JP2003085376A - Automatic portfolio design system and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an automatic portfolio design system capable of quickly and positively forming an optimum portfolio of assets. SOLUTION: In the automatic portfolio design system 1, a transitional situation over time of the sum total of object assets when it is considered that a present portfolio will be maintained in the future is forecasted on the basis of object assets particular information, expected earning rate information (earning rate information pre asset class) of each asset class composing the assets and expenditure contents particular information, and a recommendation portfolio of the object assets is determined so as to improve the transitional situation over time in response to a forecast result. Accordingly, the optimum portfolio of the assets can be quickly and positively formed without much expert knowledge at an individual level or the like.

Description

Detailed Description of the Invention

[0001]

TECHNICAL FIELD The present invention relates to a portfolio automatic design system and a recording medium.

[0002]

2. Description of the Related Art In Japan, the so-called bubble economy collapsed in the 1990s, and the real estate price fell sharply, leading to the collapse of stock prices and asset stock prices and entering a long-term recession. Moreover, due to the bad debt problem, which can be said to be the so-called "bad" of the bubble economy in the 1980s, not only the financial conditions of banks and other financial institutions have deteriorated and low interest rates have continued, but some financial institutions A crisis situation has begun to occur, such as business failure. As a measure to break the current situation, the Japanese government
By the end of the year, it has announced that it will proceed with financial liberalization, which has been subject to many restrictions, and will embark on financial reform under the name of the "Big Bang in Japan."

Under these circumstances, not only various financial institutions and investors, but also the general public, are required to fundamentally change their consciousness about asset management in order to open their perspectives for the future. For example, looking at an individual's life, various events (i.e., funding events) that require funding are waiting, such as marriage, housing, child education, and retirement. And if the funds and assets in hand are limited, it may be difficult or impossible to handle all kinds of financial events. This means that the life of the individual will collapse.

As a method of avoiding the failure as described above, it is conceivable to cut down the living expenses or reduce the target amount of the fund event, but this has no direct relation to the fund event to be done. It's not a positive way to do it, as it involves the hardships and sacrifices of life, or at least partly abandon the desired financial event goals. Therefore, another possible method is to manage the assets at an investment return rate that can be achieved by all financial events. However, in this era of low interest rates, ordinary deposits and savings such as ordinary deposits and time deposits can only expect interest rates below 1%, and it is unlikely that a significant profit effect can be expected. Therefore, it is effective to look at various highly profitable products such as stocks or investment trusts and incorporate them into assets.

Further, with the above-mentioned financial liberalization, entry into the fields of banking, securities and insurance will be promoted. For example, high profits such as investment trusts at bank counters, which are not permitted under the conventional financial system, will be provided. It has already been decided that the sale of sex products will start in 1997. With the increasing interest of these individuals in these highly profitable products, the financial industry will enter a period of fierce competition over the next few years, expanding sales and improving services in each industry. It is expected that each move to will develop for the survival.

[0006]

[Problems to be Solved by the Invention] The above-mentioned high-profitability products have high profitability as seen in typical examples of stocks. In extreme cases, the risk of failure such as bankruptcy is extremely high. Therefore, in order to incorporate these products into assets and operate them properly, the so-called risk diversification concept is important. In short, if you increase the ratio of highly safe products (asset or asset class) that do not have a risk of loss of principal in assets, risk will decrease, but total profitability will decrease and The probability of achieving a financial event is reduced. On the contrary, if the ratio of highly profitable products is increased, the total profitability is increased and the probability of achieving all financial events is increased, but the risk of failure is also increased. Therefore, when a plurality of asset classes with different risk-returns are combined in a certain allocation (portfolio), there should be an allocation point (so-called best mix) that can minimize risk while achieving all financial events.

However, the calculation of this best mix is generally troublesome, and even a person having specialized knowledge requires a long time, and it may not be possible to deal with it at an individual level with little knowledge. Even if the best mix of assets could be calculated accurately, the next issue is how to allocate them to individual financial events rationally. Therefore, extremely sophisticated knowledge and judgment are required to solve such problems related to fund management, but it is impossible at present to take an accurate and prompt approach at the individual level with little experience. Close to.

Moreover, such a problem is not limited to the purchaser side. For example, when demand for high-profitability products increases and sales competition intensifies, it becomes difficult for new banks to avoid the worries of selection unless they strive to improve services to acquire customers. To that end, it is also an important strategy to provide specific information as part of the service, such as giving appropriate advice when purchasing a product, considering the asset status of the purchaser.
However, since the absolute experience is insufficient at present, it can be said that it is desperate to acquire the information provision know-how that can withstand the competition within a short period of time.

An object of the present invention is to provide a portfolio automatic design system that can quickly and surely form an optimal portfolio of assets without having much specialized knowledge at the individual level and the like. It is to provide a recording medium storing a program for realizing a function on a computer.

[0010]

[Means and Actions / Effects for Solving the Problems] In order to solve the above-mentioned problems, the portfolio automatic design system of the present invention uses a current total amount and a current portfolio (hereinafter, , The current portfolio) to directly or indirectly identify the target asset identification information for inputting the target asset identification information, and the expenditure content identification information that directly or indirectly identifies the expected expenditure content in the future. Expense content specific information input means for inputting, asset class profit rate information storage means for storing asset class profit rate information for directly or indirectly specifying future expected return rates for each asset class, and present Forecast information on the time-dependent transition of the total amount of the target assets when the portfolio is considered to be maintained in the future (below That asset transition basic prediction information)
Is generated based on the target asset identification information, the expenditure content identification information, and the asset class return rate information, and the asset transition basic forecast information generation means, the generated asset transition basic forecast information, and the asset class return rate Based on the information, a recommended portfolio deciding means for deciding a recommended portfolio of the target asset for improving the above-mentioned temporal transition situation, and a recommended portfolio outputting means for outputting the decision contents of the recommended portfolio are provided. Characterize.

The asset class is an asset type,
Basically, it can be freely set, but for example, safety financial assets (or products such as principal deposits, time deposits, savings deposits, fixed amount savings, discounted financial bonds, interest-bearing financial bonds, medium-term financial assets, whose principal is substantially guaranteed. JGB funds, MMFs (money management funds), public and corporate bond investment trusts, loan trusts, gold savings accounts, mortgage securities, etc.) Profitability financing with a higher expected return rate than safety financial assets, although there is a possibility of principal loss Assets (or products: Stocks, investment trusts, convertible bonds, bonds with warrants, foreign currency deposits, actual dividend-type money trusts, etc.)
And at least two types can be included.
Further, if necessary, among the safety financial assets, those with particularly high liquidity (for example, ordinary deposits, MMFs, medium-term government bond funds, etc.) can be set as liquidity financial assets by separating asset classes. The asset class is not limited to financial assets, and may be fixed assets such as land and buildings, minerals, metal ingots, agricultural products, or industrial products. On the other hand, a portfolio is a type allocation of target assets, that is, a ratio of each asset class to the target assets.

