Summary

In this chapter, we have discussed multiple-factor linear models. Those models could be viewed as a simple extension of the CAPM, a single one-factor linear model. These multifactor models include the Fama-French three-factor, Fama-French-Carhart four-factor, and Fama-French five-factor models.

In the next chapter, we will discuss various properties for time series. In finance and economics, a huge amount of our data is in the format of time series, such as stock price and Gross Domestic Product (GDP), or stocks' monthly or daily historical prices. For time series, there exist many issues, such as how to estimate returns from historical price data, how to merge datasets with the same or different frequencies, seasonality, and detection of auto-correlation. Understanding those properties is vitally important for our knowledge development.