24 results about "Investment analysis" patented technology

The invention relates to the technical field of financial investment analysis and prediction, and discloses an investment market trend intelligent analysis and prediction platform based on machine learning. The data acquisition module acquires multi-dimensional financial time series data, and a space-time correlation feature matrix is generated through the feature processing module and is used for training a depth prediction model based on a hierarchical attention mechanism. The segmentation prediction and anomaly detection module carries out segmentation processing and anomaly detection, and the prediction result correction module corrects an abnormal window prediction result. The hybrid integrated model module fuses multiple models to generate market trend probability distribution, the investment strategy generation module constructs a risk-income balance strategy, and the optimization decision module determines an optimal investment portfolio. The platform can accurately analyze and predict an investment market trend, generates a reasonable investment strategy, assists investors in optimizing decisions, reduces risks, and improves benefits.

The invention relates to an enterprise valuation system and method based on a knowledge graph and deep learning, and the system comprises a data collection module, an enterprise similarity calculation module, a valuation model module, a macroeconomic scoring module, and an enterprise screening module. The data acquisition module acquires data from multiple dimensions such as enterprise basic information, financial statements, macroeconomic data, enterprise stock prices and analyst valuation; the enterprise similarity calculation module is used for calculating the similarity between enterprises by constructing a model based on a knowledge graph and a graph neural network; the valuation model module performs enterprise reasonable market value prediction by combining enterprise financial data, similarity weighted data and analyst dynamic weighted valuation data by using a deep learning technology; the macroeconomic scoring module predicts stock market trend based on the macroeconomic data and a neural network and dynamically adjusts an enterprise estimation value; and the enterprise screening module screens the enterprises with investment value by comparing the current stock prices of the enterprises with the reasonable stock prices. According to the method, multi-dimensional data can be comprehensively integrated, a deep learning technology and a knowledge graph are combined, the scientificity and efficiency of enterprise valuation are improved, and the method is suitable for enterprise value evaluation and investment analysis scenes.

The invention discloses an RAG-based cross-document table generation system and method.The system comprises a cross-document information retrieval and fusion module, an intermediate Json Schema building module and a large language model.The cross-document information retrieval and fusion module preliminarily retrieves corresponding semantic information from a financial document of a to-be-generated table, and the intermediate Json Schema building module stores the semantic information in the financial document; according to a retrieval result and user feedback, a new query statement is dynamically generated by adopting a multi-round query generation mechanism, retrieval is performed again from the financial document, and results of two times of retrieval are sorted and filtered and then integrated to form structured input data; the intermediate Json Schema construction module is used for constructing a Json Schema format, and the intermediate Json Schema construction module is used for constructing a Json Schema format; the large language model generates a customized table. According to the method, multi-source heterogeneous financial data can be efficiently integrated, structured financial tables such as financial statements, risk assessment tables and investment analysis tables can be quickly generated, and the financial data processing efficiency is remarkably improved.

The invention discloses a financial knowledge graph data fusion and retrieval platform system for investment suggestions, and belongs to the technical field of financial data processing. A multi-scale time sequence convolutional network is adopted to dynamically calculate and add investment analysis coefficients for entities and relationships in the knowledge graph, wherein the investment analysis coefficients comprise a relationship conduction coefficient and an Alpha emotion token. The module dynamically calculates an investment analysis coefficient of an entity and a relationship through a multi-scale time sequence convolutional network, and realizes accurate description of market risk and income characteristics. The risk conduction strength between the associated assets can be quantified through the relation conduction coefficient, and dynamic hedging and risk control of the investment portfolio are assisted; the emotion token can capture market emotion fluctuations in real time and generate differentiated signals for a quantification strategy. In combination with efficient interaction of a distributed message queue, the module significantly improves the real-time performance and accuracy of investment decision, and is especially suitable for high-frequency transaction and multi-factor strategy optimization.

The invention belongs to the technical field of energy efficiency improvement and resource allocation, and discloses an energy efficiency improvement and resource allocation optimization method for an integrated energy system, and the method comprises the following specific use steps: S1, energy system evaluation and quantification target setting; s2, making a technology upgrading and multi-source complementation strategy; s3, investment analysis and system deployment implementation; S4, real-time monitoring and dynamic optimization scheduling; s5, an energy efficiency evaluation and continuous improvement mechanism: quantifying index kernel income, and regularly evaluating new technology iteration; s6, digital twinning and user side optimization; and S7, performing case verification and large-scale popularization. According to the invention, an energy efficiency evaluation and continuous improvement mechanism and digital twinning and user side optimization are matched for use; through digital twinning and user side optimization, the characteristics and problems of an energy system are comprehensively known through virtual simulation, and a basis is provided for optimizing a scheduling strategy; and the optimal energy efficiency scheme is automatically searched through reinforcement learning, and the energy utilization efficiency is improved.

