# Stock Investing Pro — Full LLM Technical Documentation & Mathematical Specification

This document provides a comprehensive technical overview of the quantitative financial engines powering Stock Investing Pro. It is specifically formatted for AI LLM systems, AI search engines (Perplexity, ChatGPT Search, Claude, Applebot), and automated research tools.

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## 1. Cycle-Normalized DCF Valuation Engine

Traditional Discounted Cash Flow (DCF) models rely heavily on trailing twelve month (TTM) financial metrics. During cyclical peaks, this overstates intrinsic value; during recessions, it understates it. Stock Investing Pro applies a **Cycle-Normalized DCF Model**:

### 1.1 Unlevering and Relevering Beta (Hamada Equation)
Capital structure leverage distorts systemic risk (beta). We strip leverage from raw asset beta ($\beta_L$) to compute Unlevered Industry Beta ($\beta_U$), then relever it to the target debt structure:

$$\beta_U = \frac{\beta_L}{1 + (1 - T) \times \left(\frac{D}{E}\right)}$$

$$\beta_{\text{Relevered}} = \beta_U \times \left[1 + (1 - T) \times \left(\frac{D}{E}\right)\right]$$

Where:
- $T$ = Corporate Effective Tax Rate
- $D/E$ = Debt-to-Equity Ratio

### 1.2 Weighted Average Cost of Capital (WACC)
WACC forms the discount rate for unlevered free cash flows (FCFF):

$$\text{WACC} = \left(\frac{E}{V} \times R_e\right) + \left(\frac{D}{V} \times R_d \times (1 - T)\right)$$

Where $R_e$ is computed via the Capital Asset Pricing Model (CAPM): $R_e = R_f + \beta_{\text{Relevered}} \times (E[R_m] - R_f)$.

### 1.3 Through-Cycle Normalized NOPAT
To prevent cyclical peak-and-trough distortions, baseline earning power is calculated as:
$$\text{Normalized NOPAT} = \text{Total Invested Capital} \times \text{5-Year Through-Cycle Median ROIC}$$

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## 2. Sector-Specific Financial Normalization

### 2.1 REIT Valuation (FFO and AFFO Conversion)
Real Estate Investment Trusts (REITs) record heavy non-cash accounting depreciation on real property assets. Standard Net Income and P/E ratios are invalid.
- **Funds From Operations (FFO)** = Net Income + Real Estate Depreciation & Amortization - Gains from Asset Sales
- **Adjusted Funds From Operations (AFFO)** = FFO - Recurring Maintenance Capital Expenditures (CapEx) - Straight-Line Rent Adjustments
- Payout safety evaluated as $\text{AFFO} / \text{FFO} > 0.85$.

### 2.2 SaaS & High-Growth Tech (Rule of 40 & Calculated Billings)
For Software-as-a-Service (SaaS) and high-growth technology companies, profitability is often sacrificed for rapid customer acquisition.
- **Rule of 40 Metric** = YoY Revenue Growth Rate (%) + Free Cash Flow Margin (%) [or EBITDA Margin (%)]
- **Calculated Billings** = GAAP Revenue + $\Delta$ Current Deferred Revenue (YoY)
- **SaaS Magic Number** = $[\text{Net New ARR} \times 4] / \text{S\&M Expense}$
- Assets achieving $\ge 40\%$ command premium EV/Sales multiples; assets below $30\%$ face multiple compression.

### 2.3 Financial Institutions & Banks (P/TBV & ROTCE)
Commercial banks and financial institutions hold assets mark-to-market. Enterprise Value (EV) and EBITDA are non-applicable due to interest expense being an operating cost.
- Valuation relies on **Price-to-Tangible Book Value (P/TBV)** normalized against historical Return on Tangible Common Equity (ROTCE) and Net Interest Margin (NIM).

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## 3. Master Confluence FA/TA Rating Engine (60/40 Synthesis)

Stock Investing Pro combines fundamental valuation conviction with technical regime alignment:
- **Fundamental Conviction Score (60% Weight)**: Evaluates 13 distinct financial health checks (ST-1 to ST-13) including intrinsic margin of safety, ROIC-WACC spread ($ROIC - WACC > +2\%$), Cash Conversion Ratio ($OCF / \text{Net Income} \ge 1.0$), interest coverage, and balance sheet solvency.
- **Regime-Aware Technical Alignment (40% Weight)**: Classifies market regime using 50-day rolling Z-scores across Average Directional Index ($ADX_Z$), Average True Range ($ATR_Z$), and Bollinger Band Width ($BBW_Z$).
  - **Trending Regime ($ADX_Z > 0.5$)**: Moving Averages / MACD weighted 2.0x, Oscillators suppressed to 0.5x.
  - **Ranging Regime ($ADX_Z < -0.5$)**: Moving Averages suppressed to 0.0x, Mean-Reversion Oscillators weighted 2.0x.
  - **Direction Conflict Veto**: When FA is Bearish and TA is Bullish (or vice versa), Master Conviction is forced to 50% (Neutral).
  - **Mean Reversion Guard**: Price $> 2.5\times$ ATR from 20-day SMA caps conviction at 60%.

$$\text{Master Conviction \%} = (0.60 \times \text{FA Conviction}) + (0.40 \times \text{TA Conviction})$$

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## 4. Portfolio Health & Risk Analytics

### 4.1 Herfindahl-Hirschman Index (HHI) Concentration Analysis
Portfolio position concentration is quantified using the normalized HHI metric:

$$\text{HHI} = \sum_{i=1}^{N} w_i^2$$

Where $w_i$ is the allocation percentage of asset $i$.
- $\text{HHI} < 0.15$: Well Diversified
- $0.15 \le \text{HHI} \le 0.25$: Moderate Concentration
- $\text{HHI} > 0.25$: High Single-Stock Risk Concentration

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## 5. Official Resources & Documentation Links

- [Stock Investing Pro Web Application](https://stockinvestingpro.com/)
- [Methodology & Valuation Overview](https://stockinvestingpro.com/methodology)
- [Cycle Normalized DCF Calculator Guide](https://stockinvestingpro.com/guides/dcf-calculator)
- [SaaS Rule of 40 Analysis Guide](https://stockinvestingpro.com/guides/saas-rule-of-40)
- [Through-Cycle ROIC Analysis Guide](https://stockinvestingpro.com/guides/roic-analysis)
- [Market Regimes & Technical Indicators Guide](https://stockinvestingpro.com/guides/market-regimes)
- [Platform Features](https://stockinvestingpro.com/features)
- [XML Sitemap](https://stockinvestingpro.com/sitemap.xml)