In the complex world of financial markets, subtle patterns often reveal themselves through careful observation and analysis. Among these is the intriguing phenomenon we can call the “Lunch Effect,” a pattern observed in U.S. stock indexes where market performance tends to exhibit a distinct positive shift immediately after the lunch break, following a typically negative or flat performance earlier in the trading day right before the lunch. This lunchtime revival is not an isolated occurrence; it shares a curious connection with the “Overnight Effect,” a well-documented tendency for the U.S. stock market to experience the bulk of its appreciation during non-trading hours, with relatively little movement during the trading day itself. Together, these effects underscore the intricate dynamics of market behavior, where timing and investor psychology play crucial roles in shaping intraday and overnight market performance. Understanding these patterns can offer valuable insights into the rhythm of the markets and the underlying factors that drive short-term price movements.
In the U.S. stock market, an ordinary day can be divided into:
For simplification purposes, let us just state that it is not easy to trade a lot of instruments during nightly sessions. Most institutional investors use cash open and cash close and auctions to execute their either buy or sell orders to manage their positions; these are times of day that provide a lot of liquidity by market markets, options dealers, and liquidity providers. During the day, there are VWAP and TWAP algorithms and buy and sell programs that divide orders during the hours of the day and are pre-programmed to execute according to the situation and act on the news without human intervention.
We, small investors and individual traders, want to ride the wave, stand on the shoulder of the beast, and find patterns we can exploit. One of those is playing the overnight gaps (“fill the gap plays”, fading it up until the previous day’s close price or any other technically arbitrary level [support, whole or half number], “gap ‘n’ go” for a further same move from the initial price) or finding quiet times during the day when there is not much going on in the sense that liquidity dries down and is maintained chiefly by big banks algos, and the exact time of that is around lunchtime of New York time.
Because there is such a significant difference between the time when the market is open and most of the action takes place and the night session, when there are limited opportunities to trade, it’s no surprise that the US stock market performance over those two periods differs—like day and night. So what do the long-term statistics show us?
Multiple academic studies have found that the US equity premium is mostly due to overnight returns. This effect is called an Overnight Anomaly, and it is described in more detail by Cooper, Cliff and Gulen in “Return Differences between Trading and Non-Trading Hours: Like Night and Day” and in “Overnight Return, the Invisible Hand Behind The Intraday Return? A Retrospective” by Branch and Ma.
The genesis of this anomaly can be traced back to the mid-90s when firms began to release positive earnings surprises outside of market hours. This practice led to an accumulation of market orders, resulting in inflated opening prices that typically recede during the first hour of trading. While liquidity premiums contribute to some extent to the positive overnight returns, they account for only a minor fraction of the disparity between night and day returns.
Not just academics noticed this pattern. A worth-reading contribution is also from the blog content of a systematic individual investor named The Magic of Overnight Stock Market Returns (I) who tried to break down returns in sessions from past and current periods:
However, the devil is in the detail. While the long-term statistics show that the overnight anomaly is clearly visible over the extended window (1994-2024), when the window is shortened, it reveals that the overnight anomaly is highly sensitive to the start and end of the selected period. In the window from 2010 to 2021, the overnight anomaly nearly disappeared, with daily performance significantly converging towards nightly performance. Yet, for instance, in the window from 2017-2020, the overnight anomaly remains strongly present. This implies that caution is needed due to the sensitivity to macroeconomic and geopolitical periods.
This convergence between the nightly and daily session in the last years brings us to the next emerging phenomenon.
According to sayings and urban legends among traders, there exists a pattern in the intraday price action that happens around the NY noon time, when human traders go for lunch and algos hunt liquidity (NASDAQ and NYSE stocks) for the power (or sour) hour of trading.
There are anecdotal but documented occurrences of short reversal during Lunch hours in NY Cash sessions. Still, they are not documented in academic papers, but some evidence is mentioned in section 1:00–2:30 p.m.: Lunchtime Lull/Reversal listed in the book The Art of Trend Trading: Animal Spirits and Your Path to Profits by Michael Parness.
