161 lines
8.9 KiB
Markdown
161 lines
8.9 KiB
Markdown
# QuantSandbox System Architecture & Quantitative Roadmap
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This document serves as the permanent, centralized system architecture design and master context for all future quantitative feature deployments.
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---
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## 1. Repository Status & Milestone Log
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### Completed Phases & Integrated Silos
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* **Phase 1.0: Portfolio Sandbox**
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* *Features*: Real-time volatility estimators, portfolio optimization mechanics, and Swamy-Arora random effects panel regression solvers.
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* *Status*: **Fully Operational (Production Lock)**.
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* **Phase 2.0: Live GJR-GARCH Scanners**
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* *Features*: Real-time rolling volatility forecasting engine that detects asymmetric leverage effects in equity volatility.
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* *Status*: **Fully Operational (Production Lock)**.
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* **Phase 3.0: Real FRED Macro Ingestion**
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* *Features*: Real-time server-side API integration with Federal Reserve Economic Data (FRED). Ingests Personal Savings Rates, Credit Card Delinquencies, Housing Starts, and Case-Shiller indices.
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* *Status*: **Fully Operational (Production Lock)**.
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* **Phase 4.7: AI & Tech Hyper-Leverage Silo**
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* *Features*: Track the AI CapEx-Overinvestment Cycle for NVDA, MSFT, GOOGL, META, and AMD. Calculates ROI-to-CapEx (Monetization Gap), Nvidia Supply-Chain Velocity Index, and Tech Infrastructure Leverage with a 60-minute caching layer.
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* *Status*: **Fully Operational (Production Lock)**.
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---
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## 2. Master Backlog Architecture: The 6-Level Cockpit Matrix
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The system tracks and synthesizes ~50 quantitative metrics divided into 6 distinct analytical levels to form a unified Market Regime Classifier.
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### Level 1: Macro & Credit Layer (21 Metrics)
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* **Inflation Vectors**: CPI YoY, Core CPI, PPI.
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* **Sovereign Yields & Term Structure**: US 10Y Yield, US 2Y Yield, 2S10S Yield Spread, High-Yield Credit Spreads.
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* **Central Bank Liquidity**: Fed Balance Sheet Assets, ECB Refinancing Rate, Fed Funds Rate, M2 Money Supply, Reverse Repo (RRP) Volumes, Treasury General Account (TGA) levels.
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* **Macro Capacity**: S&P 500-to-GDP Ratio (Buffett Indicator Proxy).
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* **Labor Market Dynamics**: Non-Farm Payrolls (NFP), Unemployment Rate, Initial Jobless Claims.
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* **Housing & Credit Velocity**: Housing Starts, Mortgage Applications Index Proxy, S&P Case-Shiller Home Price Index.
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* **Consumer Stress Indexes**: Credit Card Delinquency Rates, Personal Savings Rate.
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### Level 2: Market Breadth Layer (8 Metrics)
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* **Moving Average Spreads**: Percentage of S&P 500 constituents trading above their 50-day and 200-day Simple Moving Averages.
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* **Volume Accumulation**: Cumulative Advance-Decline Line (A/D Line) scaled by volume.
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* **McClellan Oscillator**: Index tracking short-term momentum shifts in net advances.
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* **High-Low Index**: Ratio of stocks making new 52-week highs to total new highs/lows.
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* **Sector Rotational Momentum**: Relative strength vectors of Defensive (XLU, XLP, XLV) vs. Cyclical/Growth (XLK, XLY, XLI) sectors.
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* **Beta Distribution spreads**: Dispersion of individual constituent betas relative to index beta.
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### Level 3: Sentiment & Positioning Flow Layer (7 Metrics)
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* **Implied Volatility Structures**: VIX, VIX/VVIX term structure spreads.
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* **Option Flows**: CBOE Equity Put/Call Volume Ratio (10-day moving average).
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* **Retail Positioning**: AAII Bulls-Bears Spread, margin debt levels in retail brokerage accounts.
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* **Institutional Positioning**: NAAIM Exposure Index, CFTC Commitments of Traders (COT) net non-commercial positioning in S&P 500 futures.
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### Level 4: Corporate Fundamental & Accruals Layer (6 Metrics)
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* **Accrual Integrity**: Sloan Ratio tracking earnings quality.
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* **Bankruptcy Probability**: Altman Z-Score for manufacturing and non-manufacturing firms.
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* **Earnings Manipulation**: Beneish M-Score tracking probability of financial statement manipulation.
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* **Financial Strength**: Piotroski F-Score (9-point fundamental health checklist).
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* **Margin Compression Dynamics**: Operating Margin YoY changes, Gross Margin trends.
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### Level 5: Technical Momentum & Volatility Layer (5 Metrics)
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* **Vol Forecasts**: Rolling GJR-GARCH downside volatility forecast vectors.
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* **Relative Strength**: 14-day Relative Strength Index (RSI).
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* **Trend Vectors**: MACD Signal Line Spreads.
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* **Range Expansion**: Average True Range (ATR) normalized by price.
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* **Beta Expansion Multipliers**: Realized beta shifts in high-beta tech components.
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### Level 6: Alternative Data Layer (3 Metrics)
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* **Supply Chain Disruption**: Supply-Chain Velocity Index (Aggregate buyer purchase obligations vs. hardware supplier inventories).
