This project studies the effects of the shape parameter estimator uncertainty at different threshold levels on the value-at-risk confidence interval for quantitative risk management (QRM) using the Generalized Pareto Distribution (GPD) from the Extreme Value Theory (EVT) approach.

The significance test for Granger causality of financial risks in stock indices

A股个人择时选股系统 — 三级择时漏斗 × 财务排雷 × 量化策略引擎 | FastAPI + Next.js 16 + SQLite

🏦 Machine Learning system for credit default prediction using a RandomForestClassifier. Features an end-to-end pipeline including synthetic financial data generation, robust preprocessing (ColumnTransformer), and comprehensive evaluation with ROC-AUC and Confusion Matrices.

Data-driven optimization of Teradyne’s excess inventory approval process using Python, lead-time adjusted demand modeling, and financial risk analysis to improve capital efficiency and reduce excess spend.

A comprehensive implementation of the ID3 Decision Tree algorithm from scratch for financial risk assessment, featuring custom entropy calculations, information gain optimization, and detailed data preprocessing.

Macro-financial stress testing framework projecting UK bank capital under baseline and adverse macroeconomic scenarios.

Global Systemic Fragility Observatory 2026 · Markov Model + Monte Carlo · Synthetic Bubble · 10 non-conventional systemic risk indicators · MCSH Framework · semanticfieldscience.org

AI-powered financial risk intelligence platform — XGBoost + RAG + LangChain + Streamlit

A statistical pipeline for multi-asset market data (2010–2025). Features automated cleaning, volatility engineering, and latent sentiment extraction using PCA and Factor Analysis

Credit-Scoring-Analysis

Loan default risk EDA — End-to-end exploratory data analysis on imbalanced financial data (11.39:1 ratio). Univariate and bivariate segmentation by income, age, education, and organization type.

Monte Carlo based portfolio analytics engine with portfolio optimization, efficient frontier, and institutional risk metrics.

Built a multi-horizon (1–5 year) bankruptcy early-warning system on 43K+ firms using 64 financial ratios. Compared Altman-style linear models (ROC-AUC ~0.71) with XGBoost (ROC-AUC up to 0.97), adding temporal regime and cost-sensitive threshold analysis.

Mortgage risk analysis and forecasting project using Python and statistical modelling

Intelligent EMI prediction & financial risk assessment platform with dual ML models (Classification + Regression) and MLflow experiment tracking

Institutional-grade early warning system for systemic deleveraging events

Predictive modeling system for identifying high-risk financial transactions using time-based validation.

Power BI dashboard analyzing loan default risk using borrower financial data and risk indicators.