According to the above-described portfolio automatic design system, the target asset specifying information, the expected return rate information (return rate information for each asset class) of each asset class (asset type) constituting the asset, and the expenditure content specifying information are provided. Based on the above, the total amount of the target assets when the current portfolio is considered to have been maintained in the future is predicted, and the target assets are recommended to receive the prediction results and improve the temporal changes. I decided to decide the portfolio. Therefore, it is possible to quickly and surely determine the optimal portfolio of assets even if the user does not have much expertise at the individual level. In addition, in the present invention, when a recommended portfolio for asset management after retirement is sought, for example, what should be a certain point in the future for the user may be virtually treated as “current”. There is.

In addition to the above-mentioned expenditure content specifying information, income content specifying information for specifying income contents other than asset management income,
Alternatively, it is possible to separately input the debt content specifying information for specifying the debt content and generate the asset transition basic prediction information in consideration of the information. As a result, more accurate asset transition basic prediction information can be obtained, which in turn can improve the accuracy of determining the recommended portfolio.

Next, the asset class return rate information may include information on the past performance value of the return rate for each asset class (return rate past performance information). Based on the past actual value of the return rate of each asset class, the expected value of the return rate of the asset in the future (expected return rate) can be predicted with a certain accuracy, and by extension, the effectiveness of the recommended portfolio determined using it It is possible to improve the sex.

Next, the recommended portfolio determining means sets the future expected value of the portfolio return rate (current portfolio expected return rate) when the current portfolio is adopted, with the investment return rate of the entire target assets as the portfolio return rate. Current portfolio expected return rate calculation means for calculating based on the asset identification information and asset class return rate information, and portfolio return rate target value setting means for setting a predetermined portfolio return rate target value that is larger than the current portfolio expected return rate And an optimum portfolio calculation means for calculating the optimum portfolio and achieving the set portfolio profit rate target value as a recommended portfolio.

In the above configuration, the investment return rate (portfolio return rate) of the entire target assets when the current portfolio (current portfolio) is adopted is calculated as the current portfolio return rate, and the portfolio return rate target value is set as the current portfolio return rate. It was set to be larger than the rate of return, and the portfolio was optimized so that the portfolio rate of return target value could be achieved, and this was made the recommended portfolio. This makes it possible to almost certainly improve the transition of the total amount of the target assets when the recommended portfolio is used as compared to when the current portfolio is used. In this case, the portfolio return rate target value is
Certain time in the future (hereinafter referred to as asset shortage time)
In the case where the total amount of assets turns negative, it is possible to set the time when the total assets turn negative to be extended by a predetermined period or more before the specific time (the asset short time). This allows a more rational determination of the recommended portfolio.

Next, the asset class return rate information is information (asset class expected return rate) that reflects the average return rate (asset class expected return rate) of each asset class calculated based on the return rate past performance information. Return information) and information that also reflects diversification (asset class diversification information)
And information that also reflects covariance between asset classes (asset class covariance information). In this case, the optimal portfolio calculation means is
It can be configured to include the following two requirements.

Efficient frontier determining means: The variance of the return rate of all the target assets (hereinafter referred to as portfolio diversification) is minimized for each value of the future expected value of portfolio return rate (hereinafter referred to as portfolio expected return rate). The asset class allocation is calculated based on the above-mentioned asset class expected return information, asset class variance information, and asset class covariance information, and shows the relationship between portfolio expected return rate, portfolio variance and asset class allocation efficiently. Determine the frontier. Portfolio return rate achievement-related probability table creating means: Assuming that the portfolio return rate follows a predetermined probability distribution (for example, normal distribution) having the average and the variance of the expected portfolio return rate and the portfolio variance, respectively. Calculate the unachieved probability or achieved probability (collectively referred to as achievement-related probability) for each value for each set of portfolio expected return and portfolio variance given for each given point on the efficient frontier. Then, the calculated values of the achievement-related probabilities are associated two-dimensionally with the expected portfolio return rate and the portfolio return rate to create a portfolio return achievement-related probability table.

The optimum portfolio calculation means is
On the above portfolio return rate achievement probability table,
Of the achievement-related probabilities corresponding to the set portfolio return target values, the expected expected return for the portfolio with the lowest unachieved probability or the highest achieved probability is read to find an efficient frontier. The asset class allocation corresponding to the portfolio expected return rate read above can be determined as the optimal portfolio.

The efficient frontier used in the above configuration is a set of optimal asset class allocations that minimize the portfolio variance (ie risk) for each expected portfolio return (ie return). The portfolio return rate achievement-related probability table summarizes the respective unachievable (or attainable) probabilities of various values of the portfolio return rate for the allocation of each asset class on the efficient frontier. By referring to this table, which portfolio expected rate of return has the lowest unachieved probability (or the highest probability of achievement) in order to achieve the preset portfolio rate of return target value. Can be determined. Then, based on the efficient frontier, the allocation of the asset class corresponding to the expected portfolio return rate with the minimum unachieved probability (or the maximized probability) is obtained, and this is determined as the optimal portfolio, that is, the recommended portfolio. To do. This makes it possible to extremely rationally determine the recommended portfolio that has the highest probability of achieving the portfolio return target value.

In the portfolio automatic designing system of the present invention, at least information on each occurrence time of one or more expected fund events and information on the final required amount thereof are based on the input expenditure content specifying information. Fund event information generating means for generating the fund event information including, asset class allocation amount calculating means for calculating the allocation amount (asset class allocation amount) of the target asset to each asset class based on the recommended portfolio, and each asset class Of the predetermined ones, the fund event allocation amount calculation means for calculating the allocation amount for each fund event for the asset class allocation amount by referring to the fund event information, and the fund event allocation for outputting the calculation result A forehead output means can be added.

For general users who have little experience or knowledge about asset management, for example, a financial event that will occur in the future in their own life rather than the problem of how to effectively allocate assets by the calculated recommended portfolio. , For example, marriage funds, childbirth costs, child education funds,
It is more important to have specific information on what asset class (type) of assets is effective for housing purchase funds, leisure funds, retirement funds, etc. According to the above configuration, the occurrence time of each cash event and the final required amount are calculated based on the input expenditure content identification information, and the allocation amount of the target asset to each asset class is calculated based on the recommended portfolio, The allocation amount for each fund event with respect to the allocation amount of a predetermined asset class is calculated with reference to the fund event information (that is, the necessary time and the amount). As a result, the user can easily obtain clearer asset management information that individually looks at various future fund events.

It should be noted that the spending content specifying information includes information on each time of occurrence of a fund event and information on the final required amount thereof, and the fund event information generating means is configured to divert this. May be. However,
It is often difficult for many users to input spending content specifying information including specific fund event information. In this case, the fund event information generation means generates fund event content identification information that specifies the content of each fund event (for example, the type of fund event, the time of occurrence, the required amount, etc.) from the input content of the expenditure content specification information. It can be configured to.

