What Is the Mosaic Theory?
The mosaic theory is an investment-research approach in which analysts assemble many small pieces of public, non‑public and non‑material information into a coherent picture of a company’s business, prospects and intrinsic value. Used responsibly, it helps analysts form investment opinions without relying on material nonpublic information (MNPI). It has been recognized as a legitimate method of analysis by parts of the investment profession, but it also has legal and ethical boundaries—illustrated by high‑profile insider‑trading prosecutions where defendants argued they had merely assembled “mosaic” information.
Key takeaways
– Mosaic theory = gathering many small, sometimes disparate data points (public and non‑public but non‑material) and integrating them to reach investment conclusions.
– The approach overlaps with Philip Fisher’s “scuttlebutt” method (talking to many industry participants and using firsthand observation).
– Legally and ethically, the critical boundary is material nonpublic information (MNPI). Using MNPI can trigger insider‑trading liability.
– Best practice: document sources and methods, avoid solicitation of MNPI, disclose research inputs to clients when required, and use compliance/legal review for borderline situations.
How the mosaic theory works (conceptual steps)
1. Define the investment question: valuation, growth potential, competitive position, takeover likelihood, etc.
2. Collect small signals from many sources: regulatory filings, management commentary, employees, customers, suppliers, job postings, web traffic, search trends and macro research.
3. Triangulate: corroborate signals across independent sources to increase confidence and reduce the chance a single noisy data point misleads you.
4. Estimate the likely material outcomes: revenue growth, margin drivers, market share swings, regulatory impacts and their timing.
5. Convert the qualitative and quantitative signals into a valuation or recommendation, documenting assumptions and the evidence supporting them.
6. Disclose methodology and sources to clients and compliance (as required); avoid using or acting on MNPI.
Mosaic Theory vs. Scuttlebutt Method
– Similarities: Both assemble many small pieces of information (often obtained through conversations and observation) to infer company prospects. Both rely on primary research and require judgment to synthesize a coherent view.
– Differences: “Scuttlebutt” (term popularized by Philip Fisher) emphasizes direct, firsthand conversations with customers, suppliers, employees and competitors; mosaic theory is broader and more explicitly references a mix of public, nonpublic and non‑material information, including third‑party data sources and alternative datasets.
Special considerations and legal/ethical boundaries
– Materiality: Information is material if a reasonable investor would consider it important in making an investment decision or if it would significantly alter the market price of the security. Materiality is a legal standard and fact‑specific.
– Nonpublic vs public: Publicly available data is generally safe to use. Nonpublic information can be used only if it is non‑material; using MNPI can be illegal.
– Solicitation of inside information: Avoid asking company insiders (e.g., executives) for MNPI or seeking to induce them to share it. Be cautious when speaking with employees—information about future earnings, product launches, or undisclosed deals may be MNPI.
– Documentation and disclosure: Keep a research log documenting sources and methods. If you’re an analyst issuing recommendations, disclose what types of information were used (e.g., public filings, employee conversations, third‑party data) while maintaining confidentiality where appropriate.
– Compliance: If you work for an investment firm, follow internal policies (wall‑crossings, blackouts, pre‑clearance) and have borderline cases reviewed by legal/compliance.
Practical steps for investors who want to apply the mosaic theory
Step 1 — Set clear objectives and information boundaries
– Define the investment thesis and what would change it (revenue/growth, margin drivers, regulatory events, M&A).
– Write down what counts as MNPI for the company (undisclosed earnings, trade secrets, upcoming mergers, pricing decisions). If unsure, assume the information could be material and consult compliance/legal.
Step 2 — Build your data checklist (sources to consult)
– Regulatory filings: 10‑K, 10‑Q, 8‑K, proxy statements (EDGAR/SEC). These are primary public documents for fundamentals and risk factors.
– Earnings calls/transcripts and investor presentations (management tone and guidance).
– Job postings and LinkedIn: hiring trends, new teams, geographic expansions and senior hires.
– Glassdoor and employee reviews: turnover, morale, and quality of management execution.
– Google Trends and web search volumes: changes in consumer interest for products/brands.
– Customer reviews and social media: product sentiment and recurring complaints.
– Industry sources and trade press: competitor moves, supplier constraints, regulatory shifts.
– Alternative data (where legal and permitted): web traffic (SimilarWeb), app downloads, satellite imagery (for supply chain/retail foot traffic), import/export filings—use reputable vendors and ensure data collection is lawful.
– Macro research and public opinion surveys (e.g., Pew Research Center) to see if societal trends may impact demand.
Step 3 — Gather and triage information
– Prioritize sources that are independent and corroborating.
– For conversational inputs (ex‑employees, customers, suppliers), avoid asking for confidential or future financial information. Frame conversations as fact‑finding rather than seeking undisclosed specifics.
– Maintain contemporaneous notes: who you spoke with, what they said, date/time and whether the information is public.
