Python vs. Excel for financial modeling

Excel and Python are both popular tools for financial modeling and liquidity forecasting, but they have their own pros and cons. Here is a comparison of Excel and Python for these tasks: Pros of Excel for financial modeling: Cons of Excel for financial modeling: Pros of Python for financial modeling: Cons of Python for financial modeling: In conclusion, both Excel and Python have their strengths and weaknesses when it comes to financial modeling and liquidity forecasting. Excel is a familiar and user-friendly tool with a wide range of built-in functions, but it can be limited in terms of scalability and […]

Tools for survival analysis

While survival analysis has been present in academia for quite some time, a lot of data scientist today focus more on neuronal networks, decision trees, random forest, grid search, KNN etc. However, the discipline of survival analysis has gained popularity in various applications. This is the case whenever an analyst it not only interested if an event occurs but rather when the event occurs. In modeling credit risk it is of particular interest when a loan default over time and in turn, understanding how the default probabilities change over time. In this context, survival analysis can help answer questions like: […]