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.

SEO and SMM Strategy and Execution

AnaChart is the largest online database for stock price targets and as such has thousands of pages dedicated to wall street analysts and to the stocks covered by them. Content on the website is dynamic and updated daily for hundred of pages. Looking for an intern that knows how to use aherf (or alike) analyze competition, creation of back links, being able to apply critical thinking where to deploy efforts and has a vision! A focal point is that AnaChart is visual tool moving towards animation and away from written content as it is in the rest of the trend elsewhere. As such the added content to the thousand of pages, strategic decision what to add and reviewing the result will be a high quality show of use case. Deploying resources on social media campaign and analysis of result on an ongoing basis Knowledge of web design, plugins, caching is a plus Understanding user behavior and improving cohort analysis Knowledge of finance, stock markets is a plus You will be working with SMM and SEO contractors who are specialists and with the CEO Analysis of the site blog content and it's impact on the domain ranking will be a regular task. Intern that will prove hers/his ability will be offered a full time position with competitive salary for New York. This is a great project for students to prove their digital marketing expertise to future employers, as the impact of their work on this project can be easily measured and communicated.