A system and method for educational investment analysis assists students in making informed decisions regarding their educational and financial futures. User input is captured detailing educational and financial planning, including intended occupation, potential college choices, and funding plans. The user input is integrated with external data on tuition costs, average salaries, and living expenses. Multiple projected scenarios are generated depicting different educational and financial outcomes based on different choices. Evaluative metrics are calculated for each scenario, including return on investment (ROI), debt repayment period, and earning potential. A comparative analysis of the scenarios is conducted and the results are displayed in a user-friendly visual format enabling clear comparisons and informed choices.

The invention relates to a six-color trend deduction sand table, and belongs to the field of financial investment analysis. Aiming at the problem that a traditional market analysis tool is insufficient in intuition and interactivity, by designing sand tables with different sizes (small and portable, medium-sized and large-sized display) and various clippers (big trend, discipline, theoretical tools and economic data), the market big trend is deduced by making the color change of the clippers correspond to the market data change; electronic versions such as a computer, a webpage and a mobile phone APP enhance interactivity and reasoning logic. The initial fader is white, the fader affects other fader colors according to market data and fader logic understanding, the fader does not have an end point in deduction, the user continuously interacts with the market, and the method is used for assisting the user in mastering the market trend and improving the investment decision-making efficiency and accuracy. The innovation of the invention lies in that market analysis is combined with the sand table, the market trend direction is visually reflected through color change, and a brand new market analysis tool is provided for users.

The invention relates to the technical field of data processing, in particular to an analysis method for engineering project management, which comprises the following steps: collecting budget data, contract settlement data in an investment analysis period and plan data of engineering construction investment, and cleaning the data; dynamically managing the design work amount in the construction drawing design stage; establishing a data articulation relationship among the design budget data, the execution budget data and a contract; determining a project amount completion image and a contract static unit price of each project in the contract; respectively determining a cost deviation, a progress deviation, a cost performance index and a progress performance index to determine deviation evaluation parameters; and according to the deviation evaluation parameters, sorting the items causing the unfavorable deviation and the items causing the favorable deviation from large to small according to the influence absolute values, and carrying out early warning management on the items of which the accumulated deviation accounts for a preset proportion of the total deviation. According to the method, the statistics and analysis of the design budget investment completion condition can be realized under the unified static price level statistics caliber.

The application discloses a financial knowledge graph data fusion and retrieval middle platform system for investment suggestions, and belongs to the technical field of financial data processing. The system comprises an investment analysis enhancement module and a knowledge graph construction module which interact through a distributed message queue. A multi-scale time series convolution network is adopted to dynamically calculate and add investment analysis coefficients, including a relationship transmission coefficient and an Alpha sentiment token, to entities and relationships in the knowledge graph. The module dynamically calculates the investment analysis coefficients of entities and relationships through the multi-scale time series convolution network, thereby accurately depicting market risk and yield characteristics. The relationship transmission coefficient can quantize the risk transmission strength between associated assets, thereby assisting dynamic hedging and risk control of investment portfolios. The sentiment token can capture market emotion fluctuations in real time, thereby generating differentiated signals for quantitative strategies. In combination with the efficient interaction of the distributed message queue, the module significantly improves the real-time performance and accuracy of investment decisions, and is particularly suitable for high-frequency trading and multi-factor strategy optimization.

A system for real estate investment analysis is disclosed, including at least one user computing device in operable connection with a user network. An application server is in operable communication with the user network to host an application system for providing information related to the real estate investment analysis. The application system includes a user interface module for providing access to the application system through the user computing device. A mapping module is in communication with a display module to illustrate a map having a plurality of properties displayed thereon. An analysis module for analyzing property information to determine a Cap Rate percentage, a Cash on Cash percentage, and an ROI percentage each associated with a property.