The fund event information may include, for a plurality of fund events, assigned asset class identification information that identifies an asset class to which they should be assigned. Then, the fund event allocation amount calculating means may refer to the allocated asset class identification information and distribute the allocation amount for each fund event to the allocation amount of the corresponding asset class. In other words, when a fund event is specified, if the asset class to which the asset should be allocated is defined in advance in the form of the assigned asset class identification information, each fund event for each asset class allocation amount The allocated amount can be easily calculated.

Further, the fund event allocation amount calculating means determines the asset class assigned to the fund event based on the information on the final required amount of the fund event and the expected return rate of the asset class corresponding to the fund event. When the asset is operated at the expected rate of return, the principal amount currently required to achieve the condition of the final required amount can be calculated and used as the above allocated amount. As a result, it is possible to rationally calculate the allocation amount currently required to achieve the condition of the final required amount of each fund event. The principal amount can be calculated by, for example, compound interest calculation using the expected return rate as the interest rate.

Further, the allocation order to the corresponding asset class allocation amount can be set in advance for each fund event, and the fund event allocation amount calculating means allocates asset classes in order from the fund event having the highest allocation order. Allocation to the forehead may be made. As a result, for example, the asset events can be allocated to the asset class allocation amount in order from the financial event of high importance, so that the user's sense of security can be further enhanced.

The recording medium of the present invention is a computer-readable CD-ROM, a floppy (registered trademark) disk, a program for causing a computer to function as each means in the portfolio automatic design system described above. The data is recorded on a recording medium such as a magneto-optical disk or a ROM card. Accordingly, the portfolio automatic designing system of the present invention can be easily realized by installing the program stored in the recording medium into the computer.

[0028]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments of the present invention will be described below with reference to the examples shown in the drawings. FIG. 1 is a block diagram showing the overall configuration of an embodiment of the portfolio automatic design system 1 of the present invention. That is, the essential part of the portfolio automatic design system 1 is a computer 50, which is provided with an I / O port 2 and is provided with a CPU 3 and RO.
A recording medium reading means such as M4 and RAM 5, a CD-ROM drive 8 or a floppy disk drive 9, a hard disk drive (hereinafter referred to as HDD: asset class profit rate information storage means) 10 and the like are connected.
Further, the I / O port 2 of the computer 50 is provided with an input means such as a keyboard 6 or a mouse 7 (target asset specific information input means, expenditure content specific information input means), printer 1.
2 and monitor 13 and other output means (functioning as recommended portfolio output means, fund event allocation amount output means, etc.) are connected.

The HDD 10 stores an operating system program (hereinafter referred to as OS) 10a and an application program 10b. The application program 10b is a basic program that operates on the OS 10a and realizes the basic functions of the portfolio automatic design system 1 of the present invention. Then, the CPU 3 executes the application program 10b to execute the asset transition basic prediction information generation means, the recommended portfolio determination means, the current portfolio expected return rate calculation means, the portfolio return rate target value setting means, the optimal portfolio calculation means, and the efficient frontier determination. means,
It becomes the main body such as a portfolio return rate achievement related probability table creating means, an asset class allocation amount calculating means, and a fund event allocation amount calculating means. In addition, in ROM4,
It stores various basic programs for controlling the hardware of the computer system. RAM5
Functions as a work area for the OS 10a or the application program 10b, and also as a memory for storing numerical values or data used by the application program 10b. The memory allocation is shown in FIG.
~ Shown in FIG.

Next, as shown in FIG. 2, the HDD 10 stores the following data used by the application program 10b. Financial asset past performance data (return rate past performance information) 10
c: An example is shown in FIG.

In other words, in the present embodiment, the target assets of the portfolio design are financial assets, and the product categories such as profitable products (stocks, investment trusts, convertible bonds, bond with warrants, foreign currency deposits, actual dividend type money trusts, etc. Liquid products (including product categories such as ordinary deposits, MMFs, medium-term government bond funds, etc.), and safety products (super term, large term term, savings deposits, fixed savings, discounted financial bonds, interest-bearing financial bonds, public and corporate bonds) There are three asset classes: investment trusts, loan trusts, gold savings accounts, and mortgage securities.

Then, the data of the rate of return (interest rate) of each asset class for each month (or another period unit such as week or quarter may be adopted), that is, γ11, γ12, γ13 ... : Asset class 1); γ21, γ22, γ23 ... (Liquidity products: Asset class 2); γ31, γ32, γ33 (Safety products: Asset class 3); (Hereinafter referred to as "accumulation period"). Further, the average value (expected return rate) γ1, γ2, γ3 of each asset class in the accumulation period, the variances V11, V22, V33, and the covariances V12, V23, V31 among the asset classes are also:
It is calculated based on the above-mentioned profit rate (interest rate) data and stored.

[0033]

[Equation 1]

Normal distribution data 10d: The data of the normal distribution shown in FIG. 10 is stored. However, the normal distribution is a probability distribution whose probability density function is represented by f (t) in the figure (where σ is the standard deviation and μ is the mean), where t is the random variable, and μ is the f (t). = 0 and σ = 1
A probability distribution having a probability density function of (t) is called a standard normal distribution. Then, in this embodiment, various t of standard normal distribution
The value of the cumulative probability density (represented by P (t) in the figure) for the value of is stored as normal distribution data.

Master data 10e related to fund event application product (assigned asset class identification information): As shown in FIG. 4, a fund event name 601 and an asset class 60
2. The data of the applicable product category 603 and the specific product name 605 belonging to each applicable product category are stored in a form associated with each other. In this embodiment, risk level data 604 is provided for profitable products to further subdivide the classification. The risk level is represented by a numerical value such as (RR) 4, and the higher the numerical value, the higher the profitability, but the higher the risk (variance of the return rate or the standard deviation), and the lower the numerical value, the lower the risk but the profit. It also means that the sex becomes low.

Product application order data 10f: As shown in FIG. 5, shows the order of allocation of fund events to the asset allocation amount to each asset class. Comment data 10g: As shown in FIG. 6, when outputting the allocated amount of each fund event, it is the data of the comment to be output in association with this.

Then, as shown in FIG. 1, among the stored contents of the HDD 10, for example, the application program 1
0b, financial asset past performance data 10c, normal distribution data 10d, financial event application product-related master data 10
e, product application order data 10f, comment data 10g
A program and data group for realizing the functions of the portfolio automatic design system 1 are supplied in the form of a recording medium such as a CD-ROM 40 or a floppy disk 41, and read from the CD-ROM drive 8 or the floppy disk drive 9. As a result, it can be installed in the computer 50. Also, these programs and data groups may be received by the receiving means such as the modem 44 from the host computer 42 which is the transmission source via the network (for example, the Internet, telephone line, etc.) 43, and downloaded to the HDD 10. May be installed by.

Hereinafter, the portfolio automatic design system 1
The operation will be described with reference to the flowcharts of FIGS. 11 to 17. First, as the first step, a simulation of the life planning of the user (diagnosed person) is performed.
This is a process for collecting information about the current asset status of the user and various factors that affect the asset in the future, and creating prediction information regarding future asset transition.

