expected utilization profit amount that can be obtained from the utilization of the transaction object purchased by the purchaser in transactions from year x month to year x month will be minimized," etc. The expected utilization profit amount is the amount of profit that the purchaser can obtain from the utilization, transportation, processing, and / or sale of the transaction object.

[0133] Next, in S1450, the input unit 110 acquires from the purchaser's operator a secondary price (fixed amount), which is the selling price when selling a product using the transaction object, or a secondary price determination formula, which is a formula for determining the selling price. The purchaser purchases the transaction object at the amount determined by the target price determination formula, uses, transports, and / or processes the purchased transaction object, and sells it for the amount of the secondary price or the amount determined by the secondary price determination formula. As a result, the purchaser can earn a profit of the expected utilization profit amount, which is determined by [secondary price (or the price output by the secondary price determination formula)] - [price output by the target price determination formula] per transaction object.

[0134] The secondary price determination formula may be a formula that depends on a market index, similar to the target price determination formula. For example, the input unit 110 inputs the structure of the secondary price determination formula, i.e., a combination of secondary price coefficients, variables, and operators. The input unit 110 inputs a specification of which variables correspond to which market indexes.

[0135] As an example, the input unit 110 inputs the following formula 3 as the secondary price determination formula S1. S1=s1×X1+s2×X2+s0… (Equation 3) In this example, the input unit 110 inputs variables X1 to X2, secondary price coefficients s0 to s2, and operators x and +. Furthermore, the input unit 110 inputs a specification that X1 corresponds to the WTI crude oil futures price and X2 corresponds to the ethylene market price. The input unit 110 receives input of values ​​for the secondary price coefficients s0 to s2 from an operator, or assigns predetermined values ​​to the secondary price coefficients s0 to s2.

[0136] The secondary price coefficients s0 to s2 are predetermined and are not subject to optimization. Alternatively, the secondary price coefficients s0 to s2 may be subject to optimization together with the target price coefficients a0 to a2. If the secondary price is a fixed amount or the like and is not determined by a secondary price determination formula, the processing of S1450 may be omitted.

[0137] Next, in S1500, the optimization unit 120 optimizes the target price coefficient of the target price determination formula acquired in S1200 so as to satisfy the constraint conditions input in S1300. The optimization unit 120 may execute the optimization process in the same manner as in S300.

[0138] Here, if the purchaser inputs constraints regarding the expected usage profit amount in S1300, the optimization unit 120 may optimize the target price coefficient so that the expected usage profit amount satisfies the constraints. For example, the optimization unit 120 optimizes the target price coefficient based on the secondary price determination formula so that the expected usage profit amount satisfies the constraints. Specifically, the optimization unit 120 may perform optimization so that the expected usage profit amount determined by [price output by the secondary price determination formula] - [price output by the target price determination formula] satisfies the constraints.

[0139] When constraints on minimum profit amounts are issued by both the seller and the buyer, the optimization unit 120 may add, automatically or in response to a request from the seller / buyer via their terminals, a new constraint that the seller's profit and the purchase profit be distributed fairly. For example, the new constraint may be added such that the ratio of the seller's profit (expected sales profit amount) to the buyer's profit (expected usage profit amount) is 50:50 (or in the range of 50 - [allowable error] to 50 + [allowable error] to 50 + [allowable error] to 50 - [allowable error]). The allowable error may be selected from a number from 1 to 49, such as 1, 3, 5, 10, or 20.

[0140] Next, in S1600, the output unit 140 outputs the results optimized by the optimization unit 120 in S500. The output unit 140 may execute the output process in the same manner as in S600. For example, the output unit 140 may output the results to both the seller's terminal and the buyer's terminal.

[0141] In S600, the seller and the buyer who have received the plurality of target price coefficients from the output unit 140 may negotiate with each other to select the target price coefficient to be adopted in the target price determination formula. After that, they can start the transaction of the transaction object by using the target price determination formula related to the target price coefficient selected through negotiation.

[0142] In the variation shown in Figure 10, by having both the seller and the buyer input constraints, the price determination support device 10 can formulate a target price determination formula that is satisfactory to both parties. Here, information such as the procurement price, procurement cost determination formula, secondary price, and secondary price determination formula may need to be kept confidential by both the seller and the buyer, and disclosure to the other party may be undesirable. Therefore, the access restriction unit 150 may restrict access to only those parties who input the procurement price, procurement cost determination formula, secondary price, and secondary price determination formula.

