Quantitative geopolitical risk dashboard tracking Iran-Israel conflict escalation via market signals, GDELT news analytics, and probabilistic portfolio regime guidance.

A market state factor based on graph automorphism group analysis. Detects market homogeneity through orbital structure of stock correlation networks, providing signals for risk management and portfolio construction.

Risk attribution report for portfolio management, using MatLab and Excel

Essential techniques to assess financial risks

Repository represents python usability of measuring and managing risks (practice tasks and real cases)

Quantitative analysis techniques with Python and Pandas to determine which portfolio is performing best across many areas: volatility, returns, risk, and Sharpe Ratios.

Quantitative risk infrastructure for Meridian Private Bank. Three Monte Carlo methods - LHS for venture valuation, scenario-based correlated simulation for macro stress testing, and historical simulation for LP reporting. Calibrated against Q1 2026 Iran war oil shock.

Real-time multi-symbol correlation matrix, MetaTrader currency strength meter and basket exposure heatmap for MT5 / MT4. Exposes hidden cross-pair risk, hedged positions and redundant trades across an entire forex portfolio.

Calculate VaR of Tesla Equity share with Historical, Variance-Covariance and MonteCarlo simulations methods

Mobile-first MRI-based market regime interpretation engine with risk-adjusted confidence modeling.

MATLAB multi-asset intelligent research dashboard with agentic AI analysis, portfolio risk, technical indicators, crypto data, and DeepSeek reports.

Portfolio credit risk modeling project evolving from independent to multi-factor migration, with regime stress and tail diagnostics. Part of a broader transition toward quantitative finance and systematic risk modeling.

Offline market risk analytics engine for VaR, ES, backtesting, stress testing, EVT, copulas, and risk attribution.

Reusable portfolio risk backend with FastAPI, CSV uploads, VaR/CVaR, drawdown, concentration, stress scenarios, Docker, and documented methodology.

Python framework for multi-asset portfolio market risk analysis including rolling beta, VaR/CVaR, Monte Carlo simulation, stress testing, and risk decomposition.

A Python-based portfolio optimization tool that implements Modern Portfolio Theory (MPT) to create efficient portfolios.

Research platform for MOEX liquidity, derivatives, risk, and execution analysis.

A credit risk modeling project using Logistic Regression to estimate Probability of Default (PD) and compute Expected Loss (EL) using a Basel-style framework. Includes stress testing under macro shocks and analysis of key drivers like interest rate, income, and debt-to-income ratio. Provides interpretable risk insights with ROC-AUC evaluation.

Full-stack portfolio risk & stress-testing platform — historical VaR/CVaR, Fama–French factor models, and crisis/macro-shock scenarios. FastAPI · Next.js · PostgreSQL · Celery.

SQL-backed volatility forecasting and market risk platform using Python, DuckDB and Streamlit, with realised volatility estimators, EWMA/GARCH/HAR forecasts, VaR/ES backtesting, regime detection, model validation reports and dashboard analytics.