That is, in S1 of FIG. 11, the following information (data) is collected by a questionnaire from the user,
Input using the mouse 7 or the keyboard 6. Note that the number of the storage destination memory area of the RAM 4 in FIG. 7 is shown in parentheses after the information name. Patient identification information (101): For example, the user's name, address, sex, date of birth, etc. Spouse / child information (102): Presence or absence of spouse, time of marriage of the user himself, number and age of children, etc.

Funding event information (103): Part of the expenditure content specifying information. For example, the following information is applicable and is input so that the type of fund event and the required amount of money can be specified. In addition, if necessary, enter the specific time when funds are needed.・ Education plan information: Information such as whether you want to be a national public or private in elementary school, junior high school, high school, university. The time when the fund is needed is specified by, for example, the backward calculation from the age of the child included in the spouse / child information. -Marriage plan information: Information such as the desired age for marriage of a child, necessary funds, and the parent's assistance rate. For example, when you need funds
It is specified by calculating backward from the age of the child included in the child information. Leisure planning information: For example, information on the amount of money (the timing of implementation, if necessary) for sports, hobbies, entertainment, sightseeing, and excursions that are regularly or irregularly performed. -Old age plan information: information on old age expenditure and income. That is,
Information such as retirement age, retirement allowance, re-employment period and income, estimated living expenses for retirement, pension income, etc. It should be noted that this is input separately from income information / expenditure information described later, but it may be input by incorporating it into the income information / expenditure information.

Income information (104): Annual income amount excluding investment income (eg salary income, income other than salary). Expenditure information (105): Part of the expenditure content specifying information, and represents spending information different from the aforementioned fund event information.
For example, general living expenses, loans, non-life insurance premiums, individual item purchase costs, etc. Financial asset information (106 to 108): Asset amount information for each asset class (profitability, liquidity, safety) held by the user. Other asset information (109): Information on asset contents other than financial assets. Enter if necessary. For example, the amount of fixed assets and the annual average increase rate. Debt information (110): Information on the debt of the user, which forms part of the expenditure content specifying information, such as debt and remaining repayment period and interest rate.

Next, by separately inputting data, the life planning simulation start time (“current” in claims) is set, and the set value is stored in the memory 111 of FIG. 7. For example, the present time of the user may be set as the start time, or a specific time in the future (for example, after marriage or after retirement of retirement age) may be set as the start time. Then, in S2 of FIG. 11, the income composition transition after the simulation start time is simulated from each of the input information described above, and the result is output (monitor 13).
Or printer 12). Note that the simulation program uses the work area 112 in FIG.
The result is stored in the memory 113. FIG. 23A shows an output example of the simulation result of the income composition transition when the retirement age is the simulation start time.
It should be noted that the output may be collectively output together with each simulation result, which will be described later, or other calculation result.

Returning to FIG. 11, in S3, the simulation of the transition of the expenditure composition after the simulation start time is performed, and the result is output. Note that the simulation program uses the work area 114 in FIG. 7 and stores the result in the memory 115. FIG. 23B shows an output example of the simulation result. Expenditures consist of general living expenses, loans, non-life insurance premiums, individual item purchase expenses, etc. specified by the above expenditure information,
It includes the amount of debt specified by the debt information (reduced with repayment) and the necessary amount for each individual financial event specified by the financial event information. Further, based on the fund event information, each fund event name and required period (expressed by the number of years from the simulation start time) and the final required amount are converted into data (these storage memories in the RAM 4 are 301 to 301 in FIG. 9). 303, 311 to 31
3, 321 to 323).

Next, proceeding to S4 in FIG. 11, for example, by calculating the difference between the income composition transition and the expenditure composition transition, a balance excess / deficiency transition is calculated and output. The program is
In FIG. 7, the work area 116 is used and the result is stored in the memory 117. FIG. 23C shows an output example of the result.

Further, in S5, the distribution ratio of each asset class of the assets held by the user, that is, the current portfolio is calculated from the inputted financial asset information, and in S6,
Its current portfolio and financial assets past performance data 10
The current expected portfolio return rate γP0 is calculated with c. For example, if the allocation ratios of asset classes 1 to 3 in the current portfolio are x01, x02, x03, the expected portfolio return rate γP0 is γ1 × x01 + γ2
It can be calculated by × x02 + γ3 × x03.

Then, in S7, a simulation of the transition of funds (borrowing) (deposit and savings or balance of borrowing) is performed. This is done by calculating the total amount of assets at present (simulation start time) based on the input financial asset information, and then performing the following calculation for each year. (1) Based on the above income composition transition and expenditure composition transition, for example, for each year, calculate the difference between annual income and expenditure, and if income exceeds expenditure, add this to the total assets as a new reserve . On the contrary, if the expenditure is higher, the total assets are deducted. (2) Calculate the investment (investment) return of assets by multiplying the total amount of assets for each year by the current expected portfolio return rate γP0, and incorporate this in the corresponding year's income. Here, the simulation program uses the work area 120 in FIG. 7 and stores the result in the memory 121. In addition, when a situation occurs in which the financial assets run out, the simulation may be performed by destroying assets (fixed assets, etc.) other than the financial assets specified by the "other asset information".

Returning to FIG. 11, from the obtained simulation result of the transition of funds (borrowing), the time T0 at which the assets are turned into borrowing (asset shorting period) is obtained. FIG. 23D and FIG. 24A show an example of the output result of the simulation. In both cases, it is clear that the assets are short-circuited at T0. The shortage of assets means that the users' future lives will be destroyed. Therefore, in S9, a target value for raising the current portfolio expected return rate γP0 in the current portfolio to avoid this failure, that is, a portfolio expected return rate target value γPt is set. The details are as shown in FIG. 12 (the processing program is shown in FIG.
Work area 124).

First, an average expected rate of return γ is set by setting a limit value (fund securing limit time) TL on the time axis (stored in the memory 123 of FIG. 7) that an asset short circuit should not occur until this time. Is increased from the current γP0 by Δγ, and a re-simulation of the transition of funds (borrowing) is performed. Then, assuming that TC is the asset shortage time in the re-simulation result (FIG. 7: stored in the memory 122), if TC ≧ TL is not satisfied, γ is further increased by Δγ and the same processing is repeated. Then, γ when TC ≧ TL is set as the portfolio expected return target value γPt (the set value is stored in the memory 125 in FIG. 7), and the re-simulation result at that time is stored (S91. ~ S97).

Returning to FIG. 11, in S10, the re-simulation result of the asset transition after the expected portfolio return γP0 is corrected to the target value γPt is output. Figure 24 (b)
Shows an example of the output. It can be seen that the assets that were shorted at T0 before the revision are not shorted to TL.

