JP2003296577A - Sales contract support system and sales contract support method - Google Patents

Abstract

(57) [Summary] [Problem] To support the planning of an appropriate trading plan. Kind Code: A1 A sales contract support system and a sales contract support method for selecting and trading a financial derivative product, wherein two types of feature amounts are calculated based on a price scenario, and a degree of change is calculated based on the two types of feature amounts. A frequency distribution is calculated, and the respective frequency distributions are totaled to determine a purchase ratio of the financial derivative product. According to the present invention, even if the technical knowledge is insufficient,
It is possible to provide a sales contract support system and a sales contract support method that can formulate an appropriate sales plan.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a sales contract support system and a sales contract support method.

[0002]

BACKGROUND OF THE INVENTION In a liberalized electricity market, generators are exposed to fluctuating power selling prices. On the other hand, in the case of thermal power generation, the prices of fuel such as heavy oil, coal, and gas fluctuate due to fluctuations in market prices overseas and fluctuations in exchange rates.

A so-called risk hedging method is effective for controlling these price fluctuation risks and raising stable profits. For example, a supply contract that fixes the power selling price for a certain period is a type of futures contract. In overseas energy markets, not only fuel and power futures and forward contracts but also more advanced financial derivatives, so-called derivative products, can be used. For more information on these, see Toyo Keizai Inc. “Financial Engineering of Electricity Liberalization”. Hereinafter, these electric power and fuel futures and derivative products are collectively referred to as energy products.

When a power supplier purchases a fuel energy product in the deregulated power market, a necessary amount is calculated based on a future fuel consumption plan, and the product is purchased based on experience while observing price trends. Since that method depends only on knowledge and experience, there has never been a technology that used to be a system for determining a purchase combination of products that can effectively suppress fluctuations in purchase costs against price fluctuations and changes.

[0005] In the above-mentioned document, although there is a description regarding the characteristics of energy products, there is no description about the effective use thereof. This also applies to many other published documents. This is because if there is an effective theory of market buying and selling, it is more profitable to use it yourself than to publish it.

As a scenario search processing method in the risk analysis of financial assets, there is a technique described in Japanese Patent Laid-Open No. 9-81640.

[0007]

In order to use these energy products, it is necessary to have sufficient knowledge and experience in markets and transactions. However, at present, even if the managers and purchasers engaged in the power generation industry in Japan have sufficient knowledge, it is impossible to gain experience in a country without a free energy market. There has been a demand for a sales contract support system that determines purchase combinations of energy products that can suppress fluctuations in purchase costs from the result of statistically processing price fluctuations.

An object of the present invention is to provide a sales contract support system and a sales contract support method capable of formulating an appropriate sales plan even if the expert knowledge is insufficient.

[0009]

SUMMARY OF THE INVENTION The present invention is a sales contract support system for selecting and selling at least one financial derivative of a spot product, a futures product and an option. A price scenario part that generates a predicted value of, and a calculation part that calculates two types of feature quantities based on the price scenario output from the price scenario part,
A calculation unit that calculates a frequency distribution of the degree of variation from each of the two types of feature amounts; and a purchase ratio determination unit that aggregates the calculated frequency distributions and determines a purchase ratio of the financial derivative product. Characterize.

[0010]

BEST MODE FOR CARRYING OUT THE INVENTION Energy products are considered to have suitable combinations for fluctuating market prices and their predicted values in view of the characteristics known from the aforementioned documents. However, the value that seems appropriate in the actual market is not necessarily optimal.

From the standpoint of actually operating the power generation equipment, the appropriate is a combination of energy products that guarantees a sufficiently low risk and profitability above a certain level, and the optimality of the value is not always guaranteed. May be. It can be said that the effect is sufficient if the risks are suppressed to the extent that it does not interfere with the operation of the power station and the profits that were initially targeted at the time of construction of the facilities were obtained.

The embodiment of the present invention is a power sale contract support system for guiding the operator of a power generation facility to a fuel purchase plan sufficient for maintaining the operation of the power generation facility due to market price fluctuations and a power sales plan. Is.

The method for determining the purchase ratio of energy products in this power sale contract support system is to calculate the differential value of the moving average of the price fluctuations of the price fluctuation data of the energy product, and to calculate the differential value, For example, if the differential value is large, purchase options, if the differential value is medium, buy futures,
If the differential value is small, a physical product is purchased, and a flag corresponding to the energy product to be purchased is set for the size of the differential value, and the flag is integrated for a certain period of time to obtain the frequency distribution corresponding to each energy product. create.

