5 MENTAL MISTAKES OF STOCK ANALYSTS
Throwback to the time a stock analyst slashed his target price on mobile handset maker Palm in 2010, from more than $4 to $0 per share. That recommendation made investors panic and pushed the firm’s stock down by over 30%. One month later, Hewlett-Packard acquired Palm for $1.2 billion (or $5.70 per share). Those who believed to the analyst’s prediction ended up castigating themselves.
Most people acknowledge stock analysts are more knowledgeable and have more expertise than an average investor in terms of assessing stocks. But at the end of the day, stock analysts are also human beings and affected by certain psychological biases.
This article explains some of the common biases affecting analysts in order to determine their credibility.
Analysts have the vulnerability to stick with their past price targets. Therefore, they fail to correctly integrate new information into their estimates. For instance, an analyst was bearish on a stock and placed a low target price for a stock of Company XYZ. But all of a sudden, some negative news about the company affected its stock. The analyst won’t frequently adjust his target since he is anchored to his previous forecasts. Conversely, positive news may be not be fully reflected in his estimates.
Also called the confirming evidence bias, every individual is affected by this to certain extent. When a person believes in something, they will frequently tend to reckon more on evidence or research backing their perspective. Their mantra is to see to believe. Let us put that view in an investing context. Investors or analysts that are bullish in the market often overweight evidence or figures supporting their investment thesis. Those who are bearish will do the opposite. To check if an analyst has this kind of bias, evaluate the consistency of the evidence being used. A year later, see if the evidence that back his view is still the same. A change in indicators used and text in the analysis postulating the old indicators are not as applicable anymore, which can be signs of a one-sided analysis.
This bias affects a person’s capacity to assess the odds in a situation the right way. This fallacy states when a person thinks the outcome of a specific random event is less possible to take place after an event or series of event. Remember that previous occurrences do not alter the likelihood particular events will happen in the future. And investing is way different from gambling. The situation in the market will not be as crystal clear as this is. However, being familiar with this bias can help an individual find it out way easier.
Herd Effect/Prudence/Status Quo
In high school, we agree with to our friends and not stick out. Same thing with investing. It demonstrates the pressure to conform among fellows. Most analysts have the tendency to come up with estimates which are relative to what everyone else is doing and avoid going too far away from the majority. This bias is one reason on why we often see so many buy recommendations in relation to sell recommendations. By doing such, analysts gain an incentive such as a continued employment. They can always blame everyone else if they are wrong after all.
Most of the time, an analyst is too confident in their capacity to predict earnings, price targets, or other economic indicators. An overly done, precise estimation is the first sign of overconfidence. Forecasting is very difficult to get right, but a good analyst will use a forecast range. An overconfident recommendation can cause others to act more often than they want to – and to lose more money, making them regret their investing decisions.
Approaches in Predicting Currency Changes
Worst Buys During Labor Day Sales
5 Stages of Becoming a Trader
4 Pillars of a Legal Contract
The One Expense that Derails Retirement
What Could Happen If…
POPULAR FOREX DEFINITION
|02:01||Rightmove House Prices||Mar|
|12:00||Current Account (sa)||Jan|
|13:00||Bundesbank Monthly Report|
|02:30||Monetary Policy Meeting Minutes|
|04:00||Credit Card Spending||Feb|
|09:00||Public Sector Net Borrowing||Feb|