Instead of repeating the re-simulation of asset transition while gradually changing the average expected rate of return γ, the following processing can be performed. That is, the asset amount (borrowing amount if negative) R is a function of the time T and the average expected rate of return γ, R = f (γ, T), using each numerical information included in the above input information. If it can be expressed by (a), T = T in the equation (a)
If L and R = 0 (that is, asset short), and if this is regarded as an equation for γ, then the portfolio expected return rate target value γPt can be obtained as its solution.

Next, proceeding to FIG. 13, the process of determining how the current portfolio should be changed in order to achieve the portfolio expected return rate target value γPt, that is, the probability of achieving the target value is the most probable. Moves to the process of calculating a rational asset class ratio (best mix) that is high. This process is roughly divided into 3 of the efficient frontier calculation in S101, the target investment return unachieved probability table (target investment return achievement achievement probability table) in S102, and the determination / output of the best mix in S103. It consists of two processing steps.

Efficient frontier is the composition ratio of the asset class in the asset for which the portfolio variance (or standard deviation: in other words, risk) is the smallest with respect to the value of each portfolio expected return rate γP (hereinafter, the optimum asset Called allocation) is the set for which.
FIG. 14 shows details of the efficient frontier calculation processing. First, in step S1101, the expected portfolio return rate γP is set to an initial value γPi (the set value is stored in the memory 201 of FIG. 8). In step S1102, the expected return rates γ1, γ2, γ3 for each asset class and the variances V11, V2 are calculated from the financial asset past performance data 10c (FIG. 3).
2, V33, and covariance between asset classes V12, V2
3. Read the values of V31 (these values are stored in memory 2 of FIG. 8).
03-211).

Next, in steps S1103 to S1105, γP
With respect to (the initial value γPi at this stage), the processing is to obtain the composition ratio (x1, x2, x3) of the asset class in the asset for which the portfolio variance VP is the minimum. First, the expected portfolio return rate γP can be expressed by the following equation 2.

[0054]

[Equation 2]

The portfolio variance VP is given by
It is represented by.

[0056]

[Equation 3]

The constraint conditions are x1, x2, x3.
, Respectively, show the distribution of asset classes in assets, so x1 + x2 + x3 = 100 (%) (10), and since the ratio does not become a negative number, x1 ≧ 0, x2 ≧ 0, x3 ≧ 0 (11)

In this case, the equation (4) of the equation 2 and the equation (9) of the equation 3 are made simultaneous, and (x1, x2, x3) should be determined so that VP is minimized (S1103). ). Where the expression (1
0), one of x1, x2, and x3 (for example, x3
18), the equation (4) is converted into a straight line α on the plane (for example, the x1-x2 plane) defined by the remaining two variables, and the equation (9) is converted into the equation (9). Similarly, it represents a quadratic curve β (a curved surface that differs depending on the value of VP). Therefore, a set of x1, x2 and x3 that minimizes the value of VP, that is, optimal asset allocation (x1C, x2
C, x3C) is determined by analyzing the geometrical positional relationship between the straight line α and the curve β when various values of VP are changed based on the quadratic programming method, and then (x1C, x2C) is determined. It can be determined by substituting the result into equation (10) and determining x3C. When multiple sets of (x1C, x2C, x3C) are obtained, only those satisfying the condition of the equation (11) are adopted (above, S1104: VP minimization analysis program is the work area of FIG. 8). 214).

Next, in S1105, the optimum asset allocation (x1C, x
2C, x3C) and the corresponding square root of minimized VP (VPC) ^1/2 (that is, the minimized portfolio standard deviation) corresponding to the value of γP in FIG. It is stored in the memory 213. Then, from S1106 to S
By advancing to 1107 and changing the value of γP by ΔγP, returning to S1103, the same processing is repeated, and data sets corresponding to various γP values are obtained one after another, as shown in FIG. An efficient frontier data set is formed in the memory 213. Note that FIG. 20 illustrates the above efficient frontier by plotting (VPC) ^{1/2 on} the horizontal axis and γP on the vertical axis (examples of optimum asset allocation values at each point are written in parentheses in the figure). Is shown).

In the steps up to this point, the optimum asset allocation (x1C, x2C, x3C) and the corresponding minimized VP (or VP ^1/2 ) are set to various γP values. Correspondingly many were calculated. Therefore, in the next step, of the various sets of the above-mentioned optimum asset allocations (x1C, x2C, x3C), the one with the highest probability of achieving the previously determined portfolio expected return target value γPt is selected. There must be.
For this purpose, first, a target investment return rate unachieved probability table is generated (FIG. 13: S102).

FIG. 15 shows details of the generation processing (the generation program is executed using the work area 214 in FIG. 8). First, in S1201, the profit rate γ and the variance V are set to initial values. However, it is assumed that (γ, V) is a point on the efficient frontier obtained earlier. Then, assuming that the profit rate target value G is a random variable, it is assumed that the G follows a normal distribution in which γ is the average and V ^1/2 is the standard deviation, and G is set to an initial value G 0 (S120).
3). Next, in S1204, Z = (G−γ) / V
^{The value} of G is converted into the variable Z that follows the standard normal distribution by ^1/2 , and the process proceeds to S1205, where the normal distribution data 10d
By referring to FIG. 2, the value of the cumulative probability density P of the standard normal distribution corresponding to Z is calculated by the interpolation method. The value of P represents the probability that the return rate (portfolio expected return rate) γ will not be achieved, that is, the unachieved probability. The value of P may be calculated by numerical integration according to the following equation 4.

[0062]

[Equation 4]

Alternatively, the value of G may be directly used without performing variable conversion, and may be calculated by numerical integration according to the following equation (5).

[0064]

[Equation 5]

Next, the program proceeds from S1206 to S1207, increases the value of G by ΔG, returns to S1204, and S12.
By repeating the processing of 05 to S1206, the value of P corresponding to the value of various G is calculated with respect to the set value of (γ, V). Then, when all the values of P for the (γ, V) are calculated, the process proceeds from S1208 to S1209, and the values of γ and V are respectively calculated on the efficient frontier by Δ.
Increase by γ and ΔV and return to S1202.
By repeating the processes of 203 to S1207, various (γ,
A set of P for V) is calculated, and this is stored in the memory 215 of FIG. 8 as a target investment return rate unachieved probability table. FIG. 21 shows an example of the target investment return rate unachieved probability table thus generated. Further, FIG. 22 is a graph showing the relationship of γ-P with various G values, with γ on the horizontal axis and P on the vertical axis.

Next, returning to FIG. 13, the determination / output process of the best mix in S103 is performed (the calculation program is executed using the work area 216 in FIG. 8). The details are shown in FIG. First, in S1301, the value of the portfolio investment return rate target value γPt is read (FIG. 8).
Memory 202: The value is copied from the memory 125 of FIG. 7). Next, in S1302, γ corresponding to G = γPt
Data representing the -P relationship is generated by referring to the generated target investment return rate unachieved probability table (memory 215), and in S1303, P is the minimum in the γ-P relationship, that is, Find the value of γP γPm that minimizes the probability that γPt is not achieved.

