JP2002083122A - System and method for evaluating financial product and storage medium storing financial product evaluation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a financial product evaluation system capable of efficiently evaluating complexity of a financial product with high precision. SOLUTION: In this financial product evaluation system 1, after a general financial product determined to have high similarity is selected on the basis of a correlation coefficient, arithmetic processing for incorporating the general financial product into a portfolio at a proper incorporation ratio is repeated until a static hedge position with a desired precision is realized. From at least the number, sort, or incorporation ratio of the general financial product included in the constructed portfolio, complexity of a specific financial product is evaluated. Therefore, the portfolio realizing the static hedge position to the specific financial product can be efficiently and precisely constructed, and consequently, complexity of the specific financial product can be evaluated efficiently with high precision.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a financial product evaluation system for evaluating the complexity of a financial product, a financial product evaluation method, and a recording medium on which a financial product evaluation program is recorded.

[0002]

2. Description of the Related Art In recent years, financial products having a complicated structure different from the conventional one, such as so-called exotic options, are being traded in the financial market. In many cases, financial instruments having a complicated mechanism have conditions or the like unique to the instrument, and the transaction value fluctuates irregularly due to various market factors. Therefore, when dealing with such financial products, greater care must be taken compared to other financial products.

[0003]

A financial institution that provides financial instruments having a complex structure different from the conventional one to general investors, etc., as described above, obtains information on how complicated the value fluctuation of the financial instruments is. It is necessary to present and alert general investors and the like, and to prevent general investors and the like from suffering unforeseen disadvantages. However, because there has been no efficient way to evaluate the complexity of financial products,
It is difficult to present information about the complexity of the financial product to be provided, and there is a possibility that unnecessary troubles may occur with general investors and the like. In the present application, a financial instrument to be evaluated is called a specific financial instrument, and other financial instruments used for evaluating the specific financial instrument are called general financial instruments.

The present invention has been made in view of the above-mentioned problems, and has been made in consideration of the above-described problems, and is provided with a financial product evaluation system, a financial product evaluation method, and a financial product capable of efficiently and accurately evaluating the complexity of a financial product. The present invention relates to a recording medium on which an evaluation program is recorded.

[0005]

SUMMARY OF THE INVENTION A financial instrument evaluation system according to the present invention is a system for evaluating the complexity of a specific financial instrument. It is characterized by comprising a configuration unit configured by general financial products and an evaluation unit that evaluates the complexity of a specific financial product based on information on general financial products configuring a portfolio.

[0006] Further, the financial product evaluation method according to the present invention comprises:
A method for evaluating the complexity of a specific financial instrument using a computer system, comprising: configuring a portfolio that realizes a static hedge position for the specific financial instrument in the computer system with a plurality of general financial instruments. And an evaluation step of evaluating the complexity of the specific financial instrument based on information on general financial instruments constituting the portfolio in the computer system.

[0007] Further, a recording medium on which the financial product evaluation program according to the present invention is recorded is a recording medium on which a computer system for evaluating the complexity of a specific financial instrument is recorded. Evaluate the complexity of specific financial instruments based on the composition process of composing a portfolio that realizes a static hedge position for specific financial instruments with multiple general financial instruments and information on the general financial instruments that make up the portfolio And evaluation processing to be performed.

[0008] As in these inventions, if a portfolio for realizing a static hedge position for a specific financial instrument is composed of a plurality of general financial instruments, information on general financial instruments included in this portfolio (particularly, information on general financial instruments). Quantity, type, inclusion ratio, etc.)
Evaluate the complexity of specific financial products. This is because the complexity of a particular financial instrument is high if it is not possible to construct a portfolio that realizes a static hedge position on the particular financial instrument without using a large number of general financial instruments or complex types of general financial instruments. However,
Conversely, if a portfolio that realizes a static hedge position for a particular financial instrument can be constructed using only a small number of general financial instruments or simple types of general financial instruments, the complexity of the specific financial instrument is low. It depends. In addition, when the general financial instruments included in the portfolio are of the same quantity and type, the inclusion ratio of each general financial instrument is almost equal (that is, if each general financial instrument is not included almost equally, the static hedge position will be If this is not possible, the complexity of the particular financial instrument is high, but conversely, there is a large bias in the inclusion ratio of each general financial instrument (ie, one or a small number of general financial instruments creates a static hedge position). If this is the case, the specific financial instrument is less complex. Therefore, according to these inventions,
It is possible to efficiently and accurately evaluate the complexity of a specific financial product.

It is preferable that the financial product evaluation system further includes an output unit that outputs an evaluation result obtained by the evaluation unit.

It is preferable that the financial product evaluation method further includes an output step of outputting the evaluation result in the evaluation step from within the computer system.

[0011] In the recording medium storing the financial product evaluation program, the computer system may include:
It is preferable to further execute an output process of outputting an evaluation result by the evaluation process.

