Investment model management device, investment model management method, and investment model management program

Abstract

To provide a technique for managing an investment fund by a portfolio obtained by combining a plurality of investment strategies.SOLUTION: An investment model management device includes: a sub-investment model management section for managing a plurality of sub-investment models which are individually operated according to predetermined investment strategies; a main investment model management section for managing a main investment model which operates an investment fund; and a portfolio determination section which determines a portfolio for allocating the investment fund of the main investment model to the plurality of sub-investment models on the basis of investment performance information of each sub-investment model.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an operation model management device, an operation model management method, and an operation model management program. [Background technology]

[0002] With the recent advances in information and communication technology, the financial industry is also actively conducting research and development into financial technology that utilizes information and communication technology, often referred to as "Fintech."

[0003] For example, in asset management, investment funds such as investment trusts and private placement funds are now being managed using investment support information provided based on computer-programmed investment strategies. Each investment strategy is formulated in accordance with the investment policy of each investment fund. For example, such investment policy is determined depending on whether the investment targets are domestic securities or foreign securities, stocks or bonds, and whether the target investors are retail investors or institutional investors, etc. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-017571 Summary of the Invention [Problem to be solved by the invention]

[0005] Various investment strategies can be formulated to correspond to each investment policy, and the investment models realized by these various investment strategies will also be diverse. The investment performance of the investment models realized by individual investment strategies may vary depending on economic conditions and market environments. If economic conditions or market environments become unexpected, investment actions relying on a specific investment strategy may result in unexpected investment performance.

[0006] One objective of the present disclosure is to provide a technique for managing investment funds through a portfolio that combines multiple investment strategies. [Means for solving the problem]

[0007] One aspect of the present disclosure relates to an operation model management device having a child operation model management unit that manages multiple child operation models, each of which is operated according to a predetermined investment strategy, a parent operation model management unit that manages a parent operation model that manages investment funds, and a portfolio determination unit that determines a portfolio for allocating investment funds of the parent operation model to the multiple child operation models based on investment performance information of each child operation model. [Effects of the Invention]

[0008] According to the present disclosure, it is possible to provide a technique for managing investment funds using a portfolio that combines multiple investment strategies. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a schematic diagram illustrating an operation scheme according to an embodiment of the present disclosure. [Figure 2] FIG. 1 is a conceptual diagram illustrating an operation model management device according to an embodiment of the present disclosure. [Figure 3] FIG. 2 is a block diagram showing a hardware configuration of an operation model management device according to an embodiment of the present disclosure. [Figure 4] 1 is a block diagram showing a functional configuration of an operation model management device according to an embodiment of the present disclosure. [Figure 5] 10 is a flowchart illustrating an operation model management process according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0011] In the following embodiment, an operation model management device that provides investment support information is disclosed.

[0012] [Operation scheme] In an investment scheme according to one embodiment of the present disclosure, when managing investment funds such as investment trusts and private placement funds, as shown in Figure 1, a parent investment model that manages the entire investment funds allocates the investment funds to multiple child investment models #1, #2, ..., #m, and manages the investment funds by receiving investment returns from each child investment model.

[0013] Each child investment model #i (i = 1, 2, . . . , m) manages the allocated investment funds according to an individual investment strategy. For example, child investment model #1 manages investment funds according to a stock investment strategy with a crisis avoidance trigger, child investment model #2 manages investment funds according to an economic environment judgment bond investment strategy, and child investment model #3 manages investment funds according to a yield curve spread trend following strategy. Note that these investment strategies are merely examples, and any other investment strategy may be used in child investment model #i.

[0014] An operation model management device 100 according to an embodiment of the present disclosure manages a parent operation model, acquires investment performance information (e.g., daily return data) for each child operation model from a child operation model database (DB) 20 that stores child operation model information for each child operation model, as shown in Figure 2, and determines how to optimally allocate the investment funds of the parent operation model to the child operation model based on the acquired investment performance information, i.e., determines an optimal portfolio for the child operation model. The operation model management device 100 then provides the determined portfolio as investment support information to a user terminal 30, such as a manager of the parent operation model.

[0015] In this way, an investment manager who manages investment funds using a parent investment model can obtain a portfolio suitable for allocating investment funds to each child investment model as investment support information from the investment model management device 100, enabling the investment funds to be managed through optimal fund allocation.

[0016] Here, the operation model management device 100 is realized by a computing device such as a server or a personal computer, and may have, for example, a hardware configuration as shown in Fig. 3. That is, the operation model management device 100 has a storage device 101, a processor 102, an interface device 103, and a communication device 104, which are interconnected via a bus B.

