In 2010, a stock analyst made headlines in the media when he reduced his target price on the struggling mobile handset maker, Palm, to $0 from over $4 per share. This caused investors in the stock to panic and drive Palm stock down by over 30%. Just one month later, to the disappointment of investors that had sold, Hewlett-Packard tendered an offer to buy Palm for $1.2 billion, or $5.70 a share. Investors that listened to this particular stock analyst's recommendation ended up kicking themselves in the butt and were left wondering what went wrong. (For more, see What Direction Is The Market Heading?)
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Most people would acknowledge that stock analysts often do have more expertise than the average investor when it comes to the fine details of analyzing stocks. However, analysts are also human and are affected by the same psychological biases as the rest of us. In this article, we will look at some of the more common biases that affect analysts to help you evaluate the credibility of stock analysts you encounter in the course of your investing process.
The first one we'll look at is called the confirmation bias, or also commonly known as the confirming evidence bias. Everyone is affected by the confirmation bias to some extent whether you realize it or not. When someone believes in something, they will often tend to give more weighting to evidence or research that supports their viewpoint. In other words, they see what they want to see.
In an investing context for example, investors or analysts that are bullish in the market will often overweight evidence or data that supports their investment thesis. Investors or analysts that are bearish will tend to do the opposite. An initial way to flag these analysts that are affected by this bias is to check the consistency of the evidence used by the analyst. For instance, suppose an analyst is bullish on the market and uses indicators such as rising GDP, falling unemployment and rising consumer confidence to support his view. If one year later, these indicators have worsened and the analyst is still ‘bullish' on the market, check to see if the evidence used to support his view is still the same. A shift of indicators used and text in the analysis arguing that the old indicators are not as relevant anymore could be signs of a biased analysis.
The next bias we'll look at is the gambler's fallacy, which is the bias that affects people's ability to correctly assess the odds in a situation. For instance, if you flip a coin 10 times and all 10 times it comes up as tails, there is something inside your brain that wants you to believe that you're due for a heads. The gambler's fallacy bias makes you believe that there is a greater odds of heads coming up on the next toss and may induce you take make risky bets. However, the probability of a heads on the next toss will still only be 50/50. In the stock market, the situation will not be as clear-cut as this is, but knowing the existence of this bias can help you spot it that much easier.
For example, this was the title of a CNBC article published in 2011: "Oil Due For A Correction?" In the article, it was noted that "... oil prices have risen to levels not seen since 2008," which is factual, but the language in the article and the supporting evidence used seemed to imply to the reader that oil was headed for an imminent correction simply because it was at such an elevated level. Similar to the coin toss example, the author may be exhibiting a gambler's fallacy bias because the thought was that oil had gone up so much it had to be "due" for a correction. There may also have been confirmation bias in the article as well judging by the fact that the bulk of the supporting evidence used backed the correction argument
Anchoring is the next psychological bias we'll take a look at. This bias refers to a person or analyst's susceptibility to sticking with previous price targets and consequently failing to correctly incorporate new information into their estimates. For example, if an analyst was fairly bullish on a stock and had a relatively high price target for a stock, and subsequently some very negative news about the stock came out, it is often the case that the analyst will not fully adjust the price target downward enough because he is anchored to his previous target. Conversely, good news can also often not be fully reflected in estimates as well.
|Earnings History||Q2 2010||Q3 2010||Q4 2010||Q1 2011|
|Source: Yahoo! Finance|
Can you see the anchoring problem here? The consensus EPS estimate for Apple is always consistently below the actual reported EPS, resulting in four consecutive earnings surprises. In this case, the analysts continuously fail to fully incorporate the good news (earnings surprise) into their next estimate. This is likely because they are anchored to their previous forecasts. (For more, see Everything Investors Need To Know About Earnings.)
Prudence/Status Quo/Herd Effect
Known by many names, the prudence bias reflects the pressure to conform among peers. Similar to the pressure in high school to conform and not stick out, this pressure for conformity also exists on Wall Street. The prudence bias is the tendency for most analysts to generate estimates that are in line with what everyone else is doing and avoid straying too far away from the pack. This is part of the reason, among others, that you often see an overwhelming number of buy recommendations relative to sell recommendations. Analysts generally have an incentive, whether that is continued employment or plausible reasons for denial, to not stray from the group consensus. After all, if they are wrong, they can always point to everyone else that was wrong as well.
The last psychological bias we'll look at is overconfidence. Overconfidence is exactly as it sounds - the analyst is too confident in their ability to forecast earnings, price targets or other economic indicators. The first sign of overconfidence is typically an overly precise estimate. For example, someone that predicts GDP will grow by 3.57% in the next quarter should be a red flag for the investor. Forecasting is notoriously difficult to get right, and the use of a forecast range is usually what you would prefer to see from a good analyst.
The danger of overconfidence is that it can cause others to act more often than they want to. For example, in the opening paragraph I described the overconfident forecast of the analyst that likely caused several investors to do something they later regretted. This is one instance where the forecast was overly precise, at exactly $0, and several different scenarios would have led to a price target that was much different.
If you follow the careers of some of the best investors of our time, one thing most of them have in common is an awareness of these psychological biases and the ability to resist them in their trades. So the next time you're about to make a trade for your portfolio, see if you, or the professional whose recommendation you're following, is affected by any of these biases. You may be surprised how much of it creeps in to everyone's trading. (For related reading, see 4 Psychological Traps That Are Killing Your Portfolio.)
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