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Are emotions always bad for investment decisions?
Not surprisingly, the answer is it depends.
The good news is that's there's no need to suppress your emotions,
if you want to trade in the market.
In fact, as we've seen before,
even professional traders respond emotionally to market events.
The key is to first, identify your emotional and physiological responses to
market events and then find the right balance between reason and emotion.
Remember that our brain is constantly trying to predict what's going to
happen next in the world.
It's constantly trying to fill in information that's missing.
Now this filling in process, this process of inferences is heavily
influenced by our past experiences and by all past and present emotions.
The interesting thing is that it works surprisingly well,
especially in simple situations.
So when we make intuitive decisions, they're often surprisingly good.
The problem is that financial markets are not simple, they're rather complex.
More importantly, financial markets are somewhat unnatural.
That is the goals, the structure, the principles that underlie financial markets
are very different from the environment that our brain has evolved for.
As a result,
our brain makes a lot of wrong assumptions about the structure of the market.
As a result, you're particularly prone to cognitive biases and
misleading emotional information,
because the financial market violates many basic principals of nature.
Let's say,
you want to approach the financial market from purely rational perspective.
And if you have the statistical skills, you may say, okay.
I'm going to take the data of the last five years, all the data and I'm going to
try and look for any indicators that would have predicted market movements.
Now the thing is if you do this, you will find such indicators.
In fact, you will probably find a few dozen of them and
you will make yourself believe that you can really predict based on these
indicators how certain stocks are going to move.
The problem is if I was to generate at random, an equally large dataset
representing five years of market data and I gave you that to analyze.
You would also find, probably dozens of correlations and
strategies within that dataset.
The problem is that this is a dataset that was generated at random.
So, the correlations that you will find in this dataset are there by pure chance and
the same is true for real financial data.
A lot of the correlations that we see are there by pure chance and
some of them are therefore, surprisingly long time and make you believe that
you've figured out how particular stocks respond to the market.
The problem is if the correlation is there by pure chance,
it will also stop by pure chance at some point.
And at that point, if you've been following that strategy,
you may end up losing a lot of money.
Now the final point is that emotions aren't always bad and
emotions can be quite accurate at times, as well.
It actually depends on the market behavior itself.
So let's say, you have a time in the market where the markets
are relatively quiet not much as happening.
In these times, your reason and your emotion tend to align quite a bit.
So the way you respond to the market emotionally,
you might be pretty much in line with what reason tells you.
However, when markets become volatile, a lot of things are happening.
Lots of fluctuations, then your emotions and
reasons start to diverge and you need to be aware of that.
So, the quiet market periods might make you believe that your emotions
are actually surprisingly good in predicting markets and
causing you to make the right decisions.
But the reason is probably, because the market is quiet and
your emotions kind of tell the same story as your reason might.
But as soon as the markets become volatile, that might change.
And now, your emotions are really bad for your investment decisions and
you should no longer follow them.
This brings us to the end of the lesson on emotion and decision-making.
Hopefully, by now, you have developed a basic understanding of
how emotions influence our financial decisions and
how that is translated into portfolio performance.
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