On the other hand, the standard deviation in the movement section of the price fluctuation is calculated, and the frequency distribution is created by the same processing.

The purchase ratio of each energy product is determined by adding these two frequency distributions or taking the weighted average.

By using a hysteresis circuit when converting the differential value or the standard deviation value into a flag, it is possible to incorporate the effect of history and suppress the frequent change of the flag value due to fluctuations.

(Example) A qualitative strategy in ordinary fuel purchase will be described. A detailed description of futures and call options will be omitted. For details, refer to the above-mentioned document "Financial Engineering of Electricity Liberalization".

In this embodiment, in order to stabilize the purchase cost or sales income of the product in the commodity market,
A system for obtaining a transaction guideline in the case of selecting at least one financial derivative product among cash, futures and options and purchasing or selling it in combination will be described.

FIG. 2 is an explanatory diagram showing the relationship between the required amount of fuel in the future and the planned purchase amount that is predetermined for energy products such as futures and options. Generally, the price of energy products is fixed monthly. The power producer estimates future fuel requirements and pre-books energy products to meet these requirements.

The difference between the reserved amount and the required amount is procured by a market price transaction (spot transaction). For example, in the case of a futures contract, a futures contract whose settlement month (contract month) is October is called an “October contract”. Since the transaction price of this futures commodity changes according to daily price fluctuations and exchange fluctuations, the price of the same fuel in the same contract month will be different depending on the date when the futures contract is concluded. Therefore, the contract date and contract price are entered in the "futures" in FIG.

In the case of a call option, the exercise price is the contract price, but since the option is a sale of rights,
A consideration (premium) for the acquisition of the right is required.
Premium is the cost at the time of contract. Like futures, even options with the same contract month and same exercise price have different premium prices depending on the contract date.

In the case of a fuel purchase transaction, based on past information,
A problem is how to effectively fill the bar graph of FIG. In the case of power sale transactions, call options are put
The task is basically the same, except that instead of the option, the width of the bar graph becomes 30 minutes, which is the standard of the principle of the same amount at the same time.

FIG. 10 qualitatively summarizes the relationship between changes in the physical price and the desired purchase amount of each energy product from the characteristics of the energy product. The price of futures products is almost linked to the physical price. The premium price of the option is also calculated based on the physical price, so it is linked to the physical price. First, with regard to options, it is costly (premium) just to acquire option rights, so if the price tends to be stable or declines, it is better to reduce the purchase amount. If prices are rising, you can expect an insurance effect, so it is better to proceed with the purchase of options. Next, futures products are basically the same as options, but unlike options, consideration does not occur at the time of purchase (even if a deposit is required, it will be settled at the time of settlement), so when it tends to be stable. Can also be used to lock in future spending. There is a high possibility that a margin will be produced if the actual product is not used when the price is rising and is used when the price is declining. In addition, there is no problem in using it when the tendency is stable.

FIG. 11 qualitatively summarizes the relationship between the degree of fluctuation of the physical price and the desired purchase amount of each energy product, as in FIG. The degree of price fluctuation is strong, that is, there is a high risk that the profit will decrease, and has the same meaning as the "upward trend" in FIG. Therefore, FIG. 11 is similar to the “stable tendency” and “upward tendency” portions in FIG. 10.

FIG. 1 shows a sales contract support system according to an embodiment of the present invention for deriving the relationships of FIGS. 10 and 2 from actual price fluctuations and converting them into purchase volume distributions.

As shown in FIG. 1, first, the price scenario section 10 outputs a history of past price fluctuations and a future predicted value. That is, the past history of the actual market price or the future predicted value is generated.

Then, two types of feature quantities are calculated based on the price scenario output from the price scenario unit 10.

As the first feature amount, the derivative of the moving average is calculated. The moving average differential calculation unit 30 takes the moving average of the output of the price scenario unit 10 and outputs the differential value.

On the other hand, the moving standard deviation is calculated as the second characteristic amount. The moving standard deviation calculation unit 20 calculates the standard deviation of the data string in a certain moving section of the output of the price scenario unit 10 in the same procedure as the moving average.

