178 C H A P T E R 5. DECISION A N A L Y S I S F U N D A M E N T A L S 5.3 we introduce dynamic Bayesian networks and influence diagrams, which model relationships among random variables that change over time. Many of the examples in this chapter concern the stock market. If you are not familiar with stocks and investing in stocks, you should first read Chapter 7, Section 7.1. 5.1 Decision Trees After presenting some simple examples of decision trees, we discuss several issues regarding their use. Then we provide more complex examples. 5.1.1 Simple Examples We start with the following example: Suppose your favorite stock N A S D I P is downgraded by a rep- utable analyst, and it plummets from $40 to $10 per share. You feel this is a good buy, but there is a lot of uncertainty involved. NASDIP's quarterly earn- ings are about to be released, and you think they will be good, which should positively influence its market value. However, you also think there is a good chance the whole market will crash, which will negatively influence NASDIP's Example 5.1