Cate brought some shares for $1000. Each day, she has to decide whether to sell, or keep them. Her profit will depend on the price she gets for them. Each morning, she gets the previous day’s closing price, and she rings her sister Megan and gets her opinion as to whether the price will go up or down today. She also knows that most of the time, the price of these shares only move within a certain range from one day to the next.

Build a dynamic decision network to model this problem.

Object-oriented Bayesian decision networks (OOBNs)

These modeling exercises should be done using a BN software package that supports OOBNs, such as Hugin or AgenaRisk. See our Quick Guides to OOBNs in Hugin in Figure 4.22 and also Appendix B.