[0017] The programs or instructions that realize the various functions and processes described below in the operational model management device 100 may be downloaded from any external device via a network, or may be provided from a removable storage medium such as a CD-ROM (Compact Disk-Read Only Memory) or flash memory.

[0018] Storage device 101 may be implemented by random access memory, flash memory, a hard disk drive, or the like, and stores installed programs or instructions as well as files, data, etc. used in executing the programs or instructions. Storage device 101 may also include a non-transitory storage medium.

[0019] The processor 102 may be realized by one or more CPUs (Central Processing Units), GPUs (Graphics Processing Units), processing circuitry, etc., which may be composed of one or more processor cores, and performs various functions and processes of the operation model management device 100 described below in accordance with programs, instructions, data such as parameters required to execute the programs or instructions, etc. stored in the memory device 101.

[0020] The interface device 103 realizes an interface between the database 20 and the user terminal 30 and the operation model management device 100. For example, a user operates a keyboard, mouse, etc. on a GUI (Graphical User Interface) displayed on the display or touch panel of the user terminal 30 to send and receive various information, data, instructions, etc. to and from the operation model management device 100 via the interface device 103.

[0021] The communication device 104 is realized by various communication circuits that execute communication processes with external devices, the Internet, a communication network such as a LAN (Local Area Network), and the like.

[0022] However, the above-described hardware configuration is merely an example, and the operation model management device 100 according to the present disclosure may be realized by any other appropriate hardware configuration.

[0023] [Operational Model Management Device] Next, an operation model management device 100 according to an embodiment of the present disclosure will be described. Fig. 4 is a block diagram showing the functional configuration of the operation model management device 100 according to an embodiment of the present disclosure.

[0024] As shown in FIG. 4, the operation model management device 100 includes a child operation model management unit 110, a parent operation model management unit 120, and a portfolio determination unit .

[0025] The child investment model management unit 110 manages multiple child investment models, each of which is managed according to a predetermined investment strategy. Each child investment model manages investment funds according to its own individual investment strategy. The investment strategy of each child investment model is set, for example, according to the investment policy of the child investment model, and may be defined using a mathematical formula, a computer program, or the like. For example, the investment funds of a parent investment model may be allocated to m child investment models #1, #2, . . . , #m.

[0026] The child investment model management unit 110 grasps the investment status of each child investment model based on, for example, the investment performance information of each child investment model extracted from the child investment model DB 20. The investment performance information of the child investment model may be, for example, daily return data. The child investment model management unit 110 may calculate statistics such as the expected return μ and the variance-covariance matrix Σ based on the daily return data r of each child investment model, or may use any data for deriving the expected return μ, the variance-covariance matrix Σ, etc.

[0027] The parent investment model management unit 120 manages the parent investment model that manages investment funds. Here, the parent investment model is managed by an investment manager such as a fund manager, and specifically, the weight w=(w1,...,w) of each child investment model #1,...,#m instructed by the investment manager is m ) and allocate the investment funds of the parent investment model to each child investment model according to the above. However, 0≦w i ≦1 and w1++w m =1.

[0028] The parent investment model management unit 120 appropriately checks the investment status of each child investment model to which investment funds have been allocated, and grasps the investment status of the parent investment model based on the investment status of each child investment model that has been checked. For example, the parent investment model management unit 120 calculates the expected return of the portfolio of the parent investment model based on the expected return of each child investment model.

[0029] The portfolio determination unit 130 determines a portfolio for allocating the investment funds of the parent investment model to multiple child investment models based on the investment performance information of each child investment model. That is, the portfolio determination unit 130 determines the optimal weight w=(w1,...,w) for allocating the investment funds of the parent investment model to each child investment model #1,...,#m. m ) is determined as the portfolio.

[0030] For example, the portfolio determination unit 130

number

[0031] Furthermore, the portfolio determination unit 130

number

[0032] Here, EVaR is defined as follows:

number

[0033] EVaR is known as a coherent risk measure that meets the following properties: Translation invariance

number

number

number

number

[0034] For example, consider the portfolio determination unit 130 allocating 10 billion yen of investment funds from a parent investment model to three child investment models #1 to #3. Here, child investment model #1 may manage the investment funds according to a stock investment strategy with a risk aversion trigger. Specifically, the stock investment strategy with a risk aversion trigger uses two types of risk aversion triggers defined by the value of the VIX index. Each trigger takes two values, risk-on and risk-off, and the strategy determines E-mini S&P 500 futures positions based on their combination.

