Trade Expectancy: How Important Is It to Be Right When Trading?

Ray Downer, Senior Trader Coach at Learn to Trade

In life we generally want to be right. This is why you may hear traders framing their trading success by saying they won nine out of the last 10 trades, or that they have a 90% success rate.

However, having lots of winning trades does not necessarily mean that you will be a profitable trader in the long run. This concept is what we’re going to explore in this article.

Let’s take two traders: Sarah and Mike are both traders that have placed 100 trades and started with the same amount of money in their trading account:

• Mike wins 75 trades and loses 25 trades
• Sarah wins 30 trades and loses 70 trades
• Who is the better trader?

Although we can see Mike is right more often than Sarah is when trading, to determine who is the better overall trader we are missing some key pieces of information.

Firstly, we need to know the amount of profit made when one of our traders is right, as well as the amount lost when wrong. Another way of putting this is that we need to know our traders’ average reward-to-risk over their 100 trades.

So let us look at both of our traders again, but this time take into consideration their reward-to-risk:

When Mike is right he makes a profit on average of £100 per trade; when wrong he makes an average £300 loss. This means that his reward-to-risk is 1:3.

When Sarah is right she makes £300 on average per trade and when she’s wrong she loses on average £100. This means she has reward-to-risk of 3:1.

This gives us a bit more insight into the traders. We can see that mike, for example, is willing to risk three times more than he stands to gain in any one trade. Sarah in contrast is looking for a bigger pay-off but not willing to risk as much as Mike per trade.

Neither of those approaches is inherently good or bad as a trading strategy.

To really understand how each of our traders’ strategies stack up against each other, we need to take into consideration the two things we have mentioned here: firstly how frequently our traders have winning trades and secondly how much is gained or lost with each trade.

In trading terms, what we are figuring out is Mike and Sarah’s trade expectancy. Trade expectancy essentially tells us how much we stand to gain or lose as a trader for every  pound risked.

Expectancy = (average gain x probability of gain) – (average loss x probability of loss)

We can make this a bit clearer using Mike and Sarah’s results:

• Mike’s expectancy per trade = (£100 win x 0.75) – (£300 loss x 0.25) = £0
• Sarah’s expectancy per trade = (£300 win x 0.3) – (£100 x 0.70 loss) = £20

What this tells us is that over the long run Mike is breaking even with each trade despite winning 75% of the time. As a trader the long term goal is of course to make a profit rather than break-even or lose money. For Mike’s strategy to become profitable he either needs to win more often and/or reduce his risk per trade.

Sarah’s expectancy tells us that she is making an average £20 per trade in the long run, even though she is winning just 30% of her trades. Her reward-to-risk strategy means that she can be wrong much more frequently than Mike, but still make a profit overall.

Both Mike and Sarah’s expectancy can improve or worsen depending on trading conditions and whether they stick to their trading plans. Nevertheless, expectancy is a good benchmark to evaluate a trading strategy. You could also think of expectancy as how much you can theoretically expect to get paid for each trade you take over time.

As we all know, it’s impossible to always be right when trading forex. However, figuring out your expectancy helps shift focus away from being right per trade to instead how right you are overall.

Ray Downer, Senior Trader Coach at Learn to Trade

In life we generally want to be right. This is why you may hear traders framing their trading success by saying they won nine out of the last 10 trades, or that they have a 90% success rate.

However, having lots of winning trades does not necessarily mean that you will be a profitable trader in the long run. This concept is what we’re going to explore in this article.

Let’s take two traders: Sarah and Mike are both traders that have placed 100 trades and started with the same amount of money in their trading account:

• Mike wins 75 trades and loses 25 trades
• Sarah wins 30 trades and loses 70 trades
• Who is the better trader?

Although we can see Mike is right more often than Sarah is when trading, to determine who is the better overall trader we are missing some key pieces of information.

Firstly, we need to know the amount of profit made when one of our traders is right, as well as the amount lost when wrong. Another way of putting this is that we need to know our traders’ average reward-to-risk over their 100 trades.

So let us look at both of our traders again, but this time take into consideration their reward-to-risk:

When Mike is right he makes a profit on average of £100 per trade; when wrong he makes an average £300 loss. This means that his reward-to-risk is 1:3.

When Sarah is right she makes £300 on average per trade and when she’s wrong she loses on average £100. This means she has reward-to-risk of 3:1.

This gives us a bit more insight into the traders. We can see that mike, for example, is willing to risk three times more than he stands to gain in any one trade. Sarah in contrast is looking for a bigger pay-off but not willing to risk as much as Mike per trade.

Neither of those approaches is inherently good or bad as a trading strategy.

To really understand how each of our traders’ strategies stack up against each other, we need to take into consideration the two things we have mentioned here: firstly how frequently our traders have winning trades and secondly how much is gained or lost with each trade.

In trading terms, what we are figuring out is Mike and Sarah’s trade expectancy. Trade expectancy essentially tells us how much we stand to gain or lose as a trader for every  pound risked.

Expectancy = (average gain x probability of gain) – (average loss x probability of loss)

We can make this a bit clearer using Mike and Sarah’s results:

• Mike’s expectancy per trade = (£100 win x 0.75) – (£300 loss x 0.25) = £0
• Sarah’s expectancy per trade = (£300 win x 0.3) – (£100 x 0.70 loss) = £20

What this tells us is that over the long run Mike is breaking even with each trade despite winning 75% of the time. As a trader the long term goal is of course to make a profit rather than break-even or lose money. For Mike’s strategy to become profitable he either needs to win more often and/or reduce his risk per trade.

Sarah’s expectancy tells us that she is making an average £20 per trade in the long run, even though she is winning just 30% of her trades. Her reward-to-risk strategy means that she can be wrong much more frequently than Mike, but still make a profit overall.

Both Mike and Sarah’s expectancy can improve or worsen depending on trading conditions and whether they stick to their trading plans. Nevertheless, expectancy is a good benchmark to evaluate a trading strategy. You could also think of expectancy as how much you can theoretically expect to get paid for each trade you take over time.

As we all know, it’s impossible to always be right when trading forex. However, figuring out your expectancy helps shift focus away from being right per trade to instead how right you are overall.