Next, the frequency distribution of the degree of variation is calculated from each of the two types of characteristic amounts.

In the first frequency distribution calculation, first, in the hysteresis circuits 40 to 60, the output from the moving standard deviation calculating section 20 falls within a preset range corresponding to each energy product of futures, futures and options. When it is off, 1 is output, and when it is off, 0 is output.

The frequency distribution calculation unit 100 counts the frequency of 1 output for each energy product with the outputs of the hysteresis circuits 40 to 60.

On the other hand, in the first frequency distribution calculation, first, in the hysteresis circuits 70 to 90, the output from the differential value calculation unit 30 of the moving average is set in advance corresponding to each energy product of the actual product, futures product and option. 1 when entering the range
Is output, and 0 is output when it is out.

The frequency distribution calculation unit 110 totals the frequency of 1 output for each energy product by the outputs of the hysteresis circuits 50 to 70.

The purchase ratio determining unit 120 sums up the outputs of the two frequency distribution calculating units 100 and 110, and calculates a desired purchase ratio of energy products corresponding to the price fluctuation at that time.

With the above configuration, an appropriate purchase ratio can be easily calculated.

The functions of the sales contract support system according to the embodiment of the present invention will be described more specifically with reference to FIGS. For the sake of simplicity, two futures contracts are the contract month and call options in which the contract price is the next month and the exercise price is the current physical price plus a certain positive value. This will be explained when determining the purchase ratio.

First, the functions of the price scenario 10, the moving standard deviation calculation 20, and the moving average differential value calculation unit 30 will be described with reference to FIG. The curve in FIG. 7 is a sample of a price scenario that is simulated in a random walk. 2 of the display of FIG.
Forty business days correspond to about one year, and prices are daily values.

The bar graph on the lower side of FIG. 7A shows the moving standard deviation of the price scenario, which is the output of the moving standard deviation calculating section 20. In the example of FIG. 7, the standard deviation of the data for the past one month is calculated for the moving standard deviation calculation day.

The bar graph in FIG. 7 (b) is the differential of the moving average of the price scenario, and is the output of the differential value calculating unit 30 of the moving average. This is also past 1 with respect to the differential calculation date of the moving average
The derivative of the moving average of the data for months was calculated.

Next, the functions of the hysteresis circuits 40 to 60 will be described with reference to FIGS. 3 and 5. Fig. 3 shows the hysteresis circuit 4
It is explanatory drawing which shows the input-output relationship of 0-60. For example, it is assumed that the moving standard deviation is at point a. At this time, the hysteresis circuit 50 corresponding to the futures outputs 1 and the other two hysteresis circuits output 0. When the input changes from point a to point b, the output does not change due to the characteristics of the hysteresis circuit, and when it reaches point c, the output of the hysteresis circuit 60 corresponding to the call option becomes 1, and the other two hysteresis The output of the circuit becomes 0.

When the input starts from point a, passes through point b, and returns to point a, the hysteresis circuit 50
Always outputs 1 and the other two hysteresis circuits always output 0. Conversely, when the input starts from the point c and reaches the point b, the output of the hysteresis circuit 60 corresponding to the call option becomes 1 and the outputs of the other two hysteresis circuits become 0 depending on the characteristics of the hysteresis circuit. In this way, the output at point b takes into consideration the influence of history.

Next, the functions of the hysteresis circuits 70 to 90 will be described with reference to FIGS. 4 and 6. 4 shows the hysteresis circuit 7
It is explanatory drawing which shows the input-output relationship of 0-90. For example, suppose that the differential value of the moving average is at point A. At this time, the hysteresis circuit 80 corresponding to the futures outputs 1 and the other two hysteresis circuits output 0. Input is from point A to B
When the point is reached, the output does not change due to the characteristics of the hysteresis circuit. When the point C is reached, the output of the hysteresis circuit 90 corresponding to the call option becomes 1, and the outputs of the other two hysteresis circuits are 0. Become.

Here, when the input starts from the point A, passes through the point B, and returns to the point A again, the hysteresis circuit 80
Always outputs 1 and the other two hysteresis circuits always output 0. Conversely, when the input starts from the point C and reaches the point B, the output of the hysteresis circuit 90 corresponding to the call option becomes 1 and the outputs of the other two hysteresis circuits become 0 depending on the characteristics of the hysteresis circuit. In this way, the output at point B takes into consideration the influence of history.

