Bond investment configuration method, device, medium and system

Abstract

The invention provides a bond investment configuration method, device, medium and system. The method comprises the following steps: acquiring bond screening conditions in a distributed storage unit of the cloud computing technology, and acquiring a current yield and a current duration of each bond based on the bond screening conditions; a preset weight and a preset range are obtained, the preset weight is the weight of the combined bond investment, and the preset range is the range of different bond investment scale proportions; and adjusting the preset weight by adopting the preset weight, the preset range, the current return rate and the current duration to obtain the adjusted preset weight, and performing corresponding combined bond investment based on the adjusted preset weight by adopting the smart contract on the block chain, thereby effectively solving the problem that the investment weight of the existing scheme is adjusted only according to the return rate, so that the investment cost is reduced. Therefore, the investment risk is high, and the stability and profit of the investment portfolio are improved.

Description

Technical Field

[0001] The present application relates to the field of cloud computing technology, and in particular to a bond investment configuration method, a bond investment configuration device, a computer-readable storage medium, and a bond investment configuration system. Background Art

[0002] Investment portfolio strategies help investors optimize their asset allocation based on their investment objectives and risk tolerance. By allocating investment proportions to different asset classes, investors can balance risk and return. Regular adjustments to the portfolio ensure that assets align with investment objectives to achieve long-term wealth growth. Implementing a bond portfolio strategy primarily involves two steps: first, constructing an investment portfolio by creating an investable bond pool based on customizable rules; second, setting a portfolio investment allocation plan by assigning investment weights to the constituent bonds within the bond pool based on their attributes.

[0003] There are many types of bonds in the bond market, each issued by a different entity and exhibiting varying risk profiles and return characteristics. Bonds trading in the secondary market also have varying remaining maturities and yields to maturity, all of which influence the investment proportions of different bonds within a bond portfolio. When establishing an investment portfolio, investors must accurately identify bonds that meet their specific investment strategies and determine the appropriate investment weights for each bond within a portfolio, navigating through vast amounts of bond data.

[0004] That is, the investment weights of existing schemes are adjusted only according to the rate of return, resulting in higher investment risks. Summary of the Invention

[0005] The main purpose of this application is to provide a bond investment configuration method, a bond investment configuration device, a computer-readable storage medium and a bond investment configuration system, so as to at least solve the problem that the investment weights of the existing solutions are adjusted only according to the rate of return, thereby resulting in higher investment risks.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for configuring bond investment is provided, including: obtaining bond screening conditions in a distributed storage unit of cloud computing technology, and obtaining the current yield and current duration of each bond based on the bond screening conditions; obtaining preset weights and preset ranges, the preset weights being the weights of the combined bond investment, and the preset ranges being the range of proportions of different bond investment scales; using the preset weights, the preset ranges, the current yields and the current durations to adjust the preset weights to obtain the adjusted preset weights, and using smart contracts on the blockchain to make corresponding combined bond investments based on the adjusted preset weights.

[0007] Optionally, the preset weight, the preset range, the current yield and the current duration are used to adjust the preset weight to obtain the adjusted preset weight, and the corresponding combination bond investment is made based on the adjusted preset weight using a smart contract on the blockchain, including: constructing a first formula according to the preset weight, the current yield and the current duration, and constructing a second formula according to the first formula and the preset range, and adjusting the preset weight using the preset range to determine the current judgment value according to the second formula; determining the optimal weight according to the current judgment value and the size of the preset range, and using the smart contract on the blockchain to make the corresponding combination bond investment based on the optimal weight.

[0008] Optionally, a first formula is constructed according to the preset weight, the current yield, and the current duration, including:

[0009] The first formula is constructed as:

[0010]

[0011] Among them, Y k is the middle value, w i is the preset weight of the i-th bond, r i is the current yield of the i-th bond, λ is the balance coefficient, d i is the current duration of the i-th bond, and D is the expected duration.

[0012] Optionally, constructing a second formula based on the first formula and the preset range includes:

[0013] The second formula is constructed as:

[0014] f k (t) = max{Y k +f k-1 (tw k )};

[0015] Among them, f k (t) is the current judgment value of the kth bond, f k-1 (tw k ) is the current judgment value of the k-1th bond, w k is the preset weight of the kth bond, or the adjusted preset weight of the kth bond, t is a preset judgment value, and the boundary of the preset judgment value is determined according to the preset range.

[0016] Optionally, obtaining preset weights includes: constructing a bond data weight mapping relationship, wherein the bond data weight mapping relationship is a mapping relationship between weights and bond data, and the bond data includes type, credibility and term; determining the preset weights based on the current bond data and the bond data weight mapping relationship.

[0017] Optionally, the optimal weight is determined based on the current judgment value and the size of the preset range, including: when the current judgment value is within the preset range, determining that the optimal weight is the adjusted preset weight corresponding to the current judgment value, or the preset weight corresponding to the current judgment value; when the current judgment value is not within the preset range, determining that the optimal weight is not the adjusted preset weight corresponding to the current judgment value, or is not the preset weight corresponding to the current judgment value.

[0018] Optionally, adjusting the preset weight within the preset range includes: continuously adjusting the preset weight with a preset step size, so that the adjusted preset weight is within the preset range.

[0019] According to another aspect of the present application, a bond investment configuration device is provided, including: an acquisition unit, used to obtain bond screening conditions in a distributed storage unit of cloud computing technology, and obtain the current yield and current duration of each bond based on the bond screening conditions; a first processing unit, used to obtain a preset weight and a preset range, the preset weight is the weight of the combined bond investment, and the preset range is the range of proportions of different bond investment scales; a second processing unit, used to use the preset weight, the preset range, the current yield and the current duration to adjust the preset weight to obtain the adjusted preset weight, and use the smart contract on the blockchain to make a corresponding combined bond investment based on the adjusted preset weight.

