The Best Days to Trade: An Empirical Analysis

In trading, the adage “timing is everything” couldn’t be more accurate. Whether you’re involved in equities or futures trading, the best days to trade may profoundly affect your returns. To that end, I analyzed the daily historical prices for $SPY to see if I can find the best days to trade, particularly if one was interested in trading indexes. What I found will clearly illustrate that choosing specific days to trade may have a high likelihood of significantly impacting your ROI. Moreover, identifying days with the highest potential for “home run” trades—based on historical data—can help guide your R-ratio when setting profit targets and stops. This holds true not just for days with historically higher odds of exceptional gains, but also for days marked by choppy or sideways price action.

The Data Doesn’t Lie

I’ve delved into two years of hard data, focusing on the daily open and close prices of $SPY for 2022 and year-to-date of 2023. The findings are unequivocal: there are good days to trade, and by definition, that means there are “bad” days to trade as well. This isn’t merely anecdotal evidence or trading lore; it’s supported by statistical analysis.

But I didn’t stop there. I also examined the most significant winners for each year, isolating the top 7% of winning trades. In simpler terms, that’s 17 out of 251 trades in 2022, and 12 out of 168 trades in 2023 so far. I wanted to understand the influence these select few trades had on the overall ROI for both years. The results might astonish you. Ready to dive in? I’ll start with 2023 first, take a look 👇 (scroll all the way to the bottom of page 4 of the PDF for the juicy data):

As illustrated by the data above, the ROI for SPY in 2023 thus far stands at a relatively decent 15.99%. Please note, this figure was derived using a straightforward daily calculation: [(Close−Open) / Open] ×100. What’s astonishing is that a mere 12 of the year’s biggest winning days are responsible for a 17.52% ROI. Yes, you read that correctly— meaning if we were to remove just those 12 pinnacle days, SPY would actually be in the red for the year thus far!

It’s crucial to note that these calculations were not made using adjusted closes or any sophisticated timing between today’s close and tomorrow’s open. The methodology was kept simple to drive home a vital point, particularly for day traders: don’t underestimate the power of choosing the right trading day. Case in point, Thursdays and Fridays alone accounted for 8 of those 12 transformative trading days!

Is This a Statistical Anomaly? Let’s Dig, Shall We?

What if these findings were merely a statistical anomaly, I mean 8 or 9 months of data isn’t sufficient to draw meaningful conclusions. Right? So, to fortify my analysis, I crunched the numbers for SPY’s performance last year as well. Just as with the 2023 data, you’ll find the most compelling insights at the bottom of page 6 of the PDF for 2022, check it out 👇:

As the data above reveals, Thursdays and Fridays yet again were the standout performers in 2022, mirroring the trends observed in 2023! Intriguingly, if one had traded only on those 17 winning days of 2022, their ROI would have soared to an astounding 49.72%. Yet, despite these outsized gains, the 2022 year closed with an overall negative ROI.

Just like in my 2023 analysis, it’s important to clarify that these calculations forego the use of adjusted closes or timing calcs between today’s close and tomorrow’s open. The analysis was intentionally straightforward to emphasize a key takeaway: in my opinion, based on the empirical data, the significance of choosing the right trading days cannot be overstated! To illustrate, Thursdays and Fridays were responsible for 11 out of the top 17 most profitable days in 2022! As noted above, the number ’17’ wasn’t chosen arbitrarily; it represents 7% of the total trades for 2022—mirroring the same percentage applied in my 2023 analysis. With 251 trades in 2022, a quick calculation (251 * 7%, rounded down) brings us to those top 17 defining trades.

Applying These Findings to Trade Setups

If you’re reading this, it’s likely you’re already leveraging systematic trading software—a trend supported by JPMorgan’s 2017 data, which indicated that around 90% of futures traders and 80% of equities traders engage in algorithmic trading. Given this context, your trading system must afford the flexibility to select specific trading days; which will also help to clearly show you best performing days, as you run your backtests. Additionally, exercise caution with your R-Ratio on days historically void of “home run” opportunities. On some days, it may be prudent to take unrealized profits quickly, while on others, letting the trade run could be more beneficial. Using historical data may help in that regard!

Next, to stay ahead in the ever-changing market landscape, your automated trading strategy should have the capability to trail price based on a percentage you set, calculated from your peak unrealized profit – a traditional trailing stop that doesn’t have custom percentage-based logic can’t do that. Furthermore, your system should possess the acumen to meticulously filter trades according to prevailing market conditions—be it bullish, bearish, sideways, or volatile. This is critical for aligning your trading decisions with the market’s direction. For example, it would be counterproductive to enter a long position in a bearish market, or to enter a short position in a bullish market. The system should also allow you to specify current market price ranges, enabling more granular control over your trades. For instance, wading into a market that’s surged by 500 ticks in the last two hours with just a 20-tick stop could see you prematurely stopped out, watching the trend you predicted unfold without you!

If you’re still navigating the trading waters without an advanced automated trading system, or if you’re contemplating a switch, I’d like to introduce you to my proprietary trading system, AITPPropTrader™ – part of a comprehensive trading suite that includes AI-based prediction modeling. This unique system stands out in the industry for its capabilities. AITPPropTrader™ embodies all the essential features and functionalities I’ve outlined above, offering you a comprehensive solution for informed and effective systematic trading.

To request a no-obligation Zoom demonstration of AITPPropTrader™ or to make general inquiries, please visit

About The Author

This blog was authored by Raffi Sosikian. Raffi is a highly proficient software engineer, and enterprise architect. He has an MBA, holds a Series 3 license, and is the principal at Pinnacle Quant, LLC, CTA, a boutique commodity trading advisory firm that specializes in building both custom trading systems (including private label for small funds to brand as their own software), as well as in-house pre-built quant and price action based automated trading systems.

Happy trading!

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