For example, in FIG. 22, G = γPt = 6%
, P is minimum around γ = 7%,
Pm is obtained as a value of about 7%. And S1
At 305, the aforementioned efficient frontier (FIG. 8: memory 2
13), the optimum asset allocation (x1C, x2C, x3C) corresponding to the γPm is calculated as the best mix (x1C
B, x2B, x3B) (value is the memory 2 of FIG. 8)
17 to 219).

In the above process, the point on the efficient frontier is determined so that the unachieved probability P for the profit rate γ is minimized.
The processing may be such that points on the efficient frontier are determined so that (= 1−P) becomes maximum.

Next, in S1306, by referring to the financial asset information stored in the memories 106 to 108 of FIG. 7, the asset amount for each asset class (profitability, liquidity, safety) held by the user is calculated. Calculate the total financial assets Q by totaling, and calculate the best mix (x1B, x2B, x
From the value of 3B), calculate the distribution amount to each asset class as follows.・ Allocation to profitable products: F1 = x1B × Q ・ Allocation to liquid products: F2 = x2B × Q ・ Allocation to safety products: F3 = x3B × Q

For example, when the expected portfolio return rate γP0 in the current portfolio is set to 2%, the portfolio expected return rate target value that does not cause an asset short-circuit by changing to the best mix (x1B, x2B, x3B) portfolio. It is possible to achieve γPt (for example, 6%) with the maximum probability. FIG. 25 shows
Best Mix and Portfolio Expected Return Rate Target Value γPt
An example is shown and output in which the and are compared with the current portfolio.

Now, the portfolio automatic design system 1
The process of (3) enters the final stage, that is, the allocation process for each fund event of the best mix. FIG. 17 shows the flow of the processing. First, the name of each financial event and the required period (expressed in the number of years k from the start of the simulation),
The data of the final required amount (hereinafter collectively referred to as “fund event data”) has already been obtained in the life planning simulation process of FIG. 11, and is stored in the memories 301 to 303, 311 to 313, 321 to 323 of FIG. Since it is stored, it is read (S201). Next, the fund event data is classified by the asset class to be allocated by first referring to the fund event application product-related master data 10e in FIG. 4 (S20).
2). Then, in S203, the fund event data is sorted in the priority allocation order with reference to the product application order data 10f of FIG. 5 for each asset class.

The following processing is then performed (S205 to S2).
13). That is, the fund event data is read out in order from the higher order of priority allocation order. Since the final required amount A of the fund event and data of the required period (after k years) are written there, assuming that the expected rate of return of the asset class is γ, for example, one-year compound interest calculation (half-year compound interest calculation Etc.), the currently required principal amount K is calculated by the following equation 6 (S207). FIG. 26A shows some calculation examples thereof.

[0073]

[Equation 6]

This K becomes the fund allocation amount for the fund event and is sequentially stored in the corresponding ones of the memories 351, 361, 371, ... Of FIG. Further, in the comment data 10g of FIG. 6, the comment data corresponding to the fund event name is read out, and the corresponding application product category and product name data is read out from the fund event application product-related master data 10e (FIG. 4). The allocated amount and the fund event name are combined. This combined data is associated with the data of the fund allocation amount as the accompanying output data, and is stored in the memories 352 and 3 of FIG.
62, 372, ... (S208). This processing is performed for each of the sorted fund event data corresponding to the asset class (S2).
09->S210->S211-> S207 flow).

In the present embodiment, the allocated amount of the fund event with the lowest priority is lower than the allocated amount F of the asset event to the asset class (stored in the memories 220 to 222 in FIG. 8). By calculating the remaining amount by subtracting all the amount allocated to the fund event in which the priority is given, there is no surplus in the asset allocation amount F. FIG. 26B shows an example of the calculation. In addition, FIG.
Then, as an example of the processing routine, the sum (skeleton sum) Sk of the allocation amount to the fund event in which the priority is given is calculated, and the sum Sk is finally subtracted from F (S2).
10, S212) is not limited to this.

Then, the processes of S205 to S213 are repeated for each asset class (S214 → S215).
→ Flow of S205), the allocation of the asset amount for all fund events ends. The above results are output from the monitor 13 or the printer 12 in a form in which a fund event name, a required period, a final required amount, accompanying output data, and the like are associated with each other for each fund event.

FIG. 27 shows an output example thereof. The output contents are basically the fund event name 501 (read out from the corresponding memory 301, 311, 321 in FIG. 9), the final required amount 502 (memory 302 in FIG. 9,
312, 322, etc.) and associated output data 305 (memory 352, 36 of FIG. 9).
2, 372, etc. are read from the corresponding ones). Also, with the accompanying output data 305,
In FIG. 27A, the calculated fund allocation amount 503b (the memories 351 and 36 in FIG. 9) is added to the comment data 503a.
(Read from the corresponding ones such as 1, 371) and the product name 503c are combined. Also, (b),
In (d) and (e), in the comment data 503a, the required time 503d (read from the corresponding memory 302, 312, 322 of FIG. 9) and the product name 503c.
And are synthesized. Further, in (c), the comment data 503a includes the required time 503d and the product category 503.
e and the product name 503c are combined.

FIG. 28 shows another output example. In this example, the risk level data 504 of the product corresponding to each fund event, the explanatory comment 505 of the selected product, and the data 506 of the change in the profit rate of the product (for example, annual profit rate change) are combined. Is displayed and output. In this case, the product event comment data 60 is included in the fund event application product-related master data 10e of FIG.
6 and data of rate of return change (eg annual rate of return data)
607 is stored in a form associated with the fund event (or the product name), and the one corresponding to each fund event is read and displayed.

The financial asset past performance data 10c, the normal distribution data 10d, the fund event application product-related master data 10e, the product application order data 10f, the comment data 10g, etc. may be changed at least in part at any time. You can For example, since the financial asset past performance data 10c becomes old year by year, it is desirable to periodically update it with new data. When a new financial product is developed, the data related to the product is added to the fund event application product-related master data 10e.
It can be added in a form associated with the fund event name, product category, risk level, and the like.

In this case, as a method of changing (or updating) the data, a CD-recording the necessary data is used.
The data is read by a CD-ROM drive 8 or a floppy disk drive 9 from a recording medium such as the ROM 40 or the floppy disk 41 (in this case, the application program 10b does not have to be particularly written in the recording medium), and the computer is read. There is a method of re-installing the data in 50 or a method of receiving necessary data from the host computer 42 via the network 43 by the modem 44 and downloading the data.

Further, in the present embodiment, the best mix is determined by referring to the efficient frontier and the target investment return rate unachieved probability table, but as a simpler method, on the efficient frontier, It is also possible to read the optimal asset allocation corresponding to the portfolio expected return rate target value γPt and adopt this as the best mix.

Various modifications that can be made to the portfolio automatic design system 1 of the present invention will be described below.

