Engineered for Alpha
Across All Market Cycles
Two-Pillar Investment Framework
- Fundamental Research (PSIF)
- Equity & ETF
- Infrastructure & Crypto
- Alcazar 5 & Risk Parity
- Machine Learning
- Dynamic Hedging
Long Market Strategy
Equity & ETF
Strategic long positions in high-conviction global equities and thematic ETFs. Our equity selection is guided by the PSIF framework — a proprietary methodology that evaluates companies across multiple dimensions of quality, sustainability, and long-term value.
Infrastructure & Crypto
Exposure to hard assets and real infrastructure provides inflation protection and income stability. Our digital asset allocation serves as the primary institutional gateway to the emerging crypto asset class, sized appropriately within a diversified portfolio.
Fundamental Research (PSIF)
The PSIF framework is Elevate's proprietary investment methodology for fundamental analysis. It provides a rigorous, repeatable process for evaluating investment opportunities across sectors and geographies, ensuring disciplined asset selection and portfolio construction.
Quantitative Strategies
Algo Trading
Algorithmic trading utilizing a robust Python-based infrastructure. Rules-based automation that removes emotional bias and executes with precision across market conditions.
High Frequency Trading
A speed-optimized subset of algorithmic trading designed to capture micro-market inefficiencies. Our HFT infrastructure enables rapid execution at scale.
LLM / AI Forecasting
Large Language Models integrated for sentiment analysis and unstructured market data processing. Advanced AI forecasting and pattern analysis for uncorrelated signal generation.
Dynamic Hedging
Variable risk profile allocation that adapts to market stress and opportunity. Our dynamic hedging framework is designed to protect capital while preserving upside participation.
Alcazar 5
Richard Dedu, Ken Luu, and Dereck Nielsen
High-volatility strategy to exploit rapid shifts in market volatility and interest rate regimes through dynamic ETF rotation
Proprietary rules-based engine with variable risk profile
Python-based algorithmic trading system with HFT capabilities
Performance Snapshot
| Metric | ECM | S&P 500 |
|---|---|---|
| Cumulative Return | 772.9% | 81.5% |
| Annualized Return | 114.6% | 0.99% |
| Sharpe Ratio | 1.65 | 1.38 |
| Max Drawdown | -41.0% | -18.8% |
| Calmer Ratio | 2.79 | 1.25 |
Past performance is not indicative of future results.
Risk Framework
Diversification
Portfolio construction across uncorrelated strategies, asset classes, and time horizons to minimize systemic exposure.
Dynamic Allocation
Continuous rebalancing and regime detection to adapt the portfolio to changing market conditions in real time.
Drawdown Controls
Hard stop-loss thresholds and volatility-triggered de-risking protocols protect capital during periods of market stress.
Correlation Monitoring
Ongoing analysis of cross-asset correlations ensures that diversification benefits are maintained throughout the portfolio lifecycle.
Stress Testing
Regular scenario analysis and stress testing against historical market crises inform portfolio construction and risk limits.
Transparency
Investors receive regular, detailed reporting on portfolio composition, risk metrics, and performance attribution.