Quantitative Platform Blueprint & Execution Handbook
A comprehensive, mathematically rigorous reference manual for professional traders, quantitative analysts, and fundamental investors. Learn the formulas, invalidation rules, statutory insider metrics, and portfolio risk equations powering this terminal.
Chapter 1: The 4 In-Terminal Modular Workspaces
Traditional terminals force analysts to scroll through hundreds of stacked widgets, causing severe cognitive overload and losing chart context. Our terminal splits analysis into 4 modular domains anchored directly beneath the live price chart:
Answers: “Where do I enter, where is my stop, and when do I take profit?” Houses the Minervini VCP accumulation ladder, Intraday Position Sizer, and ATR14 volatility bands.
Answers: “What are politicians, corporate executives, and option market makers doing?” Displays US House/Senate STOCK Act filings, dark pool ATS volumes, and options sweeps.
Answers: “How healthy is the company and what is the macro regime?” Displays 5-Factor profile radar, 9-point Piotroski F-Scores, and FRED 10Y-2Y yield curve spreads.
Answers: “If a peer or supplier collapses, how does the shock cascade?” Displays directed supply-chain topologies, Cornish-Fisher M-VaR, and self-healing hit rate calibrations.
Chapter 2: Algorithmic Execution Formulas & Sizing Math
Our execution engine replaces emotional discretion with concrete mathematical boundaries based on Mark Minervini's Volatility Contraction Pattern (VCP) and Linda Raschke's 20 EMA pullback setup.
📐 1. Exact Position Sizing Equation
Never risk more than your pre-defined capital threshold ($1\%–2\%$ of account equity per trade). The terminal calculates exact share volume using:
Example: With a \$50,000 portfolio risking 1% (\$500) buying NVDA at \$213.05 with a Stop Loss at \$201.35 (\$11.70 per share risk), the sizer dictates buying exactly 42 shares.
🎯 2. Dual Take-Profit Ladder (TP1 & TP2)
Formula: Spot + (2.5 * ATR14). Once price touches TP1, sell 50% of the position to lock in profit and automatically raise the stop loss on the remaining 50% to breakeven.
Formula: Spot + (4.5 * ATR14). Trail the remaining 50% runner along the 20 EMA until a daily candle closes below the moving average.
Chapter 3: Congressional STOCK Act & Political Alpha
Under Public Law 112-105 (Stop Trading on Congressional Knowledge Act of 2012), members of the US Congress and Senate are legally required to disclose securities transactions within 45 days.
How the Terminal Filters Actionable Political Signals:
- Filing Lag Decay: Trades disclosed near the 45-day statutory deadline are penalized in conviction scoring to prevent retail traders from buying the tail end of an expired legislative catalyst.
- Committee Jurisdiction Overlap: Trades are weighted 2.5x higher when a member sits on a committee with direct oversight of the traded asset (e.g. Armed Services purchasing Defense contractors, Energy & Commerce purchasing Semiconductors).
- Option Sweeps vs. Equity: Deep In-The-Money (ITM) Call purchases (e.g., Nancy Pelosi LEAPS) indicate leveraged institutional accumulation with defined downside floor risk.
Chapter 4: 5-Factor Fundamental DNA & Piotroski Score
The platform synthesizes thousands of fundamental balance sheet data points into a multi-dimensional quantitative profile:
Calculated via 3-year revenue CAGR, forward EPS expansion rate, and free cash flow acceleration.
Measures Return on Invested Capital (ROIC > 15%), gross profit margin moats, and low financial leverage.
Derived from PEG ratio, EV/EBITDA multiple discounts, and enterprise DCF fair value spreads.
Scores 8-9 indicate pristine balance sheet quality; scores ≤ 3 signal structural accounting insolvency.
Chapter 5: Tail Risk Modeling & Cornish-Fisher Modified VaR
Standard Gaussian Value-at-Risk assumes that asset returns follow a symmetric normal distribution. In reality, equity markets exhibit negative skewness (sharp crashes) and excess kurtosis (fat tails).
Cornish-Fisher Expansion Formula:
Where S represents sample skewness, K represents excess kurtosis, and z_alpha represents the standard normal quantile (e.g. 1.645 for 95% confidence). This accurately reflects real-world tail crash risk during market liquidity shocks.