Day of the Week Effect: What the Research Shows for Traders
The day of the week effect is the finding that market returns and volatility are not spread evenly across weekdays. In stocks, the best-documented pattern is weaker returns and higher volatility on Mondays than on Fridays. But the pattern changes with the era, the index and the market, so it works as context for your decisions and not as a forecast for next Monday.
TL;DR
The effect is a long-studied stock-market anomaly: a meta-analysis covering 1980 to 2022 found lower average returns on Mondays and Tuesdays and higher returns on Wednesdays and Fridays.
Volatility patterns look more robust than return patterns. US research spanning 1928 to 2023 finds lower mean returns and higher volatility on Mondays than on Fridays.
Results depend on the sample period and the index, and the effect was stronger in the 1980s and 1990s than it is now.
Forex and Bitcoin show their own weekday quirks, and they do not copy the stock-market pattern.
Before you trade a weekday pattern, test it on your own data, with costs, and judge it by sample size.
Table of Contents
What the day of the week effect actually is
The day of the week effect (also called the weekday effect, the Monday effect or the weekend effect) is a calendar anomaly. Average returns, or the size of price swings, differ by weekday in a way that a perfectly random market would not produce. Academics treat it as an anomaly because it challenges the Efficient Market Hypothesis, the idea that prices already reflect available information and that no day should be systematically better or worse.
The stock version is usually called the weekend effect: returns are lower on Mondays than on Fridays. Investopedia notes it was first documented by Frank Cross in 1973. The same page says it has fluctuated over the decades, disappearing between 1987 and 1998 before resurging.
Two things get mixed up in most discussions, so keep them apart:
Return effects: does the average close-to-close change differ by weekday?
Volatility effects: does the size of the moves, up or down, differ by weekday?
For a trader, the second often matters more. A day with wider swings changes your stop placement, position size and the odds of getting stopped out, even when the average direction is no different.
What decades of stock-market data show
The broadest recent evidence is a 2024 meta-analysis of day-of-the-week studies covering data from 1980 to 2022. It found lower average daily returns on Mondays and Tuesdays, with Wednesdays and Fridays showing higher returns. It also stresses that findings depend on the time period and the index chosen, so the results are not uniform.
A 2025 paper on US indicators from 1928 to 2023 adds detail on shape, not just averages. It documents negative conditional skewness on Mondays. In plain terms, Mondays are more likely than Fridays to deliver frequent small gains with an occasional large loss. That is a risk-profile statement, not a direction call.
Here is how the main findings line up:
Study focus | Period | Main weekday finding |
Meta-analysis of many markets | 1980 to 2022 | Lower returns Monday and Tuesday, higher Wednesday and Friday |
US stock indicators | 1928 to 2023 | Lower mean return and higher volatility on Monday than Friday |
S&P 500 | January 1973 to October 1997 | Highest volatility Friday, lowest Wednesday; highest returns Wednesday, lowest Monday |
Five developed markets | 1988 to 2002 | |
US expected volatility (VIX-based) | 2000 to 2020 |
Look at the S&P 500 row against the 2025 US row. One finds the highest volatility on Friday in the 1970s and 1990s, the other finds higher volatility on Monday than Friday over almost a century. Both can be true because they measure different windows and different things. That is the main lesson of this research: the pattern is real in the aggregate and unstable in the details.
The Monday volatility story in the VIX
One of the more useful findings for active traders comes from options-implied volatility. A 2022 analysis of 30-day expected volatility across US securities and indices found that expected volatility is systematically higher on Mondays and lower on Fridays. The significant jumps came mainly in the first two Mondays and the fifth Monday of the month. The same study used sign tests to check whether weekday changes differ from a 50% coin flip, checked robustness across subsamples, and reported that theoretical trading profits persisted after reasonable transaction costs.
Treat that last point carefully. It describes theoretical profits in a research setting. It does not mean a retail trader will capture them with real fills, slippage and emotions.
Not just Monday: the Tuesday effect
Mondays get the headlines, but several markets show weak Tuesdays. Research notes that some markets, such as Japan, Australia and Turkey, have a Tuesday effect with a significantly negative mean return, lower than Wednesday, Thursday and Friday. One common reading is that Asian and Australian sessions are partly responding to the weak US Monday that finishes hours earlier. If you trade global indices or index futures, this is a reminder that your local weekday and the market’s weekday are not always the same story.
Why would weekdays differ at all?
Nobody has a single settled explanation. The main proposals researchers offer are:
Investor behavior. Investopedia points to the irrational trading of individual investors, especially extra selling on Mondays after negative news, as at least one contributing factor. Other ideas listed there include bad news released on Fridays and short selling around the weekend.