By performing the output as in these inventions, it becomes possible to easily visually recognize the evaluation result of the complexity.

In this financial instrument evaluation system, the constituent means stores a payoff distribution of a specific financial instrument as an evaluation target payoff distribution, and stores a payoff distribution of each general financial instrument; A correlation coefficient calculating means for calculating a correlation coefficient with a payoff distribution of each general financial instrument; and a selecting means for selecting a constituent financial instrument to be included in a portfolio from a plurality of general financial instruments based on the correlation coefficient. , Based on the distribution of payoffs to be evaluated and the distribution of payoffs of constituent financial instruments,
An incorporation ratio calculating means for calculating an incorporation ratio of the constituent financial instrument, an incorporation means for composing a portfolio by incorporating the infrastructural instrument at the incorporation ratio, and an incorporation object incorporated by the incorporation means Difference distribution calculation for calculating the difference distribution obtained by subtracting the payoff distribution of the financial product and the evaluation payoff distribution based on the inclusion ratio of the target financial product calculated by the inclusion ratio calculation means from the evaluation target payoff distribution. Means, sensing that the difference distribution does not reach a predetermined condition, and selecting the difference distribution as a new evaluation target payoff distribution,
The work of calculating the inclusion ratio by the above-mentioned inclusion ratio calculation means, and
The re-execution of the incorporation into the portfolio by the incorporation means is performed again, and when the difference distribution reaches a predetermined condition, the selection operation by the selection means and the incorporation ratio calculation by the incorporation ratio calculation means are performed. And a determination means for ending the work of incorporating into the portfolio by the incorporating means.

[0014] In the financial instrument evaluation method, the configuration step may include storing, in the computer system, a payoff distribution of the specific financial instrument as a payoff distribution to be evaluated, and storing a payoff distribution of each general financial instrument. Step, a correlation coefficient calculating step of calculating a correlation coefficient between the evaluation target payoff distribution and the payoff distribution of each general financial instrument in the computer system; and Selecting a constituent financial instrument to be included in the portfolio from the general financial instruments of the above, and, within the computer system, the set of the constituent financial instruments based on the evaluation target payoff distribution and the payoff distribution of the constituent financial instruments. Inclusion ratio calculation step for calculating the insertion ratio In the computer system, an incorporation step of composing a portfolio by incorporating the constituent financial instruments at an incorporation ratio, and in the computer system, a payoff distribution of the constituent financial instruments incorporated in the incorporation step, A difference distribution calculating step of calculating a difference distribution obtained by subtracting the evaluation payoff distribution based on the inclusion ratio of the constituent financial instrument calculated in the inclusion ratio calculating step from the evaluation target payoff distribution; Within, it is sensed that the difference distribution does not reach a predetermined condition, and the difference distribution is set as a new evaluation target payoff distribution, and the selection step, the inclusion ratio calculating step,
And performing the insertion step again, and detecting that the difference distribution has reached a predetermined condition, and performing the selection step, the insertion ratio calculation step, and the determination step of terminating the insertion step. Preferably, it is provided.

In the recording medium on which the financial product evaluation program is recorded, in the configuration processing, the computer system stores a payoff distribution of a specific financial product as a payoff distribution to be evaluated and a payoff distribution of each general financial product. Based on the correlation coefficient, based on a correlation coefficient calculation processing for calculating a correlation coefficient between the payoff distribution of the evaluation target payoff and the payoff distribution of each general financial instrument,
Based on a selection process of selecting a constituent financial instrument to be included in a portfolio from a plurality of general financial instruments, and calculating an incorporation ratio of the constituent financial instrument based on an evaluation target payoff distribution and a payoff distribution of the constituent financial instrument. An incorporation ratio calculation process, an incorporation process for configuring a portfolio by incorporating the constituent financial products at an incorporation ratio,
The payoff distribution of the constituent financial instrument incorporated by the inclusion processing, and the evaluation payoff distribution based on the inclusion ratio of the constituent financial instrument calculated by the inclusion ratio calculation processing are calculated from the evaluation target payoff distribution. A difference distribution calculation process of calculating the reduced difference distribution, and sensing that the difference distribution has not reached a predetermined condition, and using the difference distribution as a new evaluation target payoff distribution, the selection process, the inclusion ratio calculation process, And performing the insertion processing again, and detecting that the difference distribution has reached a predetermined condition, and performing the selection processing, the insertion ratio calculation processing, and the determination processing for terminating the insertion processing. It is preferable to execute it.

These inventions provide a specific method of constructing a portfolio for realizing a static hedge position for a specific financial instrument. That is, according to these inventions, general financial instruments that are determined to have high similarity based on the correlation coefficient are selected, and the general financial instruments are included in the portfolio at an appropriate inclusion ratio. Further, such an incorporation process is repeated until a static hedge position with desired accuracy can be realized. Therefore, it is possible to efficiently and highly accurately construct a portfolio that realizes a static hedge position for a specific financial instrument, and thereby more efficiently and accurately evaluate the complexity of a specific financial instrument. become.

