JP4360980B2 - System and method for setting up and receiving conditions in risk exchange related to weather - Google Patents

Description

  The present invention relates to a system used to set a payment / payment amount condition when two operators existing at different points exchange weather-related risks using the measurable weather at either point as an index, and Regarding the method.

  For electric power companies and gas companies, changes in temperature are a variable factor for earnings. For example, in an electric power company, the higher the summer temperature, the higher the demand for power due to cooling, and the higher the profit. Conversely, the lower the summer temperature, the worse the profit. On the other hand, in the gas company, the higher the summer temperature, the lower the demand for hot water supply gas and the higher the profit. On the other hand, the lower the summer temperature, the worse the profit. As described above, the electric power company and the gas company generate a risk of fluctuation in profitability in the opposite direction depending on the temperature.

  Therefore, conventionally, in order to hedge the risk of fluctuation in profits due to temperature as described above (referred to as “temperature risk” in the present application), there is a case where temperature risk is exchanged between the electric power company and the gas company. That is, when the temperature is higher than usual, the hedge amount is paid from the power company whose profit is improved to the gas company whose profit is worsened. On the contrary, when the temperature is lower than normal, the gas whose profit is improved is paid. The company pays the hedge amount to a power company whose profits deteriorate.

In relation to this exchange of temperature risk, for example, Patent Literature 1 discloses a system for enabling exchange of temperature risk between businesses existing in different regions. The temperature risk exchange method disclosed in this document is, for example, when a Tokyo electric power company and an Osaka gas company exchange temperature risks, and when both the Tokyo temperature and the Osaka temperature are higher than usual, Tokyo Pay the hedge amount from the power company in Osaka to the gas company in Osaka and pay the hedge amount from the gas company in Osaka to the power company in Tokyo when the temperature in Tokyo and Osaka are both lower than usual, otherwise The hedge amount is not paid out.
JP 2004-78903 A

  As described above, in the temperature risk exchange method disclosed in Patent Document 1, since the temperatures of the two regions (Tokyo and Osaka in the above example) where each business operator is located are used, the payment amount is calculated from the temperature at each point. The scheme for determination becomes complicated. Therefore, a simple scheme method capable of determining the payment amount using only one point as an index is desired.

  The present invention has been made in view of the above points, and uses only weather that can be measured, such as the temperature at any one of the businesses present at different points, to the weather between these businesses. The purpose is to be able to exchange the risks involved.

In order to achieve the above-mentioned object, the present invention is designed to receive and pay money when two operators existing at different points exchange weather-related risks using measurable weather at either point as an index. A system used to set the forehead condition,
A point acquisition unit for acquiring information representing two points where the operator exists;
A weather acquisition unit that acquires weather data representing a history of past weather at each of the two points;
A regression analysis unit that performs a regression analysis of the weather data of the other point based on the weather data of one of the two points;
Based on the regression analysis result by the regression analysis unit, a regression error distribution calculation unit for calculating the distribution of the regression error,
A dead zone determining unit that determines a dead zone when determining the amount of payment according to the weather based on the calculated distribution of regression errors.

  According to the present invention, based on the regression error distribution when the weather at two points is subjected to regression analysis, the dead zone when determining the amount of payment according to the weather is determined. Here, the dead zone is a meteorological range in which the amount paid and received is zero regardless of the deviation from the annual value of the weather. Therefore, even if the weather fluctuates within the range corresponding to the meteorological regression error distribution at both points, no money is paid or received. For this reason, payment is reversed between the case where the risk exchange related to the weather is performed using the weather at one of the two operators as an index and the case where the risk exchange related to the weather is performed using the weather at the other point as an index. Can be prevented from occurring. For example, temperature and precipitation data can be used as the weather data in the present invention.

  The present invention further includes a data normalization unit that normalizes the acquired weather data based on the probability distribution, and the regression analysis unit performs a regression analysis based on the normalized weather data. Also good.

  Moreover, the system of this invention is good also as providing the reference | standard location acquisition part which acquires the information showing said one point.

  Further, the system of the present invention accepts an input of an allowable value of the probability that the payment when the weather at one of the two points is used as an index and the payment when the other weather is used as an index are reversed. An acceptable probability input unit may be provided, and the dead zone determination unit may determine the dead zone based on the calculated regression error distribution and the inputted tolerance value.

