Ryan Watts

I'm Ryan Watts, a Statistics and Data Science student at the University of Colorado Boulder with an unshakeable fascination for capital markets that began in high school and has only intensified over time. There's something magnetic about the intersection of mathematical rigor and real-world application that drew me to quantitative finance, where elegant algorithms meet the raw volatility of financial markets, and results are delivered in real-time.

My journey started simply enough during my sophomore year of high school, dabbling with moving average strategies for Bitcoin on Robinhood. What began as curiosity quickly became a multi-year rabbit hole that led me deep into the mechanics of spreads, market microstructure, high-frequency trading, and the mathematical foundations that underpin modern markets. This exploration transformed me from a casual observer into an active market maker, applying statistical models and algorithmic strategies to capitalize on inefficiencies in illiquid cryptocurrency markets.

Today, my work spans everything from developing sophisticated trading frameworks like TradeByte (built with Python and Rust for performance-critical components) to implementing complex statistical models for options pricing and correlation strategies. At CU Quants, I quickly rose from member to VP and eventually President, leveraging my skills in AWS, Python, and quantitative modeling to lead our club's technical initiatives. We focus on rigorous backtesting, risk management, and the application of advanced mathematical concepts like Markov processes and stochastic calculus to real-world trading scenarios.

Beyond the markets, I'm drawn to intellectual challenges that mirror the quantitative thinking required in finance: poker strategy (with its probability calculations and game theory), mathematical puzzles, and complex optimization problems. Having lived in both Colorado and New York, I've developed an appreciation for different perspectives on finance and life. When I'm not coding trading algorithms or running Monte Carlo simulations, you'll find me on the slopes skiing or exploring Colorado's trails on my bike.

Capital markets captivate me because they represent the ultimate real-time feedback loop, where statistical models meet market reality, and success is measured not just in academic understanding, but in tangible, immediate results that validate or challenge your quantitative hypotheses.