I'm an investment professional based in Frankfurt, with experience across sovereign reserve management, fixed income, insurance portfolios and private markets.
Before moving to Germany, I worked in International Markets & Investments at the State Bank of Pakistan, managing institutional portfolios through the pandemic recovery, the global inflation shock and the monetary-tightening cycle that followed. That experience drew me towards more systematic investment analysis and eventually to Frankfurt School’s Master of Finance in Capital Markets. I later worked on investment analytics and private-market portfolios at Allianz Investment Management.
I’m particularly interested in the point where markets, investment judgement and technology meet—and whether an idea remains useful when it encounters real data, changing regimes and imperfect information.
- Build and test models for portfolio construction, asset allocation and investment risk
- Analyse fixed income, credit, macro regimes and private markets
- Apply Python, machine learning and data analysis to practical investment questions
- Test whether models remain useful out of sample and across changing market conditions
- Turn technical findings into clear, decision-focused investment analysis
Languages & Core Technologies
Python · SQL · R · Stata · VBA
Data Science & ML
pandas · NumPy · scikit-learn · statsmodels · NLP · FinBERT · Jupyter
Data Engineering & Analytics
Power BI · Power Query · DAX · Excel · Tableau
Tools & Deployment
Git · GitHub · GitHub Pages · VS Code
Investment Data & Platforms
Bloomberg · Refinitiv Eikon · S&P Capital IQ · Compustat · eFront · MSCI ESG Manager
Finance & Investment
Fixed Income · Rates & FX · Asset Allocation · Portfolio Construction · Credit Risk · VaR · Stress Testing · Monte Carlo Simulation · Private Markets · ESG Analysis
Python Econometrics Forecasting Portfolio Construction
Tests whether information embedded in equity markets can improve tactical allocation between high-yield and investment-grade corporate bonds. The research uses recursive out-of-sample forecasts, portfolio tests and robustness checks to distinguish plausible relationships from genuinely useful signals.
Repository · Article
Python Asset Allocation Fixed Income Risk Management
Translates policy, macroeconomic and market-stress indicators into four market regimes and corresponding portfolio allocations. The framework is designed to participate in supportive markets while becoming more defensive as risk rises.
Python Credit Risk Monte Carlo Stress Testing
Simulates a CPDO using regime-dependent credit spreads, jump diffusion and dynamic leverage. The analysis also examines how pre-crisis rating assumptions could materially understate the product’s default risk.
Python Portfolio Optimisation Retirement Planning Monte Carlo
Builds an investable retirement plan by combining German statutory pension projections with an ETF portfolio, a dynamic glide path, tax considerations, Monte Carlo simulation and adverse-market stress tests.
Python NLP Machine Learning FinBERT
Compares traditional TF-IDF classifiers with FinBERT embeddings for identifying bearish and bullish financial tweets, including how decision thresholds change when missing negative information is particularly costly.
- 🤖 Exploring how machine learning can improve financial forecasting and investment research
- 📊 Building more intuitive tools for portfolio analysis and data visualisation
- 🌍 Learning more about private markets, sustainable investing and changing institutional portfolios
- 📚 Deepening my work in quantitative finance, fixed income and risk modelling
Outside finance, I like exploring places on foot. One of my favourite experiences was hiking to Nanga Parbat Base Camp; other trips have taken me to Chitta Katha Lake in Kashmir, the Haramosh Valley and historical sites from Mohenjo-daro to Makli. Since moving to Germany, I’ve continued the habit on its hiking trails. I also play squash and rarely turn down a conversation about history or geopolitics.