Statistical Modeling in Anaconda

In this chapter, we will first present the simplest statistical model: the one-factor linear model. To make the learning process more interesting, we will discuss an application of such a model: the famous financial model called the Capital Asset Pricing Model (CAPM). In terms of processing data, we will show you how to detect and remove missing values, and how to replace missing values with means or other values in R, Python, or Julia. Also, outliers would distort our statistical results. Thus, we need to know how to detect and deal with them. After that, we talk about multi-factor linear models. Again, to make our discussion more meaningful, we will discuss the famous Fama-French 3-factor and 5-factor linear models, and the Fama-French-Carhart 4-factor linear model. Then, we will discuss how to rank those different models, that is, how to measure...