Biscayne Capital

Systematic Digital Asset Strategies Through Research-Driven Quantification

We develop and apply rigorous mathematical models to digital asset markets. Our research-driven approach seeks uncorrelated returns by exploiting structural inefficiencies in global cryptocurrency exchanges.

>1.2
Target Sharpe Ratio
<0.1
Beta to BTC
<12%
Target Volatility

Empirical Rigor and Theoretical Foundation

Our approach combines academic discipline with practical engineering to develop robust trading strategies.

Hypothesis-Driven Research

We begin with testable hypotheses about market structure, grounded in economic theory and empirical observation. Each hypothesis undergoes rigorous statistical validation before implementation.

  • Literature review of relevant academic work
  • Exploratory data analysis
  • Clear null and alternative hypotheses

Systematic Methodology

Our strategies are fully systematic, removing discretionary elements to ensure consistency and scalability. We prioritize reproducibility and transparency in our research process.

  • Rules-based decision making
  • Version-controlled research code
  • Automated backtesting frameworks

Risk-First Mindset

Risk management is integrated at every stage, from strategy design to execution. We emphasize understanding tail risks and maintaining robust positions under stress scenarios.

  • Daily Value-at-Risk limits
  • Stress testing against historical extremes
  • Real-time exposure monitoring

Academic Foundation

Building on established work in market microstructure, statistical arbitrage, and high-frequency trading literature.

Empirical Testing

Rigorous out-of-sample testing with careful attention to data snooping and overfitting concerns.



Live Implementation

Careful deployment with phased capital allocation and continuous performance monitoring.



Interdisciplinary Research Excellence

Our team combines deep domain expertise from quantitative finance, computer science, and applied mathematics.

Academic Pedigree

Our researchers hold advanced degrees from leading institutions and contribute to peer-reviewed journals in quantitative finance and computational statistics.

MIT
Stanford
Princeton
Cambridge

Industry Experience

Team members have held senior positions at leading quantitative trading firms, bringing proven expertise in systematic strategy development and execution.

Two Sigma
Jane Street
Renaissance
Citadel

Research Focus Areas

Market Microstructure Cross-Exchange Arbitrage Statistical Factor Models On-Chain Analytics Optimal Execution Risk Parity

Quantitative Approach to Digital Assets

Our focus on cryptocurrency markets is driven by unique quantitative opportunities.

Rich Data Environment

24/7 markets generate continuous, high-frequency data for model training and validation. On-chain transparency provides additional signal dimensions not available in traditional markets.

Fragmented Liquidity

Multiple trading venues create persistent pricing inefficiencies. Our cross-venue execution infrastructure systematically captures these relative value opportunities.

Evolving Market Structure

Continuous innovation in market design and trading mechanisms creates new sources of alpha for systematic strategies with rapid research cycles.

Market Structure Analysis

We maintain active research on cryptocurrency market microstructure, including:

  • Order book dynamics across centralized and decentralized venues
  • Market impact and transaction cost analysis
  • Cross-asset correlation patterns and regime detection
  • Funding rate arbitrage and basis trading

Research and Execution Platform

Purpose-built systems supporting our research and trading activities.

Research Environment

Python Jupyter PostgreSQL

Collaborative research platform with version-controlled notebooks, reproducible backtesting, and shared data access.

  • Factor research and signal development
  • Statistical testing framework
  • Performance attribution tools

Execution Systems

C++ Rust Kubernetes

Low-latency execution infrastructure with smart order routing across multiple cryptocurrency exchanges.

  • Direct market access connections
  • Real-time risk checks
  • Transaction cost analysis

Institutional-Grade Risk Framework

Multi-layered risk controls designed for volatile digital asset markets.

1

Strategy-Level Controls

Pre-trade validation, position limits, and scenario analysis at the strategy level.

2

Portfolio-Level Monitoring

Real-time exposure tracking, Value-at-Risk calculations, and correlation monitoring.

3

Operational Safeguards

Circuit breakers, counterparty risk limits, and security protocols.

99.9%
Historical VaR Coverage
<15%
Maximum Drawdown Target
Real-time
Exposure Monitoring

Institutional Investor Inquiries

We work exclusively with accredited investors, family offices, and institutional partners. For detailed information on our strategies, performance, and due diligence materials, please contact our investor relations team.

Past performance is not indicative of future results. Investments involve risk, including potential loss of principal. Digital asset investments are particularly volatile.