First, in the above-mentioned embodiment, after calculating the recommended portfolio and the portfolio return rate at that time, the asset class is allocated by the recommended portfolio, and the allocation amount to each asset class is allocated to each fund event. I was doing. However, some users do not necessarily adopt the recommended portfolio. For example, a portfolio with a higher return rate (but with a higher risk) may be used for a more adventurous asset management, or conversely the return rate may decrease slightly. It is also possible that there will be a desire to try safer asset management. In this case, custom portfolio identification data for directly or indirectly identifying any desired portfolio can be input, and in the processing of FIG.
The allocation amount to each asset class may be calculated based on the portfolio specified based on the custom portfolio specifying data. The allocation processing for each fund event to the allocated assets to each asset class can be performed in the same manner as the processing of FIG. Further, in this case, it is more convenient if the calculation result of the recommended portfolio (best mix) is temporarily output and the user can input the custom portfolio specifying data by referring to the output result.

Next, the asset short period calculated in the life planning simulation process of FIG. 11 may be later than the fund securing limit period TL in time series from the beginning. This means that even with the current portfolio maintained, all future funding events have been achieved and there is still more. In this case, at least one of various additional functions described below can be added. Notify that there is no problem in maintaining the current portfolio as it is by outputting notifications such as messages. By inputting the custom portfolio specific data described above, the portfolio return rate is adjusted upward according to the desired portfolio. In this case, the allocation process for each fund event can be similarly performed using the portfolio after the upward correction. Calculate the portfolio return rate γmin when the asset shortage period is the fund securing limit period TL, and calculate γm
difference between in and the expected return rate γP of the current portfolio γP−γ
The portfolio is modified so that the expected rate of return γP increases according to min. In this case, the allocation process for each fund event can be similarly performed using the modified portfolio.

Next, the setting of the asset class shown in the above embodiment is merely an example. For example, a safety product and a liquid product are integrated, and these are integrated into a safety product. It can also be two asset classes with a profitable product. On the contrary, it is also possible to further divide the asset class and set it. In this case, it is not particularly hindered to subdivide the asset class into individual product categories or product levels. As an example, even if the target assets are narrowed down to stocks among profitable products and individual stock brands are respectively adopted as asset classes, the processing of the portfolio automatic design system 1 described above is It can be done in exactly the same way. Furthermore, the asset class is not limited to financial assets,
For example, fixed assets such as land and buildings, minerals, metal ingots,
It may be an agricultural product or an industrial product.

Next, each component (means) of the portfolio automatic design system 1 shown in FIG.
It is configured as a somewhat closed system consisting of and peripheral devices directly connected to it, but each component (means)
It is also possible to disperse the host devices connected via the communication network and the terminals connected thereto. FIG. 29
Shows an example thereof.

That is, the portfolio automatic design system 1 having this configuration is used in the communication network 702 such as the Internet.
And a host device 700 connected thereto via a modem 701 serving as a transmitting / receiving means, and a plurality of terminals 703 connected via a modem 752 also serving as a transmitting / receiving means. In the following, the same components as those in FIG. 1 are designated by the same reference numerals and the description thereof will be omitted, and only the differences will be mainly described.

First, the main part of the host device 700 is configured almost the same as the computer 50 of FIG.
A program and data similar to those in FIG. 2 are stored in 10. However, the difference from the device of FIG. 1 is that the user inputs information (data) necessary for each process to the communication network 7
This is performed from the terminal 703 side connected via 02. Each terminal 703 has its own I / O port 751.
And CPU 754, ROM 755, RA connected to it
It is configured as a computer including an M756, and the keyboard 6 and the mouse 7 as the above-mentioned input means are connected to the I / O port 751. The printer 12 and the monitor 13 as output means are also connected to the I / O port 751.

Information input by the keyboard 6 or the mouse 7 on the terminal 703 side (that is, each of the above items 1 to 3 in S1 of FIG. 11) is transferred to the communication network 702.
11 through 17 by the application program 10b (FIG. 2).
Each processing shown in is executed. Then, the result of the processing (for example, S2, S3, S4, S7, S10 in FIG. 11, S1304, S1306 in FIG. 16, S216 in FIG. 17, etc.).
Is transmitted to the accessed terminal 703 via the communication network 702, and is output to the printer 12 or monitor 13 of the terminal 703 there. It is convenient to provide the terminal 703 with an HDD 753 for downloading the result of the above processing.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of a hardware configuration of a portfolio automatic design system of the present invention.

FIG. 2 is an explanatory diagram showing storage contents of an HDD.

FIG. 3 is an explanatory diagram showing an example of the contents of financial asset past performance data.

FIG. 4 is an explanatory diagram showing an example of contents of fund event application product-related master data.

FIG. 5 is an explanatory diagram showing an example of contents of product application order data.

FIG. 6 is an explanatory diagram showing an example of contents of comment data.

FIG. 7 is an explanatory diagram showing a memory configuration in a RAM.

FIG. 8 is another explanatory diagram of the same.

FIG. 9 is another explanatory view of the same.

FIG. 10 is an explanatory diagram of a normal distribution.

FIG. 11 is a flowchart showing the flow of a life planning simulation process.

FIG. 12 is a flowchart showing details of portfolio expected return rate target value setting processing in FIG. 11.

FIG. 13 is a flowchart showing the flow of a best mix calculation process.

FIG. 14 is a flowchart showing details of efficient frontier calculation processing in FIG.

FIG. 15 is a flowchart showing details of target investment return rate unachieved probability table generation processing in FIG. 13;

16 is a flowchart showing the details of the best mix determination / output process of FIG.

FIG. 17 is a flowchart showing the flow of a best mix allocation process by fund event.

FIG. 18 is a schematic diagram illustrating the principle of optimal asset allocation calculation using a quadratic programming method.

FIG. 19 is an explanatory diagram showing a storage state of a data group of an efficient frontier in the memory.

FIG. 20 is a graph showing an example of an efficient frontier.

FIG. 21 is an explanatory diagram showing an example of a target investment return rate unachieved probability table.

FIG. 22 is a graph visualizing FIG. 21.

FIG. 23 is an explanatory diagram showing an output example of a life planning simulation.

FIG. 24 is an explanatory diagram showing, in comparison, output result examples of asset (borrowing) transitions before and after portfolio correction.

FIG. 25 is an explanatory diagram showing an example of comparing and outputting each portfolio before and after correction.

FIG. 26 is an explanatory diagram showing a calculation example of asset allocation to a fund event.

FIG. 27 is an explanatory diagram showing an example of a result output of asset allocation to a fund event.

FIG. 28 is an explanatory view showing another example of the same.

FIG. 29 is a block diagram showing an example of a hardware configuration of a portfolio automatic design system using a communication network.

