🔌 Claude Code Plugin for institutional-grade equity research. Install with /plugin marketplace add. Generates professional buy/sell recommendations with comprehensive fundamental analysis, technical indicators, and risk assessment. Educational use only - not financial advice.

Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf

🤖 Your personal AI financial analyst - Advanced stock analysis with GPT-4 | Real-time market insights | Professional trading interface

A sophisticated financial analysis bot powered by OpenAI, designed to provide in-depth financial insights and recommendations based on company data.

This repository contains the equity research report (pdf), stock pitch slide deck (ppt), financial models (xl), and a couple other preliminary analysis slides all conducted for the purpose of researching Mead Johnson Nutrition company. All the documents were prepared by me for a potential investment opportunity when I was a Senior Analyst for the Student Investment Fund at the School of Accounting and Finance at the University of Waterloo.

中国股票分析师-china-stock-analyst

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An AI-powered video app where you choose a persona (Financial Analyst, News Anchor, Professor) and get a live, face to face rundown on any topic, stock watchlist, or academic paper, backed by real-time search data.

This is a versatile Python library tailored for the Tehran Stock Exchange, offering robust tools for processing and analyzing TSE symbol data. It enables users to apply custom text filters for efficient data handling, ideal for traders and analysts seeking streamlined data analysis.

Web scraper that stores fundamental stock data, analyst estimates, and earnings surprises as .pkl and/or .csv

An evaluation of stock price prediction algorithms using analyst ratings

We compiled the analyst reports from Morningstar for 15 largest companies in retail and technology sector and extracted the specific text. Then extracteed sentiments using VADER general sentiment lexicon and through Loughran and MCdonald financial sentiment lexicon. S&P Capital IQ and Yahoo Finance was also our data source. We applied statistical modeling, both linear and logisitc regressions to predict the percentage change in the stock price from day of publication of report to 3 time periods and our model showed some sigificant results with over 95% accuracy and validated our hypothesis.

The Financial Analysis Crew is a Streamlit app that simplifies financial stock analysis. With the power of LLM-driven agents, users can seamlessly gather and analyze stock market data to generate comprehensive financial insights. Perfect for investors, analysts, and anyone interested in making data-driven financial decisions.

This project was completed with the intention of helping Tesla stock investors better understand how to make decisions where the stock market is very volatile by training different models through historical and social media data analytics. Behavioral economics shows that public emotions can profoundly affect individual behavior and decision making. In order for investors to utilize it, business analysts must understand the behaviors and attitudes of the public within the finance context. Nowadays, social media perfectly tracked by data reflects the public emotions and sentiment about stock movement. Also, tremendous stock marketing news can be used to capture a trend of stock movement. The fundamental trading and decision making for main techniques rely on expert training and prediction. This article concentrated on tweets and stock news, and I applied sentiment analysis and machine learning models, especially, XGBoost to tweets and news extracted from Elon Musk tweets, Nasdaq and New York Times News about Tesla. Only by understanding the values and priorities of the public sentiment of Tesla stock will investors be able to make significant decisions. In addition, I conducted two models- ARIMA and RNN(LSTM) in forecasting the Tesla stock price. I compare their results with the prediction performances of the classical ARIMA and RNN.

For this project, you will assume the role of a Data Scientist / Data Analyst working for a new startup investment firm that helps customers invest their money in stocks. Your job is to extract financial data like historical share price and quarterly revenue reportings from various sources using Python libraries and webscraping on popular stocks. After collecting this data you will visualize it in a dashboard to identify patterns or trends. The stocks we will work with are Tesla, Amazon, AMD, and GameStop. Dashboard Analytics Displayed A dashboard often provides a view of key performance indicators in a clear way. Analyzing a data set and extracting key performance indicators will be practiced. Prompts will be used to support learning in accessing and displaying data in dashboards. Learning how to display key performance indicators on a dashboard will be included in this assignment. We will be using Plotly in this course for data visualization and is not a requirement to take this course. Watson Studio In the Python for Data Science, AI and Development course you utilized Skills Network Labs for hands-on labs. For this project you will use Skills Network Labs and Watson Studio. Skills Network Labs is a sandbox environment for learning and completing labs in courses. Whereas Watson Studio, a component of IBM Cloud Pak for Data, is a suite of tools and a collaborative environment for data scientists, data analysts, AI and machine learning engineers and domain experts to develop and deploy your projects. Review criteria There are two hands-on labs on Extracting Stock Data and one assignment to complete. You will be judged by completing two quizzes and one peer review assignment. The quizzes will test you based on the output of the hands-on labs. In the peer review assignment you will share and take screen shots of the outcomes of your assignment.

