Case Studies & Proof Points
Our research and analysis demonstrates how we approach solving complex problems in trading systems, protocols, and market infrastructure.
DEX Market Making Strategy
The Challenge: How do professional market makers optimize capital efficiency and minimize impermanent loss on Uniswap V3? Where should you concentrate liquidity to maximize returns?
Our Analysis: We modeled liquidity provision strategies, analyzed price range optimization, and identified when market making is profitable vs. destructive.
Key Findings:
- Concentrated liquidity can increase capital efficiency by 10-100x, but requires active management
- Price range selection directly impacts profitability
- Gas costs and slippage can eliminate profits if not managed carefully
Why It Matters: Trading firms deploying $10M+ in DEX liquidity make decisions based on this type of analysis. A 1% improvement in capital efficiency = $100K+ in additional returns.
→ See the full analysis: DEX Market Maker Strategy (Uniswap V3)
Protocol Vulnerability & Risk Analysis
The Challenge: How do you systematically identify and analyze security vulnerabilities in DeFi protocols? What does a 6-month exploit investigation reveal about protocol design flaws?
Our Analysis: We conducted an in-depth investigation of the Hedgey exploit, analyzing how attackers exploited mechanism design flaws and what it means for protocol security.
Key Insights:
- Many vulnerabilities stem from game theory oversights, not just code bugs
- Exploit patterns repeat across similar protocol designs
- Early detection requires understanding both the code AND the incentives
Why It Matters: Protocols invest millions in security audits. Understanding vulnerability patterns helps protocols design safer mechanisms.
→ Read the investigation: Hedgey Exploit - 6 Month Analysis
On-Chain Data Architecture & Observability
The Challenge: How do you build a scalable system for monitoring, analyzing, and querying billions of on-chain transactions? How do you make blockchain data actionable?
Our Analysis: We designed a data observability architecture using OpenTelemetry, Kafka, and other enterprise tools for real-time blockchain monitoring.
Why It Matters: Trading firms and protocols need real-time visibility into market activity. Poor data architecture = slow decision-making = lost opportunities.
→ Read the technical guide: Blockchain Data Observability with OpenTelemetry
MEV & Trading Analysis
The Challenge: How do you monitor MEV extraction in real-time? What patterns reveal profitable trading opportunities in relay activity?
Our Analysis: We built systems to analyze MEV-Boost relay trading, identify patterns, and measure profit extraction.
Why It Matters: Understanding MEV helps traders find edge and protocols design fairer mechanisms.
→ Read the analysis: MEV-Boost Relay Trade Profit Monitor
Market Microstructure & Regime Analysis
The Challenge: Do cryptocurrency markets behave like traditional markets? Are price movements stationary and predictable, or regime-dependent and chaotic?
Our Analysis: We tested stationarity assumptions in crypto price data and found that regimes change based on market conditions.
Why It Matters: Trading strategies that work in one market regime fail in another. Understanding regime dynamics prevents strategy failure.
→ Read the analysis: Crypto Regime Stationarity
Liquidity Shock & Mean Reversion Trading
The Challenge: When DEX liquidity suddenly dries up, prices spike. Can traders exploit mean reversion during these liquidity shocks?
Our Analysis: We modeled liquidity shock dynamics and identified conditions where mean reversion trading is profitable.
Why It Matters: Understanding liquidity dynamics reveals high-edge trading opportunities.
→ Read the analysis: DEX Liquidity Shock & Mean Reversion Trading
What These Case Studies Show
Our Approach:
- Deep Technical Understanding — We don't just surface-level analysis; we understand the math, code, and incentives
- Practical Orientation — All analysis is tied to real business impact (cost savings, revenue opportunities, risk mitigation)
- Diverse Expertise — We can work across trading systems, protocols, data infrastructure, and market analysis
- Publication Track Record — Our work is rigorous enough to publish, which means it's rigorous enough for your business decisions
Who We've Helped:
- Trading firms optimize execution and find trading edge
- Protocols understand vulnerability patterns and incentive design
- Dev teams architect scalable on-chain data systems
- Researchers validate quantitative hypotheses
Ready to Work Together?
If you see problems similar to these in your business:
Next Steps:
- Schedule a brief call to discuss your specific challenge
- We'll outline a proposed approach and timeline
- Decide on the right engagement model (retainer, project, or hourly)
We typically work with:
- Trading firms ($10M+ AUM)
- Protocols designing V2+ mechanisms
- Dev studios building trading infrastructure
Not sure if your challenge fits? → Schedule a call anyway. We can point you in the right direction.