Carbon transaction simulation transaction platform and practical training management scoring system

Abstract

The invention relates to a carbon transaction simulation transaction platform and a practical training management scoring system, and aims to improve strategy selection, profit and loss evaluation, market judgment and risk control capabilities of a user in carbon transaction practical training. The system comprises a user-defined function module, an intelligent guide module, a multi-role user module, a market simulation module, a big data module and a multi-dimensional evaluation module, a user can open or close specific functions, such as market analysis and transaction strategies, according to requirements, the intelligent guide module provides personalized recommendation according to user behavior habits and preferences, and the user experience is improved. The multi-role user module is provided with investor, enterprise and government supervision roles and has different market operation authorities and responsibilities, the market simulation module simulates market dynamics through supply and demand, price fluctuation and policy influence models, and the big data module collects user data and provides personalized practical training suggestions. And the multi-dimensional evaluation module comprehensively evaluates the transaction strategy, the result and the market analysis of the user.

Description

Technical Field

[0001] The invention relates to a carbon trading simulation trading platform and a training management scoring system. Background Art

[0002] In the field of carbon trading simulation trading platform and training management, traditional methods are usually based on preset functional modules and fixed operating procedures. These platforms often lack flexibility and cannot be personalized according to the different needs of users. In addition, traditional platforms often cannot effectively simulate the impact of market changes and government policies, which makes the user's training experience very different from the actual market environment, and it is difficult to provide accurate trading strategy recommendations and evaluations. In general, the problem with existing technologies is that there are still limitations in user personalized experience, big data analysis, and multi-dimensional evaluation, which makes the user experience poor when using the platform for training.

[0003] Therefore, there is a need for a carbon trading simulation trading platform and a training management scoring system that can more flexibly meet the users' training needs and provide a training experience that is closer to the actual market. Summary of the invention

[0004] The purpose of the present invention is to solve the deficiencies of the above existing technologies and provide a carbon trading simulation trading platform and a training management and scoring system. Through user-defined function modules, intelligent guidance modules, multi-role user modules, simulated market modules, big data modules and multi-dimensional evaluation modules, users can obtain better trading strategy selection, trading profit and loss evaluation, market trend judgment and risk control capabilities in training. The following is a specific solution:

[0005] The carbon trading simulation trading platform and training management scoring system include a user-defined function module, which is used to allow users to selectively open or close function modules according to personal needs. The function modules include a market analysis module and a trading strategy module; an intelligent guidance module, which includes a user behavior analysis module and a recommendation algorithm module. The user behavior analysis module is used to automatically recommend related function modules and operation paths through the recommendation algorithm module according to the user's behavior habits and preferences; a multi-role user module, including an investor role, an enterprise role and a government regulatory role. The investor role has the authority to buy and sell carbon quotas, the enterprise role must follow government regulatory policies to control carbon emissions, and the government regulatory role regulates the market by formulating policies and regulatory rules; a simulated market module, the simulated The market module has a supply and demand relationship model, a price fluctuation model and a policy impact model. The supply and demand relationship model is used to simulate the impact of market supply and demand changes on carbon quota prices, the price fluctuation model is used to simulate carbon quota price fluctuations caused by market factors, and the policy impact model is used to simulate the impact of government policies on the market; a big data module is used to collect and analyze user behavior data and provide personalized training suggestions and strategies; a multi-dimensional evaluation module, which includes a trading strategy evaluation module, a trading result evaluation module and a market analysis evaluation module. The trading strategy evaluation module is used to evaluate the user's trading strategy selection, the trading result evaluation module is used to evaluate the user's trading profit and loss, and the market analysis evaluation module is used to evaluate the user's market trend judgment and risk control capabilities.

[0006] Furthermore, the user-defined function module also includes a user interface module for displaying information and responding to operations.

[0007] Furthermore, the operation steps of the intelligent guidance module include: during operation, the user behavior analysis module records the user's operation behavior data in real time, such as click path, transaction frequency and page dwell time; the user behavior analysis module summarizes these data and transmits them to the recommendation algorithm module for subsequent intelligent recommendation; the recommendation algorithm module uses machine learning algorithm to analyze user behavior data, and combines the user's historical transaction records and preferences to generate personalized function modules and operation path recommendations; the recommendation results are notified to the user through the user interface module in the form of pop-up windows or message notifications.

[0008] Furthermore, the authority to buy and sell carbon quotas includes using a user interface module to buy and sell carbon quotas, and formulating a trading plan through a market analysis module and a trading strategy module.

[0009] Furthermore, the carbon emission control in compliance with government regulatory policies includes purchasing carbon emission permits and monitoring carbon emissions through a simulated market module.

[0010] Furthermore, the market regulation by formulating policies and regulatory rules includes monitoring the market operation through a multi-dimensional evaluation module and regulating the market by formulating policies and regulatory rules.

