- Classified stocks according to their industry and operating characteristics, tested up to 164 fundamental indicators for stocks in the same classification, and constructed strategies based on the valid indicators shown in the test results.- Improved the original single-factor testing and multifactor model back-testing framework, and reduced the run time by 60% compared to the original.- Maintained the factor database and wrote the data dictionary for the factors.

- Constructed an industry momentum-enhancing strategy in stock markets based on the herd effect, with an annualized return of 16% and a Sharpe ratio of 1.5 when considering transaction fees.- Predicted futures spreads based on Bayesian formulas and developed arbitrage strategies by comparing actual spreads with predicted spreads.

- Assisted in the construction of the risk database and the update test of the risk management platform using SQL.- Developed a Python-based framework for testing the validity of credit risk control models.- Constructed a credit scoring model using logistic regression and random forest algorithm.- Predicted the asset growth rate of the money fund “Smart Deposit” using a linear model, improving the accuracy by 30%.

- Assisted in the project "The Asian Financial Observation 2018".- Reviewed the banking industry in Southeast Asia and summarized its development in terms of asset size, asset quality, profitability and growth.

- Analyzed company and product strategy based on target markets, consumer preference and industry trends.- Conducted fundamental analysis using financial statements with focus on growth, profit quality, and market share.- Assisted industry analysts with weekly, monthly and in-depth research reports.