[0020] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0021] According to another aspect of the present application, a bond investment configuration system is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the described methods.

[0022] By applying the technical solution of this application, the distributed storage system can efficiently store and process massive amounts of bond data, including but not limited to bond yields and durations. Leveraging the big data processing capabilities of cloud computing, this data can be analyzed in real time to obtain the current yield and current duration of each bond, providing comprehensive information support for investment strategies. By introducing duration as a key parameter for weight adjustment, combined with preset weights and investment scale ratios, it is possible to optimize portfolio risk management while pursuing maximum yield, ensuring the stability of the portfolio when interest rates change. Smart contracts on the blockchain can automatically execute investment decisions based on the adjusted preset weights. At the same time, smart contracts can solidify the rules for multi-dimensional weight adjustments, ensuring that under all market conditions, investment strategies can be strictly implemented in accordance with preset risk control indicators, reducing the risks caused by human intervention. Leveraging the real-time data processing capabilities of cloud computing, market changes such as yield curve movements and credit rating adjustments can be continuously monitored. By comprehensively considering yield and duration, this application can more comprehensively quantify the risk of an investment portfolio. Duration, as an indicator of the sensitivity of bond prices to interest rate fluctuations, can help investors assess the potential losses of a bond portfolio when interest rates rise. That is, this application can dynamically adjust the weight of the bond portfolio based on yield and duration, realize the quantification, optimization and automated execution of the investment strategy, thereby effectively solving the problem that the investment weight of the existing scheme is adjusted only according to the yield, resulting in higher investment risks, and improving the stability and profitability of the investment portfolio. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings that constitute part of this application are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation on this application. In the drawings:

[0024] Figure 1 A schematic diagram of a flow chart of a bond investment configuration method provided according to an embodiment of the present application is shown;

[0025] Figure 2 A structural block diagram of a bond investment configuration device provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0027] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] As introduced in the background technology, there are many types of bonds in the bond market. Different types of bonds are issued by different issuers and have different risk levels and return characteristics. The remaining terms and yields to maturity of bonds circulating in the secondary market are different. The above factors will affect the investment proportions of different bonds in the bond portfolio. When setting up an investment portfolio, investors need to accurately find bonds that meet different investment strategies from a large amount of bond data and determine the investment weight of each bond. In order to solve the problem that the investment weight of the existing solution is adjusted only according to the yield, thereby resulting in a higher investment risk, the embodiments of the present application provide a bond investment configuration method, a bond investment configuration device, a computer-readable storage medium and a bond investment configuration system.

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0031] In this embodiment, a method for configuring bond investments that runs on a mobile terminal, a computer terminal, or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0032] Figure 1 This is a flow chart of a method for configuring bond investments according to an embodiment of the present application. Figure 1As shown, the method includes the following steps:

[0033] Step S101: obtaining bond screening conditions in a distributed storage unit of cloud computing technology, and obtaining the current yield and current duration of each bond based on the above bond screening conditions;

[0034] Duration is calculated by discounting future cash flows to their present value at the current yield. Each present value is multiplied by the number of years from now until that cash flow occurs, and the sum is divided by the current bond price. In short, duration is the weighted average of the time required for each period of a bond's cash flow to be paid. This value reflects the bond's average maturity and measures the bond's price sensitivity to interest rate fluctuations.

[0035] A specific usage scenario for obtaining bond screening conditions in a distributed storage unit of cloud computing technology and obtaining the current yield and current duration of each bond based on the above bond screening conditions is:

[0036] Bond screening criteria, including credit rating, remaining maturity, and coupon rate, are set within the cloud computing platform's distributed storage units. For example, only bonds with an AAA credit rating, a remaining maturity of 2 to 7 years, and a coupon rate of at least 3% are selected. Leveraging its powerful data processing capabilities, the cloud computing platform captures eligible bond data from multiple global financial data sources in real time and stores it in the distributed storage units. The current yield and duration of each bond are updated in real time, allowing users to instantly monitor the dynamic performance of their portfolios. This data is processed by the cloud computing platform's multi-dimensional weighting algorithm, which comprehensively considers two key metrics: yield and duration. Suppose, at a certain point in time, the system identifies a bond A with an AAA credit rating, a current yield of 4%, and a duration of 3 years; and another bond B with an AAA credit rating, a current yield of 3.5%, and a duration of 2.5 years. Based on yield and duration, the system automatically adjusts the weights of bonds A and B in the portfolio to maximize returns and minimize risk. For example, if the system predicts a short-term rise in interest rates, it will tend to reduce the weight of longer-duration bond A and increase the weight of shorter-duration bond B, thereby mitigating the impact of interest rate fluctuations on the portfolio's value. The portfolio's performance and risk profile are monitored in real time via cloud computing. If the portfolio's duration deviates significantly from expectations or its yield falls below the target level, the cloud platform will automatically adjust the bond weights to ensure the portfolio strategy meets its predetermined objectives.

[0037] The system retrieves bond screening criteria from the distributed storage unit of cloud computing technology and, based on these criteria, obtains the current yield and duration of each bond. The benefits of applying this system to the specific use case are as follows: Cloud computing's distributed processing architecture can rapidly process large amounts of bond data, significantly reducing decision-making time. By analyzing yields and durations in real time, the system can dynamically adjust bond portfolios and effectively manage interest rate risk. Investors can set their own risk preferences and return targets, and the system optimizes their bond portfolio accordingly, providing personalized investment advice. Cloud computing technology provides a high degree of transparency across all decision-making processes and data processing steps, allowing investors to easily track the composition and changes of their portfolios, fostering trust. Furthermore, it can automate trading strategies and monitor market changes in real time, reducing human error and improving the accuracy and efficiency of trade execution.