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* **Employment Demand**: Tech sector job postings scraped from aggregators.
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* **Credit Card Transactions**: Real-time consumer retail spending proxies.
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---
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## 3. Whale Reconnaissance Layer
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Designed to track the equity holdings of institutional boutique Value and Small-Cap asset managers via SEC Form 13F filings.
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```mermaid
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graph TD
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A[SEC 13F Filings Ingestion] --> B{Filter Boutique Managers}
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B -- AUM < $5B & High Active Share --> C[Extract High-Conviction Long Positions]
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B -- Large Index Funds --> D[Discard]
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C --> E[Compute Quarterly Position Shifts]
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E --> F[Generate Whale Satellite-Screener Score]
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```
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### Screener Specifications
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* **Target Universe**: Boutique managers with Asset Under Management (AUM) between $100M and $5B, exhibiting an Active Share $> 80\%$.
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* **Quant Filters**:
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1. **Concentration Index**: Top 10 holdings must exceed $50\%$ of the total reported portfolio value.
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2. **Position Size Changes**: Track quarterly additions ($\Delta W_{i} > 2\%$) where the manager is actively building a stake.
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3. **Co-ownership Clusters**: Identify stocks bought by 3 or more selected boutique managers simultaneously.
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---
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## 4. Deep-Dive Corporate Terminal Specifications
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When evaluating an individual equity ticker, the terminal computes three quantitative risk markers:
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### I. The Sloan Ratio (Earnings Quality Indicator)
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Measures the proportion of earnings backed by non-cash accruals. A high ratio indicates that earnings are driven by accounting accruals rather than real operating cash flows.
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#### Mathematical Formulation:
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$$\text{Sloan Ratio} = \frac{\text{Net Income} - \text{Operating Cash Flow} - \text{Investing Cash Flow}}{\text{Total Assets}}$$
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#### Alert Thresholds:
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* **Stable Accruals**: $\le 5\%$ (Green)
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* **Elevated Accruals**: $5\% < \text{Sloan Ratio} \le 10\%$ (Amber)
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* **Toxic Accruals (Manipulative Risk)**: $> 10\%$ (Flashing Neon Rose-Red)
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---
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### II. Analyst Revision Impulse (ARI)
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Tracks the momentum of consensus earnings estimates over a rolling 14-day window to identify positive or negative structural inflections before earnings reports.
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#### Mathematical Formulation:
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$$\text{ARI}_{t} = \sum_{h=1}^{H} \frac{E_{t}(\text{EPS}_{h}) - E_{t-14}(\text{EPS}_{h})}{E_{t-14}(\text{EPS}_{h})}$$
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Where:
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* $E_{t}(\text{EPS}_{h})$ is the consensus EPS estimate at day $t$ for fiscal period $h$.
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* $H$ represents the number of forward fiscal quarters modeled (standard $H=4$).
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---
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### III. GJR-GARCH Downside Buffer
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Calculates the conditional Value-at-Risk (VaR) and Expected Shortfall (ES) at a $99\%$ confidence level over a 10-day forward horizon using volatility projections from Module 1.
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#### Mathematical Formulation:
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$$\sigma_{t}^2 = \omega + \left(\alpha + \gamma I_{t-1}\right) \epsilon_{t-1}^2 + \beta \sigma_{t-1}^2$$
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$$\text{VaR}_{99\%, 10D} = P_{t} \times \left(1 - e^{z_{0.01} \times \sqrt{10} \times \sigma_{t}}\right)$$
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Where:
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* $I_{t-1} = 1$ if $\epsilon_{t-1} < 0$, and $0$ otherwise (asymmetric shock multiplier).
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* $z_{0.01}$ is the $1\%$ quantile of the standardized residual distribution (Student-t or Normal).
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---
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## 5. Multi-Regime Transition Classifier
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The core cognitive brain of the sandbox dynamically adjusts allocation weights across our portfolio modules based on estimated macroeconomic and market states.
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```mermaid
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graph LR
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A[Level 1-6 Inputs] --> B[Dynamic Z-Score Solver]
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B --> C[Markov-Switching Model]
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C --> D{Regime Output}
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D -->|Regime 0: Risk-On| E[Overweight Equities/Growth]
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D -->|Regime 1: Transition| F[Neutral / Hedge overlay]
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D -->|Regime 2: Risk-Off| G[Overweight Bonds/Cash/Short Vol]
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```
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### Model Specifications
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1. **Regime Estimation**: A 3-state Markov-Switching Vector Autoregressive (MS-VAR) model classifying the market into:
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* **Regime 0 (Expansion/Risk-On)**: Low volatility, positive macro surprise, expanding supply-chain velocity.
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* **Regime 1 (Late-Cycle/Transition)**: Softening breadth, rising credit spreads, negative monetization gaps.
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* **Regime 2 (Contraction/Risk-Off)**: High realized volatility, yield curve uninversion, consumer savings depletion.
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2. **Dynamic Weight Allocation**:
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$$\mathbf{W}_{t} = s_t \mathbf{W}_{\text{Risk-On}} + (1 - s_t) \mathbf{W}_{\text{Risk-Off}}$$
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Where $s_t \in [0, 1]$ represents the filtered probability of being in the expansionary regime at time $t$.
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