Further, in the financial instrument evaluation system for incorporating a general financial instrument by the above-mentioned insertion process, the constituent means may include a payoff distribution of the specific financial instrument and a plurality of general financial instruments, and the payoff distribution of the specific financial instrument and each of the general financial instruments. It is also preferable to further include a payoff distribution calculation unit that calculates by performing an independent trial calculation using a plurality of sets of market variables that affect a change in the value of the financial instrument.

Further, in the above-mentioned financial instrument evaluation method for incorporating general financial instruments by the insertion processing, the configuration step includes, within the computer system, determining a payoff distribution of the specific financial instrument and a plurality of general financial instruments. It is preferable that the method further includes a payoff distribution calculating step of calculating by performing an independent trial calculation using a plurality of sets of market variables that affect a change in the value of the financial instrument and each of the general financial instruments.

Further, in the recording medium storing a financial product evaluation program for incorporating general financial products by the above-mentioned insertion process, the above-mentioned configuration process includes the step of providing the computer system with a payoff distribution of a specific financial product and a plurality of general financial products. It is also preferable to further execute a payoff distribution calculation process of calculating a value by performing an independent trial calculation using a plurality of sets of market variables that affect the value change of the specific financial instrument and each of the general financial instruments.

Particularly for complex financial products, it is often difficult to obtain an analytical solution for obtaining a payoff distribution indicating the degree of value change due to market factors or the like. Therefore, if the payoff distribution of a specific financial instrument and a general financial instrument is calculated by performing an independent trial calculation (so-called Monte Carlo simulation) using a plurality of sets of market variables that affect the value change of the specific financial instrument and a general financial instrument, In addition, it becomes possible to obtain a payoff distribution of a complicated financial product for which it is difficult to obtain an analytical solution, and thus it is possible to evaluate the complexity of various specific financial products.

Further, in the financial instrument evaluation system for incorporating general financial instruments by the inserting means, the correlation coefficient calculating means uses a payoff distribution θ _{CV to be} evaluated and a payoff distribution θ _E of each general financial instrument, It is also preferable to calculate the correlation coefficient γ by the above equation (1).

[0022] In the financial instrument evaluation method for incorporating general financial instruments in the inserting step, in the correlation coefficient calculating step, the evaluation target payoff distribution θ _CV and the payoff distribution θ _E of each general financial instrument are used. It is also preferable to calculate the correlation coefficient γ by the above equation (2).

In addition, the above-described integration process allows the general financial
Record of the financial instrument valuation program to be included
In the medium, in the correlation coefficient calculation process, the
Payoff distribution θ in the computer system_CVAnd each one
Payoff distribution θ of general financial products _EAnd the correlation coefficient γ is

(Equation 3) It is also preferable to calculate by:

By calculating the correlation coefficient using such a mathematical expression, the correlation between the payoff distribution of the evaluation object and the payoff distribution of general financial instruments can be derived with high accuracy.
This makes it possible to more efficiently and accurately configure a portfolio that realizes a static hedge position, and thus to more efficiently and accurately evaluate the complexity of a specific financial instrument.

[0025] In the financial instrument evaluation system for incorporating general financial instruments by the inserting means, it is preferable that the selecting means selects a target financial instrument based on an absolute value of a correlation coefficient.

[0026] In the financial instrument evaluation method for incorporating a general financial instrument in the inserting step, it is preferable that in the selecting step, the target financial instrument is selected based on an absolute value of a correlation coefficient.

[0027] In addition, in the recording medium storing a financial product evaluation program for incorporating general financial products by the above-described insertion process, the selection process includes the step of: It is also preferable to make the user select a financial product.

If the absolute value of the correlation coefficient is high, the reverse operation is performed for selling and buying even if the sign is different (for example, if the specific financial product is “buy”, the general financial product is set to “sell”). It is possible to take a hedging position. Therefore, if the financial instruments to be structured are selected based on the absolute value of the correlation coefficient, the range of choice is expanded, and it is possible to more efficiently construct a portfolio that realizes a static hedge position, and as a result, specific financial instruments It becomes possible to evaluate the complexity of the product more efficiently.

[0029]

BRIEF DESCRIPTION OF THE DRAWINGS FIG.
Preferred embodiments of a financial product evaluation system, a financial product evaluation method, and a recording medium on which a financial product evaluation program is recorded according to the present invention will be described in detail. In the description of the drawings, the same or corresponding elements will be denoted by the same reference characters, without redundant description.

First, the configuration of the financial instrument evaluation system according to the present embodiment will be described with reference to FIG. The financial product evaluation system 1 includes an input unit 11, a payoff distribution calculation unit 13, a financial product data storage unit 15, an operation unit 2, an evaluation unit 29, an evaluation data storage unit 31, and an output unit 33. Prepare. The calculation unit 2 includes a correlation coefficient calculation unit 17, a selection unit 19, an insertion ratio calculation unit 21, an insertion unit 23, a difference distribution calculation unit 25, and a determination unit 27.

