• By combining big data, machine learning and cloud computing, we have developed a fully automated artificial intelligence investment network capable of self-evolution• The AI investment network can provide both classic trading strategies and alternative trading strategies. Core technologies include: policy network, neural network, reinforcement learning, supervision machine learning• We currently provide both App and API for institutional and retail investors to automate the whole investment process, including analyzing mass data, making investment decisions, trading and risk reporting ​•Websites: https://www.ainvest.io/eng

• Worked with research analysts, portfolio managers, and traders from the Global Asset Allocation team on a daily basis to assist in their investment processes• Focused on the development, implementation and management of multi-asset class portfolios including Dynamic Asset Allocation Funds, Absolute Return Funds, Age-based Retirement and College Savings funds• Assisted analysts in the research process including the execution of various short-term analysis projects • Built and updated tools and models using a wide variety of spreadsheet, statistical analysis, and database software applications; tools and models range from individual security analysis to top-down econometric modeling• Created spreadsheets and other documents that effectively communicated key investment positions and risks to team

• Built automatic portfolio rebalancing algorithm to optimize risk-adjusted return, modified threshold rebalancing ranges and frequency. Validated through historical test and Monte Carlo simulations and tracked Sharpe ratio and VaR• Worked closely with associates. Delivered a one-hour presentation and proposed portfolio rebalancing recommendations to the department of Investment Advisory and Portfolio Construction. The project received high remarks from department heads

• Formulated a predictive statistical model to forecast daily volume of mortgage origination, adopted Time Series, Stepwise and Principal Component Regression to improve prediction accuracy and test robustness• Evaluate open source and internally-developed modeling and analytics tools using real business data• Integrate internal data with external data sources and APIs to discover actionable insights• Design and craft rich data visualizations to extract insights and communicate stories to customers and company leadership

• Created a cross currency arbitrage strategy taking advantage of different market liquidity conditions, adopted time series method to predict future liquidity risk based on Liquidity Adjusted VaR

• Assisted team with SEOs of China Modern Dairy Holdings and China National Salt Industry Corporation, prepared material for presentations and attended team meetings• Performed financial modeling and created dynamic three statements, discounted cash flow and trading comparables valuation

• Researched on interest rates of interbank market, interest rate products, LIBOR scandal and the development of SHIBOR