[0038] Step S102, obtaining a preset weight and a preset range, wherein the preset weight is the weight of the combined bond investment, and the preset range is the range of proportions of different bond investment scales;

[0039] Among them, obtaining the preset weight includes: constructing a bond data weight mapping relationship, the above-mentioned bond data weight mapping relationship is a mapping relationship between weight and bond data, and the above-mentioned bond data includes type, credibility and term; determining the above-mentioned preset weight based on the current bond data and the above-mentioned bond data weight mapping relationship.

[0040] Specifically, by constructing a bond data weight mapping relationship, the investment strategy can be refined to each bond type, credibility (such as credit rating) and maturity. This means that investors can set more personalized weights based on the specific attributes of the bonds, rather than adopting a one-size-fits-all configuration approach. For example, for bonds with high credit ratings, investors may set higher initial weights because such bonds have a lower risk of default; while bonds with longer maturities may be given lower weights to manage interest rate risk. This approach makes the construction of investment portfolios more refined and strategic, and can better match investors' risk preferences and return targets.

[0041] Step S103, using the above-mentioned preset weights, the above-mentioned preset ranges, the above-mentioned current yield and the above-mentioned current duration, adjust the above-mentioned preset weights to obtain the adjusted above-mentioned preset weights, and use the smart contract on the blockchain to make corresponding portfolio bond investments based on the above-mentioned adjusted preset weights.

[0042] Portfolio bonds: This refers to an investment strategy where investors combine multiple different types of bonds to achieve specific investment objectives. Portfolio bonds typically include bonds of different types, and may also include bonds of different issuers, maturities, and credit ratings, thereby reducing the investment risk associated with individual component bonds.

[0043] Weight: refers to the relative proportion allocated to each bond by investors when building a bond portfolio based on their own investment strategy, risk tolerance, return expectations and other factors. This proportion represents the value and importance of each bond in the portfolio.

[0044] In the above steps, the distributed storage system used for computing can efficiently store and process massive amounts of bond data, including but not limited to bond yields and durations. Leveraging the big data processing capabilities of cloud computing, this data can be analyzed in real time to obtain the current yield and duration of each bond, providing comprehensive information support for investment strategies. By introducing duration as a key parameter for weight adjustment, combined with the preset weights and investment scale ratio range, this approach optimizes portfolio risk management while maximizing returns, ensuring the portfolio's stability in the face of interest rate fluctuations. Smart contracts on the blockchain can automatically execute investment decisions based on the adjusted preset weights. Furthermore, smart contracts can solidify the rules for multi-dimensional weight adjustments, ensuring that investment strategies are strictly implemented in accordance with preset risk control indicators under all market conditions, reducing the risks associated with human intervention. Leveraging the real-time data processing capabilities of cloud computing, market changes, such as shifts in the yield curve and credit rating adjustments, can be continuously monitored. Once market conditions change, the investment strategy can rapidly adjust the preset weights to ensure a balanced return and risk profile for the portfolio. Thanks to the transparency and immutability of the blockchain, all adjustment processes and results are visible to all participants, enhancing the transparency and fairness of investment decisions. By comprehensively considering yield and duration, this application can more comprehensively quantify the risk of the investment portfolio. Duration, as an indicator of the sensitivity of bond prices to interest rate changes, can help investors assess the potential losses of the bond portfolio when interest rates rise. Incorporating duration into the weight adjustment rules can limit interest rate risk while pursuing high returns, thereby optimizing the overall risk performance of the investment portfolio. It can be seen that through the distributed storage and processing capabilities of cloud computing technology, and the automatic execution of smart contracts and rule solidification of blockchain technology, this application can dynamically adjust the weight of the bond portfolio based on yield and duration, and realize the quantification, optimization and automated execution of investment strategies, thereby effectively solving the problem that the investment weights of existing solutions are adjusted only according to yield, resulting in higher investment risks, and improving the stability and profitability of the investment portfolio.

[0045] This approach uses dynamic programming to optimize bond portfolios, transforming the multi-objective optimization problem of yield and duration into a single-objective optimization problem by introducing a penalty system. This significantly simplifies the solution. Furthermore, the method for configuring the initial bond weights and the constraints on their selection are clarified, thereby optimizing the efficiency of the dynamic programming calculation process for bond portfolio weights.

[0046] Dynamic programming is a method used in mathematics, computer science, and economics to solve complex problems by breaking them down into relatively simpler sub-problems.

[0047] The process of adjusting the preset weights using the preset weights, the preset range, the current yield, and the current duration in step S103 to obtain adjusted preset weights, and making corresponding bond portfolio investments based on the adjusted preset weights using a smart contract on a blockchain includes:

[0048] Constructing a first formula based on the preset weights, the current yield, and the current duration, and constructing a second formula based on the first formula and the preset range, and adjusting the preset weights using the preset range to determine the current judgment value based on the second formula;

[0049] Specifically, the first formula above is constructed as:

[0050]

[0051] Among them, Y k is the middle value, w i is the preset weight of the i-th bond, r i is the current yield of the i-th bond, λ is the balance coefficient, d i is the current duration of the i-th bond, and D is the expected duration.