  The system according to the present invention may further include a dead band output unit that outputs information representing the determined dead band. In this case, the dead band output unit transmits information representing the dead band to the computers of the two operators. It is good also as transmitting to.

  The system of the present invention may include a payment / payment condition setting unit that sets a payment / payment condition based on the determined dead zone and transmits information representing the set payment / payment condition to the computers of the two operators. Good.

In addition, the present invention is a method for setting a payment / payment amount condition when two operators existing at different points exchange weather-related risks using the weather at one of the points as an index. Computer
Receiving the designation of two points where the operator exists;
Obtaining weather data representing past weather history at each of the two points;
Performing regression analysis of meteorological data at the other point based on meteorological data at one of the two points;
Calculating a regression error distribution based on a regression analysis result by the regression analysis unit;
Based on the calculated regression error distribution, determining a dead zone related to the weather when determining the payment amount according to the weather,
A condition setting method for risk exchange related to weather, characterized by

  According to the present invention, it is possible to exchange weather-related risks between these operators using only measurable weather such as the temperature of one of the operators present at different points. It becomes.

  Hereinafter, a system according to an embodiment of the present invention will be described. The system of the present embodiment is for supporting the setting of the condition for receiving and paying the hedge amount according to the temperature when two companies existing in different regions exchange the temperature risk.

First, the principle of temperature risk exchange according to the present embodiment will be described.
As described in the section of the prior art above, conventionally, for example, between power companies and gas companies such as electric power companies and gas companies, which receive the risk of fluctuations in revenue in the opposite direction due to high and low temperatures, receive hedge amounts according to the high and low temperatures. By paying, the temperature risk is exchanged. Conventionally, when the temperature risk is exchanged only between businesses existing in the same region, or when businesses in different regions exchange temperature risk as in Patent Document 1, these two regions are exchanged. Both temperatures are being used. This is because the temperature fluctuation tendency varies from region to region, so when the payment conditions for operators in different regions are determined using the temperature in one region, the unreasonable results described below will occur. It will occur. Hereinafter, an example in which a business operator α (for example, a gas company) in Tokyo and a business company β (for example, an electric power company) in Fukuyama exchange temperature risks will be described in detail with reference to FIGS.

  FIG. 1 is a diagram showing annual changes in average temperatures in Tokyo and Fukuyama in the summer (July to September). As shown in the figure, although the temperature fluctuations at both locations show similar trends, it can be seen that the temperature levels are reversed in some years.

  FIG. 2 is a diagram illustrating an example of a payment condition for setting a payment amount based on a deviation of the temperature from the annual value. As can be seen from FIG. 1, the temperature at each point has a trend of gradually increasing. Therefore, for example, a reference temperature for each year is obtained by a least-squares line according to this trend, and this reference temperature is used as an annual value. In addition, since the standard deviation of the temperature probability distribution varies from region to region, as shown in FIG. 2, the amount of payment is determined using the value obtained by normalizing the deviation from the annual value with the standard deviation of the temperature probability distribution as the horizontal axis. Yes.

  In this example, the operator α in Tokyo is, for example, a gas company, and the profit deteriorates as the summer temperature increases. The operator β in Fukuyama, for example, is an electric power company, and the income increases as the summer temperature increases. It is supposed to be a company that improves. In the example of FIG. 2, the payment amount when the payment from the business operator α to the business operator β occurs is represented by a positive value, and the payment when the payment from the business operator β to the business operator α occurs. The amount is expressed negatively. Therefore, under the payment / payment conditions shown in the figure, when the temperature is higher than usual (the payment amount is negative), payment from the operator β to the operator α is performed.

  FIG. 3 shows (a) when the payment amount is determined using the temperature in Tokyo according to the payment condition shown in FIG. 2, and (b) when the payment amount is determined using the temperature in Fukuyama. Indicates the amount paid. As mentioned above, there is a certain degree of correlation between the temperature in Tokyo and the temperature in Fukuyama, so almost the same payments occur regardless of the calculation, but the year enclosed in an ellipse in the figure In the case of (a) and the case of (b), the positive and negative amounts of payment are reversed. For example, the amount received and paid determined using the temperature in Tokyo in 1983 is positive (payment from the operator α to the operator β), while the amount paid and received determined using the temperature in Fukuyama is negative (the operator payment from β to operator α). In this case, if the amount of payment is set using the temperature in Tokyo, the Fukuyama operator β should receive payment of the hedge amount to compensate for the deterioration in profits due to the low temperature in Fukuyama. You will have to pay. In this way, if the amount of payment is reversed depending on the temperature at which point is used, the place where you should receive payment (or pay to the other party) using the temperature of your location is conversely paid to the other party This leads to an unreasonable situation (hereinafter referred to as “reverse payment”) in which the payment is received (or payment is received from the other party).

