Although research has documented the importance of emotion in risk perception, little is known about it in the context of everyday life. Using the Experience Sampling Method (ESM), 94 part-time students were prompted at random—via cellular telephones—to report on mood state and three emotions and to assess risk on thirty occasions during their working hours. The emotions—valence, arousal, and dominance—were measured using self-assessment manikins (SAMs) (Bradley & Lang, 1994). Hierarchical linear models (HLM) revealed that mood state and emotions explained significant variance in risk perception. In addition, valence and arousal accounted for variance over and above “reason” (measured by severity and possibility of risks). Six risks were re-assessed in a post-experimental session and found to be lower than their real-time counterparts. The study demonstrates the feasibility and value of collecting representative samples of data with simple technology. Evidence is also provided to demonstrate the statistical consistency of the HLM estimates. Copyright © 2010 John Wiley & Sons, Ltd.