Timing of bad news. The information release hypothesis says firms tend to release good news quickly and push bad news out after the close on Friday, which can weigh on demand on Monday, as a US study of 1952 to 2006 describes.
Informed traders. The same study notes the proposal that informed traders hold more information on Mondays than on other days, which could raise the variance of price changes.
Liquidity. Researchers argue that high volatility often comes with low volume, because liquidity traders are unwilling to participate in volatile periods, as in the five-country volatility study.
A mix of rational and irrational drivers. The authors of the VIX study suggest both kinds of drivers explain the non-random movement of expected volatility on Mondays and Fridays.
For a trader, the practical takeaway is that the causes are partly human: weekend news digestion, risk-off positioning before time off, and thinner or more nervous participation at the edges of the week. Human habits change slowly, but they do change, which is one reason the effect fades and returns.
The effect fades, and that matters
The meta-analysis reports that the day-of-the-week effect was more substantial in the 1980s and 1990s. Investopedia describes the weekend effect vanishing for a stretch between 1987 and 1998. When a pattern becomes well known, traders act on it, and acting on it competes it away. A strategy that buys Friday close and sells Monday close would have looked very different depending on which decade you test.
That is why the honest summary is not “Mondays are bad.” It is “Mondays have, on average, had lower returns and higher volatility in a lot of data, with exceptions large enough to hurt you if you trade it blindly.”
Forex and crypto: different markets, different weekdays
Forex
Forex runs around the clock on weekdays, so the weekend gap works differently from stocks. A 2008 study of yen/dollar spot rates in Tokyo, London and New York found that the traditional Monday effect disappeared. Tuesday showed negative, significantly lower returns, while Thursday showed a significantly higher return than the other weekdays. If you trade currency pairs, the stock Monday pattern is a poor guide, and each pair should be checked on its own.
Bitcoin and crypto
Crypto trades seven days a week, so there is no closed weekend to produce a gap. Even so, weekday patterns appear. A study of Bitcoin data from 2013 to 2018 found that the day-of-the-week effect on returns varies with the sample period, while significantly high volatility showed up consistently on Mondays and Thursdays. The researchers also observed that Bitcoin’s high Monday mean return is a response to higher Monday volatility, and that finding held up after controlling for major stock and forex returns.
The lesson: in crypto, volatility timing looks sturdier than return direction. If you are weighing how Bitcoin behaves against other major coins, this comparison of Bitcoin and Ethereum popularity is a useful companion, because weekday behavior can differ between assets. Note too that the Bitcoin sample ends in 2018, long before the current market structure of spot products and heavy derivatives trading, so check recent data before leaning on it.
What is the worst day of the week for the stock market?
If you need a one-line answer, the research supports this: historically the weakest returns cluster at the beginning of the week, most often Monday, with Tuesday weak in some markets. That is an average across many observations, not a prediction. Individual Mondays have been big up days and some of the worst crashes have hit on other days. Use “worst day” as a description of the historical average and not as a reason to avoid the market.
How to test a weekday pattern before you trust it
A weekday pattern is only useful if it survives scrutiny. This is the process that the better studies follow, scaled down for a trader with a spreadsheet or a journal.
Define the claim in one sentence. For example: “On my instrument, Monday sessions have a wider range than Friday sessions.” Vague claims cannot be tested.
Pull enough data. Count observations per weekday. A few dozen Mondays is thin. Several hundred is better. State the sample size next to every result.
Check more than one period. Split the data into subsamples, such as halves or by year. The Bitcoin research shows how a return effect can change with the window. If the pattern only appears in one slice, it is probably noise.
Test against chance. The VIX study used sign tests against a 50% baseline. You can do a simple version: how often was Monday’s change positive, and is that meaningfully different from half?
Separate return from volatility. Measure average return and average range or standard deviation separately. Volatility patterns tend to be more usable for sizing and stops.
Subtract costs. Spreads, fees, funding and slippage can erase a small edge. The research says profits persisted after reasonable costs in theory; your own costs may differ.
Re-test out of sample. Hold back recent data and see whether the pattern still shows up there.
When traders ask how to size trades on high-volatility days, order choice matters too. Our guide to market versus limit orders covers how fills behave when markets move fast.
Using weekday patterns without fooling yourself
Three habits keep the effect in its proper role.
Use it as a risk filter, not an entry trigger. If Mondays tend to carry higher volatility, widen your risk planning on Mondays or trade smaller, rather than buying or shorting just because it is Monday.
