• Designed models for company to quantify market risk. Reduced about 17% and 30% risk for different time periods.• Conducted stress testing for different type of risks and other large model validations, improved about 25% ratio model accuracy.

• Monitored futures market and stock market and executed trading according to strategies to maximize returns. • Kept up to date with market news and exchange rules and notified clients in a timely manner.• Mining market data (equity market data, commodity market data…) to find market drivers and develop trading strategies (trend following strategy, statistical arbitrage strategy, factor-based investing, machine learning…) with Python; optimizing different trading strategies (Parabolic SAR, Fama-French three factor model…) • Calculating and setting warning signals for different financial products based on the daily volatility of their underlying assets; analyzing the reasons for value changes and writing reports.

• Digitized factors, collected and processed data, and build models to find the correlations between car crashes and weather factors and to quantify the importance of each factor for the car accidents.• Offered possible solutions to reduce car accident claims based on the results of models. Reduce the number of claims and increase the profitability.

• Lead a team of 6 students in building models to estimate economic capital, quantify the operational risk, and allocate capital across the business into different sales, products and portfolios• Perform various distribution analyses to estimate the frequencies for six loss categories and the Value At Risk under a 99.9% confidence level based on a transformed dataset, quantifying the maximum loss of each category for the next year.• Adopt the basic indicator approach and standardized approach based on the requirements of Basel II to find the range for economic capital of operational risk.• Analyze the firm’s risk profile and allocate the capital into different platforms based on their proportions of total potential loss, improving the accuracy of risk estimation.

• Built structure models and statistical scoring models based on the analyses of target companies’ financial statements to calculate the default probabilities and improved the precision of the model by removing irrelevant factors, transforming variables and winsorizating.• Analyzed the impact of the interest rate change under the term structure model on financial market (exchange rate, swap, duration gap…) and the hedging strategies, and built model to estimate the potential interest rate risk and to quantify the durations of different financial products (zero-coupon bond, floating-rate bond…)• Analyzed applicants' financial status, credit, and property and provided credit division with support to determine feasibility of granting loans.• Analyzed clients’ risk appetite and liquidity tolerance and gave investment suggestions according to some liquidity models and finance ratios.

• Built daily trading volume model to quantify the liquidity risk of a given transaction and analyzed the causes of liquidity risk and hedging strategies.• Performed extensive valuations and pricing analyses based on SEC filings (10K, 10Q…) and utilized momentum strategy and models to estimate the performances of certain stock and portfolio, providing supervisor with support to give suggestions to clients.• Ran regression to find the relations between the target portfolio and other stocks, conducted the stress testing, simulated the performances and discussed hedging methods with team members.• Priced financial products (options, swaptions…) to ensure no arbitrage.