representativeness - biases

CFA Level III Portfolio Management
#1

Dear all - I’ve started studying for level iii now and am doing schweser’s Q&A.

came across a representativeness question

Analyst M routinely adjusts his previously vague forecasts to fit new information that has just been made available making his forecast look better than it actually was. Analyst Q judges the probability of her forecast being correct on how well the available data fits the outcome. Which of the following behavioral biases are M and Q displaying? M is displaying:

A)

hindsight bias and Q is displaying representativeness.

B)

illusion of control bias and Q is displaying self-attribution bias.

C)

illusion of knowledge and Q is displaying availability bias.

Hindsight bias is when the analyst selectively recalls details of the forecast or reshapes it in such a way that it fits the outcome.

In representativeness, an analyst judges the probability of a forecast being correct on how well the available data represent (i.e., fit) the outcome. The analyst incorrectly combines two probabilities: (1) the probability that the information fits a certain information category, and (2) the probability that the category of information fits the conclusion.

Illusion of knowledge is when the analyst thinks they are smarter than they are. This, in turn, makes them think their forecasts are more accurate than the evidence indicates. The illusion of knowledge is fueled when analysts collect a large amount of data.

The illusion of control bias can lead analysts to feel they have all available data and have reduced or eliminated all risk in the forecasting model; hence, the link to overconfidence.

The availability bias is when the analyst gives undue weight to more recent, readily recalled data. Being able to quickly recall information makes the analyst more likely to “fit” it with new information and conclusions.

In self-attribution bias analysts take credit for their successes and blame others or external factors for failures. Self-attribution bias is an ego defense mechanism, because analysts use it to avoid the cognitive dissonance associated with having to admit making a mistake.

I don’t understand the representativeness explanation - do you?

#2

I think of representativeness bias as “IF, THEN scenarios”. If a firm is high P/E then it’s a growth stock". Just because a high pe is present doesn’t automatically make it representative of a growth stock.

#3

Think of representativeness as: if analyst likes leisure water sports (kiteboarding) than if he encounters kite boarding company forecast he gives more positive attention/emphasis to that company.

It is like past will persist and all new info is classified based on the past experienced

R

#4

thanks guys!

#5

I’m confused about this bias. The curriculum says that in representativeness bias, ‘‘people tend to classify new information based on past experiences and classifications. They believe their classifications are appropriate and place undue weight on them.’’ But then it goes onto saying that ‘‘In Bayesian terms, FMPs tend to underweight the base rates and overweight the new information —resulting in revised beliefs about probabilities and outcomes that demonstrate an overreaction to the new information.’’

Aren’t these two sentences contradictory?