[0011] Furthermore, the impact of the simulated market supply and demand changes on the carbon quota price includes real-time monitoring of user trading behavior and dynamically adjusting the market price of carbon quotas according to the supply and demand situation of buyers and sellers.

[0012] Furthermore, the carbon quota price fluctuations caused by the simulated market factors include uncertainties in the simulated market, such as the impact of policy changes and emergencies on the carbon quota price, which is used to make the price fluctuations closer to the real market environment.

[0013] Furthermore, the simulation of the impact of government policies on the market includes simulating the impact of different policies on the market according to the decision of the government's regulatory role, such as the introduction of carbon emission tax and the allocation policy of carbon trading quotas.

[0014] Beneficial effects: The user-defined function module allows users to selectively turn on or off function modules according to personal needs. The market analysis module and trading strategy module greatly enhance the user experience, making the platform more in line with the actual needs of users and improving the pertinence and effectiveness of practical training;

[0015] The intelligent guidance module can automatically recommend relevant function modules and operation paths according to the user's behavior habits and preferences through the user behavior analysis module and the recommendation algorithm module, which not only reduces the user's learning cost, but also helps users quickly find the training strategy that suits them and improves the training efficiency; the setting of the multi-role user module simulates the three roles of investors, enterprises and government regulators in the actual carbon trading market, allowing users to experience the market behavior and market interaction of different roles on a single platform, which enhances the practicality and fun of the training;

[0016] The supply and demand relationship model, price fluctuation model and policy impact model built into the simulation market module can truly simulate market supply and demand changes, price fluctuations and policy impacts, allowing users to more accurately grasp market dynamics during training and improve their ability to judge market trends and control risks. The introduction of the big data module enables the system to collect and analyze user behavior data and provide users with personalized training suggestions and strategies, which not only helps users discover their own shortcomings, but also optimizes trading strategies in a data-driven manner. The multi-dimensional evaluation module evaluates users from multiple dimensions such as trading strategies, trading results and market analysis to help users fully understand their training results and make better improvements. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1It is a structural diagram of the carbon trading simulation trading platform and the practical training management scoring system. DETAILED DESCRIPTION

[0018] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with embodiments and drawings. The embodiments are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0019] In this embodiment:

[0020] Please see Figure 1 , the carbon trading simulation trading platform and training management scoring system include user-defined function modules, which are used to allow users to selectively open or close function modules according to personal needs. The function modules include market analysis modules and trading strategy modules; intelligent guidance modules, which include user behavior analysis modules and recommendation algorithm modules. The user behavior analysis module is used to automatically recommend related function modules and operation paths through the recommendation algorithm module according to the user's behavior habits and preferences; multi-role user modules, including investor roles, enterprise roles and government regulatory roles. The investor role has the authority to buy and sell carbon quotas, the enterprise role must follow the government regulatory policy to control carbon emissions, and the government regulatory role regulates the market by formulating policies and regulatory rules; simulated market module, simulated The pseudo-market module contains a supply and demand relationship model, a price fluctuation model and a policy impact model. The supply and demand relationship model is used to simulate the impact of changes in market supply and demand on carbon quota prices. The price fluctuation model is used to simulate carbon quota price fluctuations caused by market factors. The policy impact model is used to simulate the impact of government policies on the market; the big data module is used to collect and analyze user behavior data and provide personalized training suggestions and strategies; the multi-dimensional evaluation module includes a trading strategy evaluation module, a trading result evaluation module and a market analysis evaluation module. The trading strategy evaluation module is used to evaluate the user's trading strategy selection, the trading result evaluation module is used to evaluate the user's trading profit and loss situation, and the market analysis evaluation module is used to evaluate the user's market trend judgment and risk control capabilities.

[0021] The user-defined function module also includes a user interface module, which is used to display information and respond to operations; the specific steps are as follows: when the user performs various operations in the system, the user behavior analysis module records the user's operation behavior data in real time, such as click path, transaction frequency, page dwell time, etc.; the user behavior analysis module summarizes this data and transmits it to the recommendation algorithm module for subsequent intelligent recommendations; the recommendation algorithm module uses machine learning algorithms to analyze user behavior data, and combines user historical transaction records and preferences to generate personalized function modules and operation path recommendations; the recommendation results are presented to users through the user interface module in the form of pop-ups, message notifications, etc., to guide users to discover and use functions or strategies that may be overlooked in the system.

[0022] The authority to buy and sell carbon quotas includes using the user interface module to buy and sell carbon quotas, and formulating trading plans through the market analysis module and the trading strategy module; complying with government regulatory policies to control carbon emissions, including managing carbon emissions through the simulation market module, including the purchase of emission permits and the monitoring of carbon emissions; regulating the market through the formulation of policies and regulatory rules, including monitoring market operations through a multi-dimensional evaluation module, and regulating the market through the formulation of policies and regulatory rules.

