Stock Price Target and Ratings Analysis and Insights

Project Objective and Scope The primary objective of this project is to empower students to utilize the AnaChart dataset —a comprehensive database of analyst stock price targets and ratings—to derive actionable insights relevant to financial research and investment analysis. By engaging with this real-world dataset, students will apply theoretical knowledge gained in the classroom to explore patterns, evaluate analyst behavior, and assess the predictive power of stock recommendations over time. This project provides a practical, hands-on opportunity for students enrolled in finance, economics, or data analytics programs to develop and demonstrate their competencies in data handling, financial analysis, and critical thinking. Dataset Overview The AnaChart dataset is the largest of its kind available in the market, containing over 800,000 analyst recommendations collected over a 15-year period and continuously updated. For the scope of this educational project, free access will be granted to a curated subset of the dataset, limited to stocks included in the NASDAQ-100 index . This subset still offers significant depth and breadth for analysis while remaining manageable for class-based projects. Please note: Computation costs incurred through querying the dataset on Google BigQuery are the responsibility of the participating university or department. AnaChart does not charge for access to the dataset for approved academic projects. For departments or institutions unable to cover BigQuery computation costs , AnaChart offers an alternative: Free Advanced-level membership accounts on anachart.com can be provided to students and faculty, enabling access to the dataset through the platform's web interface. To qualify, users must log in using a verified university email address , and the project must be formally approved for academic use. . Tasks and Activities Students will engage in a series of structured tasks that mirror the stages of a real-world data analysis workflow: Data Familiarization Understanding the structure, fields, and context of the AnaChart dataset. Reviewing metadata to identify key variables for analysis. Data Cleaning and Preparation Handling missing or inconsistent values. Filtering for relevant tickers within the NASDAQ-100. Transforming data for usability (e.g., converting dates, calculating returns, standardizing rating scales). Exploratory Data Analysis (EDA) Identifying trends in analyst recommendations over time. Evaluating the distribution and frequency of price target updates. Analyzing correlation between analyst ratings and stock price performance. Advanced Statistical and Financial Analysis Measuring analyst accuracy and consistency. Identifying potential biases or herding behavior among analysts. Backtesting the performance of recommendation-based strategies. Visualization Creating charts, heatmaps, and dashboards to communicate insights. Using tools such as Python (Matplotlib, Seaborn), R, Tableau, or Power BI. Interpretation and Recommendation Synthesizing insights into coherent investment theses. Developing data-driven recommendations for hypothetical investment portfolios. Deliverables Each student group (or individual, if applicable) will be responsible for producing the following: Project Proposal : A brief outline of the analysis plan, research questions, and methodologies. Data Analysis Notebook : A reproducible code-based report (e.g., Jupyter Notebook or R Markdown) showcasing all analysis steps and results. Final Report : A comprehensive written report that includes: Executive summary Methodology Key findings Visualizations Limitations and areas for further research Investment recommendations (if applicable) Presentation : A 10–15 minute presentation summarizing the project outcomes and insights. Suggestions for Enhancement To further enrich the project and align it with professional practice, consider: Bringing in a guest speaker from the investment research industry to provide context. Hosting a peer-review session where students evaluate each other’s findings. Incorporating ethical considerations , such as the implications of analyst influence on retail investors. Encouraging comparative analysis across sectors or time periods.

Content Creation SEO and SMM Strategy and Execution

Project Objective and Goals The main objective of this project is to strengthen AnaChart’s digital presence through consistent, high-quality content creation tailored for both Search Engine Optimization (SEO) and Social Media Marketing (SMM) . Interns will research, draft, and publish engaging blog posts and social media updates that highlight AnaChart’s unique value in delivering analyst price targets, ratings, and market insights. Key goals include: SEO-driven content development : Produce blog articles that are optimized for search engines to increase organic traffic and improve keyword rankings. Social media growth and engagement : Create and schedule posts that resonate with AnaChart’s target audience across platforms (e.g., LinkedIn, X/Twitter, Facebook) to build brand awareness and foster interaction. Content calendar execution : Plan and maintain a consistent posting schedule aligned with financial market trends, product updates, and industry news. Brand positioning : Strengthen AnaChart’s credibility as a trusted source for analyst recommendations by delivering fact-based, accessible, and timely content. Performance tracking : Monitor analytics for blog and social media content, learning to adjust strategies for greater reach and effectiveness. This project gives interns the opportunity to apply creative, analytical, and strategic skills in real-world digital marketing, while directly contributing to AnaChart’s growth and visibility.