Summary of "8 Powerful Ways I use AI to Research, Screen & Invest in Stocks (with demo)"
Summary of "8 Powerful Ways I use AI to Research, Screen & Invest in Stocks (with demo)"
This video explores how artificial intelligence (AI) can be leveraged in various aspects of stock research, screening, and investing. The presenter provides an in-depth explanation of AI concepts, practical demonstrations, and step-by-step guidance on using AI tools effectively, particularly focusing on investing in the Indian market.
Key Financial Strategies, Market Analyses, and Business Trends Presented:
- Understanding AI and Its Components in Investing:
- AI is a broad field with specializations like machine learning, deep learning, generative AI, and large language models (LLMs).
- LLMs like ChatGPT, Gemini, Claude, Bard, and industry-specific models trained on financial data (earnings transcripts, research reports, etc.) are crucial for investment research.
- Prompt Engineering for Effective AI Use:
- Crafting clear, detailed prompts is essential to get useful AI outputs.
- Six building blocks of a good prompt:
- Task: Define the specific action (e.g., write, analyze).
- Context: Provide background details (market size, growth drivers).
- Examples: Attach relevant reports or data for reference.
- Persona: Assign a role to the AI (e.g., equity research analyst).
- Format: Specify output style (tables, bullet points, word count).
- Tone: Set the communication style (formal, friendly, technical).
- Demonstration of AI in Investment Research:
- Using platforms like Proview.ai and Grock to summarize earnings calls, rewrite reports in simple language, and generate detailed sector analyses.
- AI can improve report quality by iterating prompts and using smart prompts that enhance input automatically.
- Limitations of AI in Investing:
- AI hallucination: AI can produce inaccurate or inconsistent information.
- Biases inherent in training data (gender, race, etc.).
- Data cutoff issues: AI models may not have the latest market information.
- Performance issues and token limits affect response depth.
- Importance of cross-verifying AI outputs and iterative questioning.
- Eight Practical Use Cases of AI in Investing:
- 1. Education: Use AI as a personal tutor to understand financial concepts and investment strategies (e.g., free cash flow, Peter Lynch’s methodology).
- 2. Screening Stocks: Filter large universes of stocks with complex criteria (e.g., monopolies growing sales >20%) beyond traditional screeners.
- 3. Market News & Analysis: Aggregate analyst opinions, sentiments, and market updates from multiple sources, saving time and effort.
- 4. Stock Analysis: Deep dive into company fundamentals, financials, and business models using AI platforms (Proview, Notebook LM) that allow uploading multiple documents and iterative Q&A.
- 5. Fundamental Analysis: Conduct comprehensive 360-degree company analysis including business model, risks, management quality, financial metrics, valuation, and outlook using detailed prompts.
- 6. Technical Analysis: Use AI to analyze price charts, technical indicators (RSI, moving averages), and set up price alerts tailored to specific criteria.
- 7. Strategy Development: Build or refine investment strategies based on anticipated market trends or scenarios (e.g., impact of rising oil prices, emerging pharma trends like GLP1 drugs).
- 8. Portfolio Analysis & Financial Planning: Upload portfolio data to AI platforms for performance tracking, risk assessment, and personalized financial planning (retirement goals, inflation adjustments).
Methodology / Step-by-Step Guide for Writing Effective AI Prompts:
- Step 1: Define the Task clearly (e.g., "Write a detailed investment report").
- Step 2: Add Context with specific details (market size, competitors, regulations).
- Step 3: Provide Examples to guide the AI on structure and depth.
- Step 4: Assign a Persona to the AI (e.g., experienced equity analyst).
- Step 5: Specify the Format of the output (tables, bullet points, word limit).
- Step 6: Set the Tone for communication (formal, friendly, analytical).
Tools and Platforms Highlighted:
- Proview.ai: An India-focused, free AI investing platform with features like smart prompts, analyst call summaries, stock screening, and interactive Q&A.
- Grock: AI tool used for summarizing and rewriting earnings call transcripts.
- ChatGPT, Gemini, Claude, Bard: Large language models used for various research and analysis tasks.
- Notebook LM: Allows uploading multiple documents related to a company and querying them interactively.
Important Considerations:
- Always verify AI-generated information due to possible inaccuracies.
- Use iterative questioning to refine AI outputs.
- Different sectors require customized screening criteria.
Category
Business and Finance