  The reverse payments as described above are caused by the fact that the temperatures in Tokyo and Fukuyama are not completely correlated, and a regression error occurs when the temperatures at both locations are regressed.

  On the other hand, in the present embodiment, based on this regression error distribution, in the money receiving and paying conditions as illustrated in FIG. 2, the dead zone related to the temperature (that is, the amount received and received becomes zero even if the temperature changes). Range), and when the deviation from the annual value of the temperature is within the range of this dead zone, it is possible to prevent the reverse payment as described above from occurring.

Hereinafter, the processing procedure of the air temperature risk exchange according to the present embodiment will be specifically described.
FIG. 4 is a flowchart showing a processing procedure for temperature risk exchange according to the present embodiment.

  First, historical temperature data (for example, average temperatures from July to September in the past year) for locations A and B (in this example, A is Tokyo and B is Fukuyama) of businesses α and β who are trying to exchange temperature risk. Is obtained (S100).

Next, the change trend of the temperature data in each region is obtained by, for example, linear approximation using the least square method, and the reference temperature μ _A and μ _B at each point are calculated using this linear approximation formula (S102). When the air temperature data illustrated in FIG. 1 is used, μ _A and μ _B are calculated as in the following equations (1) and (2), respectively.
μ _A = −64 + 0.045 × (A.D. year) (1)
μ _B = −58 + 0.042 × (A.D. year) (2)

Next, the annual actual temperatures T _A and T _B at each point are normalized using the reference temperatures μ _A and μ _B calculated by the equations (1) and (2). For example, when it is assumed that the distribution of (T _A −μ _A ) and (T _B −μ _B ) is a normal distribution, normalized temperatures t _A and t _B are obtained by the following equations (3) and (4) ( S104).
_{t A = (T A -μ A} ) / σ A ··· (3)
t _B = (T _B −μ _B ) / σ _B (4)
However, σ _A and σ _B are standard deviations of the distribution of (T _A −μ _A ) and (T _B −μ _B ), respectively.

Next, a designation input as to whether the businesses α and β use the temperature at the point A or B to exchange the temperature risk is accepted (S106). For example, when the temperature at point A is used, the regression coefficient r is obtained by performing regression analysis of the normalized temperature t _A at point A using the normalized temperature t _B at point _B (S108).

Next, the regression error ε is calculated by the following equation (5) (S110).
ε = t _A −r · t _B (5)
That is, the regression error ε is an error between the temperature at point A estimated by regression analysis using the temperature at point B and the actual temperature at point A, and the temperatures at point A and point B are not completely correlated. Occur. FIG. 5A shows an example of the regression error ε calculated using the example of FIG. 1, and FIG. 5B shows the distribution of the regression error ε of FIG.

Next, based on the probability distribution of the regression error ε, a dead zone in the payment / receipt condition is set (S1112). This dead band is set assuming that the distribution of the regression error ε shown in FIG. 5B is a normal distribution, for example, and the probability that the above-described reverse payment will occur based on the standard deviation σ _ε in the normal distribution. Are set to be equal to or less than the specified allowable probability P. For example, if the allowable probability P is 10%, the occurrence probability 5% value in the standard normal distribution (the value of x such that the value obtained by integrating the standard normal distribution function from 0 to x becomes 0.45) is 1.65. Therefore, the dead zone is set in the range of −1.65σ _ε to 1.65σ _ε . However, this value is based on the standard deviation of the temperature distribution, and in order to convert this value to the temperature, the value is multiplied by the standard deviation of the temperature distribution at the target point. That is, when the temperature risk exchange is performed based on the temperature at the point A as in this example, the dead zone is from −1.65σ _ε · σ _A (° C.) to 1.65σ _ε · σ _A (° C.). .

  Using the dead zone set in this way, for example, as shown in FIG. 6, the receiving and paying conditions including the dead zone are determined (S114). Then, the determined payment / payment conditions are transmitted to the businesses α and β (S116), and if the consent of both is obtained (S118), the payment / payment conditions are fixed. On the other hand, when consent is not obtained, it returns to S100 and repeats a process on another condition.

