Managed bonds portfolio.Created investment strategy on government and corporate bonds.

Modeled the yield and return of inflation-related bonds and simulated its performance in varying market conditions;Built machine learning ensemble models to predict market return, applied the results to generate the trading signal and back-tested its efficiency in portfolio optimization.

Text Mining project

Enhanced the quantitative value investing algorithm and improved stocks selection step using decision tree models;Developed the quant system containing data preprocessing, portfolio construction, and back-test analysis in Python.

Constructed time series model to predict mutual funds’ds’ future returns and give corresponding rating scores;Designed a global asset allocation product, by combining machine learning-based assets' returns forecasting and market timing models (This product has become the best seller among 5 concurrent products at RENRENDAI);Conducted quantitative strategies and back-tested quantitative trading strategies on Quantopian.

Built a data fusion system to monitor the features of peer-to-peer (P2P) lending companies in China;Developed an ensemble learning-based P2P fraud detection system, which successfully gave warning signals to nearly 100 P2P companies prior to their bankruptcy.

Interviewed the managers at Bank of China (BOC), to help them analyze and classify BOC products;Optimized and complemented the product catalog of BOC, by summarizing more than 1000 products' features.

♣ customer activities and collected data on credit, futures and insurance industries