About River Rose Financial

Economic Research and Quantitative Investing Platform

Our Mission

River Rose Financial is dedicated to developing and deploying sophisticated quantitative investing/trading strategies that leverage advanced algorithms, statistical modeling, and machine learning techniques. Our mission is to generate consistent, risk-adjusted returns by identifying and exploiting market inefficiencies through data-driven decision-making and precision execution.

Trading Strategy

Our flagship strategy focuses exclusively on the Micro E-Mini Nasdaq 100 (MNQ) futures contract, combining several key advantages:

Tax Efficiency: 60/40 tax treatment under Section 1256 provides favorable tax benefits on mark-to-market derivatives
High Liquidity: Deep order books and tight spreads enable efficient execution at scale
Volatility Capture: Technology-heavy composition provides ample intraday opportunities
Leverage Management: Micro contracts allow precise position sizing and risk control

Our algorithms employ a multi-faceted approach incorporating technical analysis, statistical arbitrage, and adaptive machine learning models that continuously evolve with market conditions. The strategy emphasizes risk management through dynamic position sizing, stop-loss protocols, and maximum drawdown controls.

Methodology

Our quantitative framework is built on three core pillars:

Signal Generation: Multiple proprietary indicators analyze macroeconomic structure, price action, volume patterns, order flow, and market microstructure
Risk Management: Position sizing algorithms dynamically adjust exposure based on volatility regime, correlation, and portfolio heat
Execution Optimization: Smart order routing minimizes market impact and slippage through adaptive execution strategies

All strategies undergo rigorous backtesting across multiple market regimes, walk-forward analysis, and paper trading validation before deployment in live markets. Performance is continuously monitored against key risk metrics including Sharpe ratio, maximum drawdown, win rate, and correlation to broader markets.

Data Sources & Technology

Our platform integrates multiple professional-grade data sources and technologies:

Market Data: Real-time and historical futures prices, volume, and order book data
Economic Data: FRED (Federal Reserve Economic Data) for macroeconomic indicators
Benchmark Data: SPY and treasury data for performance comparison and risk assessment
Infrastructure: Cloud-hosted PostgreSQL database with automated backup and redundancy
Analytics: Python-based analysis using pandas, numpy, Scikit Learn, Pytorch, and advanced visualization libraries

Performance Transparency

We believe in complete transparency. Our performance dashboard displays actual trade results including:

Real-time equity curves and cumulative returns
Individual trade details with entry/exit prices and commissions
Win/loss ratios and average trade returns
Risk metrics including volatility, Sharpe ratio, and maximum drawdown
Correlation analysis versus market benchmarks
Comparison to risk-free rate (90-day SOFR)

All performance metrics are calculated using actual executed trades with commissions included, providing an accurate representation of real-world results.

Risk Disclosure

Trading futures and derivatives involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. The data presented on this platform is for informational and educational purposes only and should not be construed as investment advice.

The high degree of leverage available in futures trading can work against you as well as for you. You should carefully consider whether futures trading is suitable for you in light of your financial condition, risk tolerance, and investment objectives. You may lose all or more of your initial investment. Although algorithms can run on substantially lower captial, we show the minimum recommended capital required to trade the strategy effectively while managing risk.

Hypothetical or simulated performance results have certain limitations. Unlike actual performance records, simulated results do not represent actual trading and may not reflect the impact of market liquidity, slippage, and other real-world factors that can adversely affect returns. We recommend using the live trading results as the primary basis for evaluating performance.

Contact & Further Information

For inquiries about our strategies, methodology, or platform capabilities, please contact us at thomas.macpherson@riverrosefinancial.com. We continuously update our research and welcome questions about our approach to quantitative investing/trading.