Analysis of market trend using Deep Learning is project that forecasts stock prices using historical data and ML models. Leveraging data collection, feature engineering, and model training. Primarily designed for the Indian stock market, it is adaptable for international markets, providing valuable insights for investors and analysts.

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Scraper for stock predictions and analysts' consensuses.

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Your personal AI stock analyst for A-shares. Daily automated analysis delivered to your inbox. Free & open source.

Production-ready Model Context Protocol (MCP) server for Yahoo Finance financial data. Real-time stock quotes, historical data, earnings reports, analyst recommendations, options chains, and more with built-in caching, rate limiting, and circuit breaker patterns.

Course Description In this course, we will introduce a number of financial analytic techniques. You will learn why, when, and how to apply financial analytics in real-world situations. We will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risks of corporate stocks, the analytical techniques can be leveraged in other domains. Finally, a short introduction to algorithmic trading concludes the course. After completing this course, you should be able to understand time series data, create forecasts, and determine the efficacy of the estimates. Also, you will be able to create a portfolio of assets using actual stock price data while optimizing risk and reward. Understanding financial data is an important skill as an analyst, manager, or consultant. Course Goals and Objectives Upon completion of this course, you should be able to: Understand the forecasting process. Evaluate a forecast. Describe time series data. Perform moving average analysis. Perform exponential smoothing. Develop a Holt-Winters model. Develop an ARIMA model. Understand how to create a portfolio of assets. Understand a basic trading algorithm.

Agentic AI Stock Analysis is an AI-powered multi-agent system that analyzes stock market trends, provides analyst recommendations, and fetches the latest news using Groq AI models. It integrates financial and web search agents to deliver real-time insights.

Scrapes analyst ratings of the stock and displays the data using plotly

The project analysis the stock markets to give good predictions. As of now it just supports Twitter Sentiment to predict stocks.

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AI-driven financial analyst system utilizing LangChain and Ollama for real-time stock analysis, market trends, and financial insights.