The input unit 11 is connected to the payoff distribution calculation unit 13 via a signal line, receives input of financial product data or the like characterizing specific financial products and general financial products, and transmits the data to the payoff distribution calculation unit 13. It has become possible. As the input unit 11, for example, a keyboard is used.

The payoff distribution calculation unit 13 is connected to the financial product data storage unit 15 via a signal line, and based on the financial product data and the like transmitted from the input unit 11, uses the Monte Carlo simulation to specify specific financial products and each of them. It is possible to calculate the payoff distribution of general financial products, and transmit an information signal including the calculation result to the financial product data storage unit 15. For general financial products for which an analytical solution for obtaining the payoff distribution is known, the input unit 1
It is possible to calculate a payoff distribution by using an analytical solution based on the financial product data transmitted from No. 1 and the like.
The financial product data storage unit 15 can store the payoff distribution of the specific financial product and each general financial product transmitted from the payoff distribution calculation unit 13.

The correlation coefficient calculating unit 17 is connected to the financial product data storage unit 15 via a signal line, and the payoff distribution (evaluation target payoff distribution) of the specific financial product stored in the financial product data storage unit 15. In addition, the payoff distribution of each general financial product can be read. The selection unit 19 is also connected via a signal line, calculates a correlation coefficient between the payoff distribution of the evaluation target and the payoff distribution of each general financial instrument, and outputs an information signal including the correlation coefficient to the selection unit 1.
9 can be transmitted. Further, the determination unit 27 is also connected via a signal line, and the difference distribution transmitted from the determination unit 27 is set as a new evaluation target payoff distribution, and the difference between the evaluation target payoff distribution and the payoff distribution of each general financial instrument is determined. It is also possible to calculate the number of relations.

The selecting unit 19 is configured to include a plurality of general financial products in the portfolio based on the correlation coefficient between the evaluation target payoff distribution transmitted from the correlation coefficient calculating unit 17 and the payoff distribution of each general financial product. It is possible to select target financial products. In addition, it is connected to the incorporation ratio calculation unit 21 and the incorporation unit 23 via signal lines, respectively, and can transmit an information signal including the evaluation target payoff distribution and the payoff distribution of the selected configuration target financial instrument. ing.

Based on the evaluation target payoff distribution transmitted from the selection unit 19 and the payoff distribution of the selected constituent financial instrument, the inclusion ratio calculation unit 21 calculates the inclusion ratio of the constituent financial instrument. Has become possible. Further, it is connected to the insertion unit 23 via a signal line, and can transmit an information signal including the calculated insertion ratio of the configuration target financial instrument to the insertion unit 23.

The incorporation unit 23 includes an evaluation target payoff distribution transmitted from the selection unit 19, a payoff distribution of the selected configuration target financial instrument, and a configuration target financial product transmitted from the inclusion ratio calculation unit 21. Based on the ratio, it is possible to construct a portfolio by incorporating constituent financial products. Further, it is connected to the difference distribution calculation unit 25 via a signal line, and transmits an information signal including the evaluation target payoff distribution and the payoff distribution of the configuration target financial instrument included in the configured portfolio to the difference distribution calculation unit 25. Has become possible.

The difference distribution calculating unit 25 receives the evaluation target payoff distribution and the payoff distribution and the inclusion ratio of the constituent financial instrument transmitted from the incorporating unit 23, and based on the payoff distribution and the inclusion ratio of the constituent financial instrument. It is possible to calculate a difference distribution by calculating an evaluation payoff distribution and subtracting this from the evaluation target payoff distribution. Further, it is connected to the determination unit 27 via a signal line, and can transmit to the determination unit 27 an information signal including the constituent financial instruments included in the portfolio and the calculated difference distribution.

The judging section 27 judges whether or not the difference distribution transmitted from the difference distribution calculating section 25 has reached a predetermined condition (for example, whether or not the variance of the difference distribution has become a predetermined value or less). It has become possible. At this time, when it is determined that the difference distribution has not reached the predetermined condition, the difference distribution can be transmitted to the correlation coefficient calculation unit 17. Also, it is connected to the evaluation unit 29 via a signal line, and when it is determined that the difference distribution has reached a predetermined condition, an information signal including the target financial instrument included in the portfolio is transmitted to the evaluation unit 29. It is possible to do.

The evaluation data storage unit 31 stores, as evaluation data, at least table data indicating the relationship between the complexity index and the quantity, type or inclusion ratio of the target financial product. The evaluation unit 29 includes an evaluation data storage unit 31
And an evaluation data storage unit 3
1 can be read. In addition, it is possible to detect at least the quantity, type, or inclusion ratio of the constituent financial instrument included in the portfolio transmitted from the determination unit 27, and to derive the complexity index with reference to the read evaluation data. ing. Furthermore, it is connected to the output unit 33 via a signal line, and can transmit an information signal including the derived complexity index to the output unit 33.

