Chapter 4: Simulating Financial and Economic Data
Introduction to Simulations
Many of the phenomena and events we study in the data science domain are complex and random. And sometimes we might need to study these events in a controlled environment. For example, a loan portfolio manager might want to study how many loans in the bank’s portfolio will default over a certain period of time, or an equity portfolio manager might be interested in learning how the portfolio would perform over time. The uncertainty faced by both portfolio managers is how to capture the future realizations of the factors that could affect their portfolios over the study period. One way is to wait for the actual outcome to happen, but that approach is unlikely to be ...
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