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TASHI-VULCAN/README.md

Hi, I’m Tashi Dawa

I build Python-based analytics projects focused on portfolio risk, financial markets, forecasting, and data-driven decision-making.

My background combines data analysis, quantitative modelling, automation, and engineering problem-solving. I am particularly interested in roles across risk analytics, portfolio analytics, financial data, credit risk, and quantitative research.

Featured Projects

Multi-Index Risk & Performance Analytics Dashboard

Interactive Streamlit dashboard for comparing global equity indices and building configurable portfolios.

  • Downloads and cleans historical market data
  • Analyses normalised performance, cumulative returns, annualised return, volatility, and maximum drawdown
  • Allows configurable portfolio weights and benchmark comparison
  • Built with Python, pandas, Streamlit, Plotly, NumPy, and yfinance

Portfolio Risk Engine

Reusable Python risk engine for multi-asset portfolios.

  • Historical and parametric Value at Risk at 95% and 99% confidence levels
  • Expected Shortfall, portfolio PnL, volatility, asset-level PnL contribution, and stress testing
  • Converts percentage risk measures into monetary portfolio impacts
  • Designed using a class-based structure for a clearer and reusable analytics workflow

Risk & Return Forecasting

Quantitative research project using ARIMA, GARCH, and Monte Carlo simulation.

  • Forecasts returns and conditional volatility
  • Compares constant-volatility and GARCH-based scenarios
  • Calculates Value at Risk, Conditional VaR, and portfolio risk measures
  • Uses Python, pandas, NumPy, statsmodels, arch, and SciPy

Technical Skills

Languages: Python, SQL, MATLAB, VBA Data & Analytics: pandas, NumPy, SciPy, scikit-learn, statsmodels, Power BI Financial Modelling: VaR, Expected Shortfall, Monte Carlo simulation, stress testing, time-series forecasting, ARIMA, GARCH Tools: Streamlit, FastAPI, PostgreSQL, Git/GitHub, Excel

Current Focus

Building practical, transparent analytics tools that turn market and portfolio data into useful risk and performance insights.

Pinned Loading

  1. Portfolio_predictor Portfolio_predictor Public

    Quantitative finance project using ARIMA, GARCH and Monte Carlo simulation to forecast returns, volatility and downside risk.

    Jupyter Notebook 1

  2. Multi_index_analytics_dashboard Multi_index_analytics_dashboard Public

    Interactive Streamlit dashboard for comparing global indices, portfolio performance, annualised volatility, drawdown and benchmark returns.

    Python

  3. portfolio-risk-engine portfolio-risk-engine Public

    Python portfolio risk engine for multi-asset portfolios, calculating VaR, Expected Shortfall, PnL contribution, volatility and stress-test losses.

    Python