WGU-Software-I-C482 COMPETENCIES 430.02.05 : Classes and Interfaces The graduate designs software solutions with appropriate classes, objects, methods, and interfaces to achieve specific goals. 430.02.06 : Object-Oriented Principles The graduate implements object-oriented design principles (e.g., inheritance, encapsulation, and abstraction) in developing applications for ensuring the application’s scalability. 430.02.07 : Application Development The graduate produces applications using Java programming language constructs to meet business requirements. 430.02.08 : Exception Handling The graduate incorporates simple exception handling in application development for improving user experience and application stability. 430.02.09 : User Interface Development The graduate develops user interfaces to meet project requirements. INTRODUCTION Throughout your career in software design and development, you will be asked to create applications with various features and functionality based on business requirements. For this assessment, you will create a Java desktop application using the solution statements provided in the requirements section of this assessment. The skills you showcase in your completed application will be useful in responding to technical interview questions for future employment. This application may also be added to your portfolio to show to future employers. The preferred integrated development environment (IDE) for this assignment is NetBeans version 11.1 or later or IntelliJ IDEA (Community Edition). Use the links in the web links section of this assessment to install one of these IDEs. If you choose to use another IDE, you must export your project into NetBeans 11.1 or later or IntelliJ IDEA format or your submission will be returned. This assessment also requires the following software: JDK 11 and JavaFX SDK or Module (for NetBeans or IntelliJ IDEA), and Scene Builder, which are also available for download in the web links section of this assessment, as well as a video demonstration of the completed application. Your submission should include a zip file with all the necessary code files to compile, support, and run your application. Your submission should also include a folder with descriptive Javadoc comments in the .java files. The zip file submission must keep the project file and folder structure intact for the IDE. In NetBeans, zip your file by going to File > Export Project > To ZIP and click Export. In IntelliJ IDEA, go to File > Export to Zip File and click OK. If you try to zip your project files with an external program, it will include the build files and make the zip files too large for submission. Note: You may receive an error message upon submitting your files because the automated plagiarism detectors will not be able to access the zipped file, but the evaluation team members will run their checks manually when evaluating your submission. SCENARIO You are working for a small manufacturing organization that has outgrown its current inventory system. Members of the organization have been using a spreadsheet program to manually enter inventory additions, deletions, and other data from a paper-based system but would now like you to develop a more sophisticated inventory program. You have been provided with a mock-up of the user interface to use in the design and development of the system (see the attached “Software 1 GUI Mock-Up”) and a class diagram to assist you in your work (see the attached “UML Class Diagram”). The organization also has specific business requirements that must be considered for the application. A systems analyst created the solution statements outlined in the requirements section of this task based on the business requirements. You will use these solution statements to develop your application. REQUIREMENTS Your submission must be your original work. No more than a combined total of 30% of the submission and no more than a 10% match to any one individual source can be directly quoted or closely paraphrased from sources, even if cited correctly. The originality report that is provided when you submit your task can be used as a guide. You must use the rubric to direct the creation of your submission because it provides detailed criteria that will be used to evaluate your work. Each requirement below may be evaluated by more than one rubric aspect. The rubric aspect titles may contain hyperlinks to relevant portions of the course. Tasks may not be submitted as cloud links, such as links to Google Docs, Google Slides, OneDrive, etc., unless specified in the task requirements. All other submissions must be file types that are uploaded and submitted as attachments (e.g., .docx, .pdf, .ppt). I. User Interface A. Create a JavaFX application with a graphical user interface (GUI) based on the attached “Software 1 GUI Mock-Up.” You may use JavaFX with or without FXML to create your GUI, or you may use Scene Builder to create your FXML file; use of Swing is not permitted. The user interface (UI) should closely match the organization of the GUI layout and contain all UI components (buttons, text fields, etc.) in each of the following GUI mock-up forms: 1. Main form 2. Add Part form 3. Modify Part form 4. Add Product form 5. Modify Product form Note: You may use one FXML file for forms with an identical UI component structure. You may also use a single window that can be switched to a different menu, or a new window can be launched for each form. As of JDK 11, JavaFX is no longer included in the JDK API but is available as an SDK or module. B. Provide Javadoc comments for each class member throughout the code, and include a detailed description of the following in your comments: • a logical or runtime error that you corrected in the code and how it was corrected • a future enhancement that would extend the functionality of the application if it were to be updated Note: For these comments to accurately export to the Javadoc comments, please add the logical and runtime error comments in the method header declaration comments where the error that was corrected occurred, and include the future enhancement comments in the comments of the main class. Please start these comments with “RUNTIME ERROR” or “FUTURE ENHANCEMENT” as applicable. II. Application C. Create classes with data and logic that map to the UML class diagram and include the supplied Part class provided in the attached “Part.java.” Do not alter the provided class. Include all the classes and members as shown in the UML diagram. Your code should demonstrate the following: • inheritance • abstract and concrete classes • instance and static variables • instance and static methods D. Add the following functionalities to the Main form: 1. The Parts pane • The Add button under the Parts TableView opens the Add Part form. • The Modify button under the Parts TableView opens the Modify Part form. • The Delete button under the Parts TableView deletes the selected part from the Parts TableView or displays a descriptive error message in the UI or in a dialog box if a part is not deleted. • When the user searches for parts by ID or name (partial or full name) using the text field, the application displays matching results in the Parts TableView. (Including a search button is optional.) If the part or parts are found, the application highlights a single part or filters multiple parts. If the part is not found, the application displays an error message in the UI or in a dialog box. • If the search field is set to empty, the table should be repopulated with all available parts. 