Prediction Market Execution Lab
Testing executable edge in Polymarket BTC short-horizon markets.
Why It Matters
This project separates apparent market edge from executable edge, which is closer to how real trading and execution research should be evaluated.
Context
Short-horizon prediction markets may show apparent pricing edge, but apparent edge is not the same as executable edge.
What I Built
I built a public research lab with sample data, notebooks, reports, dashboard, execution diagnostics, calibration analysis, ML filtering, and risk simulation.
Research Workflow
- ▹Market data sample
- ▹Signal construction
- ▹Execution funnel
- ▹Fill diagnostics
- ▹Calibration analysis
- ▹Risk simulation
- ▹Public-safe reporting
Key Highlights
- ▹Separates theoretical pricing edge from executable edge.
- ▹Includes public-safe sample data, research reports, notebooks, and a live dashboard.
- ▹Analyzes execution funnel, probability calibration, ML filtering, and risk simulation.
- ▹Explicitly avoids profitability claims and private execution-sensitive details.
What This Demonstrates
- ▹Market microstructure reasoning
- ▹Data analysis and research communication
- ▹Separating theoretical signal from executable outcome
- ▹Building public-safe research artifacts without exposing sensitive execution data
Representative Artifacts
Execution Funnel
Visualizing the degradation of theoretical edge into executable edge due to frictions.
Calibration Simulation
Modeling probability accuracy and risk exposure across varied market conditions.
Research Dashboard
Abstract view of market depth, liquidity metrics, and execution diagnostics.
Tech Stack
This project is presented as a public research and portfolio artifact. It does not represent financial advice, trading advice, or a claim of trading profitability.