Local Stochastic Rough Volatility: Pathwise Filtering and the Conditional Density Equation
Pathwise filtering for local stochastic rough volatility models through the conditional density equation.
Upload any quantitative research — arxiv, journal, or internal,
and get a structured, reproducible implementation. Same day.
Product
Library
Pathwise filtering for local stochastic rough volatility models through the conditional density equation.
Consistency conditions for option prices across maturities when bid-ask spreads are bounded.
How utility preferences and risk measures interact when a portfolio is chosen.
Liquidating positions across several assets in dark pools exposed to adverse selection.
How it works
Upload a PDF or research document
Choose the models and, optionally, add a dataset from DataHub
Watch the analysis progress and explore the Research Report
Access your GitHub repository and continue development
What you get
Review experiment results, assessments, and reproducibility insights in one comprehensive report
Every implementation is stored in its own GitHub repository, ready to fork, modify, and maintain
Fine-tuned AI models, accessible via MCP for your agent workflows
Who it’s for
Publish reproducible code alongside your research
Move from research to implementation without days of boilerplate engineering
Publish reproducible code alongside your research
Convert quantitative research into production-ready code
Get started