Building Our Own Research Reports (Q2 2025)
Why Self-Produced Research?
Institutional research from big banks or boutique firms is notoriously expensive and often locked behind paywalls. We have access to the same raw data (earnings, 10-Ks, management commentary) that they do. The difference is curation and analysis. Our intention is to:
Automate the Gathering: Our Agents already parse SEC filings, transcripts, and sector news.
Apply Valuation Models: DCF (Discounted Cash Flow), comps, ratio analysis.
Summarize 10-K / 10-Q: Distill risk disclosures, growth strategies, or competitive landscapes.
Highlight Analyst Q&A: Pinpoint recurring questions from institutional analysts (e.g., about supply chain challenges, new product lines).
All of this data is free—it’s public domain under SEC rules. What’s expensive is the time and expertise to compile it into cohesive research. We want to automate 80-90% of that, with final polishing by an LLM-based summarizer.
Need for Sector-Specific Model Training
Not all industries speak the same language:
Tech: Frequent references to TAM (total addressable market), SaaS metrics, monthly active users.
Pharma: FDA approvals, clinical trials, phase progress.
Energy: Commodity prices, upstream vs. downstream, refining margins.
We plan to train sector-specific NLP models that better understand domain jargon. This could mean fine-tuning open-source LLMs on specialized corpora (e.g., all biotech 10-Ks from the last decade) so that when we parse a new filing, we accurately capture the context.
Making It Accessible
Final research reports will be:
Freely Available: Downloadable PDFs or web-based interactive versions.
Searchable: Users can query, “Show me companies with net margins > 20% in the software sector,” and get a pre-generated short list plus insights.
Tied to Real-Time Data: If a company updates guidance or an analyst changes a rating, the digital research page updates automatically.
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