what AI tools, platforms are you using for research, modeling and diligence?

Based on the most helpful WSO content, here are some insights and recommendations for tools, programming languages, and AI platforms that can help automate various tasks for a research analyst:

Tools and Platforms:

1. Python:

   • Data Scraping: Use Python to write scripts that scrape data from APIs like FRED or Bloomberg.
   • Report Generation: Automate the creation of reports from the scraped data.
   • Natural Language Processing (NLP): Analyze earnings calls, summarize company presentations, and extract key phrases.

2. Excel Add-ins:

   • Automation: Utilize Excel add-ins to automate repetitive tasks. However, Python can often do these tasks more efficiently.

3. Business Intelligence (BI) Tools:

   • Data Munging: Tools like SQL for data manipulation and BI tools for visualization can be very useful.

Programming Languages:

1. Python:

   • Widely used for automation, data analysis, and machine learning.
   • Libraries like Pandas, NumPy, and Scikit-learn are essential for data manipulation and machine learning tasks.

2. SQL:

   • Useful for querying databases and handling large datasets.

AI Tools:

1. Machine Learning Algorithms:

   • Predictive Modeling: Use machine learning to predict company performance based on historical data.
   • Sentiment Analysis: Analyze the sentiment of earnings calls and other textual data.

2. Natural Language Processing (NLP):

   • Summarization: Tools that can summarize long documents, such as company presentation decks and earnings call transcripts.
   • Risk Phrase Identification: Identify risky language in earnings calls.

Practical Applications:

• Automating Financial Models: Generate financial models from reported financials.
• Highlighting Changes: Automatically highlight changes to risk factors in documents like 10-Ks.
• Readable Summaries: Create readable summaries of key portions of financial documents.

Learning Resources:

• Online Courses: Platforms like Udacity offer courses on machine learning and AI.
• Competitions: Participating in machine learning competitions on platforms like Kaggle can help improve your skills.

By leveraging these tools and platforms, you can significantly reduce the manual effort involved in data entry, analysis, and reporting, making your job more efficient and less stressful, especially during earnings season.

Sources: https://www.wallstreetoasis.com/forum/hedge-fund/machine-learning-taking-over-hf-research-analyst-roles-in-near-future?customgpt=1, AI in fundamental investing, Q&A: Former no-name IB Analyst --> Data science/Artificial Intelligence position at large quantitative hedge fund, Work at top AM -- AI will virtually kill of entry-level roles in AM over the next 5yrs, Using Python to Automate tasks in ER/IB