Bayes' statistical rule remains the status quo for modeling belief updating in both normative and descriptive models of behavior under uncertainty. Recent research has questioned the use of Bayes' rule in descriptive models of behavior, presenting evidence that people overweight 'good news' relative to 'bad news' when updating ego-relevant beliefs. In this paper, we present experimental evidence testing whether this 'good-news, bad-news' effect extends to belief updating in the domain of financial decision making, i.e. the domain of most applied economic decision making. We find no evidence of asymmetric updating in this domain. In contrast, the average participant in our experiment is strikingly close to Bayesian in her belief updating. However, we show that this average behavior masks the existence of three distinct types of updating behavior - each of which is distinct from Bayesian, but none of which displays the 'good-news, bad-news' effect.