[0052] directly points to the total expected return of the portfolio, while The introduction of the deviation between duration and expected value as a risk measure ensures effective control of interest rate risk while maximizing returns. This design helps investors achieve the highest possible returns while taking appropriate risks. The balance coefficient allows investors to adjust based on their risk preferences. For example, risk-averse investors may choose a higher λ, thereby giving duration deviation a greater weight in the first formula. This indicates that they prioritize portfolio risk control and are willing to sacrifice some returns in exchange for more stable duration performance. Conversely, risk-seeking investors may choose a lower λ, indicating a willingness to take greater risk in pursuit of higher returns. By setting an expected duration value, investors can predetermine the portfolio's sensitivity to changes in market interest rates. For example, if market interest rates are expected to rise, investors can set a lower D, aiming to reduce interest rate risk by shortening the portfolio duration. The first formula minimizes duration deviation by adjusting the preset weight of the i-th bond, helping investors to proactively react to market changes and adjust their portfolios, thereby improving their ability to withstand market fluctuations.

[0053] The second formula above is constructed as:

[0054] f k (t) = max{Y k +f k-1 (tw k )};

[0055] Among them, f k (t) is the above current judgment value of the kth bond, f k-1 (tw k ) is the above current judgment value of the k-1th bond, w k is the above-mentioned preset weight of the kth bond, or the above-mentioned preset weight after adjustment of the kth bond, t is the preset judgment value, and the boundary of the above-mentioned preset judgment value is determined according to the above-mentioned preset range.

[0056] Specifically, the current judgment value of the kth bond is determined in a gradient form, so as to facilitate updating the preset weights of the k bonds one by one.

[0057] Based on the above current judgment value and the size of the above preset range, the optimal weight is determined, and the corresponding above combination bond investment is made based on the above optimal weight using a smart contract on the blockchain.

[0058] Specifically, when the above-mentioned current judgment value is within the above-mentioned preset range, the above-mentioned optimal weight is determined to be the adjusted above-mentioned preset weight corresponding to the above-mentioned current judgment value, or the above-mentioned preset weight corresponding to the above-mentioned current judgment value; when the above-mentioned current judgment value is not within the above-mentioned preset range, it is determined that the above-mentioned optimal weight is not the adjusted above-mentioned preset weight corresponding to the above-mentioned current judgment value, or is not the above-mentioned preset weight corresponding to the above-mentioned current judgment value.

[0059] If the current judgment value is within the preset range, the determined optimal weight reflects the investor's pre-defined risk assumptions and market strategy execution. This ensures that investment decisions not only maximize returns but also adhere to the guiding principles of risk management and investment strategy. For example, if the preset range is set to limit the weight of any single bond to no more than 10%, and the optimization model calculates an optimal weight of 8% for a particular bond, this indicates that the weight adjustment meets the risk limit and helps maintain portfolio diversification and stability. If the current judgment value is not within the preset range, it means that market conditions may not be consistent with the investor's initial assumptions, or that the portfolio performance has deviated from the target range. In this case, not using the preset weight corresponding to the current judgment value can prompt investors to re-evaluate market conditions and adjust their strategies to adapt to the new market conditions. For example, if the calculated optimal weight for a particular bond exceeds the preset upper limit due to market changes, this may indicate that investors need to reconsider the weight of that bond to avoid excessive exposure to the risk of a single bond. A key goal of portfolio management is to avoid excessive asset concentration, which increases the impact of a single risk point. At the same time, excessive diversification can also reduce the overall return of the portfolio. By comparing the preset range with the current judgment, bond weights can be dynamically adjusted to ensure neither excessive concentration in a few high-yield bonds nor excessive diversification, which could impact the portfolio's return potential. Combining the preset range with the current judgment allows investment decisions to be based on scientific calculations, incorporating actual market conditions and the investor's strategic principles. This mechanism helps avoid decisions based on intuition or single market signals, enhancing the scientific and rational nature of portfolio management.

[0060] Smart contracts can automatically execute optimally weighted bond investment transactions without human intervention. Once the optimal weights are determined, the smart contract immediately searches for suitable counterparties within the blockchain network based on these weight parameters and executes the buy and sell transactions, significantly improving the efficiency of portfolio adjustments. Furthermore, all transactions are conducted on the blockchain, ensuring transparency and enhancing investor trust in the investment process. Smart contracts can respond to market changes and updates to optimal weights in real time, ensuring that portfolios can be rapidly adjusted to the most advantageous configuration. This real-time nature is particularly important in the bond market, where even small changes in interest rates can significantly impact bond prices and the duration of a portfolio. The automated execution of smart contracts reduces human error and improves transaction accuracy.

[0061] In one embodiment of the present application, adjusting the preset weight using the preset range includes: continuously adjusting the preset weight with a preset step size, and the adjusted preset weight is within the preset range.

[0062] Specifically, the second formula is applied to each adjusted preset weight within a preset range to determine whether the adjusted preset weight is optimal. By fine-tuning the weight distribution within a preset step size, investors can gradually explore and optimize the weight distribution within their bond portfolio to find the optimal balance between risk and return. This fine-tuning approach avoids large jumps in weights and reduces the market impact or transaction costs that could result from excessive adjustments. Furthermore, adjustments within a limited range ensure that weight changes do not exceed investors' risk tolerance and strategic framework.

[0063] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the bond investment configuration method of the present application will be described in detail below with reference to specific embodiments.

[0064] This embodiment relates to a specific bond investment configuration method, including:

[0065] Enter the bond screening condition (X). First, obtain the basic information of the bond from the outside, including the bond code, bond abbreviation, bond full name, face rate, issue price, issuer, issuer rating, maturity, etc. Then enter the bond screening condition X, such as the issuer rating is AAA or BBB, the maturity is less than 5 years and greater than 1 year, etc., recorded as [X1,X2,…,X n According to the bond screening condition X, the bond combination B[B1,B2,…,B n ].