The output unit 33 receives the information signal containing the complexity index transmitted from the evaluation unit 29, and displays or prints at least the quantity or type of the target financial instrument and the complexity index in the form of a table or the like by image display or printing. It is possible to output. As the output unit 33, for example, a display or a printer is used.

On the other hand, the recording medium storing the financial product evaluation program according to the present embodiment includes a general-purpose computer system including input means such as a keyboard and output means such as a display and a printer, as well as the above-mentioned financial product evaluation system 1. A program for providing a function equivalent to that of each element is recorded. Therefore, a system equivalent to the above-mentioned financial product evaluation system 1 is formed by reading this financial product evaluation program into a computer system. More specifically, for example, a CPU included in a computer system performs the functions of the calculation unit, the selection unit 19, the insertion unit 23, the determination unit 27, the evaluation unit 29, and the like in the financial product evaluation system 1, and includes, for example, a hard disk memory. Perform the function of each storage unit and the like. Further, input means such as a keyboard performs the function of the input unit 11 and the like in the financial product evaluation system 1, and output means such as a display and a printer performs the function of the output unit 33 and the like.

Next, the operation (financial product evaluation method) of the financial product evaluation system 1 according to the present embodiment will be described with reference to the flowchart shown in FIG. In the present embodiment, the specific financial instrument to be evaluated is an Asian option A, and the European option E _{1 is used} as a plurality of general financial instruments that are candidates for constituting a portfolio for realizing a static hedge position for the Asian option A. It will be described an example of using a to E _N.

First, financial product data of a specific financial product and each general financial product is input using the input unit 11 (Step 1, hereinafter abbreviated as S1). The financial product data is data characterizing each financial product, and corresponds to an expiration date, an exercise price, and the like for options. Also,
The input unit 11 is used to input market variable conditions that affect the value change of the specific financial instrument and each general financial instrument.
Market variables are variables used in calculating the payoff distribution, and include interest rates, stock prices, exchange rates, and the like.
The market variable condition indicates a condition that determines a possible range of these market variables.

After the financial product data and market variable conditions are input, the payoff distribution calculator 13 performs a Monte Carlo simulation based on the financial product data and market variable conditions, and calculates the payoff distribution of the specific financial product and each general financial product. It is calculated (S2). That is, in the Monte Carlo simulation, a random market variable is generated based on the market variable condition for each trial, and the value of the specific financial instrument and each general financial instrument corresponding to the market variable is calculated based on the financial instrument data. By performing such independent trials a predetermined number of times (for example, 100,000 times), a value change distribution of the specific financial instrument and each general financial instrument is formed, and this is calculated as a payoff distribution.
The payoff distribution of the specific financial product and each general financial product calculated in this way is stored in the financial product data storage unit 15 (S3).

Next, the arithmetic processing is performed in the arithmetic section 2. In this calculation process, the calculation process of the correlation coefficient (S
4), processing for selecting a configuration target financial instrument (S5), processing for calculating an inclusion ratio (S6), processing for inclusion in a portfolio (S5)
7) and the process of calculating the difference distribution (S8) are repeatedly performed, and the constituent financial instruments are sequentially included in the portfolio. Hereinafter, these calculation processes will be described in detail (note that, unless otherwise specified, the case where the n-th calculation process is performed after the (n-1) calculation processes have already been performed will be described).

First, the correlation coefficient calculation unit 17 reads out a distribution function to be evaluated (evaluation target payoff distribution θ _CV ) and a payoff distribution θ _E of each general financial instrument. In addition,
The evaluation initial value of the target payoff distributed as (a value in the first calculation process) is payoff distribution theta _A particular financial instruments stored in financial product data storage 15 is substituted.
That is,

(Equation 4) (The numbers on the left and right shoulders indicate the number of repetitions of the arithmetic processing, and are used similarly in the following equations). In addition, in the n-th (second or later) calculation processing, the previous (that is, n−
The difference distribution calculated by the difference distribution calculation unit 25 during the (first) calculation processing is substituted as the evaluation target payoff distribution.

The correlation coefficient calculating section 17 calculates the read-out payoff distribution θ _CV for evaluation and the general financial product E
Correlation coefficient gamma _j the payoff distribution theta _{E, j} of _j is

(Equation 5) (S4). More specifically,
Equation (5) is

(Equation 6) Can be expressed as

The selection unit 19 refers to the correlation coefficient between the evaluation target payoff distribution calculated by the correlation coefficient calculation unit 17 and the payoff distribution of each general financial instrument, so that the absolute value of the correlation coefficient is the highest. One general financial product is selected, and its payoff distribution is set as the payoff distribution of the configuration target financial product in the n-th calculation process (S5). That is,

(Equation 7) It will be.

