Panamax

Trading:PanamaxFreight and Commodities Analytics:CapesizeIron OreContainersWeatherDigitalization:Vessel PerformanceInternal Application Development

Under the Maritime and Port Authority Global Internship Award (MPA GIA)Panamax Desk (Maritime / Ocean Transportation)• Using VBA and Stata, conducted analysis on Cycle data to determine the best performing cycles and their composition for the recommendation of future cycle constructions• Using the Veson iMOS platform, extracted vessel Voyage data (For various journey inclusive of NOPAC backhauls, AUS backhauls, Conti, etc)• Subsequently applied VBA scripts to clean data, determine appropriate Weather Factor (WF%) to apply to pricing strategies

• Individually responsible for branch-wide sales, accounts and administration; generated 300 accounts for SGD 180,000 in Q2 and 337 accounts for SGD202,000 in Q3 2017, for respective sales increments of 37% and 41% over the previous year, and surpassing set targets within 80% of the allotted time period• Generating an annual revenue stream of 1.5 million alongside the General Manager at the company HQ via the development of optimized sales pitches, considering customer preferences, budget and spending patterns• Conceptualized various ideas for company-wide sales and marketing initiatives such as online platform adverts via slogan design, strategic product placement and target audience determination• Developed materials for the group’s coaching arm, which eventually won the company 2 governmental school contracts at the Primary and Secondary level

• Conducted forecasting of possible risk losses of SGX-DC and its clearing members with 20-year trading data, by writing Python codes, applying machine learning models (Random Forest, SVM, Ridge, LASSO, Elastic Net, PLS) to:i) impute/proxy missing returns data, and subsequently,ii) generate daily Mark-to-Market Profit and Loss• Construction of actuarial models (non-parametric) to determine the appropriate level of risk coverage required by SGX-DC• Implemented prototypes of SGX risk management framework, particularly for Industry-Wide Stress Test• Analyzed SGX statistical stress test Python codes, to identify possible loopholes in capturing possible unrealized market movements and phenomena• Conducted quantitative comparisons of empirical distribution of returns to SGX framework output to determine the appropriateness, rigor, and validity of their risk management systems