Calendar Effects

Does the New Year’s Day holiday, a time of replanning and income tax positioning, systematically affect investors in a way that translates into U.S. stock market returns? To investigate, we analyze the historical behavior of the S&P 500 Index during the five trading days before and the five trading days after the holiday. Using daily closing levels of the S&P 500 Index around New Year’s Day for 1951-2022 (72 observations), we find that: Keep Reading

Does the U.S. stock market have a predictable pattern of returns around ends of calendar quarters? Do funds deploy cash to bid stocks up at quarter ends to boost portfolio values in quarterly reports (with subsequent reversals)? Or, do they sell stocks to raise cash for fund redemptions? Is any end-of-quarter effect distinct from the Turn-of-the-Month (TOTM) effect? To investigate, we calculate average daily stock market (S&P 500 Index) returns before and after ends of calendar quarters and compare those returns to TOTM returns. Using daily closes of the S&P 500 Index during January 1928 through mid-December 2022, we find that: Keep Reading

Does the Christmas holiday, a time of putative good will toward all, give U.S. stock investors a sense of optimism that translates into stock returns? To investigate, we analyze the historical behavior of the S&P 500 Index during five trading days before through five trading days after the holiday. Using daily closing levels of the S&P 500 Index for 1950-2021 (72 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 reliable and material market capitalization (size) effect among U.S. stocks around the turn-of-the-year (TOTY)? To check, we track cumulative returns from 20 trading days before through 20 trading days after the end of the calendar year for the Russell 2000 Index, the S&P 500 Index and the Dow Jones Industrial Average (DJIA) since the inception of the Russell 2000 Index. We also look at full-month December and January returns for these indexes. Using daily and monthly levels of all three indexes during December 1987 through January 2022 (35 December and 35 January observations), we find that: Keep Reading

Do hopes and fears of U.S. election outcomes, and associated political machinations, alter the “normal” seasonal variation in monthly stock market returns? To check, we compare average returns and variabilities (standard deviations of returns) by calendar month for the S&P 500 Index during years with and without quadrennial U.S. presidential elections and biennial congressional elections. Using monthly S&P 500 Index closes over the period December 1927 through September 2022 (nearly 95 years), we find that: Keep Reading

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