In the inclusion ratio calculation unit 21, the inclusion ratio α _n of the target financial instrument selected by the selection unit 19 is represented by

(Equation 8) (S6). If the correlation coefficient between the evaluation target payoff distribution and the payoff distribution of the constituent financial instrument is a negative value, the specific financial instrument and the constituent financial instrument perform reverse operations for buying and selling (for example, If the financial instrument is “buy”, the general financial instrument is referred to as “sell”), which means that the hedging position can be taken. Therefore, the inclusion ratio α _n calculated here is also a negative value.

The incorporation unit 23 incorporates the configuration target financial instrument selected by the selection unit 19 at the incorporation ratio calculated by the incorporation ratio calculation unit 21 until the previous (n−1) th operation processing. A portfolio is formed together with the constituent financial instruments already included (S7).

The difference distribution calculation unit 25 subtracts the average value from the payoff distribution of the selected constituent financial product and multiplies it by the inclusion ratio (referred to as the payoff distribution for evaluation in the present application), and calculates the result from the payoff distribution for evaluation. As a result, the difference distribution to be the payoff distribution to be evaluated in the next (n + 1) th calculation processing is calculated (S8).
If this calculation process is specifically described,

(Equation 9) Can be expressed as

The determination section 27 determines whether or not the difference distribution calculated by the difference distribution calculation section 25 has reached a predetermined condition (S9). This judgment processing is to judge whether or not the portfolio constituted by the calculation processing up to this time realizes a static hedge position with desired accuracy. Specifically, the variance of the difference distribution is equal to or less than a predetermined value. Is determined. If the determination unit 27 determines that the difference distribution does not reach the predetermined condition (in the above example, the variance of the difference distribution is not less than or equal to the predetermined value), the calculation up to this time is performed. Assuming that the portfolio constituted by the processing has not realized the static hedge position with the desired accuracy, the arithmetic processing of S4 to S8 is performed again. At this time, the correlation coefficient calculation unit 17 reads out the difference distribution calculated in the current calculation processing as the next evaluation target payoff distribution.

On the other hand, if the determination unit 27 determines that the difference distribution has reached the predetermined condition (in the above example, the variance of the difference distribution has become equal to or less than the predetermined value), Assuming that the portfolio constituted by the above calculation process can realize a static hedge position with a desired accuracy, information including general financial instruments constituting the portfolio and their inclusion ratios is evaluated as, for example, table data as shown in FIG. The result is transmitted to the unit 29, and the arithmetic processing ends.

After the completion of the arithmetic processing, the evaluation unit 29
The complexity of the specific financial product is evaluated in (S1
0). That is, the evaluation unit 29 detects at least the quantity, type, or inclusion ratio of the configuration target financial instrument included in the portfolio transmitted from the determination unit 27, and reads out the evaluation data stored in the evaluation data storage unit 31, The complexity index is derived by referring to the evaluation data and at least the quantity, type, or inclusion ratio of the detected constituent financial instrument. For example, when the evaluation unit 29 detects that the number of constituent financial products is m, the type is European option, and each of the inclusion ratios is x%, the corresponding complexity index “AA” is evaluated. It will be derived from the data. Then, the output unit 33 that has received the evaluation result outputs result information including the number of configuration target financial products constituting the portfolio and the complexity index, for example, as shown in FIG. 4 (S11). ).

As described above, according to the present embodiment, a general financial instrument whose similarity is determined to be high based on the correlation coefficient is selected, and the general financial instrument is included in the portfolio at an appropriate inclusion ratio. The calculation process is repeated until a static hedge position with desired accuracy can be realized. Then, the complexity of the specific financial instrument is evaluated from at least the quantity, type, or inclusion ratio of the general financial instrument included in the configured portfolio. Therefore, a portfolio that realizes a static hedge position for a specific financial instrument can be configured efficiently and with high accuracy, and the complexity of the specific financial instrument can be evaluated efficiently and with high accuracy.

Further, according to the present embodiment, the complexity of a specific financial instrument can be evaluated efficiently and with high accuracy, so that it can be applied to the calculation of hedging costs and the rating of financial instruments. . For example, when it is determined that the complexity of a specific financial instrument is high, it can be used as a basis for calculating a relatively high hedging cost or highly appraising the rating of the financial instrument.

It should be noted that the financial product evaluation system, the financial product evaluation method, and the recording medium on which the financial product evaluation program according to the present invention is recorded are not limited to those described in the above-described embodiment. Various modifications can be made according to the above. For example, in the above embodiment, an example was given in which the specific financial product was an Asian option and the general financial product was a European option.
Other financial instruments can be used.

Also, in the above embodiment, an example of calculating the payoff distribution of a specific financial instrument and a general financial instrument using Monte Carlo simulation has been mainly described. However, the payoff distribution of a general financial instrument for which an analytical solution is known is described. The calculation unit 13 can also calculate the payoff distribution using the analytical solution. For general financial products for which an analytical solution is not known, the payoff distribution is calculated using the Monte Carlo simulation as described in the above embodiment.

