"Overconfidence bias" refers to a tendency that humans have to be more confident in their abilities and knowledge than they should be. It means we often believe we are better or more knowledgeable than we actually are, leading to potential mistakes or poor decision-making.
Full definition
There are a number of behavioral biases that contribution to this problem
including overconfidence bias, over optimism bias, hindsight bias and the illusion of control.
This not only applies to confirmation bias, but
also overconfidence bias (I know this because I study this... no way you could know more), gambler's fallacy (it happened before, so it has to happen again), and even anchoring (mind made up before getting enough information).
Studies in behavioral finance, which look into the effects of investor psychology on stock prices, also reveal investors are subject to many biases such as confirmation, loss aversion and
overconfidence biases.
The overconfidence bias is a cognitive bias, but one with emotional overtones.
Another factor that we believe has supported stocks early in 2017 has been a carryover from the final quarter of 2016:
the overconfidence bias.
Common biases plaguing investors include: representative bias, cognitive dissonance, home country bias, familiarity bias, mood and optimism,
overconfidence bias, endowment effects, status quo bias, reference point and anchoring, law of small numbers, mental accounting, disposition effects, attachment bias, changing risk preference, media bias and internet information bias.
So one solution would be to demand a greater margin of safety (that is, the gap between price and «value») or increase your discount factor as Russell suggests, to counteract
the overconfidence bias — or alternatively, using it as the basis of a more sophisticated measure of price / value (which I think is what Russell actually does) in a relative approach.
This creates
an overconfidence bias.
(My comment: this is a useful filter to counter hindsight and
overconfidence bias.)
Fuelled by time - based billing pressures, issues arise such as unnecessary competition,
overconfidence bias, and hoarding, rather than sharing knowledge assets.