  The system 10 of the present embodiment performs the processing from the input of the temperature data in S100 to the setting of the dead zone in S112, the setting of the payment condition in S114, or the transmission of the payment condition in S116 in the temperature risk exchange process described above. Is to do.

  FIG. 7 is a hardware configuration diagram of the system 10 according to the present embodiment. As shown in the figure, a system 10 includes a CPU 100, a memory 102, a storage device 104 such as a hard disk device, a drive device 106 such as a CD-ROM or DVD-ROM, a display device 108, an input device 110 such as a keyboard or a mouse, The computer system includes a communication interface device 112 and the like.

  FIG. 8 is a functional block diagram of the system 10 of the present embodiment. As shown in the figure, the system 10 includes a point acquisition unit 20, a reference location acquisition unit 22, a weather data acquisition unit 24, a data normalization unit 26, a regression analysis unit 28, a regression error distribution calculation unit 30, and an allowable probability input unit 32. , The dead zone determining unit 34 and the dead zone output unit 36 are provided. These functional units 20 to 32 are realized by the CPU 100 reading a program installed in the storage device 104 into the memory 102 and executing it.

  Further, the system 10 is connected to a temperature database server 12 that stores past temperature data of each region in the country as, for example, a value of average temperature every month. The temperature database server 12 provides the system 10 with past temperature data of the area requested by the system 10. Further, as shown in the figure, the system 10 may be connected to user computers 14 and 16 of business operators α and β who are going to exchange temperature risks via a network. The user computers 14 and 16 may be computer systems such as personal computers and workstations, or may be mobile terminals such as mobile phones and PDAs. In short, any information processing apparatus that can communicate with the system 10 may be used. Communication between the system 10 and the temperature database server 12 and the user computers 14 and 16 is controlled by the communication interface device 112.

  The point acquisition unit 20 acquires point designation information indicating the locations A and B of the two companies that are to exchange the temperature risk. In addition, the reference site acquisition unit 22 acquires information indicating which temperature of the two points is used as an index to exchange the temperature risk. Acquisition of such information may be performed by receiving input from the input device 110 of the system 10 or may be performed by receiving information input by the user computer 14 or 16 via a network.

The meteorological data acquisition unit 24 acquires the temperature data representing the past actual temperatures T _A and T _B of the acquired points A and B, for example, by requesting the temperature database server 12 online. However, the present invention is not limited to this. For example, the data may be read from a storage medium such as a CD-ROM or DVD-ROM in which the temperature data of each place is stored.

Data normalization unit 26, weather data acquisition unit 24 has acquired each point A, the temperature T _A of _B, the reference temperature for each year by performing linear approximation calculation by the example method of least squares T _B mu _A and mu _B And standard deviations σ _A and σ _B of the distribution of (T _A −μ _A ) and (T _B −μ _B ) are calculated. Then, using these calculated values, the temperatures are normalized according to the above equations (3) and (4), and the normalized temperatures t _A and t _B are calculated. The calculation of the reference temperatures μ _A and μ _B is not limited to linear approximation, and may be performed by curve approximation such as quadratic or cubic. In short, the reference temperatures μ _A and μ _B may be calculated by performing an appropriate approximation according to the temperature trend.

Based on the normalized temperatures t _A and t _B , the regression analysis unit 28 performs a regression analysis of the normalized temperature at the other point using the normalized temperature at one point acquired by the reference site acquisition unit 22. The regression coefficient r is calculated.

The regression error distribution calculation unit 30 calculates a regression error ε using the calculated regression coefficient r, and obtains a probability distribution of the regression error ε. Specifically, when the point A is acquired by the reference location acquisition unit 22, ε = t _A −r · t _B
Is used to calculate the regression error ε, and when the point B is acquired, ε = t _B −r · t _A
To calculate the regression error ε. Assuming that the distribution of the regression error ε thus calculated is, for example, a normal distribution, the standard deviation σ _ε of the normal distribution is calculated.

  The allowable probability input unit 32 receives an input of an allowable value (allowable probability) P of the probability that reverse payment will occur depending on which temperature is used. For example, when the occurrence of reverse payment is set to a level of once every 10 years, 10% is input as the allowable probability P.