[0066] Set the initial weight strategy (Y), according to the bond portfolio B[B1,B2,…,B n ], set the bond weight allocation scheme according to the three dimensions of subject, bond type and remaining term. In the subject dimension, bonds are classified according to the subject rating and the weight of each category is determined. For example, the investment scale is allocated to the subject with an AAA rating at a weight of 30%, and the remaining 70% weight is evenly distributed among all other rated subjects. The rating weight of each subject is recorded as Y1[Y 10 ,Y 11 ,…,Y 1m ]; The variety dimension is recorded as Y2[Y 20 ,Y 21 ,…,Y 2n ]; The term dimension is classified into long-term, short-term and medium-term to determine the investment proportion of bonds with different terms Y3[Y 30 ,Y 31 ,Y 32 ]. Under the above three dimensions, each bond in each category determines its investment proportion in the corresponding dimension according to equal weight or market value weight. Finally, the result of normalizing the multiplication result of the weight obtained in each dimension within the overall portfolio is used as the initial weight allocation result of each bond, which is recorded as WI [W I1 ,W I2 ,…,W In For example, the weight score of bond B1 in the above example is M1=Y 10 *Y 21 *Y 32 (Assuming its rating type is AAA, marked with 0; its type is target support agency bond, marked with 1; and its maturity is short-term, marked with 2), the final initial weight WI1 of the bond is:

[0067]

[0068] Set limiting conditions (S). On the basis of determining the initial investment scale, it is also necessary to set limiting conditions for the investment scale ratio of different bonds. For example, the investment scale should not exceed 3% of its market scale to ensure the feasibility of the investment strategy and the impact on market fluctuations, and the investment scale ratio of a single bond should not exceed 10% to control the portfolio investment concentration, etc., denoted as S[S1, S2, ... S n ].

[0069] Use dynamic programming optimization algorithm to find the optimal strategy for the investment ratio of different bonds in the bond portfolio: Assume that the data is obtained: bond portfolio B[B1,B2,…,B n The yield to maturity of a single bond Bi in the bond valuation is recorded as r i , duration is denoted as d i .

[0070] The pros and cons of a bond portfolio weighting strategy involve two evaluation dimensions: return and risk. Return can be calculated using the portfolio yield indicator, while portfolio duration, as an indicator of the sensitivity of its price fluctuations to changes in market interest rates, can be used to measure the portfolio's investment risk. Generally speaking, while longer-duration bond portfolios may achieve higher returns when interest rates fall, they also face greater risk of rising interest rates. Therefore, it is necessary to find a balance between duration and return to achieve the optimal configuration of portfolio risk and return. The calculation of the portfolio's return and duration are both related to the bond weighting. The weighting scheme w[w1,w2,…,w n The return rate of the combination is The duration of the combination is Taking into account the portfolio yield and duration performance, the objective function is determined:

[0071]

[0072] That is, the asset portfolio return is maximized through weight configuration rules, and the deviation between the portfolio duration and the expected value is minimized as much as possible. Among them, λ is the balance parameter and D is the expected value of duration, which is set by the user according to his investment goals, risk tolerance, etc.

[0073] The weight allocation process of the above investment portfolio is solved according to the dynamic programming problem, that is, for each bond B in the portfolio i The weight distribution of can be regarded as a decision-making process in n stages, w i is the weight ratio of the i-th bond, which is also the decision variable of this stage. The weight scale allocated from the 1st bond to the i-th bond is recorded as T i , as the state variable of the i-th stage, then T n =100%, and the state transition rule is:

[0074] w i =T i -T i-1 ;

[0075] When the state variables are given, the bond weight w i The values within the restricted range are the decision set of stage i.

[0076] It can be seen that the total weight of the portfolio has been allocated to 100%, which is the terminal state of the weight strategy allocation. We can use the recursion of the known terminal state and assume that the optimal value function f k (t) is the maximum Y of the investment weight ratio that does not exceed t until the kth stage. The main constraint is the bond weight limitation condition S[S1,S2,……S q ], that is, the problem is the maximum value of the following situations:

[0077]

[0078] w i Satisfy S.

[0079] The optimal function sequence satisfies the following recursive equation. For the k-stage portfolio, the optimal performance is Y k , according to the state transition rule, the remaining tw k Can be used for B1,...,B k-1 These investment proportions must be optimal over the first k-1 phases, and the kth phase must be optimal for the entire portfolio. The initial state f0(t) indicates that even after all bonds in the portfolio have certain investment proportions, there is still a certain amount of surplus, which can be considered as the remaining amount for investment in practice.

[0080] f k (t) = max{Y k +f k-1 (tw k )};

[0081] f0(t)=t.

[0082] When solving, the range of t values can be decomposed. The boundary of t values is determined by the limiting condition S of the bond weight configuration. Assuming that the weight value interval obtained by taking the intersection of each condition is [0, Q], the step size of the interval decomposition is recorded as Δq, then the range of t values is 0, Δq, 2Δq, ..., nΔq = Q. When calculating, starting from f0(t) = t, using the recursive equation, calculate the value of f1(t) at all discrete points, and record the corresponding optimal decision w1(t). Similarly, calculate f n (t) and w n (t), and finally substitute back to get the optimal solution.

[0083] To optimize the solution process, the bonds in the portfolio can be sorted according to their yield to maturity, with the highest yield bond (assuming it is bond B) m ) is used as the starting point of the decision state, and the initial bond weight ratio W is prioritized. Im The maximum value of the portfolio yield is obtained by calculating the values within the maximum boundary Q interval, and the weights are adjusted within the constraints to reduce the deviation between the portfolio duration and the expected value. The performance of the combination on the objective function is used to optimize the value selection method of the decision variables and reduce unnecessary solution calculations.

