Are we always rational?
This was the question I posed in my previous article on the psychological biases that investors face. Over the last few decades, there have been many proponents in the academic world who argue that investors are not always rational. They suffer from psychological biases which may negatively affect them.
A Quick Recap
Let’s start with a simple question, just like before.
If it takes 5 minutes for 5 machines to produce five items, how long would it take 100 machines to produce 100 items?
Our gut reaction is to answer 100 minutes.
But this intuitive answer is wrong.
Don’t worry, though. This wrong answer was given by many MIT students too.
Essentially, we have two systems of thinking. System 1 is intuitive and quick, while System 2 is slow, effortful and deliberate.
Most likely, the intuitive but wrong answer of 100 minutes comes from System 1. But to get to the correct answer of 5 minutes, we need to pause and think deeper.
In my previous article, I also explained several common biases, such as the sunk cost fallacy, the empathy gap and the overconfidence bias.
The sunk cost fallacy is the fallacy of using costs that have already been incurred to make decisions. The empathy gap states that we underestimate how we will behave in other emotional states relative to the one we are currently in. Finally, the overconfidence bias simply means that we are too confident about our own abilities.
In this article, I will share a few more fallacies that we are likely to fall into.
Neglect Of Statistical Probabilities
I will be visiting the United States next year and many of my family and friends have remarked to me that the US is dangerous to visit due to the gun violence there. My mother, especially, was quite worried about my safety. To dispel her worries, I pulled out some statistics on gun violence.
I found that in 2017, there were 12 deaths due to gun violence per 100,000. This might sound a lot to you, but did you know that there were 1,000 deaths from car accidents per 100,00 people that year?
In other words, I am more likely to die from a car accident than from a gun shooting. Yet, our worries on gun violence and a car accident are not proportional.
How does this apply to investing?
During the dot-com boom of the early 2000s, valuations of technology companies sky-rocketed. Many of these companies were new and unprofitable, and some even had no revenue!
But investors somehow believed that those companies were very valuable.
True, some of these companies did emerge to become superstars, such as Amazon and Apple, but many of them faltered and declared themselves bankrupt in a few years.
I think many of these investors could have forgotten to ask themselves what the probability of these new companies succeeding was.
With a large sample of technology companies, there will definitely be a few who will succeed brilliantly and generate great returns. However, the vast majority of these dot-com companies turned out to be bad investments.
Hence, if you are betting on a company that has a bad track record or one that does not even have a track record, it would be helpful to ask yourself what the statistical probability of this company succeeding would be.
Let’s try to play a simple game.
In this first scenario, you have two options. Option A is that you can either walk away with a guaranteed win of $75. Option B is that you have a 75% chance of winning $100, and a 25% chance of winning nothing.
The second scenario is simply the reverse of the first scenario. Option C is that you can walk away with a guaranteed loss of $75. Option D is that you have a 75% chance of losing $100, and a 25% chance of losing nothing.
If you are like most people, you would have preferred option A over option B in the first scenario, and option D over option C in the second scenario.
In other words, you prefer a sure gain of $75 over a potential chance of winning $100, and you also prefer a possible chance of making no losses over a sure loss of $75.
From a rational point of view, this seems inconsistent.
The explanation psychologists give, is that we are averse to losses.
This means that our degree of pain when we are losing money is much larger than the degree of happiness when we win money.
This makes us want to take less risk when it comes to gains and more risk when it comes to losses.
How does this relate to investing?
This can relate to investing in several ways.
First, when it comes to potential gains, we may prefer low-risk or risk-free investments over more risky ones, even if the more risky strategies may promise a lot higher returns.
Second, if the investments we are holding have increased in price, we may be tempted to just sell off these investments and lock in the gains, even if there is a high chance that these investments may continue to perform.
These two examples do show that we are more afraid of taking on risk when potential gains are at stake. However, the reverse is true when we are dealing with potential losses.
We may be reluctant to sell an investment that has performed badly, holding on to the hope that this investment will improve over time, even if there is a good chance that losses may continue. In other words, we don’t want to lock in our losses.
There could also be the scenario where we want to hold on to a losing stock until it has rebounded back to our entry price, such that we neither make nor lose any money from this investment. This is also loss aversion, but the sunk cost fallacy is at play too.
To illustrate this effect, let me ask you two questions.
Is the population of Afghanistan higher or lower than 200 million? Next, what do you think is the population of Afghanistan?
Chances are, your answer would be around 200 million. If we change the figure of “200 million” to “10 million”, your answer would most likely float around that number too.
The actual population of Afghanistan is close to 35 million, but our minds use the number “200 million” and “10 million” as anchors.
This can happen unconsciously too.
When subjects of an experiment were asked to spin a wheel of fortune and subsequently guess the percentage of African states which were part of the United Nations, it was discovered that the percentage they guessed was similar to the number derived from spinning the wheel.
The anchoring effect is how our minds tend to consider a particular value of some unknown number before we make an estimation.
How does this relate to investing?
I think the anchoring effect is prominent in investing during market bubbles and in value investing.
One of the greatest market bubbles occurred in the early 2000s. During that period, Internet companies had extremely high valuations, despite having little production or sales to show for it.
During the dot-com bubble itself, investors kept bidding the share prices higher. Even though these stocks were very expensive, investors thought that there was little chance that the share prices could drop significantly. Their minds were already anchored on the already high share prices, so a low share price was unlikely or even unimaginable.
Eventually, the market crashed, and stocks that were once expensive almost became worthless overnight.
Another application of this phenomenon could be in value investing, where we try to buy undervalued stocks. However, the anchoring bias may mean that we tend to predict that a cheap stock would remain that way, when in reality the share price of the stock may rise over time.
In this two-part series, we have seen how certain biases have affected us not only in our daily lives, but in investing as well. You might feel that biases are bad, but they are an everyday part of human living that we should learn to cope with.
In fact, some biases might originate from our System 1 thinking, which though flawed at times, is incredibly useful for us. I find that reminding myself that I am biased in situations helps me to at least act in a more rational way.
Man may not be the fully rational creature that economists envision, but we can find ways to cope with our biases when they fail us.
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