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 1951-2018 (68 observations), 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 1950-2017 (68 events), we find that: Keep Reading

As a follow-up to “Sunspot Cycle and Stock Market Returns” a reader asked: “Sunspot activity does have a direct relationship to weather. Could one speculate on the agriculture market using the sunspot cycle?” To investigate, we relate sunspot activity to the fairly long U.S. Producer Price Index (PPI) for grains. Using monthly averages of daily sunspot counts and monthly PPI for grains during January 1926 (limited by PPI data) through October 2018, we find that: Keep Reading

A reader asked whether Charles Nenner, self-described as “the talk of Wall Street since accurately predicting some of the biggest moves in the Markets over the past few years,” accurately forecasts equity and commodity markets. We consider the following:

• In his July 2007 discussion of the “Nenner Methodology at the Bloomberg Studio”, Charles Nenner cites sunspot activity as a specific key indicator for equity returns. Per this source, he believes that the sunspot cycle correlates strongly with equity markets via the predictable effects of magnetic field disturbances on investors.
• In “Sunspots Predict ‘Major Crisis’ After 2013: Chartist”, he states: “If there is a high intensity of sunspots, markets rise, if their intensity lowers, markets go down because sunspots affect people’s mood.”

Is there a reliable relationship between sunspot activity and stock market returns? Using monthly averages of daily sunspot counts and monthly levels of Shiller’s S&P Composite Index (also monthly averages of daily levels) during January 1871 (limited by the Shiller data) through October 2018, we find that: Keep Reading

Is there a flip side of cyclic relative weakness to the cyclic relative strength described in “Pervasive 12-Month (and 5-Day) Relative Strength Cycles?”? In their October 2018 paper entitled “Seasonal Reversals in Expected Stock Returns”, Matti Keloharju,Juhani Linnainmaa and Peter Nyberg test whether cyclic weakness (seasonal reversal) balances the cyclic strength (seasonality) effect. For example, if a stock is seasonally strong in March, it may be seasonally weak across other months. They test this hypothesis using actual monthly U.S. stock returns and simulated returns calibrated to actual returns. Specifically, they compute correlations between average historical returns for a stock during one month and the sum of its historical average returns during other months. In robustness tests, they repeat this test for 10-year subperiods and for daily U.S. stock returns, monthly non-U.S. stock returns, monthly country stock indexes, monthly country government bond indexes and monthly commodity returns. Finally, they construct the following three factors for U.S. stocks by first each month sorting stocks into two size groups (small and big market capitalizations) and then:

1. Seasonality factor – Sorting each size group into three average same-calendar-month past return portfolios. The factor return is the difference in value-weighted returns between the two highest-average portfolios and the two lowest-average portfolios.
2. Seasonal reversal factor – Sorting each size group into three average other-calendar-month past return portfolios within each size group. The factor return is the difference in value-weighted returns between the two lowest-average and the two highest-average portfolios.
3. Annual-minus-non-annual factor – Sorting each size group into three portfolios based on the difference between the average same-calendar-month and other-calendar-month returns. The factor return is the difference in value-weighted returns between the two largest-difference and the two smallest-difference portfolios.

Using U.S. monthly and daily stock returns since 1963 and monthly returns for country stocks and stock market indexes, country government bond indexes and commodities since the end of 1974, all through 2016, they find that:

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Is the U.S. equity turn-of-the-month (TOTM) effect exploitable as a diversifier of other assets? In their October 2018 paper entitled “A Seasonality Factor in Asset Allocation”, Frank McGroarty, Emmanouil Platanakis, Athanasios Sakkas and Andrew Urquhart test U.S. asset allocation strategies that include a TOTM portfolio as an asset. The TOTM portfolio buys each stock at the open on the last trading day of each month and sells at the close on the third trading day of the following month, earning zero return the rest of the time. They consider four asset universes with and without the TOTM portfolio:

1. A conventional stocks-bonds mix.
2. The equity market portfolio.
3. The equity market portfolio, a small size portfolio and a value portfolio.
4. The equity market portfolio, a small size portfolio, a value portfolio and a momentum winners portfolio.

They consider six sophisticated asset allocation methods:

1. Mean-variance optimization.
2. Optimization with higher moments and Constant Relative Risk Aversion.
3. Bayes-Stein shrinkage of estimated returns.
4. Bayesian diffuse-prior.
5. Black-Litterman.
6. A combination of allocation methods.

They consider three risk aversion settings and either a 60-month or a 120-month lookback interval for input parameter measurement. To assess exploitability, they set trading frictions at 0.50% of traded value for equities and 0.17% for bonds. Using monthly data as specified above during July 1961 through December 2015, they find that:

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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 1950-2017 (68 events), we find that: Keep Reading

Do intraday U.S. stock returns still tend to reverse preceding overnight returns as found in prior research? In their August 2018 paper entitled “Overnight Return, the Invisible Hand Behind The Intraday Return? A Retrospective”, Ben Branch and Aixin Ma revisit prior research on the relationship between overnight and intraday returns of U.S. stocks. Specifically, they relate average intraday stock returns to preceding average overnight returns based on: (1) whether average overnight returns are positive or negative; and, (2) by ranked fourths (quartiles) of average overnight returns. They perform a separate regression analysis to isolate correlation effects among overnight, intraday and one-leg lagged overnight and intraday returns. Using daily open-to-close and close-to-open returns for a broad sample of U.S. stocks during January 2011 through December 2017, they find that: Keep Reading

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 from December 1987 through January 2018 (31 December and 31 January observations), we find that: Keep Reading

Does the U.S. stock market have a predictable pattern of returns around the 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 1950 through September 2018 (275 quarters), we find that: Keep Reading