[0084] In addition to the yield index, this application also introduces the duration index as one of the criteria for measuring the quality of an investment portfolio. When conducting specific evaluations, the calculation is not based on the assumed fixed asset investment risk coefficient. Instead, the portfolio risk level is set based on the degree of deviation between the portfolio weighted duration and the investor's expected duration. The dynamic programming algorithm is applied to the calculation of the bond portfolio investment ratio. By setting the balance coefficient and the expected duration value, the multi-objective function of maximizing the bond portfolio investment yield and minimizing the duration is converted into a single-objective function optimization problem. Combined with a series of limiting conditions, the optimal solution for the investment ratio of the bond portfolio in terms of yield and expected risk performance can be obtained. Based on real investment research scenarios, a method for initially setting the investment ratio of a bond portfolio is provided, namely, selecting three dimensional attributes: bond issuer rating, bond type, and remaining maturity classification, and allocating weights to different classifications under each dimension. The investment ratio of each component bond in the portfolio is obtained according to equal weight or market value weight in different dimensions. Finally, the weight ratio obtained in each dimension multiplied by the proportion in the portfolio is regarded as its initial investment weight. This method meets the needs of most scenarios. Furthermore, based on the initial setting of the investment ratio and the constraints on liquidity and concentration in real scenarios, the solution process of the dynamic programming algorithm can be optimized on the basis of simulating actual investment transactions.

[0085] The dynamic programming algorithm is used to replace the traditional linear programming algorithm, avoiding the limitation that linear programming can only seek the maximum and minimum values of the objective function through simple linear constraints. This application introduces duration into the measurement criteria for evaluating the quality of bond portfolios, and uses the balance coefficient and expected value to transform the multi-objective function of yield and duration performance into a single-objective function optimization problem. Combined with the actual application requirements of setting the portfolio weight ratio, the dynamic programming algorithm can set complex constraints. By defining states, state transition equations and boundary conditions, the bond portfolio investment allocation problem is decomposed into a series of sub-problems, and finally the optimal investment ratio allocation plan that comprehensively considers the bond portfolio yield and duration performance is obtained.

[0086] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0087] The embodiments of the present application also provide a configuration device for bond investment. It should be noted that the configuration device for bond investment in the embodiments of the present application can be used to execute the configuration method for bond investment provided in the embodiments of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the details that have been described will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0088] The following introduces the bond investment configuration device provided in the embodiment of the present application.

[0089] Figure 2 This is a structural block diagram of a bond investment configuration device provided according to an embodiment of the present application. Figure 2 As shown, the device includes:

[0090] An acquisition unit 21 is configured to acquire bond screening conditions in a distributed storage unit of cloud computing technology, and acquire the current yield and current duration of each bond based on the bond screening conditions;

[0091] The first processing unit 22 is used to obtain a preset weight and a preset range, wherein the preset weight is the weight of the combined bond investment, and the preset range is the range of proportions of different bond investment scales;

[0092] The second processing unit 23 is used to adjust the above-mentioned preset weights using the above-mentioned preset weights, the above-mentioned preset ranges, the above-mentioned current yield and the above-mentioned current duration to obtain the adjusted above-mentioned preset weights, and use the smart contract on the blockchain to make corresponding portfolio bond investments based on the above-mentioned adjusted preset weights.

[0093] The above-mentioned device can dynamically adjust the weight of the bond portfolio based on yield and duration, realize the quantification, optimization and automatic execution of investment strategies, and effectively solve the problem that the investment weight of the existing scheme is adjusted only according to the yield, resulting in higher investment risks, thereby improving the stability and profitability of the investment portfolio.

[0094] In one embodiment of the present application, the second processing unit includes a first processing module and a second processing module. The first processing module is used to construct a first formula based on the above-mentioned preset weights, the above-mentioned current yield and the above-mentioned current duration, and to construct a second formula based on the above-mentioned first formula and the above-mentioned preset range, and to adjust the above-mentioned preset weights using the above-mentioned preset range to determine the current judgment value according to the above-mentioned second formula; the second processing module is used to determine the optimal weight based on the above-mentioned current judgment value and the size of the above-mentioned preset range, and to use the smart contract on the blockchain to make the corresponding above-mentioned combination bond investment based on the above-mentioned optimal weight.

[0095] Smart contracts can automatically execute optimally weighted bond investment transactions without human intervention. Once the optimal weights are determined, the smart contract immediately searches for suitable counterparties within the blockchain network based on these weight parameters and executes the buy and sell transactions, significantly improving the efficiency of portfolio adjustments. Furthermore, all transactions are conducted on the blockchain, ensuring transparency and enhancing investor trust in the investment process. Smart contracts can respond to market changes and updates to optimal weights in real time, ensuring that portfolios can be rapidly adjusted to the most advantageous configuration. This real-time nature is particularly important in the bond market, where even small changes in interest rates can significantly impact bond prices and the duration of a portfolio. The automated execution of smart contracts reduces human error and improves transaction accuracy.

[0096] In one embodiment of the present application, the first processing module includes a first construction module, which is used to construct the above-mentioned first formula:

[0097]

[0098] Among them, Y k is the middle value, w i is the preset weight of the i-th bond, r i is the current yield of the i-th bond, λ is the balance coefficient, d i is the current duration of the i-th bond, and D is the expected duration.

[0099] directly points to the total expected return of the portfolio, while The introduction of the deviation between duration and expected value as a risk measure ensures that interest rate risk is effectively controlled while maximizing returns. This design helps investors achieve the highest possible returns while taking appropriate risks. The balance coefficient allows investors to adjust based on their risk preferences. For example, risk-averse investors may choose a higher λ, thereby giving duration deviation a greater weight in the formula. This indicates that they prioritize portfolio risk control and are willing to sacrifice some returns in exchange for more stable duration performance. Conversely, risk-seeking investors may choose a lower λ, indicating a willingness to take greater risk in pursuit of higher returns. By setting an expected duration value, investors can predetermine the portfolio's sensitivity to changes in market interest rates. For example, if market interest rates are expected to rise, investors can set a lower D, aiming to reduce interest rate risk by shortening the portfolio duration. The first formula minimizes duration deviation by adjusting the preset weight of the i-th bond, helping investors to proactively react to market changes and adjust their portfolios, thereby improving their ability to withstand market fluctuations.

