--- title: "Value Intelligence Platform" description: "Reproducible value-investing screen with a deterministic multi-factor scoring engine" url: "https://www.shreejitverma.com/value-investing" author: "Shreejit Verma" --- VALUE\_INTELLIGENCE\_v4.5 # Quant Value Research Analyzing the "Architects" of wealth through the lens of modern quantitative finance. Moat decomposition using the 7 Powers framework and deep factor analysis. RESEARCH\_CORE · STATIC\_SNAPSHOT UNIVERSE · 10 SECURITIES FACTORS · 5 FUNDAMENTAL DATA · FY2024 FILINGS [VIEW METHODOLOGY](https://www.shreejitverma.com/value-investing#methodology) Wide ### Top Composite 85.6 · NVDA - Exceptional quality ### Median ROE 40.4% · universe median fundamentals ### Median FCF Margin 31.4% · cash conversion leverage ### Median D/E 0.25 · balance-sheet risk ### 7\_POWERS\_DECOMPOSITION MSFT · AUTHOR'S JUDGMENT · HAMILTON HELMER 95 #### Switching Costs Loss of value if customer switches to alternative. 88 #### Network Economies Value increases as more people use the product. 92 #### Scale Economies Unit cost declines as volume increases. 45 #### Counter-Positioning New business model that incumbents cannot copy. 85 #### Branding Higher perceived value due to reputation. 78 #### Cornered Resource Preferential access to a valuable input. ### QUALITY\_VALUE\_SCREEN FY2024 annual filings, curated 2026-07 · fundamentals only, no market data | | | | | | | | | Signal | | --------------------- | ------ | ----- | ----- | ----- | ---- | --------- | ---- | ----------- | | NVDA · NVIDIA | 91.9% | 62.5% | 46.7% | 64.3% | 0.11 | 14.6 USD | 85.6 | Exceptional | | V · Visa Inc. | 50.4% | 65.7% | 51.8% | 9.3% | 0.53 | 65.2 USD | 66.7 | Strong | | ASML · ASML Holding | 41.1% | 32.2% | 32.5% | 19.1% | 0.25 | 142.7 EUR | 60.6 | Strong | | META · Meta Platforms | 34.2% | 42.2% | 32.8% | 18.4% | 0.16 | 197.0 USD | 58.3 | Strong | | AAPL · Apple Inc. | 164.7% | 31.5% | 27.9% | 8.5% | 1.87 | 22.7 USD | 46.7 | Solid | | MSFT · Microsoft | 32.8% | 44.6% | 30.2% | 14.3% | 0.25 | 97.9 USD | 46.1 | Solid | | ADBE · Adobe Inc. | 39.7% | 31.2% | 36.7% | 13.9% | 0.40 | 94.2 USD | 45.0 | Solid | | GOOGL · Alphabet | 30.8% | 32.1% | 20.8% | 16.7% | 0.09 | 69.2 USD | 37.8 | Solid | | ORCL · Oracle | 120.7% | 29.1% | 22.3% | 6.1% | 9.71 | 16.2 USD | 33.3 | Watch | | INFY · Infosys | 30.2% | 21.0% | 14.5% | 9.5% | 0.01 | 6.7 USD | 20.0 | Watch | 10 securities · composite = weighted percentile ranks · ASML figures in EUR · see methodology below ### ARCHITECT\_PERSPECTIVES #### Warren Buffett MOAT The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any given company and, above all, the durability of that advantage. SIGHT:Would appreciate the "unbelievable" moat of the Windows/Office franchise and its high return on capital. #### Charlie Munger STANDARD The big money is not in the buying and the selling, but in the waiting. SIGHT:Understood the power of the "standard" in computing and the multi-generational compounding effects. #### Peter Lynch TEN\_BAGGER Go for a business that any idiot can run – because sooner or later, any idiot is probably going to run it. SIGHT:Values the "boring but essential" utility nature of enterprise software that businesses cannot function without. ### RISK\_ANTI\_MODELS QUALITATIVE #### Complexity Trap Opaque accounting or organizational structure concealing systemic risk. #### Financial Engineering Growth driven by buybacks and leverage rather than operations. #### Diworsification Expansion into low-return, unrelated businesses. #### The Fall from Godhood Cultural decay and loss of founding vision. Red flags from the historical cases below, reviewed by hand. They are not part of the composite score. framework\_trace (illustrative) \[OK\] Running 7 Powers analysis for Microsoft (MSFT)... \[INFO\] Switching Costs: Office 365 / ERP integration detected \[INFO\] Network Economies: GitHub / LinkedIn growth sync \[SIGNAL\] Scale Economies: Azure infrastructure moat identified \[INFO\] Cornered Resource: OpenAI exclusive Azure partnership \[WARN\] Counter-Positioning: Lower score due to incumbent nature \[INFO\] Calculating Graham-Number for Tech Sector... \_ ### METHODOLOGY #### Factor model Each security is scored on 5 price-independent fundamental factors. Raw values are converted to cross-sectional percentile ranks within the 10-name universe (mean rank for ties), oriented so higher is better, and combined with the weights below. The composite is therefore scale-free and robust to outliers; signals are fixed thresholds on the composite (75/55/35), not discretionary calls. | Factor | Formula | Weight | | ------------------------ | --------------------------------------- | ------ | | Return on Equity | net income / shareholder equity | 30% | | Operating Margin | EBIT / revenue | 20% | | FCF Margin | (operating cash flow - capex) / revenue | 20% | | Revenue 5y CAGR | (revenue / revenue 5y ago)^(1/5) - 1 | 15% | | Debt / Equity (inverted) | total debt / shareholder equity | 15% | Graham Number = sqrt(22.5 x EPS x book value per share) - reported per share for reference, outside the composite. #### Data and limitations - Inputs are approximate, rounded figures transcribed from each company's FY2024 annual filing (FY2024 annual filings, curated 2026-07). This is a static research snapshot, not a live feed. - Market prices are deliberately excluded, so the screen measures business quality, not valuation. A cheap-vs-expensive judgment still requires comparing the Graham Number and quality score against the prevailing price. - The universe is small and hand-picked toward well-known compounders, so percentile ranks are relative to a strong peer group - a mediocre rank here can still be an excellent business globally. - ASML reports in EUR; ratios are currency-neutral but the Graham Number is in EUR per share. - Nothing on this page is investment advice; it is a methodology demonstration. Factor weights are subjective research priors, not fitted parameters. Changing them changes the ranking; the point of publishing them is that the ranking is reproducible. ### HISTORICAL\_ANTI\_MODELS LEARNING\_FROM\_THE\_FALLEN CAUTIONARY\_TALES\_ONLY DEEP\_RESEARCH #### General Electric 2000 - 2024 Critical Failure Complexity Trap & Over-Financialization Destruction \-92% Peak-to-Trough COMPLETE #### Nokia 2007 - 2013 Critical Failure Platform Burning & Innovation Blindness Destruction Loss of Mobile Dominance ACTIVE #### IBM 2012 - 2022 Critical Failure Financial Engineering & Buyback Trap Destruction Decade of Underperformance