Introduction to Overnight Movements in the Stock Markets
Does it make sense to open positions to take advantage of overnight movements in the stock markets?
Fist of all, we should start by clarifying that today, most global futures markets are essentially open 24 hours a day.
So, nighttime hours could be seen as just another part of the regular daily trading session.
However, that changes if we’re talking about stocks. In this case, both US and European markets are only open during the middle hours of the day, no more than 6 to 8 hours.
So at night, they are actually closed. That’s why our discussion will focus mainly on the stock market.
At the beginning we asked whether it can be profitable to open long positions right before the daily market close, then simply wait until the next day’s open to close them and see if they’ve gained.
The answer is yes, but under certain conditions. That is, the market must actually move overnight rather than staying flat at the previous day’s closing price. That movement needs to be generally bullish, since we’re opening long positions, and more importantly, it has to be consistent and reliable over time.
So it needs to be a feature of the market’s nature. Let’s take a look together.
Initial Strategy to Test the Basic Conditions (with Script)
We ran our first test using the SPY, the largest ETF based on the S&P 500. It’s the one with the longest track record among US index ETFs (it was launched back in 1993) and it’s definitely the one with the largest market capitalization in the world.
We then used this simple script on daily bars, assuming each trade was executed with a fixed value of $10,000.
Keep in mind this instrument is traded during the same hours as the stock market, which means from 9:30 in the morning to 4:00 in the afternoon, Exchange time.
The code, as you can see, has two parts or, you could say ,two engines, which you can switch using the “overnight” input.
In the first case, if we set the input to 1, we buy at the bar close, effectively at the end of the session since we’re using daily bars, and then we close the position at market open on the next day’s bar.
In the second case, with the “overnight” input set to 0, we do the exact opposite. We buy at the bar open, so at session open, and sell at the bar close, so market close.
Results of the Base Strategy: The Bias Exists, But…
This dual-engine setup is obviously meant to let us compare the difference between opening and holding a long position during regular market hours, the cash session, versus holding the same position overnight while the markets are closed.
We then grouped the equity curves into these slides, which we’re about to go through now, so we can speed up our analysis.
In this image, we see the profit curve from holding long positions overnight on the SPY during the 1990s.
In the next slide, we see the same strategy based on the overnight bias, but from 2000 to the present day.
I would say the first conclusion is clear. This bias does exist, and it has for quite a long time.
In the 1990s, it was incredibly consistent. Just look at the equity curve we saw earlier. From 2000 onward, however, the curve still moves upward but is much less consistent, with a lot more ups and downs.
Let’s move on. Here we have the second strategy, which trades during the regular daily session, that is, during the cash session when markets are open. And once again, the first image refers to the 1990s.
The situation is completely opposite to what we saw before. We even have a negative net profit.
Let’s now look at the more recent period, from 2000 onward. In this case, we do have a better curve than the previous one, it is at least positive, but it’s still pretty inconsistent and makes less than the overnight version.
Here we have $6,193 compared to over $14,000 from the other one, so more than double.
Let’s also take a look at the other US stock indices to confirm whether this bias is actually a common feature across all these markets.
Here we’ve plotted the ETF on the Nasdaq. We’re starting from the year 2000 because this one came later than the S&P 500 version.
Even so, we still see a very steady and rising curve. The same goes for the Dow Jones, and finally, for the Russell 2000.
So I’d say in all cases we see rising equity curves, some more consistent than others, but what’s certain is that the bias is clearly confirmed.
But Is It Really That Simple?
So far so good. We open our position at the end of the session, wait through the night, and the next morning, most of the time, we collect our gains.
But is it really that simple? Not quite. And we can see that in this slide, where we’ve summarized some of the major events of the past 25 years.
The fall of the Twin Towers, the Dot-com bubble, the 2008 Subprime mortgage crisis and the collapse of Lehman Brothers, more recently the COVID pandemic, the war in Ukraine, and more recently, the Liberation Day announcement of tariffs back in April 2025.
All these events caused shocks in the stock markets and, of course, also impacted our strategy, as you can see in the equity curve.
The downside is that being long during these events or periods is obviously far from ideal, especially since the markets are closed and we cannot act on our trade, and there is no stop loss that can protect us.
So I would say that the overnight bias clearly exists, it is evident, and it pays off in terms of profitability, even if it comes with more risk compared to trading only during the day session.
Is there a way to completely eliminate this risk? Unfortunately, the answer is no.
These events can happen at any time, including overnight, and by definition, they are unpredictable.
However, we can certainly reduce some of the weaknesses of this strategy, and in this second part of this video, we’ll see how.
Testing New Conditions to Manage Risk
For our test, we’ll use the basket of 100 stocks that make up the Nasdaq as our reference.
We’ll set the start date for the backtest as 2010, simply because some of the major tech companies that now carry the most weight in the index weren’t publicly traded before 2010. Just think of Tesla or Meta, for example.
We run the backtest, and this is the equity curve we get. This is our starting point.
We can see that it basically mirrors what we saw earlier on the ETFs.