[0100] In one embodiment of the present application, the first processing module includes a second construction module for constructing the second formula:

[0101] f k (t) = max{Y k +f k-1 (tw k )};

[0102] Among them, f k (t) is the above current judgment value of the kth bond, f k-1 (tw k ) is the above current judgment value of the k-1th bond, w k is the above-mentioned preset weight of the kth bond, or the above-mentioned preset weight after adjustment of the kth bond, t is the preset judgment value, and the boundary of the above-mentioned preset judgment value is determined according to the above-mentioned preset range.

[0103] In one embodiment of the present application, the first processing unit includes a third processing module and a fourth processing module. The third processing module is used to construct a bond data weight mapping relationship. The above-mentioned bond data weight mapping relationship is a mapping relationship between weight and bond data. The above-mentioned bond data includes type, credibility and term; the fourth processing module is used to determine the above-mentioned preset weight based on the current bond data and the above-mentioned bond data weight mapping relationship.

[0104] By constructing a bond data weight mapping relationship, investment strategies can be refined to each bond type, credibility (such as credit rating) and maturity. This means that investors can set more personalized weights based on the specific attributes of the bonds, rather than adopting a one-size-fits-all configuration approach. For example, for bonds with high credit ratings, investors may set higher initial weights because such bonds have a lower risk of default; while bonds with longer maturities may be given lower weights to manage interest rate risk. This approach makes the construction of investment portfolios more refined and strategic, and can better match investors' risk preferences and return targets.

[0105] In one embodiment of the present application, the second processing module includes a first determination module and a second determination module. The first determination module is used to determine that the optimal weight is the adjusted preset weight corresponding to the current judgment value, or the preset weight corresponding to the current judgment value, when the current judgment value is within the preset range; the second determination module is used to determine that the optimal weight is not the adjusted preset weight corresponding to the current judgment value, or is not the preset weight corresponding to the current judgment value, when the current judgment value is not within the preset range.

[0106] If the current judgment value is within the preset range, the determined optimal weight reflects the investor's pre-defined risk assumptions and market strategy execution. This ensures that investment decisions not only maximize returns but also adhere to the guiding principles of risk management and investment strategy. For example, if the preset range is set to limit the weight of any single bond to no more than 10%, and the optimization model calculates an optimal weight of 8% for a particular bond, this indicates that the weight adjustment meets the risk limit and helps maintain portfolio diversification and stability. If the current judgment value is not within the preset range, it means that market conditions may not be consistent with the investor's initial assumptions, or that the portfolio performance has deviated from the target range. In this case, not using the preset weight corresponding to the current judgment value can prompt investors to re-evaluate market conditions and adjust their strategies to adapt to the new market conditions. For example, if the calculated optimal weight for a particular bond exceeds the preset upper limit due to market changes, this may indicate that investors need to reconsider the weight of that bond to avoid excessive exposure to the risk of a single bond. A key goal of portfolio management is to avoid excessive asset concentration, which increases the impact of a single risk point. At the same time, excessive diversification can also reduce the overall return of the portfolio. By comparing the preset range with the current judgment, bond weights can be dynamically adjusted to ensure neither excessive concentration in a few high-yield bonds nor excessive diversification, which could impact the portfolio's return potential. Combining the preset range with the current judgment allows investment decisions to be based on scientific calculations, incorporating actual market conditions and the investor's strategic principles. This mechanism helps avoid decisions based on intuition or single market signals, enhancing the scientific and rational nature of portfolio management.

[0107] In one embodiment of the present application, the first processing module includes an adjustment module for continuously adjusting the preset weight with a preset step size, and the adjusted preset weight is within the preset range.

[0108] The second formula is then applied to each adjusted weight within the preset range to determine whether the adjusted weight is optimal. By fine-tuning the weights in preset steps, investors can gradually explore and optimize the weight distribution within their bond portfolio to find the optimal balance between risk and return. This fine-tuning approach avoids large jumps in weights, minimizing the market impact or transaction costs that could result from over-adjustments. Furthermore, adjustments within a limited range ensure that weight changes do not exceed investors' risk tolerance and strategic framework.

[0109] The bond investment configuration device includes a processor and memory. The acquisition unit, first processing unit, and second processing unit are stored as program units in the memory. The processor executes the program units stored in the memory to implement the corresponding functions. The modules are all located in the same processor; alternatively, the modules can be located in different processors in any combination.

[0110] The processor contains a core, which retrieves the corresponding program unit from memory. One or more cores can be configured, and adjusting the core parameters can address the problem of existing solutions where investment weights are adjusted solely based on rate of return, resulting in higher investment risk.

[0111] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0112] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is run, the device where the computer-readable storage medium is located is controlled to execute the bond investment configuration method.

[0113] An embodiment of the present invention provides a processor, which is used to run a program, wherein the program executes the bond investment configuration method when running.

[0114] An embodiment of the present invention provides a device comprising a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements at least the following steps: obtaining bond screening conditions from a distributed storage unit of cloud computing technology, and obtaining the current yield and current duration of each bond based on the bond screening conditions; obtaining preset weights and preset ranges, wherein the preset weights are weights for combined bond investments, and the preset ranges are ranges of investment scale ratios for different bonds; adjusting the preset weights using the preset weights, the preset ranges, the current yield, and the current duration to obtain adjusted preset weights, and performing corresponding combined bond investments based on the adjusted preset weights using a smart contract on a blockchain. The device herein may be a server, a PC, a PAD, a mobile phone, or the like.