[0143] For example, the access restriction unit 150 may allow only the buyer's terminal to access the secondary price determination formula and / or the selling price itself (i.e., the secondary price), but not the seller's terminal. Also, the access restriction unit 150 may allow only the seller's terminal to access the procurement cost determination formula, but not the buyer's terminal.

[0144] As an example, the access restriction unit 150 may not display the input screen for the secondary price determination formula and / or the secondary price displayed in S1450 on the seller's terminal, and may require a password set by the purchaser to access the information on the secondary price determination formula and / or the secondary price.As an example, the access restriction unit 150 may not display the input screen for the procurement cost determination formula and / or the procurement cost displayed in S1400 on the buyer's terminal, and may require a password set by the seller to access the information on the procurement cost determination formula and / or the procurement cost.

[0145] In the example shown in Figure 10 above, one seller and one buyer each input constraints, a procurement cost determination formula, a secondary price determination formula, etc. to perform optimization. Alternatively, more parties may participate in optimization. For example, one seller and multiple buyers may input constraints, etc. to perform optimization.

[0146] As an example, the system inputs constraint A and procurement cost determination formula A from the seller, and constraint B1 and secondary price determination formula B1 from buyer 1, and executes optimization. Furthermore, the system inputs constraint A and procurement cost determination formula A from the seller, and constraint B2 and secondary price determination formula B2 from buyer 2, and executes optimization. As a result, the seller obtains (multiple) target price coefficients 1 optimized between the seller and buyer 1, and (multiple) target price coefficients 2 optimized between the seller and buyer 2. The seller may then select either target price coefficient 1 or target price coefficient 2, whichever is more advantageous to him / her. Alternatively, the price determination support device 10 may select either target price coefficient 1 or target price coefficient 2, whichever is more likely to satisfy the seller's constraints.

[0147] The seller may sell the trading object to only one selected party or to both selected parties, or the seller may sell the trading object to buyer 1 and buyer 2 using different target price determination formulas, using target price coefficient 1 and target price coefficient 2, respectively.

[0148] For example, multiple sellers and one buyer may input constraints and the like to perform optimization. As an example, constraint 1 and procurement cost determination formula 1 from seller 1, and constraints and a secondary price determination formula from the buyer are input, and optimization is performed. Constraint 2 and procurement cost determination formula 2 from seller 2, and constraints and a secondary price determination formula from the buyer are further input, and optimization is performed. As a result, the seller obtains (multiple) target price coefficients 1 optimized between seller 1 and the buyer, and (multiple) target price coefficients 2 optimized between seller 2 and the buyer. The buyer may then select the target price coefficient 1 or the target price coefficient 2 that is most advantageous to him or her. Alternatively, price determination support device 10 may select the target price coefficient 1 or the target price coefficient 2 that more closely satisfies the buyer's constraints.

[0149] There may be three or more sellers and / or buyers. The price decision support device 10 may perform optimization for all combinations of sellers and buyers, and provide target price coefficients and conclude transactions only for the combination that satisfies the constraints to the highest extent, the combination with the n highest number of constraints (n is a predetermined integer) that satisfy the constraints, and the combination that satisfies the constraints to a threshold or more.

[0150] Various embodiments of the present invention may be described with reference to flowcharts and block diagrams, where the blocks may represent (1) stages of a process in which operations are performed or (2) sections of an apparatus responsible for performing the operations. Particular stages and sections may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable medium, and / or a processor provided with computer-readable instructions stored on a computer-readable medium. Dedicated circuitry may include digital and / or analog hardware circuitry, and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuitry may include reconfigurable hardware circuitry, including logical AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, memory elements such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and the like.

[0151] A computer-readable medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that the computer-readable medium having instructions stored thereon comprises an article of manufacture containing instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable media may include electronic, magnetic, optical, electromagnetic, and semiconductor storage media. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray disc, memory stick, integrated circuit card, and the like.

