Volatility in financial markets has made active trading very popular, but the influx of new traders has met with mixed success.
Why is this, and how can losses be avoided?
IG forex broker examined the traits of the most successful traders – as well as the least successful. Some clear patterns emerged which separated profitable traders from those who ultimately lost money. And indeed, there was one particular mistake we saw repeated over and over again.
What is it?
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So now that you registered for the webinar let’s get back to our research.
Why do most traders lose money?
The first is encouraging: traders made money most of the time, as they closed over 50% of all trades at a gain.
In other words, traders were ‘right’ more often than not. This was true across a broad range of markets.
Figure 1. Data source: IG accounts and trades, excluding clearing accounts, money managers, and eligible contract participants.
The above chart shows over 30 million real closed trades conducted by IG clients worldwide across 15 of the most popular markets. The blue bar shows the percentage of trades which ended with a profit for the client, while the light blue bar shows the percentage of trades which ended in a loss.
For example, the EUR/USD saw an impressive 64% of all trades closed out at a gain.
But if traders were right more than half of the time, why did most lose money?
This chart says it all. In blue, you see the average number of points which traders earned on profitable trades. In light blue, it shows the average number of points lost in losing trades.
We can now clearly see why traders lose money despite being right more than half the time: traders lose significantly more money on losing trades than they make on their winning trades.
Let’s use the FTSE 100 as an example. Figure 1 shows us traders closed 64% of all FTSE 100 trades out at a gain, while figure 2 shows the average losing trade was worth 35 points – yet the average winner was only 15 points.
Although traders were correct nearly two-thirds of the time, they lost more than twice as much on their losing trades than earned on winning trades. A similar pattern can be observed across the entire range of popular markets.
So what could be the reason for this?
Cutting losses and letting profits run
Our data shows that traders were very good at identifying profitable trading opportunities and closed over 50% of all trades at a gain. Ultimately, though, they still lost overall as outsized losses more than offset winning trades.
Open nearly any book on trading and the advice is the same: control your losses and let your profits run. Losses are an inevitable part of trading. Identify when a trade has gone against you and close it out at as small a loss as possible. Failure to do so could see a losing trade wiping out your trading capital before you can take advantage of the next opportunity.
The flip side is equally important: if a trade is in your favour, let it run. It’s tempting to accept a ‘sure thing’ and close a trade at a small gain. But consistently doing so, while taking outsized losses, is almost certainly a losing strategy.
If the solution is so simple and advice so readily available, why is this issue so common?
The answer: human nature. As humans, we have natural tendencies which cloud our decision-making.
Let’s look at a basic thought experiment to explore this further.
Understanding decision making through winning and losing
What if you were offered a simple wager? You’re asked to guess the result of a single coin flip. Assume it’s a fair coin which is equally likely to show ‘heads’ or ‘tails’.
If you guess correctly, you’ll win $1000. Guess incorrectly, and you’ll receive nothing. Let’s call this ‘choice A’.
But to make things interesting, you’ll also be given ‘choice B’ – a sure $400 gain. Which one would you choose?
From a logical perspective, choice A makes the most sense as the mathematical ‘expected return’ is $500, which would maximise profit.
We used this formula to calculate the ‘expected return’ (probability of winning x gain) + (possibility of losing x loss) = expected return.
That means the mathematical probability of winning $500 is greater (50% x $100 = $500) than losing $0 (50% x $0 = $0).
Choice B isn’t wrong per se – with zero risks of loss you couldn’t be faulted for accepting a smaller gain. And you stand the chance of making no profit whatsoever with choice A – in effect, losing the $400 offered in choice B.
It’s no surprise that similar experiments show most will choose ‘B’. When it comes to gains, we most often become risk-averse and take a sure profit.
But what about potential losses?
Using the same coin, you’re offered the equal likelihood of a $1000 loss and $0 in ‘choice A’. ‘Choice B’ is an inevitable $400 loss. Which option would you choose?
In this instance, choice B minimises losses and appears to be the logical choice – yet similar experiments have shown that most would choose ‘A’. When it comes to losses, we become risk-seeking. Most avoid risk when it comes to gains, yet actively seek risk if it means avoiding a loss.
A hypothetical coin flip is hardly something to lose sleep over, but this natural human behaviour is problematic if it extends to real-life decision-making. And it’s this dynamic which explains the most common mistake in trading.
But how can you prevent it?
Losses hurt far more than gains give pleasure.
Daniel Kahneman and Amos Tversky published what has been called a ‘seminal paper in behavioural economics’, which showed that humans most often made irrational decisions when faced with potential gains and losses. Their work wasn’t specific to trading but had clear implications for our studies.
The core concept was simple yet profound: most people make economic decisions not on expected utility but on their attitudes towards winning and losing. It’s usually assumed that a rational person would make decisions purely based on maximising gains and minimising losses. Yet this is empirically false – look no further than our real trading data.
Our data suggest traders felt it was ‘good enough’ to take an average 15-point gain on winning FTSE 100 trades, yet gave up an average of 35 points on their losers.
Such a dynamic very likely helps explain why our data shows 64% of all of these FTSE 100 trades were winners – it was easy to take profits but hurt too much to take losses.
Ultimately we aim to turn a profit in our trades, but to do so, we must force ourselves to work past our natural emotions and act rationally in our trading decisions.
If the desired goal were to maximise profits and minimise losses, a $500-point gain would completely offset a $500-point loss.
Avoid the common pitfall.
You need to ensure that you treat losses and gains the same when trading, and this means following a straightforward rule: always seek a potential reward at least as large as your possible loss.
We typically refer to this as a risk vs reward ratio. If you risk losing the same number of points as you hope to gain, your risk vs reward ratio is 1-to-1 (also written 1:1). This simple rule makes it possible to lose on half of your trades and still break even.
It’s certainly possible – and in some cases advisable – to use a risk/reward ratio above 1:1. But as a bare minimum, using a 1:1 ratio is preferable.
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