About me
“Invest when the market is down” is the first oversimplified concept that was broken down for me in my investments class at 7:30 AM on a Monday this fall. This is where I truly started enjoying reading about the stock market, questioning the concepts, challenging what I believed was correct, and then answering the "why" using technical analysis behind every market change.
On the trading side, I worked on systematic trading using technical indicators and regime analysis, volatility modeling, and portfolio optimization. I've backtested trading strategies on 5-8 year historical data and with an 80% accuracy rate by building systematic models that prompt entry/exit signals and I've backtested strategies on real securities, analyzing equity curves and optimizing performance iteratively. On the investment side, I evaluated opportunities rigorously using capital budgeting frameworks, from equities to commercial real estate, using NPV, Profitability Index, and Payback Period analysis to make data-backed recommendations.
I'm proficient in R for data analysis, predictive modeling, statistical forecasting, and data visualization (Tableau). I've completed Google's Machine Learning Crash Course and built classification and regression models on real datasets.
What drives me: People! My passion isn't just finance; it's using data to solve problems that affect us and drive better decisions, whatever the industry.