The dead zone determination unit 34 determines a dead zone based on the input allowable probability P and the standard deviation σ _ε of the distribution of the regression error ε. That is, as described above, for example, if the allowable probability P is 10%, ± 1.65σ _ε (when the unit is converted into temperature, ± 1.55 using the standard normal distribution function of 1.65) 1.65σ _ε · σ (° C.); σ is the dead zone of the standard deviation of the temperature distribution at the point used for temperature risk exchange.

  Then, the dead zone output unit 36 displays and outputs the determined dead zone on the display device 108 or transmits it to the user computers 14 and 16 of the business operators α and β as indicated by broken line arrows in the figure. The businesses α and β refer to this dead zone and determine, for example, a delivery condition as shown in FIG. In the example of FIG. 6, the straight line J of the basic receiving and paying condition is shifted to both sides of the dead zone. However, the present invention is not limited to this. It is also possible to adopt a configuration in which only 0 is within the range.

  FIG. 10 shows, for example, a case where the Fukuyama operator does not consider the regression error for each case where the temperature risk exchange is performed using the temperatures of Fukuyama, Tokyo, and Sapporo (that is, with broken lines in FIGS. 6 and 9). When the dead zone is not taken into consideration as shown by the straight line J shown in FIG. 6, when the payment condition of FIG. 6 is used (the payment condition (1)), and when the payment condition of FIG. 9 is used (the payment condition (2) )) Shows the number of reverse payments in the past 30 years. As can be seen from this figure, when the Fukuyama operator used the temperatures in Tokyo and Sapporo, the dead zone was in contrast to the 6th and 9th reverse payments if the dead zone was not taken into account. 6 and 9 in consideration of the above, the number of occurrences of reverse payment is zero. Therefore, it can be seen that the reverse payment can be prevented even when the Fukuyama business operator exchanges temperature risks with the business operators in Tokyo and Sapporo.

  FIG. 11 shows the annual average amount of payment for each case as in FIG. As shown in the figure, a certain amount of payment is generated even when a dead band is provided in the payment condition, and it can be understood that the effect of hedging the temperature risk can be maintained.

  As described above, according to the present embodiment, even when an operator existing at a different point exchanges temperature risk, a simple scheme based only on the temperature at one of the points is used, while receiving the opposite. It is possible to prevent an unreasonable temperature risk exchange called payment.

  In addition, fluctuations in temperature have a significant impact on the operator's profit and loss when the temperature deviates significantly from the annual value. When the deviation from the annual value is small, it is necessary to pay for the exchange of temperature risks. The reality is that the nature is small. Therefore, as in this embodiment, if a dead zone is provided in the payment condition, payment will occur only when a large deviation from the annual value occurs. A suitable temperature risk exchange can be performed.

  In the above embodiment, the dead zone is set on the assumption that the distribution of the regression error ε is a normal distribution. However, the present invention is not limited to this, and the distribution of the regression error ε is another distribution such as a t distribution. A dead zone may be set assuming that

  In the above embodiment, the system 10 executes the process until the determined dead band is output. However, the present invention is not limited to this. That is, the slope of the straight line J in FIG. 6 or FIG. 9 is registered in advance, and the payment condition as shown in FIG. 6 or FIG. 9 is set on the screen based on the determined dead zone and this slope. Alternatively, the data may be output or transmitted to the user computers 14 and 16 of the businesses α and β online.

  In addition, if the acceptance / rejection of the set payment conditions is received online from the user computers 14 and 16 of the business operators α and β, and if it is not accepted, the change of the point where the temperature is used, the gradient of the payment amount, etc. By allowing various conditions to be changed online, a contract for temperature risk exchange may be established on the system 10.

  In the above embodiment, the case where the exchange of the temperature risk is performed in order to hedge the income risk due to the temperature fluctuation, but the profit of the operator may be affected by other weather conditions such as precipitation in addition to the temperature. The present invention can also be applied to risk exchange based on precipitation. That is, for two businesses that are adversely affected by profits due to the magnitude of precipitation, regression analysis of precipitation data at both points is performed in the same manner as in the above embodiment, and a dead zone is set based on the regression error. Thus, appropriate risk exchange can be performed while using precipitation at one of the points.

