Mohammad Valizadehmoghadam

It analyzes unstructured news to surface emerging fraud and scam trends across jurisdictions, automates monitoring workflows, and supports proactive operational risk stakeholders with API-driven delivery.

The notebook covers instrument pricing and sensitivities, historical simulation for VaR and Expected Shortfall, VaR backtesting, a severe macro stress scenario, risk limits, DV01 by tenor, factor correlations, and FRTB liquidity horizon scaling.

It follows the same order of steps a desk would use so the story stays grounded in practice.

The index combines long-horizon cleaned data, GARCH-based resilience signals, and anomaly detection (e.g. Isolation Forests, K-Means) to produce stability scores and flag outliers compared with traditional econometric baselines.

I combined returns, fundamentals, and index data into a panel and replicated seven style factors. Each month names land in five equal weight quintiles; the factor return is the spread between top and bottom. I compare to Capital IQ with Newey-West inference, apply a turnover haircut, and include a book to price case study plus subsample checks.

The work evaluates alternative risk transfer (ART) structures, benchmarks peers, scenarios for setup and annual fees, and highlights capital optimization opportunities for senior stakeholders.

Planned scope includes Python-based workflows, VaR and related risk measures, and optimization methods for portfolio construction — details will be updated as the project matures.