Many economic time series do not have a constant mean and most exhibit phases of relative tranquility followed by periods of high volatility. Much of the current econometric research is concerned with extending the Box–Jenkins methodology to analyze these types of time-series variables. This chapter has three aims:

- Examine the so-called
*stylized facts*concerning the properties of economic time-series data. Casual inspection of GDP, financial aggregates, interest rates, and exchange rates suggests they do not have a constant mean and variance. Many seem to have a decided upward trend, while others seem to meander and show periods of high and low volatility. A stochastic variable with a constant variance is called**homoskedastic**as opposed to**heteroskedastic.**^{1}For series exhibiting volatility, the unconditional variance may be constant even though the variance during some periods is unusually large. - Formalize simple models of variables exhibiting heteroskedasticity. Asset holders are interested in the volatility of returns over the holding period, not over some historical period. This forward-looking view of risk means that it is important to be able to estimate and forecast the risk associated with holding a particular asset. As such, this chapter will develop the tools necessary to model and forecast conditional heteroskedasticity.
- Analyze a number ...

Start Free Trial

No credit card required