[0023] Simulating the impact of changes in market supply and demand on carbon quota prices includes real-time monitoring of user trading behavior and dynamically adjusting the market price of carbon quotas based on the supply and demand of buyers and sellers; simulating carbon quota price fluctuations caused by market factors includes simulating uncertainties in the market, such as the impact of policy changes and emergencies on carbon quota prices, to make price fluctuations closer to the real market environment; simulating the impact of government policies on the market includes simulating the impact of different policies on the market based on decisions made by the government's regulatory role, such as the introduction of a carbon emission tax and the allocation policy of carbon trading quotas.

[0024] The big data module provides users with more accurate services by collecting and analyzing user data. The specific implementation methods are as follows: the big data module automatically collects all transaction behavior data of users on the platform, including but not limited to transaction records, module usage records, trading strategy selection, etc.; the system conducts in-depth analysis of these big data through the user behavior analysis module to identify user trading habits, strategy preferences and other characteristics; the system generates personalized training suggestions and strategies for users, and presents them to users through the user interface module to help users improve their trading capabilities.

[0025] The multi-dimensional evaluation module comprehensively evaluates the user's trading behavior and results through a multi-dimensional evaluation system. The specific implementation methods are as follows: the trading strategy evaluation module evaluates the effectiveness of the user's trading strategy based on the user's selection and execution in the trading strategy module; the trading result evaluation module comprehensively considers the user's trading records and calculates the user's trading profit and loss, including total profit, maximum loss, rate of return and other indicators; the market analysis evaluation module evaluates the user's ability to judge market trends and risk control capabilities, provides feedback to users, and helps users improve their analysis methods and trading decisions.

[0026] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. Carbon trading simulation trading platform and training management scoring system, characterized by: It includes a user-defined function module, which is used to allow users to selectively turn on or off function modules according to personal needs. The function modules include a market analysis module and a trading strategy module; an intelligent guidance module, which includes a user behavior analysis module and a recommendation algorithm module. The user behavior analysis module is used to automatically recommend related function modules and operation paths through the recommendation algorithm module according to the user's behavior habits and preferences; A multi-role user module, including an investor role, an enterprise role and a government regulatory role. The investor role has the authority to buy and sell carbon quotas, the enterprise role must follow government regulatory policies to control carbon emissions, and the government regulatory role regulates the market by formulating policies and regulatory rules; a simulation market module, the simulation market module has a supply and demand relationship model, a price fluctuation model and a policy impact model. The supply and demand relationship model is used to simulate the impact of market supply and demand changes on carbon quota prices, the price fluctuation model is used to simulate carbon quota price fluctuations caused by market factors, and the policy impact model is used to simulate the impact of government policies on the market; a big data module is used to collect and analyze user behavior data and provide personalized training suggestions and strategies; a multi-dimensional evaluation module, the multi-dimensional evaluation module includes a trading strategy evaluation module, a trading result evaluation module and a market analysis evaluation module. The trading strategy evaluation module is used to evaluate the user's trading strategy selection, the trading result evaluation module is used to evaluate the user's trading profit and loss, and the market analysis evaluation module is used to evaluate the user's market trend judgment and risk control capabilities.

2. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that ,The user-defined function module also includes a user interface module for ,displaying information and responding to operations.

3. The carbon trading simulation trading platform and training management scoring system according to claim 2 is characterized in that: The operation steps of the intelligent guidance module include: during operation, the user behavior analysis module records the user's operation behavior data in real time, such as click path, transaction frequency and page dwell time; the user behavior analysis module summarizes these data and transmits them to the recommendation algorithm module for subsequent intelligent recommendation; the recommendation algorithm module uses a machine learning algorithm to analyze the user behavior data, and combines the user's historical transaction records and preferences to generate personalized function modules and operation path recommendations; the recommendation results are notified to the user through the user interface module in the form of pop-up windows or message notifications.

4. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that: The authority to buy and sell carbon quotas includes using the user interface module to buy and sell carbon quotas, and formulating a trading plan through the market analysis module and the trading strategy module.

5. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that: The carbon emission control in compliance with government regulatory policies includes purchasing carbon emission permits and monitoring carbon emissions through a simulated market module.

6. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that: The aforementioned regulating the market by formulating policies and regulatory rules includes monitoring the market operation through a multi-dimensional evaluation module and regulating the market by formulating policies and regulatory rules.

7. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that: The simulated impact of changes in market supply and demand on the price of carbon quotas includes real-time monitoring of user trading behavior and dynamically adjusting the market price of carbon quotas based on the supply and demand conditions of buyers and sellers.

8. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that: The carbon quota price fluctuations caused by the simulated market factors include uncertainties in the simulated market, such as the impact of policy changes and emergencies on the carbon quota price, which are used to make the price fluctuations closer to the real market environment.

9. The carbon trading simulation trading platform and training management scoring system according to claim 1 is characterized in that: The simulation of the impact of government policies on the market includes simulating the impact of different policies on the market according to the decision of the government's regulatory role, such as the introduction of carbon emission tax and the allocation policy of carbon trading quotas.

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