VC INVESTOR DASHBOARD

AI Infrastructure
Intelligence Platform

Quantitative analysis engine combining 13F institutional flow data with multi-factor signal generation and reinforcement-learning portfolio optimization.

2.32
OOS Sharpe Ratio
+88.9%
Annual Return
5
Alpha Sources
6/6
Walk-Forward Windows
+88.9%
Annual Return
RL-Enhanced Strategy
2.32
Sharpe Ratio (OOS)
Out-of-Sample
-11.4%
Max Drawdown
Risk-Managed
+14.2%
Alpha (Annualized)
vs. S&P 500
0.67
Beta
Market Exposure
Live Analysis

Company Intelligence

Real-time analysis combining institutional flow data, multi-factor signals, and regime context for any AI infrastructure company.

Try: NVDA TSMC CEG MSFT AVGO ANET

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NVDA
NVIDIA Corporation
Semiconductors
92
TAF Score
Current Signals
Momentum (5d) +3.4%
Momentum (20d) +12.0%
Mean Rev Z-Score -0.45
Volatility Regime Low
Trend Bullish
Regime Context
Current Regime Risk-On
VIX Level 14.2
Regime Confidence 82%
TAF Exposure 39.5%
Institutional Positioning
13F Net Flow (QoQ) Increasing
Top Holders Signal Accumulating
Smart Money Score 7.2 / 10
Core semiconductor holding, highest TAF sector weight
Walk-Forward Validation

Robustness Verification

Six expanding-window out-of-sample tests confirm strategy robustness across different market regimes.

✓
6/6 ROBUST
All validation windows passed
2.18
Avg Sharpe
+12.8%
Avg Alpha
-14.1%
Worst DD
Performance Analysis

Strategy Comparison

Fixed allocation baseline vs. RL-enhanced adaptive strategy with dynamic regime-aware positioning.

Fixed Allocation Baseline
Annual Return +42.3%
Sharpe Ratio 1.48
Max Drawdown -18.7%
Beta 0.89
Alpha (Ann.) +7.1%
Sortino Ratio 2.01
Win Rate 54.2%
RL-Enhanced Strategy
Annual Return +88.9%
Sharpe Ratio 2.32
Max Drawdown -11.4%
Beta 0.67
Alpha (Ann.) +14.2%
Sortino Ratio 3.87
Win Rate 61.8%
Alpha Sources

Five Independent Signal Generators

📊
13F Flow Analysis
Institutional positioning signals from quarterly SEC filings across elite AI-focused funds
📈
Multi-Factor Momentum
Cross-timeframe momentum signals (5d, 20d, 60d) with volatility-adjusted weighting
⚖
Mean Reversion
Statistical z-score based entry/exit signals for short-term dislocations
🎯
Regime Detection
VIX-based regime classifier with confidence-weighted exposure scaling
🤖
RL Optimization
Reinforcement learning agent for dynamic position sizing and portfolio rebalancing
How It Works

Analysis Pipeline

Five-stage intelligence pipeline from raw data to execution-ready signals.

1
13F Analysis
Ingest and parse quarterly 13F filings from elite AI-focused hedge funds. Track position changes, new entries, exits, and sizing shifts.
2
Signal Generation
Generate multi-factor signals: momentum across timeframes, mean-reversion z-scores, volatility regime detection, institutional flow scoring.
3
RL Enhancement
Reinforcement learning agent processes raw signals to optimize position sizing, entry timing, and portfolio-level allocation decisions.
4
Risk Management
Dynamic drawdown limits, regime-aware exposure caps, correlation monitoring, and tail-risk hedging. Max 39.5% single-sector exposure.
5
Execution
Walk-forward validated signals delivered with confidence scores, regime context, and institutional alignment metrics.
Portfolio Composition

TAF Sector Allocation

Concentrated exposure to AI infrastructure value chain with risk-managed sector caps.

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