Currently I am Global Quantitative Analyst at Bank of America. I can be reached at ffeng38@gatech.edu or fengfly@outlook.com • During Summer 2022, I am interning as Global Quantitative Analyst at Bank of America at Atlanta. My role is to quantify how energy price change impacts green building rental rates under different climate scenarios using regression models. In addition, I will find relevant factors (like macroeconomics factors and other indicators) to predict CRE (commercial real estate) probability of default (PD), loss given default (LGD) and etc. using classification modelsIn addition, I have the following skills:• Design and Implement Algorithmic Trading Strategies: Firstly, I designed trading strategies using both technical, fundamental variables and applying machine learning models like lightGBM/SVM to construct long-short portfolio based on predicted stock returns. Then, I did extensive amount of work of feature engineering based on the basic factors (ex. financial ratios, technical indicators) using techniques like genetic programming, generated features from ML models and etc. Lastly, I constructed different neural network (NN) models (ex. 1-d CNN, LSTM, DNN) and used the weighted predictions from ensemble of different NN models to adjust my portfolios (both stock selection and allocation) in order to get a higher risk-adjusted return.• Data/Quantitative Analytics: Extensive data analytics using Python, R and MATLAB throughout a number of data analysis and CS courses, projects (housing project, relational database project, financial market project, Monte Carlo Simulation Project, etc.) and two summer quant internships in which I efficiently applied my data analysis skills.• Financial Modelling: extensive application of factor models learned from classes and machine learning models to make prediction of future commodity price, and making long/short position-neutral trading strategies, pair trading strategies and etc. I assisted financial traders (forex & commodity futures) in finding trading opportunities.