Imperial MSc Finance Supplemental Essay Example: Boundary Case (Score 93)

I built proficiency in Python and R through coursework and applied projects during my BSc Finance at Universitas Indonesia. Python experience began in econometrics modules using pandas and statsmodels for regression analysis, then deepened through self-directed financial modelling—Monte Carlo simulations and risk-metric computation. In R, I completed time-series forecasting assignments with the forecast and tidyverse packages, developing fluency in data wrangling and visualization. I have also used Excel VBA to automate financial calculations and scenario analysis in group projects, bridging classroom methods and practical workflow. The clearest output of these skills is a portfolio risk dashboard I built for my finance applied project. Using Python, I integrated yfinance and matplotlib to collect and visualize historical price data for a basket of Indonesian equities, then constructed an interactive Jupyter Notebook tool to simulate portfolio returns under different weighting schemes. The dashboard let my team analyse how volatility and correlation shaped portfolio risk; we presented findings to faculty and a local asset management firm. The project required translating quantitative methods into actionable insights, reinforcing my ability to connect programming with financial decision-making. I recognise the MSc will demand stronger data-analytics capability. I am currently completing a Coursera course on machine learning with Python, focusing on supervised learning techniques relevant to asset pricing. Before term starts I also plan to finish the programme's recommended pre-sessional modules in statistics and coding so I can contribute confidently to group work and engage fully with the technical curriculum from day one.