Calendar Effects

Investor mood may affect financial markets. Sports may affect investor mood. The biggest mood-mover among sporting events in the U.S. is likely the National Football League’s Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super Bowl focusing and anxiety-relieving? Presumably, post-game elation and depression cancel between respective fan bases. Using past Super Bowl dates since inception and daily/weekly S&P 500 Index levels for 1967 through 2022 (56 events), we find that: Keep Reading

Do annual stock market swing returns swing around their average like a pendulum? In the November update of his 2022 paper entitled “Periodic Structure of Equity Market Annual Returns and Their Predictability”, Daniel Pinelis investigates whether annual returns of the S&P 500 Index and the NASDAQ Composite Index exhibit reliable periodicity. Specifically, he models an oscillator indicator that accumulates directional imbalances in annual stock index returns and applies the indicator, in combination with statistical, graphical and machine learning methods, to estimate extent and timing of further market declines from the current levels. Using annual returns for the S&P 500 Index since the mid-1960s and for the NASDAQ Composite Index since the early 1970s, both through late 2022, he finds that:

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Is there a best time of the month for measuring momentum within the Simple Asset Class ETF Momentum Strategy (SACEMS)? To investigate, we compare 21 variations of baseline SACEMS by shifting the monthly return calculation cycle from 10 trading days before the end of the month (EOM) to 10 trading days after EOM. For example, an EOM+5 cycle ranks assets based on closing prices five trading days after EOM each month. We focus on gross compound annual growth rate (CAGR) and gross maximum drawdown (MaxDD) as key performance statistics for the Top 1, equally weighted (EW) Top 2 and EW Top 3 portfolios of monthly winners. Using daily dividend-adjusted prices for SACEMS assets during mid-February 2006 through mid-October 2022, we find that:

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Do morning and afternoon stock returns convey different meanings due to gradual dissipation of information asymmetry among traders during the trading day (as the market digests overnight news)? In their August 2022 paper entitled “A Tale of One Day: Morning Momentum, Afternoon Reversal”, Haoyu Xu and Xiaoneng Zhu investigate differences in implications for reversal and momentum strategies among morning (9:30AM – 11:30AM), midday (11:30AM – 2:00PM) and afternoon  (2:00PM – 4:00PM). Specifically, they:

• For each stock each month, cumulate returns over these three intervals.
• Sort stocks into tenths, or deciles, based either on cumulative returns over the most recent month (for reversal testing) or compounded cumulative returns from 12 months ago to one month ago (for momentum testing) for different combinations of these three intervals.
• Reform various long-short portfolios using extreme deciles to explore the different predictive powers of past morning and afternoon returns.

For reversal tests, they apply equal weighting. For momentum tests, they consider both value and equal weightings. They calculate raw returns, 3-factor (market, size, book-to-market) alphas and 4-factor (adding momentum) alphas as essential performance statistics. They use conventional strategies using full daily returns as benchmarks. Using intraday and daily return data for a broad sample of U.S. common stocks priced at least $5 during 1993 through 2018, they find that:

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Does the U.S. stock market respond predictably to Federal Open Market Committee (FOMC) announcements, typically released between 14:00 and 14:20 EST? In the August 2022 version of their paper entitled “The FOMC Announcement Reversal”, Tommaso Baglioni and Ruy Ribeiro examine the relationship between pre-FOMC announcement returns and post-FOMC announcement returns. Specifically, they test a reversal strategy that buys (sells) E-mini S&P 500 just before announcement at 13:50 EST when the return during the 24 hours before the announcement is negative (positive) and closes the position at the end of the trading day. They buy at the ask and sell at the bid to account for trading frictions. They compute average cumulative return per round trip transaction and Sharpe ratio as average return divided by standard deviation (standardized to reflect one trading day and the number of hours the position is open). They consider two subperiods (October 1997 through March 2011 and April 2011 through January 2020). They also look at interactions of strategy performance with four measures of economic conditions: market uncertainty (VIX), economic policy uncertainty, monetary policy uncertainty and consumer sentiment. Using intraday E-mini S&P 500 prices, exact FOMC announcement release data and measures of economic conditions on FOMC announcement dates during mid-October 1997 through January 2020 (a total of 180 scheduled FOMC announcements), they find that:

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Over at least the past three decades, 100% or more of the return (0% or negative return) on a wide range of risky assets occurs when markets are closed (open). Is this overnight effect important to investors? In their June 2022 paper entitled “Night Moves: Is the Overnight Drift the Grandmother of All Market Anomalies”, Victor Haghani, Vladimir Ragulin and Richard Dewey briefly review the dozen or so papers exploring this effect, mostly focused on broad stock market returns. They then take a closer look at whether the effect applies to individual U.S. stocks and discuss implications for investors. Using results of past research and overnight and intraday prices for selected exchange-traded funds (ETF) and stocks as available since the mid-1990s through May 2022, they find that: Keep Reading

A subscriber asked whether the Turn-of-the-Month (TOTM) effect applies to currencies. To investigate, as in the past, we define TOTM as the interval from the close five trading days before to the close four trading days after the last trading day of the month (a total of eight trading days, centered on the monthly close). We measure TOTM returns for the following four exchange-traded funds (ETF):

Invesco DB US Dollar Bullish (UUP)
Invesco CurrencyShares Euro Currency (FXE)
Invesco CurrencyShares Japanese Yen (FXY)
WisdomTree Chinese Yuan Strategy (CYB)

Using daily dividend-adjusted prices for these ETFs from their respective inceptions through mid-June 2022, we find that: Keep Reading

Are there anomalies for U.S. stock market returns around equity option expiration (OE) days (normally the third Friday of each month, but the preceding Thursday when the market is closed on the third Friday)? To investigate, we examine close-to-close S&P 500 Index returns from five trading days before through five trading days after a moderately large sample of OE days. Using daily closing prices for the index during January 1990 through February 2022 (386 OE days), we find that:

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Does the overnight return effect found pervasively among equity markets, as summarized in “Persistence of Overnight/Intraday Equity Market Return Patterns”, also hold for other asset classes? To investigate, we compare open-to-close (O-C) and close-to-open (C-O) average returns, standard deviations of returns and cumulative performances for the exchange-traded funds (ETF) used as asset class proxies in the Simple Asset Class ETF Momentum Strategy (SACEMS). Using daily dividend-adjusted opening and closing prices of these ETFs during mid-December 2007 (inception of the youngest ETF) through early March 2022, we find that: Keep Reading

With reference to “Turn-of-the-Month Effect Persistence and Robustness” and “Persistence of Overnight/Intraday Equity Market Return Patterns”, a subscriber asked about a strategy that is long SPDR S&P 500 ETF Trust (SPY) only from market close to market open during the turn-of-the-month (TOTM). To investigate, we consider three strategies:

1. TOTM Close-to-Open: long SPY from close-to-open during TOTM, and otherwise in cash (eight round-trip trades per month).
2. TOTM Close-to-Close: long SPY continuously during TOTM, and otherwise in cash (one round-trip trade per month).
3. B&H: buy and hold SPY.

We initially ignore trading frictions, but then look at breakeven frictions for the first strategy. Because of trading frequency, we ignore return on cash. We focus on compound annual growth rate (CAGR) and maximum drawdown (MaxDD) based on daily data as key performance statistics. Using daily dividend-adjusted opens and closes for SPY during February 1993 (inception) through February 2022, we find that: Keep Reading