By using the hysteresis circuit, it is possible to prevent the output from changing frequently when the moving standard deviation, which is the variation amount, or the differential value of the moving average changes subtly. It also has the effect of not unnecessarily increasing the purchase rate of call options, which are expensive to purchase rights.

FIGS. 5 and 6 show the input / output relationship of FIGS. 3 and 4 as a time series. As shown in the figure, while the moving standard deviation and the differential value of the moving average change with time, the output of the circuit corresponding to which energy product becomes 1 depending on where in the area divided by the hysteresis circuit exists. Is decided.

FIG. 8 shows an example of the counting result in the two frequency distribution calculators 100 and 110 for counting the outputs of the six hysteresis circuits. When the price fluctuation in a certain section is processed, the frequency distribution of the differential value of the moving standard deviation and the moving average is obtained as shown in FIG.

In the purchase ratio determination 130, the ratio of this frequency distribution may be used as it is to determine the purchase ratio of each energy product, or the purchase ratio may be determined using some calculation process, for example, a linear or non-linear mapping function. You may decide.

From the above description, it is possible to determine the futures contract for the next month, the call option for which the current month is the next month and the exercise price is higher than the actual price, and the purchase ratio of the actual products. When attempting to purchase call options with different strike prices, the hysteresis circuits 60 and 90 corresponding to the call options can be subdivided for each strike price to obtain a finer option purchase ratio as shown in FIG. I can. Similarly, for futures, you can purchase futures with different contract months.

The sales contract support system according to the embodiment of the present invention can be used not only for fuel but also for electric power trading.
In this case, the option is a put option,
The calculation formula and handling are the same as for the call option.

The sales contract support system according to the embodiment of the present invention determines the purchase amount ratio of energy products by combining the hysteresis circuits. Similar results can be obtained by replacing this hysteresis circuit with a fuzzy inference circuit. When a fuzzy inference circuit is used, the learning function of the neural network can also be used to build a self-learning contract support system.

In this embodiment, a method of calculating the purchase ratio of energy products in a certain future section from the history of price fluctuations in the past certain period has been shown. By inputting a future price fluctuation prediction value as the price scenario 10, it is possible to determine an appropriate purchase ratio of energy products if high-precision prediction is possible. The Monte Carlo method can also be used to predict the future. This is a method of statistically processing the obtained purchase ratio while generating innumerable price scenarios. Price Scenario 1 of Embodiment of the Present Invention
If a statistical process is performed such as generating an infinite number of 0s and adding the obtained frequency distributions to all scenarios, the purchase ratio that will produce an average effect for all possible scenarios will be determined. You can

[0053]

According to the present invention, it is possible to provide a sales contract support system and a sales contract support method capable of making an appropriate sales plan even if the expert knowledge is insufficient.

[Brief description of drawings]

FIG. 1 shows a configuration diagram of a sales contract support system according to an embodiment of the present invention.

FIG. 2 is an explanatory diagram showing a purchase mode of fuel.

FIG. 3 is an explanatory diagram showing a logic of a hysteresis circuit that is an embodiment of the present invention.

FIG. 4 is an explanatory diagram showing the logic of the hysteresis circuit according to the embodiment of the present invention.

FIG. 5 is an explanatory diagram showing an input / output relationship of the hysteresis circuit according to the embodiment of the present invention.

FIG. 6 is an explanatory diagram showing an input / output relationship of the hysteresis circuit according to the embodiment of the present invention.

FIG. 7 is an operation explanatory diagram of a sample of price fluctuation, calculation of moving variance, and calculation of differential value of moving average.

FIG. 8 is an explanatory diagram showing calculation results of two frequency distributions according to the embodiment of this invention.

FIG. 9 is an explanatory diagram showing an example of a frequency distribution calculated for purchasing option products having different strike prices according to the embodiment of the present invention.

FIG. 10 is an explanatory diagram showing a relationship between past changes in fuel prices and effects of energy products.

FIG. 11 is an explanatory diagram showing a relationship between past fluctuations in fuel price and effects of energy products.

