What is Lexington QRG?
Hear what our members have to say about their experience
"Lexington QRG taught me how to apply statistical models and mathematical analysis to real markets. Learning to backtest strategies and calculate risk-adjusted returns has been invaluable for my quantitative finance journey."
"I never realized how powerful Python could be for market analysis. Building algorithmic trading strategies and coding technical indicators has shown me the intersection of computer science and quantitative finance."
"The club's focus on data-driven decision making transformed how I approach markets. Using regression analysis and probability theory to identify market inefficiencies is far more reliable than emotional trading."
"Even as a beginner, I'm learning to use mathematical models like moving averages and Bollinger Bands. The systematic approach to risk management through position sizing formulas makes trading feel like applied mathematics."
"Developing my own quantitative strategies using machine learning techniques set me apart in college applications. The skills in statistical arbitrage and pairs trading I learned here are directly applicable to my future in finance."
"Understanding concepts like Sharpe ratios, beta calculations, and portfolio optimization theory has given me a huge edge. The club's emphasis on backtesting and data validation ensures our strategies are statistically sound."
