As an FRM candidate, I focus on quantitative risk analysis, portfolio analytics, and financial modeling. Through data-driven tools and analytical models, I apply financial theory to real market data to better understand portfolio behavior, risk exposure, and market dynamics.
I'm Karamjeet Singh, an FRM candidate with a strong interest in financial risk management, quantitative analysis, and portfolio analytics.
I enjoy exploring how financial markets behave and how risk can be measured, modeled, and better understood using data. My work combines financial theory with AI to build data driven models to analyze portfolios, evaluate risk exposure, and study market dynamics.
I am particularly curious about how analytical tools and quantitative frameworks can transform complex market data into structured insights that support better financial decision-making.
Mean-variance optimization engine. Computes the efficient frontier, Max Sharpe, Min Variance and Equal-Weighted portfolios from live yFinance data. SLSQP solver with short-selling toggle.
Institutional-grade VaR engine. Historical, Parametric and Monte Carlo simulation with true daily-path drawdown analysis. Multi-portfolio comparison with sensitivity matrix across horizons and confidence levels.
Open to full-time roles and research collaborations in quantitative finance and risk analytics.
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