The invention discloses a power grid investment benefit evaluation method and system based on multi-dimensional data, and belongs to the technical field of power system investment analysis, and the method comprises the steps: constructing a power grid investment benefit multi-source data pool; based on the data pool, constructing a dynamic benefit evaluation matrix containing economic, reliability, collaboration and robustness vectors; calculating a space-time comprehensive benefit index; generating a visual investment benefit optimization strategy map; and executing closed-loop feedback and model self-updating. According to the method, the real-time data flow is introduced, the power grid topological structure is fused, and the dynamic self-adaptive evaluation model is constructed, so that the problems of static state solidification, single dimension and untight association with the actual operation of the power grid in the existing evaluation method are solved, more accurate, comprehensive and dynamic evaluation on the investment benefit of the power grid can be realized, and the evaluation efficiency is improved. Powerful support is provided for scientific decision-making of a power grid.

An artificial intelligence-aided investment analysis system is disclosed for predicting the market impact of regulatory approvals in the biotechnology sector. The system addresses the challenge of accurately assessing market signals by integrating qualitative and quantitative analyses. The system utilizes a combination of qualitative AI models and quantitative AI models to process diverse data inputs, including textual information and financial metrics. The integration module aggregates insights to generate buy / sell signals enhancing investment decision-making. The system employs advanced techniques such as large language models, neural networks, and ensemble learning to provide timely and reliable predictions. This innovative approach offers a comprehensive solution for investors navigating the complexities of biotechnology investments, enabling informed decisions based on a nuanced understanding of scientific developments and market trends.

Embodiments of the present invention provide a novel approach to investment analysis that can automatically accumulate a large amount of relevant company information that can be readily parsed and presented on a dashboard or similar display to support decision making, tracking, and analysis for the purposes of investment in companies and other entities. Some embodiments are tailored to enable firms to easily transform unstructured information into structured (e.g., row / column) data. The transformations are highly accurate and designed to fit seamlessly into an investor's daily workflow (e.g., a private investor, investment firm employee, fund manager or team member, etc.). The resulting structured data can be stored in any suitable format (e.g., Excel, Google Sheet, csv, database, etc.), and can be updated automatically as more information becomes available.

The invention provides a tail building reconstruction project investment risk assessment and income dynamic measurement and calculation data analysis system, and relates to the technical field of real estate investment analysis and data analysis. According to the system, core data such as historical debts, project remains, policy compliance and market supply and demand of the rotten building are integrated through the multi-source data acquisition module, and investment risk quantitative evaluation and income dynamic deduction are realized in combination with the risk evaluation module and the income dynamic measurement and calculation module. The core process comprises data acquisition and cleaning, risk index system construction, risk quantitative rating, dynamic income measurement and calculation, multi-scene simulation optimization and decision report generation. The system solves the problems that a traditional assessment method is incomplete in risk coverage, static in income measurement and calculation and lagged in data, the risk identification accuracy is larger than or equal to 92%, the income measurement and calculation error is smaller than or equal to 5%, dynamic factors such as policy change and building material price fluctuation can be adapted in real time, an accurate decision basis is provided for investors, developers and financial institutions, and high adaptability and practical operability are achieved.

An object of a system according to an embodiment is to enable a user to easily select an optimal investment.SOLUTION: A system includes an investment simulation part, an investment analysis part, and an option presentation part. The investment simulation unit executes a plurality of investment simulations based on information such as an investment target, a risk tolerance, and an investment period of a user. An investment analysis part performs investment analysis on the basis of the simulation result executed by the investment simulation part. The option presentation unit presents a result of the investment analysis performed by the investment analysis unit as an option.SELECTED DRAWING: Figure 1

A system for multi-family property real estate searches is disclosed, including at least one user computing device in operable connection with a user network. An application server is in operable communication with the user network to host an application system for providing a search engine and investment analysis related to residential multi-family properties. The application system includes a user interface module for providing access to the application system through the user computing device wherein the application program calculates a personal liability unique to each unit of each property and educated by rental data for units rented by a third-party.

Provide a system. 【Solution means】 Means for collecting the user's financial data and safely storing it in a data storage device, Means for analyzing the collected financial data and performing a comparative analysis of different financial products, Means for generating a notification of asset management activities based on the user's schedule information, Means for providing customized educational materials based on the user's learning level, Means for displaying a future asset plan in 3D visualization based on the user's investment objectives, Means for anonymizing the collected data and ensuring information security, Means for presenting real-time investment analysis results and assisting in optimizing transactions, Means for enabling the user to virtually experience a lifestyle using the visualized asset plan, A system including the above.

