Econometrics
ECO1012 Econometrics & Forecasting
Throughout the Econometrics and Forecasting module, I have gained practical exposure to statistical analysis, regression modeling, and data-driven forecasting methods that are vital in modern finance. A core aspect of this coursework involves coding, particularly in Python, to clean and visualise datasets, build predictive models, and evaluate outcomes under various financial scenarios. These skills have proven invaluable in developing my individual project, “CUAN: Small Steps Today, Big Rewards Tomorrow,” where I applied these coding techniques to simulate pension contributions over a 45-year horizon.
By blending frameworks from behavioural economics, such as “Save More Tomorrow,” with the FIRE (Financial Independence, Retire Early) movement, the project demonstrates how data analytics and forecasting can illustrate the impact of systematic savings on retirement outcomes.
Beyond theoretical exercises, the coding projects in this module mirror the demands of the finance industry: real-time data sourcing, complex model-building, and clear, evidence-based reporting. The Colab notebook I created validates CUAN’s higher returns compared to Ireland’s auto-enrolment system and showcases how effective coding practices, like iterative data cleaning and regression analysis, enhance both the precision and clarity of financial forecasts.
Our Group App and Pitch Video
