Theoretical Framework Literature Review

Overconfidence

Investors tend to have too much confidence in the accuracy of their own judgments. So, researchers focused on detecting the accuracy of investors' judgments and its relation with their confidences.

The concept of overconfidence was tackled by many cognitive behavioral experiments and surveys in which subjects overestimate their own predictive abilities and the precision of the information they've been given.

Nevins defined overconfidence as people who overestimate their own abilities. He found that investors and analysts were particularly overconfident in the domains where they have some knowledge. They approved that one effect of overconfidence is overtrading, which leads to poor investment decisions. At the same time, overconfidence is the tendency of people to overestimate their knowledge, abilities, and the precision of their information.

Chuang & Lee found that overconfidence makes investors overweigh their own private information at the expense of ignoring publicly available information, and they justified their research by studying other academic' research and studies to prove that overconfident investors mistakenly attribute market gains to their own ability to pick winning stocks. The view of Phung was that, overconfident individuals overestimate or exaggerate their ability to successfully perform a particular task.

Many researchers studied overconfidence and analyzed the detrimental effects of overconfidence by investors; these studies revealed that investors were overconfident in their investing abilities and such will result in making investment mistakes.

Therefore, according to previous researchers the overconfidence factor is one of the most detrimental biases that an investor can show, and this is because investors behavioral are naturally underestimating downside risk, trading too frequently, and holding under diversified portfolio.

Those studies measured overconfidence by dividing its concept into several dimensions: Chaffai measured the overconfidence by using two dimensions (stock retained periods, amount of information to be collected).

Chuang & Lee measured overconfidence by (accumulated experience, colleagues benchmarking, brokerage firms' consultancy, certainty of answers for random questions).