With the idea of studying the Overnight Anomaly and price action around lunchtimearound the Lun in mind, we obtained intraday data and decided to run our own analysis. Our timeframe is from the famous (first) Flash Crash of May 6, 2010, up to May 2024, and we considered doing this study only on S&P 500 INDEX (^SPX) represented by SPDR S&P 500 ETF Trust (SPY) data for our backtest.
Data about open and closing prices are from Yahoo Finance. We used the closing prices adjusted for splits and dividends and also adjusted the open prices. Hourly data were downloaded manually from Finram. (Data preprocessing was underdone with an essential stack of data engineering involving UNIX shell commands.) Hourly data were also adjusted for splits and dividends.
All times adhere to New York, Eastern Time (ET) (UTC-4). (As a side note, since our readers are not only American, we use the convention of 12-hour clock notation; basically, AM is morning, marking time before noon, and PM is making time after noon.).
The first thing we did was to download hourly data (data in hour samples) and look at the Overnight Effect and whether it still takes place:
From our investigation, we concluded (pretty much the same as the blog post and academic research mentioned above) that overnight effects still exist to some extent. However, nightly and daily sessions converged. The difference in return is not as strong as it was before; nightly sessions still outperform, but the spread is not statistically significant anymore.
And what about the Lunch Effect?
The second thing we did was to divide daily sessions into individual parts by hours, and we wanted how market performs in the morning, around lunchtime, and in the afternoon. We were initially especially interested in short-time reversal opportunities to expose in day trading timeframes. But did it materialize? Let the data decide.
From the plotted graph figure, we see that from cash open (9:30) up until 11 AM, we see modest gains and there is a little bit of pullback, negative drift from 11 AM to 12 PM. Subsequently, in the next hour, the market goes up on average, from 13 PM to 14 PM, too. Then, it is often churning and moving sideways, not having a distinctly trending move up until close, including the last hour of the trading day during the primary session, often dubbed as the Power Hour.
One should be aware that this is a price action from 2010, from the time when the convergence between the daily and nightly sessions started. But this finding does not guarantee that the market will be the same in the next 10 years if there are some policy changes (broader overnight trading, prolonging, or even having 24/5 markets, etc.).
So, what may be the simple Lunch Effect strategy?
The investment universe would contain only SPDR S&P 500 ETF Trust (SPY) (as a side note, the found findings shall be applicable within the same timeframes by other trading vehicles such as near-term [front] futures on the index itself [S&P 500 E-mini Futures, Continuous contract; CME_MINI-ES1!] or CFDs).
Based on our simplified model, we would propose the following rules:
Alternatively, if you are a discretionary trader: Look for shorting opportunities from 11 a.m. until 12 p.m.; afterward, look for opportunities to enter into long positions.
And how does this simple intraday strategy fare?
This is the equity curve (taking performance over time into account):
And pretty much the standard format of our reporting for performance and risk metrics:
Having reversed trades (short, then long) during lunch increases performance, albeit at the expense of the return-to-risk metrics. So, speculating on the after-lunch uptrend can be preferable for traders who prefer to just go long.
The main idea of this article was to disseminate lunch hour price action trading patterns, and ultimately, we somewhat succeeded in finding some relationships that can be exploited in the easily performed trading strategy we present. We hope to have provided some new remarks on how the session’s performances are developing. But there are still nuances that need to be covered. Tweaking the strategy’s parameters has potential, and it gives us a good perspective on revisiting it in the future.
Author: Cyril Dujava, Quant Analyst, Quantpedia
Are you looking for more strategies to read about? Sign up for our newsletter or visit our Blog or Screener.
Do you want to learn more about Quantpedia Premium service? Check how Quantpedia works, our mission and Premium pricing offer.
Do you want to learn more about Quantpedia Pro service? Check its description, watch videos, review reporting capabilities and visit our pricing offer.
Are you looking for historical data or backtesting platforms? Check our list of Algo Trading Discounts.
Or follow us on:
Facebook Group, Facebook Page, Twitter, Linkedin, Medium or Youtube
Share onLinkedInTwitterFacebookRefer to a friendBe first to know, when we publish new content