2. The Products pane • The Add button under the Products TableView opens the Add Product form. • The Modify button under the Products TableView opens the Modify Product form. • The Delete button under the Products TableView deletes the selected product (if appropriate) from the Products TableView or displays a descriptive error message in the UI or in a dialog box if a product is not deleted. • When the user searches for products by ID or name (partial or full name) using the text field, the application displays matching results in the Products TableView. (Including a search button is optional.) If a product or products are found, the application highlights a single product or products or filters multiple products. If a product or products are not found, the application displays an error message in the UI or in a dialog box. • If the search field is set to empty, the table should be repopulated with all available products. Note: A product’s associated parts can exist independent of current inventory of parts. You are not required to display sample data upon launching your application. You do not need to save your data to a database or a file; data for this application is nonpersistent and will reside in computer memory while in use. 3. Exit button • The Exit button closes the application. E. Add the listed functionalities to the following parts forms: 1. The Add Part form • The In-House and Outsourced radio buttons switch the bottom label to the correct value (Machine ID or Company Name). • The application auto-generates a unique part ID. The part IDs can be, but do not need to be, contiguous. - The part ID text field must be disabled. • The user should be able to enter a part name, inventory level or stock, a price, maximum and minimum values, and company name or machine ID values into active text fields. • After saving the data, users are automatically redirected to the Main form. • Canceling or exiting this form redirects users to the Main form. 2. The Modify Part form • The text fields populate with the data from the chosen part. • The In-House and Outsourced radio buttons switch the bottom label to the correct value (Machine ID or Company Name) and swap In-House parts and Outsourced parts. When new objects need to be created after the Save button is clicked, the part ID should be retained. • The user can modify data values in the text fields sent from the Main form except the part ID. • After saving modifications to the part, the user is automatically redirected to the Main form. • Canceling or exiting this form redirects users to the Main form. F. Add the following functionalities to the following product forms: 1. The Add Product form • The application auto-generates a unique product ID. The product IDs can be, but do not need to be, contiguous. - The product ID text field must be disabled and cannot be edited or changed. • The user should be able to enter a product name, inventory level or stock, a price, and maximum and minimum values. • The user can search for parts (top table) by ID or name (partial or full name). If the part or parts are found, the application highlights a single part or filters multiple parts. If the part or parts are not found, the application displays an error message in the UI or in a dialog box. • If the search field is set to empty, the table should be repopulated with all available parts. • The top table should be identical to the Parts TableView in the Main form. • The user can select a part from the top table. The user then clicks the Add button, and the part is copied to the bottom table. (This associates one or more parts with a product.) • The Remove Associated Part button removes a selected part from the bottom table. (This dissociates or removes a part from a product.) • After saving the data, the user is automatically redirected to the Main form. • Canceling or exiting this form redirects users to the Main form. Note: When a product is deleted, so can its associated parts without affecting the part inventory. The Remove Associated Part button removes a selected part from the bottom table. (This dissociates or removes a part from a product.) 2. The Modify Product form • The text fields populate with the data from the chosen product, and the bottom TableView populates with the associated parts. • The user can search for parts (top table) by ID or name (partial or full name). If the part or parts are found, the application highlights a single part or filters multiple parts. If the part is not found, the application displays an error message in the UI or a dialog box. • If the search text field is set to empty, the table should be repopulated with all available parts. • The top table should be identical to the Parts TableView in the Main form. • The user may modify or change data values. - The product ID text field must be disabled and cannot be edited or changed. • The user can select a part from the top table. The user then clicks the Add button, and the part is copied to the bottom table. (This associates one or more parts with a product.) • The user may associate zero, one, or more parts with a product. • The user may remove or disassociate a part from a product. • After saving modifications to the product, the user is automatically redirected to the Main form. • Canceling or exiting this form redirects users to the Main form. Note: The Remove Associated Part button removes a selected part from the bottom table. (This dissociates or removes a part from a product.) G. Write code to implement input validation and logical error checks using a dialog box or message in the UI displaying a descriptive error message for each of the following circumstances: • Min should be less than Max; and Inv should be between those two values. • The user should not delete a product that has a part associated with it. • The application confirms the “Delete” and “Remove” actions. • The application will not crash when inappropriate user data is entered in the forms; instead, error messages should be generated. H. Provide a folder containing Javadoc files that were generated from the IDE or via the command prompt from part B. In a comment above the main method header declaration, please specify where this folder is located. I. Demonstrate professional communication in the content and presentation of your submission. File Restrictions File name may contain only letters, numbers, spaces, and these symbols: ! - _ . * ' ( ) File size limit: 200 MB File types allowed: doc, docx, rtf, xls, xlsx, ppt, pptx, odt, pdf, txt, qt, mov, mpg, avi, mp3, wav, mp4, wma, flv, asf, mpeg, wmv, m4v, svg, tif, tiff, jpeg, jpg, gif, png, zip, rar, tar, 7z

Code used for my current work about using analyst report to predict stock market.

Beginner-friendly Yahoo Finance MCP server for Claude. Get real-time stock data, charts, financials, analyst ratings, and compare multiple companies.