[0115] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that is initialized with at least the following method steps: obtaining bond screening conditions in a distributed storage unit of cloud computing technology, and obtaining the current yield and current duration of each bond based on the above bond screening conditions; obtaining preset weights and preset ranges, the above preset weights are the weights of the combined bond investment, and the above preset ranges are the ranges of the proportions of different bond investment scales; using the above preset weights, the above preset ranges, the above current yields and the above current durations, adjusting the above preset weights to obtain the adjusted above preset weights, and using the smart contract on the blockchain to make corresponding combined bond investments based on the above adjusted above preset weights.

[0116] The present application also provides a bond investment configuration system, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include a method for executing any of the above methods. The system can dynamically adjust the weight of the bond portfolio based on yield and duration, and realize the quantification, optimization and automated execution of the investment strategy, thereby effectively solving the problem that the investment weight of the existing scheme is adjusted only according to the yield, resulting in higher investment risk, and improving the stability and profitability of the investment portfolio.

[0117] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing device, can be centralized on a single computing device, or can be distributed across a network of multiple computing devices. They can be implemented using program code executable by the computing device, and thus, can be stored in a storage device and executed by the computing device. In some cases, the steps shown or described herein can be performed in a different order than that shown, or can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0118] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0119] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0122] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0123] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0124] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0125] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0126] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0127] 1) The bond investment configuration method of the present application can dynamically adjust the weight of the bond portfolio based on yield and duration, realize the quantification, optimization and automated execution of the investment strategy, thereby effectively solving the problem that the investment weight of the existing scheme is adjusted only according to the yield, resulting in higher investment risk, and improving the stability and profitability of the investment portfolio.

[0128] 2) The bond investment configuration device of the present application can dynamically adjust the weight of the bond portfolio based on yield and duration, realize the quantification, optimization and automated execution of investment strategies, thereby effectively solving the problem that the investment weights of existing solutions are adjusted only according to yield, resulting in higher investment risks, and improving the stability and profitability of the investment portfolio.

[0129] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A bond investment allocation method, characterized in that: include: Obtaining bond screening conditions in a distributed storage unit of cloud computing technology, and obtaining a current yield and a current duration of each bond based on the bond screening conditions; Obtaining a preset weight and a preset range, wherein the preset weight is the weight of the combined bond investment, and the preset range is the range of proportions of different bond investment scales; The preset weight, the preset range, the current yield and the current duration are used to adjust the preset weight to obtain the adjusted preset weight, and a smart contract on the blockchain is used to make a corresponding combined bond investment based on the adjusted preset weight.

2. The method according to claim 1, characterized in that The preset weight, the preset range, the current yield, and the current duration are used to adjust the preset weight to obtain the adjusted preset weight, and a smart contract on a blockchain is used to make a corresponding portfolio bond investment based on the adjusted preset weight, including: Constructing a first formula based on the preset weights, the current yield, and the current duration, and constructing a second formula based on the first formula and the preset range, and adjusting the preset weights using the preset range to determine a current judgment value based on the second formula; The optimal weight is determined according to the current judgment value and the size of the preset range, and the corresponding combined bond investment is made based on the optimal weight using a smart contract on the blockchain.

3. The method according to claim 2, characterized in that A first formula is constructed based on the preset weight, the current yield, and the current duration, including: The first formula is constructed as: Among them, Y k is the middle value, w i is the preset weight of the i-th bond, r i is the current yield of the i-th bond, λ is the balance coefficient, d i is the current duration of the i-th bond, and D is the expected duration.

4. The method according to claim 3, characterized in that According to the first formula and the preset range, a second formula is constructed, including: The second formula is constructed as: f k (t)=max{Y k +f k-1 (t-w k )}; Among them, f k (t) is the current judgment value of the kth bond, f k-1 (tw k ) is the current judgment value of the k-1th bond, w k is the preset weight of the kth bond, or the adjusted preset weight of the kth bond, t is a preset judgment value, and the boundary of the preset judgment value is determined according to the preset range.

5. The method according to claim 1, wherein Get preset weights, including: Constructing a bond data weight mapping relationship, wherein the bond data weight mapping relationship is a mapping relationship between weight and bond data, wherein the bond data includes type, credibility, and term; The preset weight is determined according to the mapping relationship between the current bond data and the bond data weight.

6. The method according to claim 2, characterized in that Determining the optimal weight according to the current judgment value and the size of the preset range includes: When the current judgment value is within the preset range, determining the optimal weight to be the adjusted preset weight corresponding to the current judgment value, or the preset weight corresponding to the current judgment value; When the current judgment value is not within the preset range, it is determined that the optimal weight is not the adjusted preset weight corresponding to the current judgment value, or is not the preset weight corresponding to the current judgment value.

7. The method according to claim 2, characterized in that Adjusting the preset weight using the preset range includes: The preset weight is continuously adjusted with a preset step size, and the adjusted preset weight is within the preset range.

8. A bond investment configuration device, characterized in that: include: an acquiring unit, configured to acquire bond screening conditions in a distributed storage unit of cloud computing technology, and acquire a current yield and a current duration of each bond based on the bond screening conditions; A first processing unit is configured to obtain a preset weight and a preset range, wherein the preset weight is the weight of the combined bond investment, and the preset range is the range of proportions of different bond investment scales; The second processing unit is used to adjust the preset weight by adopting the preset weight, the preset range, the current yield and the current duration to obtain the adjusted preset weight, and use the smart contract on the blockchain to make corresponding combined bond investments based on the adjusted preset weight.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A bond investment configuration system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method of any one of claims 1 to 7.

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