文件列表:

check.py
enitymadadadad.py
final matc
gui.py
hist_menu - Copy - Copy.py
hist_menu - Copy.py
hist_menu.py
ii.py
matching.py

**Problem Statement** Given the real time unstructured data of the relevant news article and structured stock data, Investors find it difficult to track and analyze the latest news and data manually in real time and to integrate it with other sources of information to make informed investment decisions _What?_ The objective of this project is to develop a system that integrates real-time news data with structured stock data to extract insights that can be used to make financial stock decisions. The system will be used by investors to identify trading opportunities, manage risk, and make informed investment decisions. **Use Cases:** Identifying trading opportunities: The system can be used to track the impact of news events on stock prices and identify trading opportunities that may not be obvious from the fundamental data or market data alone. Managing risk: The system can be used to monitor social media sentiment and get a sense of the overall sentiment towards a particular stock or market. This information can be used to manage risk and avoid making investment decisions that are likely to be unpopular with investors. Making informed investment decisions: By integrating different types of data, the system can provide investors with a more comprehensive understanding of the factors that are driving stock prices. This can help them to make more informed investment decisions, such as when to buy or sell a stock. **Why?** In the dynamic world of finance, quick and accurate decision-making is paramount. This system would serve as a vital tool to address this challenge by merging real-time news data with structured stock information. This integration enables investors to uncover hidden insights, analysts to refine their predictions, and advisors to offer more valuable guidance. **Requirements** The problem statement caters to a critical requirement, driven by the diverse and compelling use cases it addresses. The need to identify trading opportunities underscores the necessity for a system that can seamlessly correlate news events with stock price fluctuations, offering investors insights other than the traditional market indicators. To effectively manage risk, a solution capable of monitoring sentiment across social media platforms becomes essential, providing an idea on market sentiment that guides investors away from unpopular choices. Equally vital is the requirement for making informed investment decisions, which necessitates a platform that combines different data types to afford a comprehensive understanding of the forces influencing stock prices. **Data acquisition** It involves sourcing and gathering the necessary data for the system’s functionality. This could include: News APIs: Integrating APIs from reputable news sources to access real-time news articles related to financial markets. Stock Market APIs: Utilizing APIs provided by stock exchanges or financial data providers to fetch structured stock data. Social Media Data: Accessing social media platforms’ data to gather sentiment and discussions related to stocks and markets. Historical Data: Incorporating historical stock and news data to analyze past trends and patterns. Data Cleaning: Ensuring the acquired data is accurate, consistent, and free from errors before integration and analysis.

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