Further, in the above-described embodiment, an example has been described in which the constituent financial instruments are incorporated one by one each time the arithmetic processing is repeated, but a plurality of constituent financial instruments may be incorporated simultaneously. For example, when m constituent financial instruments are to be included at the same time, the inclusion ratio α _k of each constituent financial instrument minimizes the variance of the evaluation target payoff distribution θ _CV (see the following equation (10)). It can be calculated as a solution of an m-ary simultaneous linear equation.

(Equation 10)

In the above embodiment, the criterion is that the variance of the difference distribution is equal to or less than a predetermined value.
It is not limited to this. Further, an input means for inputting the judgment condition may be provided so that the judgment condition can be changed each time the portfolio is constructed.

Further, in the above-described embodiment, a static hedge position is realized for a specific financial instrument by sequentially incorporating general financial instruments based on a correlation coefficient between an evaluation target payoff distribution and a payoff distribution of each general financial instrument. We have explained the example of constructing a portfolio,
Other known techniques for constructing a portfolio can also be used. Examples of other known techniques are simply delta values,
The risk neutralization method that composes a portfolio so that risk indicators such as vega values are neutral, and the “Static Hedging of Ex
otic Options (Journal of Finance, vol.LIII, no.8,
June 1998) ").

[0062]

According to the financial product evaluation system, the financial product evaluation method, and the recording medium on which the financial product evaluation program is recorded according to the present invention, it is possible to efficiently and accurately evaluate the complexity of a financial product. Will be possible.

If the evaluation result is output, the evaluation result of the complexity can be easily visually recognized.

Further, by using a method of sequentially incorporating the constituent financial instruments and financial instruments based on the correlation coefficient to construct a portfolio, a portfolio for realizing a static hedge position with respect to a specific financial instrument can be more efficiently and accurately calculated. This makes it possible to efficiently and accurately evaluate the complexity of a specific financial instrument.

Further, by calculating the payoff distribution of a specific financial instrument and a general financial instrument by performing an independent trial calculation using a plurality of sets of market variables affecting the value change of the specific financial instrument and a general financial instrument, It becomes possible to obtain a payoff distribution of a complex financial product for which it is difficult to obtain a solution, and thus it is possible to evaluate the complexity of a wide variety of specific financial products.

Further, if the correlation coefficient is calculated using the above-described formula, the correlation between the payoff distribution of the evaluation object and the payoff distribution of general financial instruments can be derived with high accuracy, and thus a static hedge position is realized. The portfolio can be configured more efficiently and with higher accuracy, and the complexity of a specific financial instrument can be evaluated more efficiently and with higher accuracy.

In addition, by selecting the constituent financial instruments based on the absolute value of the correlation coefficient, the range of selection is expanded, so that a portfolio realizing a static hedge position can be configured more efficiently. As a result, the complexity of a specific financial product can be more efficiently evaluated.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a financial product evaluation system according to an embodiment.

FIG. 2 is a flowchart illustrating an operation (a financial product evaluation method) of the financial product evaluation system according to the embodiment.

FIG. 3 is a chart showing an example of data transmitted to an evaluation unit in the financial product evaluation system according to the embodiment.

FIG. 4 is a chart showing an output example of the financial product evaluation system according to the embodiment.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Financial product evaluation system, 2 ... Operation part, 11 ... Input part, 13 ... Payoff distribution calculation part, 15 ... Financial product data storage part, 17 ... Correlation coefficient calculation part, 19 ... Selection part, 21 ...
Incorporation ratio calculation unit, 23 ... insertion unit, 25 ... difference distribution calculation unit, 27 ... determination unit, 29 ... evaluation unit, 31 ... evaluation data storage unit, 33 ... output unit

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Inventor Shunji Takubo 1-5-1 Otemachi, Chiyoda-ku, Tokyo F-term in IBJ Daiichi Financial Technology Co., Ltd. 5B055 CC00

Claims (13)