[Explanation of symbols]

1 Portfolio automatic design system 3 CPU (Asset transition basic forecast information generation means, recommended portfolio determination means, current portfolio expected return rate calculation means, portfolio return rate target value setting means, optimal portfolio calculation means, efficient frontier determination means,
Portfolio profit rate achievement related probability table creating means, asset class allocation amount calculating means, fund event allocation amount calculating means 6 Keyboard 7 Mouse (target asset specific information input means, expenditure specific information input means) 10 Hard disk drive (by asset class) Profit rate information storage means) 10b Application program (program) 12 Printer 13 Monitor (recommended portfolio output means, fund event allocation amount output means) 40 CD-ROM (recording medium) 41 floppy disk (recording medium) 50 Computer

Claims (11)

[Claims] 1. A target asset identification for inputting target asset identification information for directly or indirectly identifying a current total amount and a current portfolio (hereinafter referred to as a current portfolio) of a target asset composed of a plurality of asset classes. Information input means, expenditure content specific information input means for inputting expenditure content specific information that directly or indirectly specifies expected future expenditure content, and direct or indirect expected future rate of return for each asset class Asset class rate of return information storage means for storing asset class rate of return information for identifying the asset portfolio, and the change over time of the total amount of the target assets when the current portfolio is considered to be maintained in the future. Forecast information (hereinafter referred to as asset transition basic forecast information), the target asset identification information, the expenditure content identification information, the Based on the asset transition basic forecast information generating means that is generated based on the asset class return information, and the generated asset transition basic forecast information and the asset class return rate information, the time-dependent transition status is improved. An automatic portfolio design system comprising: a recommended portfolio determining means for determining a recommended portfolio of the target asset for enabling the recommended portfolio output means for outputting the determined content of the recommended portfolio. 2. The asset class is a safe financial asset whose principal is substantially guaranteed, and a profitable financial asset that may have a principal loss but has a higher expected return rate than the safe financial asset. 2. The portfolio automatic design system according to claim 1, including at least two types. 3. The asset class return rate information includes information on a past performance value of the return rate for each asset class (hereinafter referred to as return rate past performance information). Portfolio automatic design system. 4. The recommended portfolio deciding means sets a future return value of a portfolio return rate in the case of adopting the current portfolio with the investment return rate of the entire target assets as a portfolio return rate (hereinafter, the current portfolio expected return rate). Setting) a predetermined portfolio return rate target value that is larger than the current portfolio expected return rate. A portfolio return rate target value setting means for performing the above, and an optimal portfolio calculation means for calculating an optimal portfolio for achieving the set portfolio return rate target value and using this as the recommended portfolio. Port described in any of 3 Orio automated design system. 5. The portfolio return rate target value is such that when the content of the asset transition basic forecast information indicates that the total amount of assets has turned negative at a certain time in the future, the time when the total asset turn negative becomes the specified value. The automatic portfolio design system according to claim 4, wherein the portfolio automatic design system is set so as to extend a predetermined period or more ahead of the period. 6. The asset class return rate information is information that reflects an average value of return rates for each asset class (hereinafter, referred to as asset class expected return rate) calculated based on the return rate past performance information. (Hereinafter, asset class expected return information), information that also reflects variance (hereinafter, asset class variance information), and information that also reflects covariance between asset classes (hereafter, asset class covariance information) ) And the optimal portfolio calculation means, the variance of the return rate of the entire target assets (hereinafter, portfolio dispersion) for each value of the future expected value of the portfolio return rate (hereinafter, portfolio expected return rate) Asset class allocation that minimizes the asset class expected return information and the asset class variance Calculated on the basis of the distribution and the asset class covariance information,
Efficient frontier determining means for determining an efficient frontier indicating the relationship between the expected portfolio return rate, the portfolio variance, and the asset class allocation, and the portfolio return rate averages the expected portfolio return rate and the portfolio variance, respectively. And the probability of achievement or non-achievement probability (hereinafter, the achievement probability or non-achievement probability is referred to as the achievement-related probability) for each value of the portfolio profit rate, assuming that it follows a predetermined probability distribution of variance. Calculated for each set of the portfolio expected return and the portfolio variance corresponding to each predetermined point on the dynamic frontier, and correlating the calculated value of the achievement-related probability with the portfolio expected return and the portfolio return. Create arranged portfolio profitability related probability table The portfolio return rate achievement-related probability table creating means is provided, and on the portfolio return rate achievement-related probability table, among the achievement-related probabilities corresponding to the set portfolio return rate target value, the unachieved probability is the highest value. Of the expected portfolio rate of return that corresponds to the one with the smallest value or the highest achievement probability, and the asset class allocation corresponding to the read portfolio expected rate of return on the efficient frontier as the optimal portfolio. The portfolio automatic design system according to claim 4 or 5, which is determined. 7. A fund for generating fund event information including at least information on each occurrence time of one or more fund events expected in the future and information on the final required amount thereof based on the input expenditure content specifying information. Event information generation means, asset class allocation amount calculation means for calculating the allocation amount of the target asset to each asset class (hereinafter referred to as asset class allocation amount) based on the recommended portfolio, and each asset class Of the predetermined ones, a fund event allocation amount calculation means for calculating the allocation amount for each fund event for the asset class allocation amount by referring to the fund event information, and a fund event for outputting the calculation result. 7. The portfolio automatic according to claim 1, further comprising: allocation amount output means. Total system. 8. The fund event information includes allocation asset class identification information for identifying asset classes to be allocated to a plurality of the fund events, and the fund event allocation amount calculation means determines the allocated asset class. The portfolio automatic design system according to claim 7, wherein the allocation amount for each fund event is distributed to the allocation amount of the corresponding asset class by referring to the information. 9. The fund event allocation amount calculating means is assigned to a fund event based on information on the final required amount of the fund event and an expected return rate of an asset class corresponding to the fund event. 9. When the assets of the asset class are operated at the expected rate of return, the principal amount currently required to achieve the condition of the final required amount is calculated and used as the allocated amount.
Portfolio automatic design system described. 10. The allocation order to the corresponding asset class allocation amount is predetermined for each of the fund events, and the fund event allocation amount calculation means is arranged in order from the fund event having the highest allocation order. 10. The portfolio automatic design system according to claim 9, which allocates to an asset class allocation amount. 11. A computer is provided with the following means for constructing a portfolio automatic design system, that is, a current total amount and a current portfolio (hereinafter referred to as a current portfolio) of target assets composed of a plurality of asset classes, directly or indirectly. Target asset specific information input means for inputting the target asset specific information for positively specifying, and expenditure content specific information input means for inputting the expenditure content specific information for directly or indirectly specifying the expected future expenditure content, Asset class return information storage means for storing asset class return information for directly or indirectly specifying a future expected return for each asset class, and the present portfolio is maintained in the future Forecast information on the time-dependent transition of the total amount of the target assets in the case of consideration (hereinafter, (Basic transition prediction information) based on the current portfolio identification information, the expenditure content identification information, and the asset class return rate information, and asset transition basic forecast information generation means, and the generated asset transition. Based on the basic forecast information and the return rate information for each asset class, a recommended portfolio determination means for determining a recommended portfolio of the target asset for improving the transitional situation over time, and the determination content of the recommended portfolio are output. A recording medium characterized by storing a program for causing the recommended portfolio output means to function as a computer-readable state.