[0035] The first trigger is risk-on if both of the following two conditions are met, otherwise it is risk-off: Condition 1: The closing price of the VIX index is less than 30. Condition 2: The closing price of the VIX index is below the upper limit of the VIX index Bollinger Band (defined as 14 days, 0.7 standard deviations)

[0036] The second trigger is defined by the following two conditions: Condition 1: The closing price of the VIX index is 24 or higher Condition 2: VIX trend (120-day difference in VIX index closing price) is positive When both Condition 1 and Condition 2 are satisfied, the trigger is risk-off. If it was risk-off the previous day and either Condition 1 or Condition 2 is not satisfied, the trigger is risk-on. The position of the E-mini S&P500 futures is defined as 100% long when both types of triggers are risk-on, 50% long when either one is risk-off, and neutral when both are risk-off.

[0037] Also, the sub-investment model #m may invest the investment funds in accordance with the economic environment judgment type bond investment strategy. Specifically, the economic environment judgment type bond investment strategy is a strategy for determining positions based on a composite indicator obtained by adding the values of each indicator of employment, prices, and economic sentiment created from three economic indicators (the number of non-farm payroll employees in the United States, the US PCE price index, and the US ISM manufacturing sentiment index). First, the employment indicator takes values from 0 to 3. Let X be the average value of the 3-month NFP TCH Index (ACTUAL RELEASE) including the latest month available on date T. When "X < 100", it is 0; when "100 ≤ X < 200", it is 1; when "200 ≤ X < 300", it is 2; when "300 < X", it is 3. Next, the price indicator takes values from 0 to 3. Let X be the average value of the 3-month PCE CMOM Index (ACTUAL RELEASE) including the latest month available on date T. When "X < 0.2", it is 0; when "0.2 ≤ X < 0.3", it is 1; when "0.3 ≤ X < 0.4", it is 2; when "0.4 < X", it is 3. Then, the economic sentiment indicator takes values from 0 to 3. Let X be the average value of the 3-month napmpmi Index (ACTUAL RELEASE) including the latest month available on date T. When "X < 50", it is 0; when "50 ≤ X < 55", it is 1; when "55 ≤ X < 60", it is 2; when "60 < X", it is 3. The composite indicator takes values from 0 to 9 by adding the three indicators. If it exceeds 4, short the 10-year US Treasury futures; if it is 4 or less, go long.

[0038] Furthermore, the sub-management model #n may manage investment funds according to a yield curve spread trend-following strategy. Specifically, the yield curve spread trend-following strategy creates two moving averages, one long and one short, based on the spread between the 10-year and 2-year U.S. Treasury bond yields, and determines positions in 10-year and 2-year U.S. Treasury bond futures based on their golden or dead crossover. First, the difference between the 10-year and 2-year U.S. Treasury bond yields is calculated daily to obtain a daily series of the 2-year / 10-year spread. Then, a 50-day moving average and a 100-day moving average are created. When the 50-day moving average crosses the 100-day moving average from bottom to top, the 10-year U.S. Treasury bond futures are shorted by 100% and the 2-year U.S. Treasury bond futures are long by 335%. Conversely, when the short-term moving average crosses the long-term moving average from top to bottom, the 10-year U.S. Treasury bond futures are longed by 100% and the 2-year U.S. Treasury bond futures are shorted by 335%.

[0039] The child investment model management unit 110 first acquires daily return data r for each child investment model #1 to #3 for a certain period. Then, the child investment model management unit 110 calculates the statistics required for portfolio optimization calculations. For example, the expected return μ for each child investment model #1 to #3 may be the average return of each child investment model #1 to #3 in the past. However, the expected return μ according to the present disclosure is not limited to this, and other expected return values ​​may also be used.

[0040] In addition, the child investment model management unit 110 can calculate the variance-covariance matrix Σ of each child investment model #1 to #3 from the daily return data r of each child investment model #1 to #3. However, the variance-covariance matrix Σ according to the present disclosure is not limited to this, and other variance-covariance matrices Σ may be used.

[0041] Then, the parent investment model management unit 120 sets the risk aversion λ1 and / or λ2. The risk aversion may be specified by the investment manager of the parent investment model, and for example, a value that enables the portfolio to achieve the required return and risk may be specified. For example, using a known backtesting method, the investment manager may select an appropriate risk aversion based on values ​​such as performance, return, standard deviation of return (volatility), and drawdown in past actual investments.

[0042] After the operator determines the parameters required for the optimization calculations of (Equation 1) and (Equation 2), such as μ, Σ, λ1, and λ2, the optimization calculations are performed. Since both the objective function and constraints of (Equation 1) and (Equation 2) are convex functions, these problems are convex programming problems. The optimization calculation algorithm uses the interior point method.

[0043] For example, if an investment manager selects risk aversion levels λ1 = 70 and λ2 = 0.01, and performs optimization calculations using market data from August 2005 to August 2023, the portfolio determination unit 130 will calculate the optimal portfolio as (w1, w2, w3) = (0.178, 0.340, 0.482). In this case, the parent investment model management unit 120 will allocate 1.78 billion yen to child investment model #1, 3.40 billion yen to child investment model #2, and 4.82 billion yen to child investment model #3 out of an investment fund of 10 billion yen.

