Managing Customer Loyalty Using Time Series Data

In Chapter 1, Time Series Modeling in the Financial Industry, we briefly touched upon the myth that every time we spoke about time series data and forecasting behavior. While this is true most of the time, it isn't valid on a lot of occasions. It was mentioned that time series data can be used for benchmarking, quality control, pattern recognition, and even estimating the effect of one variable on the observed values of another variable. Survival analysis focuses on estimating time to an event. In Chapter 2, Forecasting Stock Prices and Portfolio Decisions using Time Series Data, while discussing ARIMA, we saw that the model primarily depends on the time component and didn't focus much on the influencer variables. Survival analysis, just like multivariate regression, can also help emphasize the role of other influencer...