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Value Allocations for December 2019 (Final)
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Momentum Allocations for December 2019 (Final)
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Calendar Effects

The time of year affects human activities and moods, both through natural variations in the environment and through artificial customs and laws. Do such calendar effects systematically and significantly influence investor/trader attention and mood, and thereby equity prices? These blog entries relate to calendar effects in the stock market.

SACEMS, SACEVS and Trading Calendar Updates

We have updated monthly allocations and performance data for the Simple Asset Class ETF Momentum Strategy (SACEMS) and the Simple Asset Class ETF Value Strategy (SACEVS). We have also updated performance data for the Combined Value-Momentum Strategy.

We have updated the Trading Calendar to incorporate data for November 2019.

U.S. Stock Market Returns Around Thanksgiving

Does the Thanksgiving holiday, a time of families celebrating plenty, 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 the three trading days before and the three trading days after the holiday. Using daily closing levels of the S&P 500 Index for 1950-2018 (69 events), we find that: Keep Reading

Extra Attention to Earliest Quarterly Earnings Announcements

Does the market react most strongly to the earliest quarterly earnings announcements? In their October 2019 paper entitled “Calendar Rotations: A New Approach for Studying the Impact of Timing using Earnings Announcements”, Suzie Noh, Eric So and Rodrigo Verdi study effects of the relative order of U.S. firm quarterly earnings announcements, which vary systematically for some firms according to the day of the week of the first day of a month. Specifically, they qualify firms by identifying those firms that exhibit systematic earnings announcement schedules (such as Friday of the fourth week after quarter ends, sometimes set in firm bylaws) for at least four consecutive same fiscal quarters. They then for each firm each fiscal quarter:

  • Calculate EA Order, ranking of earnings announcement date divided by number of firms with the same fiscal quarter-end.
  • Compute change in EA Order compared to the same fiscal quarter last year, indicating a calendar acceleration or delay in announcement. Positive (negative) change in EA Order indicates delay (acceleration)
  • Examine effects of change in EA Order on media coverage (number of articles), stock trading volume and stock return from one trading day before to one trading day after earnings announcement.

Using sample of 76,622 firm-quarters during 2004 through 2017, they find that: Keep Reading

SACEVS with Quarterly Allocation Updates

Do quarterly allocation updates for the Best Value and Weighted versions of the “Simple Asset Class ETF Value Strategy” (SACEVS) work as well as monthly updates? These strategies allocate funds to the following asset class exchange-traded funds (ETF) according to valuations of term, credit and equity risk premiums, or to cash if no premiums are undervalued:

3-month Treasury bills (Cash)
iShares 20+ Year Treasury Bond (TLT)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR S&P 500 (SPY)

Changing from monthly to quarterly allocation updates does not sacrifice information about lagged quarterly S&P 500 Index earnings, but it does sacrifice currency of term and credit premiums. To assess alternatives, we compare cumulative performances and the following key metrics for quarterly and monthly allocation updates: gross compound annual growth rate (CAGR), gross maximum drawdown (MaxDD), annual gross returns and volatilities and annual gross Sharpe ratios. Using monthly dividend-adjusted closes for the above ETFs during September 2002 (earliest alignment of months and quarters) through September 2019, we find that:

Keep Reading

National Election Cycle and Stocks Over the Long Run

“Stock Market and the National Election Cycle” examines the behavior of the U.S. stock market across the U.S. presidential term cycle (years 1, 2, 3 or 4) starting in 1950. Is a longer sample informative? To extend the sample period, we use the long run S&P Composite Index of Robert Shiller. The value of this index each month is the average daily level during that month. It is therefore “blurry” compared to a month-end series, but the blurriness is not of much concern over a 4-year cycle. Using monthly S&P Composite Index levels from the end of December 1872 through August 2019 (about 37.5 presidential terms), we find that:

Keep Reading

Stock Market and the National Election Cycle

Some stock market experts cite the year (1, 2, 3 or 4) of the U.S. presidential term cycle as a useful indicator of U.S. stock market returns. Game theory suggests that presidents deliver bad news immediately after being elected and do everything in their power to create good news just before ensuing biennial elections. Are some presidential term cycle years reliably good or bad? If so, are these abnormal returns concentrated in certain quarters? Finally, what does the stock market do in the period immediately before and after a national election? Using daily and monthly S&P 500 Index levels from January 1950 through August 2019 (nearly 70 years and about 17 presidential terms) and focusing on “political quarters” (Feb-Apr, May-Jul, Aug-Oct and Nov-Jan), we find that: Keep Reading

Stock Returns Around Labor Day

Does the Labor Day holiday, marking the end of summer vacations, signal any unusual return effects by refocusing U.S. stock investors on managing their portfolios? By its definition, this holiday brings with it any effects from the turn of the month. To investigate the possibility of short-term effects on stock market returns around Labor Day, we analyze the historical behavior of the stock market during the three trading days before and the three trading days after the holiday. Using daily closing levels of the S&P 500 Index for 1950 through 2018 (69 observations), we find that: Keep Reading

Optimal Cycle for Monthly SMA Signals?

A subscriber commented and asked:

“Some have suggested that the end-of-the-month effect benefits monthly simple moving average strategies that trade on the last day of the month. Is there an optimal day of the month for long-term SMA calculation and does the end-of-the-month effect explain the optimal day?”

To investigate, we compare 21 variations of a 10-month simple moving average (SMA10) timing strategy generated by shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM). Specifically, the 21 variations represent calculation cycles ranging from 10 trading days before EOM (EOM-10) to 10 trading days after EOM (EOM+10). We apply the strategy to the S&P 500 Index as a proxy for the U.S. stock market. The strategy holds the S&P 500 Index (cash) whenever the index is above (below) its SMA10 as of the most recent monthly calculation. Using daily S&P 500 Index closes and 3-month Treasury bill (T-bill) yields as the return on cash during January 1990 through mid-June 2019, we find that: Keep Reading

Monthly Returns During Presidential and Congressional Election Years

Do hopes and fears of election outcomes in the U.S. affect 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 Dow Jones Industrial Average (DJIA) during years with and without quadrennial U.S. presidential elections and biennial congressional elections. Using monthly closes for the DJIA over the period October 1928 through May 2019 (nearly 91 years), we find that: Keep Reading

Stock Market Behavior Around Mid-year and 4th of July

The middle of the year might be a time for funds to dress their windows and investors to review and revise portfolios. The 4th of July celebration might engender optimism among U.S. investors. Are there any reliable patterns to daily U.S. stock market returns around mid-year and the 4th of July? To check, we analyze the historical behavior of the S&P 500 Index from five trading days before through trading days after both the end of June and the 4th of July. Using daily closing levels of the index for 1950-2018 (69 years), we find that: Keep Reading

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