[0044] The investment model management device 100 described above can solve a portfolio optimization method that takes both volatility and downside risk into account as a convex optimization problem by including EVaR, a convex risk indicator, in the objective function. The third term in (Equation 2) penalizes large portfolio losses. This penalty is intended to reduce the risk of sudden large losses in the portfolio and to penalize particularly large losses, rather than equally penalizing above- and below-average returns, as with risk measured by variance. Because market conditions are known to persist for a certain period of time, periods in which a portfolio suffers large losses are likely to be unevenly distributed over time. By reducing sudden large risks (downside risk), it is possible to reduce cumulative losses in the portfolio, such as drawdowns. For example, comparing (A) when λ1 = 10 and λ2 = 0 with (B) when λ2 = 0.1, case (A) is consistent with the mean-variance method of (Equation 1). When a backtest is performed using data from August 2005 to January 2024, the maximum two-week drawdown occurs at 4.67% in case (a), whereas in case (b) EVAR, the maximum two-week drawdown is reduced to 3.76%.

[0045] [Operational Model Management Processing] Next, an operation model management process according to an embodiment of the present disclosure will be described. The operation model management process is executed by the above-described operation model management device 100, and more specifically, may be realized by one or more processors 102 of the operation model management device 100 executing one or more programs or instructions stored in one or more storage devices 101. Figure 5 is a flowchart showing the operation model management process according to an embodiment of the present disclosure.

[0046] As shown in FIG. 5, in step S101, the operation model management device 100 acquires investment performance information for multiple child operation models. Here, each child operation model is managed according to a predetermined investment strategy. For example, the investment performance information may be daily return data r for each child operation model. Based on the acquired daily return data r, the operation model management device 100 can calculate statistics such as the average return and variance-covariance matrix of each child operation model.

[0047] In step S102, the operation model management device 100 determines a portfolio for allocating the investment funds of the parent operation model to multiple child operation models based on the investment performance information of each child operation model. For example, the operation model management device 100 may determine the portfolio based on the risk aversion of the portfolio against volatility. Alternatively, the operation model management device 100 may determine the portfolio based on the risk aversion of the portfolio against downside risk.

[0048] In step S103, the operation model management device 100 outputs the portfolio as investment support information. Specifically, the operation model management device 100 may provide the determined portfolio to the manager of the parent operation model as investment support information. Upon obtaining the investment support information, the manager may refer to the provided portfolio to determine how to allocate the investment funds of the parent operation model to each child operation model.

[0049] According to the above-described embodiment, an investment manager who manages investment funds using a parent investment model can obtain a portfolio suitable for allocating investment funds to each child investment model as investment support information from the investment model management device 100, and can manage the investment funds with optimal fund allocation.

[0050] Although the examples of the present disclosure have been described in detail above, the present disclosure is not limited to the specific embodiments described above, and various modifications and variations are possible within the scope of the gist of the present disclosure as set forth in the claims. [Explanation of symbols]

[0051] 20 Child Operational Model Database 30 User terminals 100 Operational model management device 110 Child Operation Model Management Department 120 Parent Operational Model Management Department 130 Portfolio Decision Department

Claims

1. a child investment model management unit that manages a plurality of child investment models, each of which is managed according to a predetermined investment strategy; a parent investment model management department that manages the parent investment model that manages investment funds; a portfolio determination unit that determines a portfolio for allocating investment funds of the parent investment model to the plurality of child investment models based on investment performance information of each child investment model; An operation model management device having:

2. The operation model management device according to claim 1 , wherein the parent operation model management unit calculates the expected return of the portfolio based on the expected return of each child operation model.

3. The operation model management device according to claim 1 , wherein the portfolio determination unit determines the portfolio based on a degree of risk aversion with respect to volatility of the portfolio.

4. The operation model management device according to claim 1 , wherein the portfolio determination unit determines the portfolio based on a degree of risk aversion to downside risk of the portfolio.

5. Obtaining investment performance information of a plurality of child investment models, each of which is managed according to a predetermined investment strategy; determining a portfolio for allocating investment funds of the parent investment model to the plurality of child investment models based on investment performance information of each child investment model; outputting the portfolio as investment support information; A computer-implemented operational model management method.

6. Obtaining investment performance information of a plurality of child investment models, each of which is managed according to a predetermined investment strategy; determining a portfolio for allocating investment funds of the parent investment model to the plurality of child investment models based on investment performance information of each child investment model; outputting the portfolio as investment support information; An operational model management program that causes a computer to execute the above.

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