AI Tools for Investors and Traders

Master AI Tools for Investors: Faster Stock Research & Smart Market Analysis

Master AI Tools for Investors and stop spending hours reading lengthy annual reports, market news, and financial statements. Learn how to use generative AI tools like Perplexity, Claude, and Google NotebookLM to analyze companies, summarize SEC filings, and build structured investment hypotheses in minutes—without any coding or technical jargon.

Why Use AI Tools for Investors & Traders?

Modern markets move fast, and processing hundreds of pages of company earnings, SGX filings, and analyst notes manually holds retail investors back. This 3-hour hands-on workshop hosted by CyberQuote bridges the gap between traditional research and modern AI analysis.

Rather than teaching broad theory or technical programming, this practical session focuses on ready-to-use workflows: gathering citation-backed news, extracting key strategic risks from 200-page annual reports, and comparing multiple company documents side by side.

Key Takeaways

By the end of this workshop, participants will be able to:

• Real-Time Market Intelligence: Use Perplexity to perform citation-backed research on stocks, recent company news, and key financial metrics.

• Rapid Report Analysis: Upload lengthy financial filings and annual reports into Claude to extract management priorities and major balance sheet risks in minutes.

• Multi-Document Research: Load multiple financial documents into Google NotebookLM to query and compare information across filings in one place.

• Structured Trade Thesis: Apply guided prompt templates to build balanced bull and bear cases for companies and identify critical watch points.

• Responsible AI Verification: Identify AI hallucination risks and apply verification techniques to cross-check AI outputs against official regulatory filings.

In-Person at
CyberQuote
Raffles Place

3 hours

1 Instructor +
TA supports

Part 1: AI-Powered Investment Research

• • • Introduction to AI for investors and traders
    • The modern investment research challenge
    • How AI can improve research speed and efficiency
    • Understanding the strengths and limitations of AI
    • Using Perplexity for real-time market and company research
    • Finding citation-backed news and financial information
    • Researching stocks, sectors, and industries efficiently
    • Creating structured company research summaries
    • Converting research into investment briefs
    • Hands-on exercises using real companies

Part 2: Financial Document Analysis with AI

• • • Using Claude to analyse annual reports and earnings transcripts
    • Extracting key financial highlights and business developments
    • Identifying risks, opportunities, and management priorities
    • Reviewing multi-year business performance
    • Summarising lengthy financial documents within minutes
    • Turning research findings into presentation-ready insights
    • Fact-checking and validating AI-generated outputs

Part 3: Multi-Document Research with NotebookLM

• • • Building an AI-powered research workspace
    • Comparing multiple annual reports and financial documents
    • Identifying changes in risks and business performance over time
    • Creating a research archive for stocks under coverage
    • Asking comparative and cross-document research questions
    • Combining multiple AI tools for richer research outputs

Part 4: Building an AI-Supported Investment Thesis

• • • Developing a structured investment research process
    • Using AI to support investment and trade thesis creation
    • Building a bull case, bear case, and key watchpoints
    • Stress-testing assumptions and challenging biases
    • Verifying investment thesis using live market information
    • Creating a repeatable AI-assisted research workflow

Part 5: Responsible AI Use for Investors

• • • Understanding AI hallucinations and common pitfalls
    • Recognising knowledge cut-offs and stale data risks
    • Fact-checking figures, dates, and financial information
    • Understanding what AI can and cannot do in investing
    • AI’s role in research, analysis, and decision support
    • Best practices for responsible AI use in investment research
    • Practical prompt templates for ongoing use

Abby Sabrina
Project Manager & ACLP Trainer

Abby Sabrina is an ACLP-certified trainer and digital transformation practitioner with over 15 years of experience across banking, healthcare, government, technology, and education sectors. With expertise in AI, digital marketing, project management, and adult learning, Abby helps professionals leverage emerging technologies to improve productivity, decision-making, and business performance.

Abby holds Master’s qualifications in Computer Science (Data Science & AI) and Digital Marketing, and is certified in PMP, PMI-ACP, PRINCE2, Scrum, ACLP, and DDDLP. With hands-on experience using AI platforms such as ChatGPT, Claude, Perplexity, NotebookLM, Microsoft Copilot, and Gemini, Abby delivers practical, real-world training that empowers learners to apply AI confidently in their work and investment research.