Applying unsupervised learning using K-means clustering.

Truth Social-driven quant backtest in R testing whether posting volume, sentiment, risk, and de-escalation language predict next-day returns in GLD and SPY. Finds limited signal for gold, but stronger risk-adjusted results for equities, where several text-based strategies outperformed Buy and Hold.

Creation and analysis of a core long-term portfolio composed of ETFs only with flexible quotes.

Back-testing and time series analysis to optimize rotational ETF strategies with downside protection.

This Shiny application analyzes the factor exposures of ETFs using the Fama–French 3-Factor Model, with region-specific factor data and rolling regressions to detect style drift over time.