[0152] The computer readable instructions may include either assembler instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0153] The computer-readable instructions may be provided to a processor or programmable circuitry of a programmable data processing apparatus, such as a general-purpose computer, special-purpose computer, or other computer, either locally or over a wide-area network (WAN) such as a local area network (LAN), the Internet, etc., which executes the computer-readable instructions to create means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0154] 11 illustrates an example of a computer 2200 in which aspects of the present invention may be embodied, in whole or in part. Programs installed on the computer 2200 may cause the computer 2200 to function as or perform operations associated with an apparatus or one or more sections of the apparatus according to embodiments of the present invention, and / or to perform a process or steps of a process according to embodiments of the present invention. Such programs may be executed by the CPU 2212 to cause the computer 2200 to perform specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0155] A computer 2200 according to this embodiment includes a CPU 2212, a RAM 2214, a graphics controller 2216, and a display device 2218, which are interconnected by a host controller 2210. The computer 2200 also includes input / output units such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card drive, which are connected to the host controller 2210 via an input / output controller 2220. The computer also includes legacy input / output units such as a ROM 2230 and a keyboard 2242, which are connected to the input / output controller 2220 via an input / output chip 2240.

[0156] The CPU 2212 operates according to programs stored in the ROM 2230 and RAM 2214, thereby controlling each unit. The graphics controller 2216 acquires image data generated by the CPU 2212 into a frame buffer or the like provided in the RAM 2214 or into the graphics controller 2216 itself, and causes the image data to be displayed on the display device 2218.

[0157] The communications interface 2222 communicates with other electronic devices via a network. The hard disk drive 2224 stores programs and data used by the CPU 2212 in the computer 2200. The DVD-ROM drive 2226 reads programs or data from the DVD-ROM 2201 and provides the programs or data to the hard disk drive 2224 via the RAM 2214. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0158] The ROM 2230 stores therein a boot program or the like that is executed by the computer 2200 upon activation, and / or programs that depend on the hardware of the computer 2200. The input / output chip 2240 may also connect various input / output units to the input / output controller 2220 via a parallel port, a serial port, a keyboard port, a mouse port, etc.

[0159] The programs are provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The programs are read from the computer-readable medium, installed in the hard disk drive 2224, RAM 2214, or ROM 2230, which are also examples of computer-readable media, and executed by the CPU 2212. Information processing described in these programs is read by the computer 2200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be configured by realizing information manipulation or processing in accordance with the use of the computer 2200.

[0160] For example, when communication is performed between the computer 2200 and an external device, the CPU 2212 may execute a communication program loaded into the RAM 2214 and instruct the communication interface 2222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 2212, the communication interface 2222 reads transmission data stored in a transmission buffer processing area provided in the RAM 2214, the hard disk drive 2224, the DVD-ROM 2201, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes reception data received from the network to a reception buffer processing area or the like provided on the recording medium.

[0161] The CPU 2212 may cause all or a necessary portion of a file or database stored on an external recording medium such as the hard disk drive 2224, the DVD-ROM drive 2226 (DVD-ROM 2201), an IC card, etc. to be read into the RAM 2214, and may perform various types of processing on the data on the RAM 2214. The CPU 2212 then writes back the processed data to the external recording medium.

[0162] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and may undergo information processing. The CPU 2212 may perform various types of processing on data read from the RAM 2214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequences of the programs, and write the results back to the RAM 2214. The CPU 2212 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored on the recording medium, the CPU 2212 may search for an entry that matches a condition specified by the attribute value of the first attribute from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0163] The above-described programs or software modules may be stored in a computer-readable medium on or near the computer 2200. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as a computer-readable medium, thereby providing the programs to the computer 2200 via the network.

[0164] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0165] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before" or "prior to," and that any order may be used unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the process must be performed in that order. The expression "A and / or B" may mean "A, B, or A and C." The expression "A, B, and / or C" may mean "any one of A, B, and C, or any combination of two or more of these." [Explanation of symbols]

[0166] 10 Price determination support device, 20 Seller's terminal, 30 Buyer's terminal, 110 Input unit, 120 Optimization unit, 130 Simulation unit, 140 Output unit, 150 Access restriction unit, 310 Input field, 320 Input field, 330 Input field, 335 Input field, 340 Input field, 350 Input field, 360 Input field, 370 Delete button, 380 Optimization button, 390 Add button, 400 Selling price setting value, 410 Selling price setting range, 500 Display screen, 510 Trial point, 520 Switch button, 600 Display screen, 610 Trial point cloud, 620 Switch button, 700 Display screen, 710 Trial point, 720 Switch button, 725 Cursor, 730 Window, 800 Display screen, 810 Broken line, 820 Switch button, 900 Display screen, 920 switching button, 930 cursor, 940 window, 2200 computer, 2201 DVD-ROM, 2210 host controller, 2212 CPU, 2214 RAM, 2216 graphics controller, 2218 display device, 2220 input / output controller, 2222 communication interface, 2224 hard disk drive, 2226 DVD-ROM drive, 2230 ROM, 2240 input / output chip, 2242 keyboard