[Explanation of symbols]

10 ... Price scenario part, 20 ... Moving standard deviation calculation part, 3
0 ... Moving average differential value calculation unit, 40, 50, 60, 7
0, 80, 90 ... Hysteresis circuit, 100, 110 ...
Frequency distribution calculation unit, 120 ... Purchase ratio determination unit.

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Akira Yamada             2-12-1 Omika-cho, Hitachi-shi, Ibaraki Prefecture             Ceremony Company Hitachi, Ltd.

Claims (7)

[Claims] 1. A sales contract support system for selecting and selling at least one financial derivative of a physical product, a futures product, and an option, which is a price scenario for generating a past history of a market price of a physical product or a future predicted value. Section, a calculation section that calculates two types of feature quantities based on the price scenario output from the price scenario section, and a calculation section that calculates the frequency distribution of the degree of change from the two types of feature quantities, respectively. And a purchase ratio deciding unit that decides a purchase ratio of the financial derivative product by summing up respective frequency distributions. 2. A transaction guideline in the case of selecting at least one financial derivative product in kind, futures and options and purchasing or selling them in combination in order to stabilize the purchase cost or sales income of the product in the commodity market. A sales contract support system for obtaining a price scenario part that generates a past history of the market price of a physical product or a future forecast value, and a moving average value of the price scenario that is the output of the price scenario part, A moving average differential value calculating unit that calculates and outputs a differential value of the moving average value; a moving standard deviation calculating unit that calculates a standard deviation in a moving section of the price scenario; and an output of the moving average differential value calculating unit. Define the range in which you should trade the futures, the range in which you should trade the futures, and the range in which you should trade the options for the size. Has a first switch circuit group that sets flags corresponding to respective financial derivative products, and trades the future range and the range in which the actual product is traded with respect to the magnitude of the output of the moving standard deviation calculation unit. A second switch circuit group which defines a power range and a range in which the option should be traded, and sets a flag corresponding to each financial derivative when the output enters the range, the first switch circuit A first frequency distribution calculating unit that aggregates outputs of the group to create a first frequency distribution; and a second frequency distribution that aggregates outputs of the second switch circuit group to create a second frequency distribution. A sales contract support system comprising: a calculation unit; and a purchase ratio determination unit that totalizes the first and second frequency distributions and determines a purchase ratio of the financial derivative product from the totalized result. 3. The sales contract support system according to claim 2, wherein the first and second switch circuit groups use a hysteresis circuit or a fuzzy arithmetic element. 4. The sales contract support system according to claim 2, wherein the purchase ratio determination unit takes a weighted average of the first frequency distribution of the first period and the second frequency distribution of the first period as a purchase ratio, A power sales contract support system characterized by a ratio. 5. The sales contract support system according to claim 2, wherein the purchase ratio determining unit takes a weighted average of the first frequency distribution of the first period and the second frequency distribution of the first period to obtain a weighted average of the purchase ratio. A power sales contract support system characterized by a ratio. 6. A sales contract support method for selecting and selling at least one financial derivative of a physical product, a futures product, and an option, the method comprising generating a past history of a market price of a physical product or a future predicted value. , A step of calculating two types of feature quantities based on the price scenario output from the price scenario part, a step of calculating a frequency distribution of the degree of fluctuation from each of the two types of feature quantities, and the calculated respective frequencies And a step of totalizing distributions and determining a purchase ratio of the financial derivative product. 7. At least one financial derivative such as cash, futures, and options is selected in order to stabilize the purchase cost of fuel in the fuel market,
A method for supporting sales contracts for fuel purchase in the case of combined purchase, in which the past history or future forecast value of the physical market price of fuel is generated in the price scenario section, and the price scenario output from the price scenario section is used. The moving average value is obtained, the differential value of the moving average value is calculated and output, the standard deviation in the moving section of the price scenario is calculated, and the actual value is calculated with respect to the size of the output of the differential value of the moving average. Define the range to trade, the range to trade futures, and the range to trade options, and when the output falls within the range, set a flag corresponding to each financial derivative,
The outputs are aggregated to create a first frequency distribution. With respect to the output of the standard deviation, the range for trading the futures, the range for trading the futures, and the range for trading the options are defined. When the output is within the range, the flag corresponding to each financial derivative product is set, the output is aggregated to create the second frequency distribution, and the first and second frequency distributions are aggregated. Then, the sales contract support method for determining the purchase ratio of the financial derivative product from the aggregation result.