Watch your own calendar. Many traders overtrade at the start of the week, chasing weekend news, or at the end, trying to “make the week.” That is a behavior pattern in you, not the market. Our pieces on how to avoid overtrading in crypto and spotting overtrading signals in a stock portfolio show how to catch it.
Let the data speak about you, too. Your own journal may show that your Wednesday trades beat your Monday trades by a wide margin. That personal weekday pattern can be more actionable than any academic average. See our trader behavior tracking guide for beginners for how to start collecting it.
Common mistakes
Treating an average as a rule. A lower average Monday return still includes many winning Mondays.
Ignoring regime. Weekday effects shift with the market environment. A pattern from a calm bull run may vanish in a volatile selloff.
Data mining. Test enough combinations (weekday, month, week of the month) and something will look significant by luck. The VIX research found that jumps clustered in specific Mondays of the month, which is the kind of detail that needs out-of-sample confirmation before you act on it.
Forgetting time zones. A “Monday” in Tokyo, London and New York are different slices of the same global flow, and crypto’s day boundary is a convention (often UTC), not a market close.
Skipping costs. Frequent weekday-based trades multiply fees.
We like the day of the week effect for one reason: it is a clean example of why traders should demand evidence before they act. A pattern can be real on average, fade over a decade, reverse in another market and still tempt people into a rule like “never trade Mondays.” That is how we built Discipline AI. Sentinel, our research system, looks at market structure, liquidity events, trend direction, volatility and market regimes across multiple cryptocurrencies and timeframes, and it weighs the strength of supporting evidence, including sample size. A weekday is one small input among many. Whether conditions favor a setup, or call for standing aside, depends on the regime you are actually in. We also think the most valuable weekday pattern is your own. Journaling, performance analytics and AI Trade Autopsies are there so you can see whether you take worse trades on certain days, and fix the behavior instead of blaming the calendar. Paper trading lets you test a weekday idea with no capital at risk before it touches real money. We do not promise profitable trades, and no calendar effect does either. We aim to make your decisions more informed, your risk planning tighter and your learning measurable. Tony
Our perspective on weekday patterns
Put your weekday hypothesis to the test
If you want to check a weekday idea against your own trading, Discipline AI brings the pieces into one app on iOS and Android: paper trading, automated trade journaling, performance analytics, risk planning tools and market-condition analysis from Sentinel. Pro is $8.99 per month, $79.99 per year or $199.99 one-off, so you can pick the billing style that suits how long you plan to test.
If you want a structured approach to the habits behind the numbers, The Disciplined Trader is available as a $79 one-off purchase. For a broader look at how the platform helps with pattern work, read about how AI detects trading patterns and what AI can and cannot do here, or start from the Discipline AI home page.
FAQ
What is the day of the week effect in simple terms?
It is the tendency for returns or volatility to differ by weekday. In US stocks, the best-known version is lower returns and higher volatility on Mondays than on Fridays. It is an average over many years, so it does not tell you what any single Monday will do.
What is the worst day of the week for the stock market?
Historically, the weakest average returns appear at the start of the week, usually Monday, and in some markets Tuesday. The 2024 meta-analysis found lower returns on both days. Averages hide a lot of variation, and the effect has weakened since the 1980s and 1990s.
Does the day of the week effect work in crypto?
Crypto shows weekday patterns, but they are less stable than a simple rule suggests. Bitcoin research covering 2013 to 2018 found that return effects changed with the sample period, while high volatility appeared consistently on Mondays and Thursdays. Test any crypto weekday idea on recent data for your own pair.
Can I trade the day of the week effect profitably?
Research suggests theoretical profits can survive reasonable transaction costs, but that is under study conditions. Real trading adds slippage, fees and behavior. Test the pattern across several periods, subtract your actual costs and practice it in paper trading before risking capital.
Why does the effect change over time?
Markets adapt. As traders learn about a pattern and trade it, the edge tends to shrink, and the drivers, such as news timing and investor behavior, shift as well. That is why studies of different eras and indexes reach different conclusions.
Sources
Day-of-the-week effect: a meta-analysis (Eurasian Economic Review)
Day-of-the-week effect on stock market returns, volatility (Taylor & Francis, 2025)
The day of the week effect on stock market volatility and volume (ScienceDirect)
The Day of the Week Effect on Stock Market Volatility (Bilkent University)
Stock market return and volatility: day-of-the-week effect (Bilkent repository)
Weekday effect of the yen/dollar spot rates (Taylor & Francis)
The day-of-the-week effect on Bitcoin return and volatility (ScienceDirect)
Understanding the Weekend Effect in Stock Markets (Investopedia)
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