Claims

1. an input unit for inputting a market index used in a target price determination formula that determines the price of a trading target based on a market index, and one or more constraints that a transaction of the trading target must satisfy; an optimization unit that optimizes a target price coefficient included in the target price determination formula so as to satisfy the constraint condition; A price decision support device comprising:

2. the input unit inputs, as at least a part of the constraint conditions, at least one of a condition on a selling price of the transaction object and a condition on an expected sales profit amount that a seller of the transaction object should obtain from the sale of the transaction object; The pricing support device according to claim 1.

3. the input unit inputs a procurement cost determination formula that determines the cost required to procure the trading object; the optimization unit optimizes the target price coefficient based on the procurement cost determination formula so that the expected sales profit amount satisfies the constraint condition. The pricing support device according to claim 2.

4. the input unit inputs the market index for a trading period in which the transaction of the trading object is expected, the optimization unit performs optimization of the target price coefficient based on price movements of the market index during the trading period; The pricing support device according to claim 1.

5. a simulation unit that generates price movements of the market index during the trading period; 5. The pricing support system according to claim 4.

6. an allowable range of the price of the trading object is set for the object price determination formula, the optimization unit optimizes the target price coefficient when the price determined by the target price determination formula is within the allowable range. The pricing support device according to claim 1.

7. the input unit inputs an upper limit and / or a lower limit of the target price coefficient as at least a part of the constraint condition; The pricing support device according to claim 1.

8. The input unit As at least a part of the constraints, at least one of a condition on the sales price that the purchaser of the transaction object should obtain by using the transaction object and a condition on the expected utilization profit amount from the sales price; Then enter the optimization unit optimizes the target price coefficient so that the expected utilization profit amount satisfies the constraint condition.

4. The pricing support system according to claim 3.

9. The input unit A secondary price determination formula that determines the sales price when the purchaser sells a product using the transaction object, or the sales price itself; Then enter the optimization unit optimizes the target price coefficient based on the secondary price determination formula so that the expected utilization profit amount satisfies the constraint condition. The pricing support device according to claim 8.

10. an access restriction unit that allows only the purchaser to access the secondary price determination formula and / or the selling price itself, but not the seller, and that allows only the seller to access the procurement cost determination formula, but not the buyer; The pricing assistance device according to claim 9.

11. The optimization unit optimizing the target price coefficient by maximizing or minimizing a value of an evaluation function that indicates the degree of satisfaction of the constraint condition; 4. The pricing support system according to claim 3.

12. the evaluation function has a block corresponding to each of the constraints; The pricing assistance device according to claim 11.

13. The optimization unit optimizing the target price coefficient for a plurality of trading objects that share the target price determination formula and different procurement cost determination formulas, using the evaluation function weighted for each trading object; The pricing assistance device according to claim 11.

14. an output unit that outputs a degree of satisfaction of the constraint condition realized by the optimized target price coefficient; The pricing support device according to claim 1.

15. the optimization unit obtains the optimized target price coefficient as a set of Pareto solutions for the constraint conditions; the output unit outputs a degree of fulfillment of the target price coefficient corresponding to the Pareto solution.

15. The pricing assistance device of claim 14.

16. the optimization unit obtains the optimized target price coefficient by sampling the target price coefficient; the output unit outputs the degree of satisfaction of the constraint condition realized by the sampled target price coefficients.

15. The pricing assistance device of claim 14.

17. the output unit outputs, for each divided period, the degree of satisfaction of the constraint condition realized by the sampled target price coefficients; 17. The pricing assistance device of claim 16.

18. the output unit outputs the range of the constraint condition together with the degree of satisfaction of the constraint condition.

17. The pricing assistance device of claim 16.

19. an access restriction unit that permits access only to users who have a viewing authority based on the degree of satisfaction of the constraints; 15. The pricing assistance device of claim 14.

20. The pricing support device according to any one of claims 1 to 17, inputting a market indicator to be used in an object price determination formula that determines a price of the trading object based on the market indicator, and one or more constraints that the trading of the trading object must satisfy; an optimization step of optimizing a target price coefficient included in the target price determination formula so as to satisfy the constraints; A pricing support method comprising:

21. The method is executed by a computer, causing the computer to: The device functions as a price determination support device according to any one of claims 1 to 17. Pricing assistance program.

Images