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Moving averages are usually one of the first technical indicators that traders will learn about and add to their charts.

When plotted on a chart, the moving average (MA) appears as a squiggly line that approximately follows price actio.n.

The shorter the time period of the MA, the closer it will follow price action.

moving average is a way to smooth out price fluctuations to help you distinguish between typical market “noise” and the actual trend direction.

New to moving averages? Learn how to use moving averages in Grade 4 of our School of Pipsology course.

A popular trading strategy involves using two moving averages: a “faster” moving average and a “slower” moving average.

For example, when the “faster” moving average crosses ABOVE the “slower” moving average, this is known as a bullish crossover.

When a bullish crossover occurs, it is considered a BUY signal.

Why?

Because when a bullish crossover occurs, the price is expected to continue to go up!

But does it?

Do bullish moving average crossovers work?

Can it predict future price action, where price trends upward?

Let’s study the past and see.

On the daily (1D) chart for GBP/USD, there was actually a bullish moving average crossover today.

The 10 SMA crossed above the 50 SMA. 

GBPUSD Bullish Moving Average Crossover

In the chart above, I used a blue circle to highlight where the 10 SMA (orange line) crossed above the 50 SMA (purple line).

If you look towards the left of the chart, you’ll notice more blue circles that denote when previous bullish MA crossovers occurred.

When the 10 SMA crosses above the 50 SMA, does price tend to continue upward? 🤔

Just by looking at the chart, it’s hard to say.

We need more data!

Data Cruncher

I decided to do a study on GBP/USD to see what happens when the 10 SMA crosses above the 50 SMA on the daily chart.

I looked back at almost ten year’s worth of data.

Here’s what I found…

Since January 1, 2010, there were 46 instances of the bullish crossover.

This means a total of 46 buy signals occurred.

I was now curious to answer the following questions:

“When a bullish crossover occurs, what happens when I buy and hold the position for 1 day and then exit?

“What if I hold the position for 3 days? 5 days? 10 days? 20 days?”

“What if I hold it even longer for 30 days? 60 days? 90 days?”

Hold Trade

When there is a bullish crossover, price is supposed to continue rising right?

So does it rise? And for how long?

Let’s take a look at the data…

GBPUSD Bullish Crossover Average Returns

The x-axis represents the different holding times (how long you keep a position open).

The y-axis represents the returns (whether price ended higher or lower).

For example, going long and holding for 1 day resulted in a -0.08% return. This means when the trade was exited, on average, the price had fallen by 0.08%.

If each of the 46 trades were held for 5 days, it was a -0.15% return.

This means when the trades were exited, on average, the price had fallen by 0.15%.

As you can see from the chart, no matter how long you stayed in the trade, on average, the price went DOWN not up!

Let’s see what else I found…

Win Rate

GBPUSD Bullish Crossover Win Rate

The chart above shows what percentage of trades ended up with a gain (or loss) at the end of the holding period.

It answers the question:

“If I go long and hold the position for X number of days, what percentage of my trades ends up with a gain or a loss?”

For example, if you held each trade for 5 days, only 37.78% of trades ended up with a gain (or positive return). The rest (62.22%) of the trades ended up with a loss (or negative return).

As you can see, holding the trade for either 3 days or 20 days were the only times that the win rate exceeded 50%.

Average Gains vs. Average Losses

GBPUSD Bullish Crossover Average Gains and Losses

The chart above shows the average gain per winning trade and the average loss per losing trade.

It answers the question:

“When my trade ends up a winner, what is the average gain? And when my trade ends up a loser, what is the average loss?”

For example, if you held a trade for 3 days and then exited,  if you won, your average gain was 94 pips. And if you lost, your average loss was 122 pips.

If you held the trade for 90 days and then exited, if you won, your average gain was 460 pips. But if you lost, your average loss was 688 pips.

Regardless of how long one held a position, the average losses were bigger than the average gains.

Having larger average losses than average gains isn’t necessarily a bad thing IF you have a high win rate.

But if you look at the earlier chart, you’ll notice that the win rates weren’t great.

If we were theoretically going to trade this as a system, since we know the win rate and the average gain and loss, we can determine the system’s expectancy.

Expectancy

Expectancy is the average amount you expect to gain or lose per trade based on previous performance.

If you’re not familiar with the concept of expectancy, check out our lesson.

GBPUSD Bullish Crossover Expectancy
The chart above shows what can expect to win (or lose) per trade depending on how long you hold the trade.

It answers the question:

“What do I expect to earn per trade in the long run?”

As expected, the numbers are horrible.

If you hold your trades for 1 day, you can expect to lose 10 pips on every trade.

If you hold your trades for 10 days, you can expect to lose 26 pips on every trade.

No matter how long you hold the trade, whether it’s 1 day or 90 days, you can expect to lose money!

Conclusion

It’s hard to argue with the data. When the 10 SMA crosses above the 50 SMA, it doesn’t mean that price will continue to go up. It’s more likely to go down!

Based on the results, it looks like it might even be better to go SHORT (instead of long) when the MA crossover occurs. 🤔🤔🤔

Is this really a bullish MA crossover or….a bullshit MA crossover?! 🤣

Let’s not give up on it just yet.

What if there is a way to “filter” the trades so rather than go long on all 46 instances of the MA crossover, we take only the “higher quality” ones? Maybe the numbers will improve?

To find out, stay tuned for the next post.

For now, here’s the data from the charts above in tabular form for the table nerds. 🤓

Holding Period % Positive % Negative Average Gain (pips) Average Loss (pips) Expectancy (pips)
1 42.22 57.78 57 -60 -10.31
3 51.11 48.89 94 -122 -11.04
5 37.78 62.22 124 -111 -21.74
10 42.22 57.78 148 -154 -25.97
20 53.33 46.67 169 -262 -31.61
30 46.67 53.33 295 -366 -56.03
60 48.89 51.11 397 -539 -79.43
90 47.73 52.27 460 -688 -134.05