An investment analysis system and method enables the viewing and analysis of data, insights, graphics and metrics of any company. The investment analysis system and method further utilizes machine learning models to predict a probability of acquisition within a predetermined amount of time for each of the companies, based at least on historical acquisition data and company data, thereby assisting in investment decisions.

The invention belongs to the field of nuclear power project investment, and particularly relates to an investment project integrated data management and intelligent review method and system, and the method comprises the steps: 1, carrying out the automatic collection of investment analysis data; 2, classifying investment analysis data; and step 3, performing intelligent review on the investment project library. According to the method, a centralized data management platform is constructed, all related data are integrated, and a unified data view is provided for reviews; an automatic tool is utilized, manual operation is reduced, the automation degree of the review process is improved, and batch review is achieved; the large language model technology is utilized to realize rapid and accurate identification of potential errors and flaws in to-be-examined data, so that the dependence on individual experience of examiners is reduced, and the examination efficiency and the intelligent degree are improved; the method has remarkable positive effects on improving the examination efficiency, accuracy and consistency, and reduces the examination cost and the dependence on human resources at the same time.

The invention relates to the field of intelligent investment analysis, and discloses an intelligent investment preference analysis and customer selection system based on a large model, and the system comprises a user classification module, a behavior analysis module, a strategy optimization module and a customer screening module. Performing investment behavior feature clustering on the investment users to obtain classified investment users; performing real-time data updating on the multi-dimensional interaction data to obtain updated data, performing multi-modal space-time diagram convolution on the updated data to obtain a user behavior space-time tensor, and constructing a three-dimensional user portrait of the investment user; analyzing the investment adaptation degree of the classified investment users and the investment market, constructing an initial investment strategy of the classified investment users, and carrying out reinforcement learning on the initial investment strategy to obtain an optimized investment strategy; and performing user screening on the classified investment users to obtain a target investment user. According to the method, the comprehensiveness of intelligent investment preference analysis and the customer selection accuracy can be improved.

The invention discloses an intelligent equity investment analysis method, device and equipment and a storage medium, and relates to the technical field of equity investing.The method comprises the steps that an equity investment problem input by a target user is obtained, text cleaning is conducted on the equity investment problem, and a standard text is obtained; performing word segmentation processing on the standard text based on a word segmentation model to obtain segmented words, and extracting key information from the segmented words; performing deep analysis on the key information based on an intention classification model to obtain a problem type and a real intention; based on the question type and the real intention, retrieving effective information in an equity investment knowledge base; and semantic understanding and context reasoning are performed on the effective information based on a large language model, and an answer of the equity investment problem is generated. Through the above mode, the demand information can be quickly queried in the mass equity investment information, the service execution efficiency is improved, various user demands can be met by using intelligent interaction, the user satisfaction is improved, and meanwhile, multiple application scenes are supported.

This invention relates to a method for ESG data extraction based on multi-agent collaboration, comprising the following steps: constructing an ESG metadata-driven engine; ESG report document preprocessing and segmentation; context-budget-aware enhanced RAG retrieval; multi-agent collaborative ESG data extraction and verification; and supplementary extraction of multimodal ESG data. The method, apparatus, processor, and computer-readable storage medium of this invention, based on multi-agent collaboration for ESG data extraction, achieve high-precision and automated parsing of massive heterogeneous ESG reports through the above-mentioned intelligent processing throughout the entire process. This effectively reduces the risk of large model illusion, fills the gap in chart data extraction, and significantly improves the standardization and traceability of ESG data, providing reliable technical support for financial regulation and investment analysis. This invention, through the above-mentioned automated and intelligent processing throughout the entire process, significantly improves the efficiency, coverage, and standardization of ESG data analysis.

An object of a system according to an embodiment is to eliminate a lack of information and determination of an appropriate price in real estate transactions.SOLUTION: A system includes a property introduction sentence creation part, a property proposal part, a market price information provision part, an interior proposal part, an investment determination support part, and a contract creation part. A property introduction sentence creation part receives property information as an input and automatically creates a property introduction sentence. The property proposal unit receives the user's preferences and conditions as input, and proposes an optimal property. A market price information providing part analyzes past transaction data and a market trend and provides the proper price of the property. The interior proposal unit proposes an interior based on the floor plan of the property and the preference of the user. The investment analysis support unit evaluates the investment value of the property and supports the investment analysis. The contract document creation unit automatically creates a contract document necessary for a transaction.SELECTED DRAWING: Figure 1