• Used Python to generate trading signals and alpha for various financial instruments, including 2-year T-Note futures, 5-year T-Note futures, 10-year T-Note futures, 30-year Treasury bond futures• Undertook thorough analysis on 10-year T-Note futures and 30-year Treasury bond futures, leveraging data from every 2-month over different time intervals• Monitored ongoing market conditions and provided trading insights, decisions, and liquidity impact analysis to make predictive modeling• Participated in a working paper on historical return and risk properties of equity-hedged options across the S&P 500 option surface with three metrics: return volatility, losses under stress tests, and conditional value at risk• Investigated the potentials for alpha gained from selling delta-hedged S&P 500 options classified by their time to maturity and moneyness

• Conducted research on Hyper-Parameter Optimization for machine learning and deep learning models including Random Forests, Gradient Boosting, SVM, and Neural Network• Performed Bayesian Optimization algorithm on various models by Python, successfully delivered the best performing hyper-parameter configurations and architectures, and acquired clear understanding of linear regression, machine learning, and deep learning models

• Participated in a working paper on historical return and risk properties of equity-hedged options across the S&P 500 option surface with three metrics: return volatility, losses under stress tests, and conditional value at risk• Investigated the potentials for alpha gained from selling delta-hedged S&P 500 options classified by their time to maturity and moneyness

• Inspected market price factors and statistics of COVID-19 to study market performance under COVID-19 conditions• Initiated a new momentum variable to indicate the increase and decrease of all factors, and examined stock market performance through Python, utilizing data of current market, COVID-19, and NYC weather• Inquired into PCA, LDA, and Ridge, found suitable factors through LASSO, and constructed models to estimate S&P 500 index• Performed back-testing and diagnostic tests such as VIF, BP test, Anderson-Darling Test, ADF, and Yule-Walker

• Researched specialized reference and market information in a team of four, including a senior analyst• Reviewed past sales performance of first party and assessed influence of internal and external variables on its products• Collected and organized relevant variables in sales forecast and determined impact of each variable to convert business problem into model for three products of first party• Investigated information on clients’ sale data, prepared PowerPoint presentations, and made translations per client needs