It is a figure which shows annual transition of the average temperature of Tokyo and Fukuyama in the summer (July to September). It is a figure showing an example of the payment conditions for setting the payment amount based on the deviation from the annual value of the temperature. According to the payment conditions shown in Fig. 2, (a) the payment amount is determined using the temperature in Tokyo, and (b) the payment amount is determined based on the temperature in Fukuyama. FIG. It is a flowchart which shows the process sequence of the air temperature risk exchange concerning this embodiment. FIG. 5A shows an example of the regression error ε calculated using the example of FIG. 1, and FIG. 5B shows the distribution of the regression error ε. It is a figure which shows an example of the payment conditions including a dead zone. It is a hardware block diagram of the system which is one Embodiment of this invention. It is a functional block diagram of the system of this embodiment. It is a figure which shows another example of the payment conditions containing a dead zone. When the Fukuyama operator does not consider the dead zone as shown by the straight line J in FIG. 6 and FIG. 9 for each case where the temperature risk exchange is performed using the temperatures of Fukuyama, Tokyo, and Sapporo, FIG. The number of occurrences of reverse payments in the past 30 years when using the payment conditions (payment conditions (1)) and when using the payment conditions shown in FIG. 9 (payment conditions (2)) FIG. It is a figure which shows the annual average amount of payment amount in each case same as FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 System 12 Temperature database server 14,16 User computer 20 Point acquisition part 22 Reference location acquisition part 24 Weather data acquisition part 26 Data normalization part 28 Regression analysis part 30 Regression error distribution calculation part 32 Permissible probability input part 34 Dead zone determination part 36 Dead band output unit 100 CPU
102 memory 104 storage device

Claims (5)

Constructed using a computer that is communicably connected to a user computer, two companies that are located at different points can exchange weather-related risks using the measurable weather at either point as an indicator. A system that is used to set conditions for the receipt and payment of money,
A database for storing weather data representing past weather history at multiple locations;
A point acquisition unit that acquires information representing two points where the operator exists from the user computer ;
A weather data acquisition unit for acquiring the weather data in each of said two points,
A data normalization unit that obtains an approximate expression of the weather data for each of the two points based on the weather data, and normalizes the weather data for each of the two points based on the obtained approximate expression; ,
A reference value acquisition unit for accepting from the user computer designation of which risk related to weather is to be exchanged based on which weather data of the two points;
A regression analysis unit that performs regression analysis of the weather data of the other point based on the normalized weather data of the specified point;
Based on the regression analysis result by the regression analysis unit, a regression error distribution calculation unit that calculates the standard deviation of the distribution of the regression error,
Accepting an input of an allowable value of the probability that the payment between the two operators is reversed when the weather data at one of the two points is used as an index and when the other weather data is used as an index An allowable probability input section ;
A dead zone determining unit that determines a dead zone that is a range of the weather data that does not cause payment between the two operators based on the standard deviation and the tolerance ;
A system for setting up and receiving conditions in risk exchange related to weather, characterized by comprising: The system according to claim 1 , further comprising a dead zone output unit that outputs information representing the determined dead zone. The dead zone output unit according to claim 1 or 2 system of any one of and transmits the information representing the dead band to the two operators of the computer. Set the payment condition received on the basis of the dead zone in which the determined, of claims 1-3, characterized in that it comprises the receipts and payments condition setting unit for transmitting information representative of the receipt and conditions set to the two operators of the computer The system according to any one of claims. It is a method for setting conditions for the amount of money to be paid and received when two companies existing at different points exchange weather-related risks using measurable weather at one of the points as an index,
A computer that is communicably connected to a user computer
Storing weather data representing past weather history at multiple locations;
Obtaining from the user computer information representing two points where the operator exists;
A step of acquiring the meteorological data in each of said two points,
Obtaining an approximate expression of the weather data for each of the two points based on the weather data, and normalizing the weather data for each of the two points based on the obtained approximate expression;
Receiving from the user computer designation of which of the two points to exchange the risk associated with weather based on the weather data;
Performing regression analysis of meteorological data at the other point based on the normalized weather data at the designated point;
Calculating a standard deviation of a distribution of regression errors based on a regression analysis result by the regression analysis unit;
Accepting an input of an allowable value of the probability that the payment between the two operators is reversed when the weather data at one of the two points is used as an index and when the other weather data is used as an index Steps ,
Determining a dead zone that is a range of the weather data that does not cause payment between the two operators based on the standard deviation and the tolerance ;
A condition setting method for risk exchange related to weather, characterized by