So it’s a fairly steady equity curve, but with some pretty sharp drawdowns during the market shocks we mentioned earlier, like in 2020 or April of this year.
Let’s take a quick look at the metrics. We see that the strategy has a net profit of 1.6 million, with a max drawdown of about $315,000.
Keep in mind that in this base version, we execute one trade per day for each stock, using the standard size of $10,000 per trade.
This version of the strategy has no filters, so we buy in any market condition, and especially, we also buy on Fridays, leaving the position open until Monday.
That means we are not only exposed overnight, but in some cases, we are also exposed over the weekend.
Now, of course, the market will inevitably price in the events that happen over the weekend when it reopens on Monday.
So now let’s try to remove at least this part of the risk by avoiding entries on Fridays.
Let’s change the input related to this, so we set the day to avoid as day 5, which is Friday, and then run the backtest.
Alright, we can see that the net profit stays roughly the same as before, so around 1,600,000.
What immediately stands out is that the maximum drawdown is cut in half.
Let’s check if this reduction in drawdown also shows up in the equity curve as a smoother profit line.
Yes, confirmed. The equity curve looks much better than the base version, especially during more significant events like COVID, 2022, and to some extent April of this year.
Now let’s check the Annual Period Analysis. Okay, we see a very consistent distribution of profits, with all years in the green except for 2016, which was definitely a low-volatility year, and that probably affected how this strategy performed.
But especially in 2022, which was mostly a bear market, we see it was the worst year, with nearly $41,000 in losses.
So let’s start here and say this type of filter works well, and we can accept it as valid.
How to Further Improve the Strategy
How can we further improve our strategy? What would be the ideal conditions for opening positions?
Is it better to buy after a positive session close and betting on the trend continuing overnight, or to buy on weakness, waiting for a bounce and relying more on the mean-reverting behavior of stock markets?
Let’s check this using the second and third scripts.
In this script here, we add a condition that today’s close must be higher than yesterday’s close. In the other one, we set the opposite condition: today’s close must be lower than yesterday’s, so a weak close.
Here we have the metrics summary for the second strategy, the one that requires a positive session close.
As you can see, the net profit drops from over 1,600,000 to less than $500,000, and more importantly, there’s no benefit in terms of drawdown reduction: it stays pretty much the same.
Results of the Best-Performing Conditions
Let’s take a look at the equity curve as well. The equity confirms the doubts we had.
It definitely doesn’t improve in terms of profit, and more importantly, not in terms of consistency either.
Now let’s move on to the other case, the one with a weak close, and here we see the situation changes dramatically.
The net profit drops to 1.1 million. And that drop makes sense because the filters lead to fewer trades overall, but in this case, the reduction is much smaller.
What really stands out is the reduction in drawdown, which is essentially cut in half.
Let’s also take a look at the equity line. The equity line fully confirms our impressions. It becomes exceptionally smooth, aside from this drawdown spike in 2020. But overall, compared to the base equity curve, it takes on a completely different shape.
So I’d say this filter, which leans more on the mean-reverting nature of markets, clearly beats the other one.
Let’s take one last look at the Periodical Analysis. Let’s check the profit distribution over the years.
We had seen in the base strategy that the year with the biggest loss was 2022. But with this filter applied, that same year turns into a solid profit.
The same goes for 2016, which had been a low-volatility year. It wasn’t marked by sharp equity declines, but in the base version of this strategy, it was still a losing year.
So I’d say this filter, combined with the one that avoids entering trades on Fridays, clearly passes the test with flying colors.
To be honest, intuitively, you might have expected the opposite, that trading only after positive closes would protect you from bad trades, especially from drawdowns during market declines.
In reality, the opposite is true. It’s better to buy on weakness. That approach even holds during bear markets, like in 2022, relying on the rebounds that eventually come.
It’s also true that during fast crashes like COVID in 2020 or in April 2025, the risk of taking heavy losses goes through the roof. So it might make sense to add more conditions that prevent entries when the close is too negative compared to the previous day, as a way to avoid jumping into an ongoing sell-off.
As always, the goal is to find the right balance between reducing risk and preserving profit.
It’s also worth noting that, since we’re working with stocks, we have the great advantage of being able to decide exactly how much we want to invest.
However, the downside is that, unlike futures, these instruments do not have built-in leverage. So we’ll need to apply further filtering to the strategy in order to get a solid and usable average trade value.
Final Considerations
Alright, we’ve reached the end of this video, where we explored the opportunities offered by the overnight bias in the stock markets.
The goal wasn’t just to confirm that this bias exists and can be used, but also to get you thinking about the clear advantages and the disadvantages of holding overnight positions in the stock market.
I’ll leave you with one more suggestion. Try applying the same strategy we tested on US markets to the major European stock markets as well.
Try it on the DAX or the EuroStoxx using ETFs, or even the futures themselves, applying it within the standard trading hours from 8:00 AM to 10:00 PM.
You’ll definitely find some useful material and ideas to explore in your own research and analysis. For now, that’s all.
See you in the next video!