[Claims] 1. A system for evaluating the complexity of a specific financial instrument, comprising: a configuration means for configuring a portfolio for realizing a static hedge position for the specific financial instrument by a plurality of general financial instruments; A financial instrument evaluation system comprising: an evaluation unit that evaluates the complexity of the specific financial instrument based on information about the general financial instrument to be configured. 2. The financial product evaluation system according to claim 1, further comprising output means for outputting an evaluation result by said evaluation means. 3. The storing means for storing a payoff distribution of the specific financial instrument as a payoff distribution to be evaluated, and storing a payoff distribution of each general financial instrument; A correlation coefficient calculating means for calculating a correlation coefficient with a payoff distribution of general financial products; and selecting a constituent financial instrument to be included in the portfolio from the plurality of general financial instruments based on the correlation coefficient. Means, based on the evaluation target payoff distribution and the payoff distribution of the constituent financial instrument, an inclusion ratio calculating means for calculating an inclusion ratio of the constituent financial instrument, and the inclusion ratio of the constituent financial instrument. An incorporation means for composing the portfolio by incorporating the portfolio financial instruments; A payoff distribution, and a difference distribution calculation unit that calculates a difference distribution obtained by subtracting the evaluation payoff distribution based on the inclusion ratio of the constituent financial instrument calculated by the inclusion ratio calculation unit from the evaluation target payoff distribution. Detecting that the difference distribution does not reach a predetermined condition, and selecting the difference distribution as a new evaluation target payoff distribution, selecting by the selecting means, calculating the insertion ratio by the insertion ratio calculating means, and Re-executing the work of incorporating the portfolio into the portfolio by the incorporating means, detecting that the difference distribution has reached the predetermined condition, and selecting the work by the selecting means; An input ratio calculation operation, and a judgment unit for terminating the insertion operation into the portfolio by the insertion unit. Item 3. The financial product evaluation system according to item 1 or 2. 4. The method according to claim 1, wherein the configuration unit uses a payoff distribution of the specific financial instrument and the plurality of general financial instruments using a plurality of sets of market variables that affect a change in value of the specific financial instrument and each of the general financial instruments. The financial product evaluation system according to claim 3, further comprising a payoff distribution calculation unit that calculates by performing an independent trial calculation. 5. The correlation coefficient calculating means calculates the correlation coefficient γ by using the evaluation target payoff distribution θ _CV and the payoff distribution θ _E of each general financial instrument. The financial product evaluation system according to claim 3, wherein the value is calculated by: 6. The financial product evaluation system according to claim 3, wherein the selection unit selects the configuration target financial instrument based on an absolute value of the correlation coefficient. 7. A method for evaluating the complexity of a specific financial instrument using a computer system, the method comprising: providing, in the computer system, a portfolio realizing a static hedge position for the specific financial instrument to a plurality of general financial instruments. A financial product evaluation comprising: a configuration step configured by a product; and an evaluation step of evaluating, in the computer system, the complexity of the specific financial product based on information on general financial products configuring the portfolio. Method. 8. The financial product evaluation method according to claim 7, further comprising an output step of outputting an evaluation result in the evaluation step from within the computer system. 9. The computer system, comprising: storing a payoff distribution of the specific financial instrument as an evaluation target payoff distribution in the computer system; and storing a payoff distribution of each general financial instrument in the computer system; In the system, a correlation coefficient calculating step of calculating a correlation coefficient between the evaluation target payoff distribution and the payoff distribution of each of the general financial instruments, and in the computer system, A step of selecting a constituent financial instrument to be included in the portfolio from general financial instruments; and, in the computer system, the constituent financial instrument based on the evaluation target payoff distribution and the payoff distribution of the constituent financial instrument. Inclusion ratio calculation step for calculating the In the computer system, an incorporation step of composing the portfolio by incorporating the configuration-targeted financial instrument at the incorporation ratio; and, in the computer system, the configuration object incorporated in the incorporation step A payoff distribution of the financial product, and a difference distribution for calculating a difference distribution obtained by subtracting the evaluation payoff distribution based on the inclusion ratio of the configuration target financial product calculated in the inclusion ratio calculation step from the evaluation target payoff distribution. Calculating step, in the computer system, sensing that the difference distribution does not reach a predetermined condition, the difference step as a new evaluation target payoff distribution, the selection step, the inclusion ratio calculation step, and , And causing the incorporating step to be performed again, 8. The method according to claim 7, further comprising: a step of detecting that the difference distribution has reached the predetermined condition, the step of selecting, the step of calculating the insertion ratio, and the step of ending the insertion step.
Or the financial instrument evaluation method according to 8. 10. The configuration step includes, in the computer system, changing a payoff distribution of the specific financial instrument and the plurality of general financial instruments to a value that affects a value change of the specific financial instrument and each of the general financial instruments. 10. The financial product evaluation method according to claim 9, further comprising a payoff distribution calculation step of calculating by performing an independent trial calculation using a set of market variables. 11. In the correlation coefficient calculating step, the correlation coefficient γ is calculated by using the evaluation target payoff distribution θ _CV and the payoff distribution θ _E of each general financial instrument. The financial product evaluation method according to claim 9, wherein the calculation is performed by: 12. The financial product evaluation method according to claim 9, wherein in the selecting step, the configuration target financial product is selected based on an absolute value of the correlation coefficient. 13. A recording medium storing a computer-readable program for evaluating the complexity of a specific financial instrument, wherein the computer system implements a static hedge position for the specific financial instrument. A financial system comprising: executing a configuration process of configuring a portfolio by a plurality of general financial products; and performing an evaluation process of evaluating the complexity of the specific financial product based on information on general financial products configuring the portfolio. A recording medium on which a product evaluation program is recorded.