Step 4 — Triangulate and quantify
– Seek independent confirmation for any potentially influential signal. If three independent sources point to the same development, the signal is stronger.
– Where possible, convert qualitative evidence to quantitative assumptions (e.g., hiring growth → capacity for sales x% → revenue impact). Run sensitivity analysis around key assumptions.
Step 5 — Build scenarios and valuation impact
– Translate findings into scenarios (base, bull, bear), noting timing and probability.
– Estimate valuation impact under each scenario and determine the catalyst that would move the market.
Step 6 — Document, disclose and get sign‑offs
– Record sources and reasoning in your research file. If you’re a professional analyst, follow your firm’s disclosure and sign‑off policies; be transparent with clients about the types of information used (without revealing confidential source identities).
– If in doubt about whether a piece of information is MNPI, do not use it until counsel clears it.
Step 7 — Monitor and update
– Continue monitoring the same signals for trend confirmation or reversal. Update your models and client communications accordingly.
Tools and concrete data points to use
– SEC EDGAR: 10‑K, 10‑Q, 8‑K filings for audited financials, risk factors and material events. (https://www.sec.gov/edgar)
– Earnings call transcripts and replays for tone and management guidance.
– LinkedIn: hiring patterns, new office openings, executive moves. Observe changes in number of employees, new teams and geography.
– Glassdoor: employee sentiment, reasons for leaving, management praise/complaints; use trends rather than single reviews.
– Google Trends: shifts in consumer interest by geography and over time. (https://trends.google.com)
– Pew Research Center: trusted public opinion and macro trend research. (https://pewresearch.org)
– Trade press, industry reports, supplier/customer interviews and competitor filings.
– Alternative‑data vendors and public data repositories if available and compliant.
Examples of safe vs risky information
– Generally safe: public SEC filings, published news, job postings, aggregated Glassdoor trends, Google Trends spikes, third‑party syndicated data bought/licensed lawfully.
– Risky / potentially MNPI: details of an undisclosed merger, unreleased quarterly results obtained from an insider, confidential contract terms, nonpublic guidance shared by executives or IR personnel.
Compliance and documenting best practice
– Maintain a “source log” for each investment with dates, nature of source (public, conversational, vendor), and any compliance reviews.
– If you are an adviser or sell recommendations, prepare a brief disclosure statement noting the principal categories of information used (public filings, primary research, third‑party datasets), and whether and how the firm reviewed potential conflicts.
– Train staff in how to speak with company insiders and how to identify and escalate MNPI.
– Use regular audits of research files to ensure policies were followed.
When mosaic theory has drawn legal attention
– Mosaic defense was raised in several insider‑trading prosecutions, notably that of Raj Rajaratnam (Galleon Group), who claimed his research was mosaic‑style; courts and prosecutors concluded his communications included material nonpublic tips and he was convicted. High‑profile cases demonstrate that claiming a “mosaic” approach is not a safe harbor against insider‑trading laws if the underlying facts involve tips of MNPI. (See DOJ statements and press coverage for details.)
Practical checklist before acting on a mosaic-based conclusion
1. Can every key input be traced to a documented source or corroborated by independent public data?
2. Does any input appear to be material nonpublic information? If yes, stop and consult legal/compliance.
3. Have you quantified how sensitive your thesis is to each assumption?
4. Have you documented your process and prepared required client disclosures?
5. Is there a clear catalyst or timeframe for your thesis to be realized? If not, assign probabilities and triggers.
Conclusion
The mosaic theory can be a powerful, disciplined research framework: by assembling many small pieces of information, investors can form a better picture of a company than reliance on headline metrics alone. However, its responsible use requires careful attention to legal boundaries (avoiding MNPI), documentation, corroboration and compliance. Combine public filings, primary conversations that avoid confidential details, alternative data and macro research (e.g., Pew) to triangulate conclusions—and always have a documented, auditable process.
Sources and further reading
– Investopedia — Mosaic Theory (definition and overview): https://www.investopedia.com/terms/m/mosaictheory.asp
– U.S. Securities and Exchange Commission (EDGAR search for 10‑K/10‑Q/8‑K filings): https://www.sec.gov/edgar
– Philip A. Fisher, Common Stocks and Uncommon Profits (scuttlebutt method), 1958.
– Pew Research Center (public opinion and trend data): https://www.pewresearch.org
– Google Trends: https://trends.google.com
– LinkedIn: https://www.linkedin.com; Glassdoor: https://www.glassdoor.com
– Reporting on Raj Rajaratnam and insider‑trading prosecutions (examples): U.S. Department of Justice press releases and major press outlets (e.g., New York Times coverage).
If you want, I can:
– Provide a one‑page printable checklist tailored to retail investors or professional analysts.
– Walk through a short case study (real or hypothetical) showing how to assemble a mosaic on a specific company using public and non‑material data.