FMT-2300 — Financial Modeling
In this course, students examine and manipulate financial data for effective financial projections. Students learn what financial modeling is and how machine learning can be used to create a model of a company or organization’s financial situation. Students also examine which software is currently used in the industry for financial modeling. Additionally, students perform basic linear regressions for financial data using software. They learn how financial models are built by determining the functional form of the models, identifying the explanatory variables, selecting the appropriate data types, and cleaning and preparing the data for analysis. Using statistical software, students estimate models, interpret coefficients, evaluate the model using statistical metrics and perform sensitivity analyses to assess model robustness. Students examine how financial modeling assists with revenue forecasting, portfolio optimization, and risk management. Lastly, students examine ethical and regulatory considerations in data analysis. Examine how basic financial models are built. Estimate a simple linear regression using statistical software. Evaluate financial models using statistical metrics. Explain the application of machine learning in financial modeling. Examine how financial modeling assists with revenue forecasting, portfolio optimization, and risk management. Evaluate ethical considerations and best practices in data analysis.
Prerequisites: ECN-2010, FMT-1100, ECN-1030