Calendar Effects

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

What best explains the decades-long pattern of strong overnight and weak intraday returns in most equity markets? In his January 2022 paper entitled “They Still Haven’t Told You”, Bruce Knuteson reviews possible explanations for this pattern and identifies the most likely. His theoretical equity index benchmark is a random walk with slight upward drift (due to general economic expansion and survivorship bias), with intraday return on average larger than overnight return due to higher intraday risk. Using close-to-open and open-to-close levels of 21 major stock market indexes as available during January 1990 through December 2021, he finds that: Keep Reading

Trading Calendar presents full-year and monthly cumulative performance profiles for the overall U.S. stock market (proxied by the S&P 500 Index) based on average daily behavior. Do monthly behaviors of U.S. stock market sectors deviate from the overall market profile? To investigate, we consider the nine Select Sector Standard & Poor’s Depository Receipts (SPDR) exchange-traded funds (ETF), all of which originate in December 1998:

Materials Select Sector SPDR (XLB)
Energy Select Sector SPDR (XLE)
Financial Select Sector SPDR (XLF)
Industrial Select Sector SPDR (XLI)
Technology Select Sector SPDR (XLK)
Consumer Staples Select Sector SPDR (XLP)
Utilities Select Sector SPDR (XLU)
Health Care Select Sector SPDR (XLV)
Consumer Discretionary Select SPDR (XLY)

Using monthly dividend-adjusted closing prices for these ETFs, along with contemporaneous data for SPDR S&P 500 (SPY) as a benchmark, during December 1998 through December 2021, we find that: Keep Reading

In response to “Combining Defensive-in-May and Sector Reversion”, a subscriber requested testing of a strategy combining seasonal effects (cyclical sectors during November through April and defensive sectors during May through October) and sector momentum. Cyclical and defensive choices are:

• Cyclical:
  • Materials Select Sector SPDR (XLB)
  • Industrial Select Sector SPDR (XLI)
  • Technology Select Sector SPDR (XLK)
  • Consumer Discretionary Select SPDR (XLY)
  • Vanguard Small-Cap Value Index Fund (VBR)
• Defensive:
  • Consumer Staples Select Sector SPDR (XLP)
  • Utilities Select Sector SPDR (XLU)
  • Health Care Select Sector SPDR (XLV)
  • Vanguard Dividend Appreciation Index Fund (VIG)
  • iShares 7-10 Year Treasury Bond (IEF)

At the end of each October, the strategy buys the one cyclical fund with the highest return over some past interval (betting on momentum). At the end of each April, the strategy sells the cyclic fund and buys the one defensive fund with the highest return over the past interval (again, betting on momentum). For convenience, we use a 6-month lookback interval to rank funds. We use buy-and-hold SPDR S&P 500 (SPY) as a benchmark. We focus on semiannual return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using semiannual dividend-adjusted prices for the selected funds during October 2006 (limited by availability of VIG) through October 2021 (defining the first and last available semiannual intervals), we find that: Keep Reading

Inspired by “The iM Seasonal ETF Switching Strategy”, a subscriber requested testing of a strategy combining seasonal effects (cyclical sectors during November through April and defensive sectors during May through October) and sector reversion. Cyclical and defensive choices are:

• Cyclical:
  • Materials Select Sector SPDR (XLB)
  • Industrial Select Sector SPDR (XLI)
  • Technology Select Sector SPDR (XLK)
  • Consumer Discretionary Select SPDR (XLY)
  • Vanguard Small-Cap Value Index Fund (VBR)
• Defensive:
  • Consumer Staples Select Sector SPDR (XLP)
  • Utilities Select Sector SPDR (XLU)
  • Health Care Select Sector SPDR (XLV)
  • Vanguard Dividend Appreciation Index Fund (VIG)
  • iShares 7-10 Year Treasury Bond (IEF)

At the end of each October, the strategy buys the one cyclical fund with the lowest return over some past interval (betting on reversion). At the end of each April, the strategy sells the cyclic fund and buys the one defensive fund with the lowest return over the past interval (again, betting on reversion). For convenience, we use a 6-month lookback interval to rank funds. We use buy-and-hold SPDR S&P 500 (SPY) as a benchmark. We focus on semiannual return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using semiannual dividend-adjusted prices for the selected funds during October 2006 (limited by availability of VIG) through October 2021 (defining the first and last available semiannual intervals), we find that: Keep Reading