Biases specific to analysts performing research are usually related to the analysts collecting too much information, which leads to the illusions of knowledge and control and to representativeness, all of which contribute to overconfidence. Two other common biases found in analysts’ research are the confirmation bias and the gambler’s fallacy.

The confirmation bias (related to confirming evidence) relates to the tendency to view new information as confirmation of an original forecast.

The gambler’s fallacy, in investing terms, is thinking that there will be a reversal to the long-term mean more frequently than actually happens. A representative bias is one in which the analyst inaccurately extrapolates past data into the future. An example of a representative bias would be classifying a firm as a growth firm based solely on previous high growth without considering other variables affecting the firm’s future.