Calendar Effects

Does the conventional wisdom to “Sell in May” (and “Buy in November”, hence also the term “Halloween Effect”) work over the long run, perhaps due to biological/psychological effects of seasons (Seasonal Affective Disorder)? To check, we turn to the long run dataset of Robert Shiller. This data set includes monthly levels of the S&P Composite Index, calculated as average of daily closes during the month. We split the investing year into two half-years (seasons): May through October, and November through April. Using S&P Composite Index levels, associated dividend yields and contemporaneous long-term interest rates (comparable to yields on 10-year U.S. Treasury notes) from the Shiller dataset spanning April 1871 through April 2021, we find that: Keep Reading

A subscriber requested evaluation of three retirement investment alternatives, assuming a constant increment invested at the end of each month, as follows:

1. 50-50: allocate each increment via fixed percentages to stocks and bonds (for comparability, we use 50% to each).
2. Seasonal 1: during April through September (October through March), allocate 100% of each increment to stocks (bonds).
3. Seasonal 2: during April through September (October through March), allocate 100% of each increment to bonds (stocks).

The hypothesis is that seasonal variation in asset class allocations could improve overall long-term investment performance. We conduct a short-term test using SPDR S&P 500 ETF Trust (SPY) as a proxy for stocks and iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD) as a proxy for bonds. We then conduct a long-term test using Vanguard 500 Index Fund Investor Shares (VFINX) as a proxy for stocks and Vanguard Long-Term Investment-Grade Fund Investor Shares (VWESX) as a proxy for bonds. Based on the setup, we focus on terminal value as the essential performance metric. Using total (dividend-adjusted) returns for SPY and LQD since July 2002 and for VFINX and VWESX since January 1980, all through December 2020, we find that: Keep Reading

Do investors swing toward optimism around U.S. presidential inauguration days, focusing on future opportunities? Or, does the day remind investors of political uncertainty and conflict? To investigate, we analyze daily returns of the S&P 500 Index around inauguration day. We consider subsamples of no party change and party change. Using inauguration dates since 1928 and daily S&P 500 Index levels during 1928 through 2020, we find that: Keep Reading

Do options of individual stocks exhibit momentum and seasonality patterns? In their November 2020 paper entitled “Momentum, Reversal, and Seasonality in Option Returns”, Christopher Jones, Mehdi Khorram and Haitao Mo investigate momentum and seasonality effects for options on U.S. common stocks. They focus on performance of straddles, combining a put and a call with the same strike price and expiration date. They balance needs for liquidity and sample size by requiring positive open interest during the holding period but not the momentum calculation interval. Specifically, on each monthly option expiration date, they:

1. Form two straddles from near-the-money options expiring next month for each for each stock: (1) the pair with call delta closest to 0.5 for calculating momentum; and, (2) the pair with call delta closest to 0.5 and with positive open interest for both the put and the call when selected for calculating momentum portfolio return.
2. Construct from these pairs zero-delta straddles using bid-ask midpoints as prices and calculate monthly straddle excess returns relative to the 1-month Treasury bill yield. This process generates about 1,600 straddles per month with average monthly excess return -5.6% and very large standard deviations.
3. Calculate momentum as average monthly excess return over a specified lookback interval (rather than cumulative return, to suppress effects of return outliers).
4. Rank straddle returns into equal-weighted fifths (quintiles) based on momentum and calculate average return for each quintile and for a portfolio that is long the top quintile and short the bottom quintile.

Using end-of-day open interest and bid-ask quotes for call and put options on U.S. common stocks from OptionMetric and trading data for underlying stocks during January 1996 through June 2019, they find that: Keep Reading

Does crude oil (an important part of commodity indexes) exhibit an exploitable price seasonality? To check, we examine three monthly series:

1. Spot prices for West Texas Intermediate (WTI) Cushing, Oklahoma crude oil since the beginning of 1986 (34+ years).
2. Nearest expiration futures prices for crude oil since April 1983 (37+ years).
3. Prices for United States Oil (USO), an exchange-traded implementation of short-term crude oil futures since April 2006 (14+ years).

We focus on average monthly returns by calendar month and variabilities of same. Using monthly prices from respective inceptions of these series through October 2020, we find that: Keep Reading

Does the U.S. stock market respond predictably to simultaneous earnings announcements of attention-grabbing companies? In their September 2020 paper entitled “Famous Firms, Earnings Clusters, and the Stock Market”, Yixin Chen, Randolph Cohen and Zixuan Wang examine U.S. stock market (E-mini S&P 500 futures) responses to earnings announcement clusters (EAC) comprised of high-attention firms. They focus on the three most prominent pre-open (AM) and three most prominent post-close (PM) EACs in each of January, April, July and October, with each announcement weighted for prominence by associated total number of Dow Jones earnings news articles during the prior calendar year. Using earnings announcements and daily prices for S&P 500 components and minute-by-minute E-mini S&P 500 futures returns during 1999-2018, and associated earnings news articles during 1998-2018, they find that: Keep Reading

The Trading Calendar presents cumulative return visualizations for the S&P 500 Index across the calendar year and across each calendar month. Three alternative perspectives on U.S. stock market performance by calendar month are: (1) percentage of positive returns; (2) ratio of average return to standard deviation of returns; and, (3) distribution of returns. Using monthly returns for the S&P 500 Index during January 1928 through December 2019 (92 observations per month), we find that: Keep Reading

Are some calendar months more likely to exhibit stock market continuation or reversal than others, perhaps due to seasonal or fund reporting effects? In other words, is intrinsic (times series or absolute) momentum an artifact of some months or all months? To investigate, we relate U.S. stock index returns for each calendar month to those for the preceding 3, 6 and 12 months. Using monthly closes of the S&P 500 Index since December 1927 and the Russell 2000 Index since September 1987, both through January 2020, we find that: Keep Reading

Has 24-hour trading of equity index futures created a reliable pattern in hour-by-hour returns? In their February 2020 preliminary paper entitled “The Overnight Drift”, Nina Boyarchenko, Lars Larsen and Paul Whelan study round-the-clock U.S. stock market performance decomposing S&P 500 Index futures returns by hour, with focus on dealer inventory management. Using 24-hour high-frequency trades and quotes for S&P 500 futures contracts during January 1998 through December 2018, they find that: Keep Reading

As implied in “Mirror Image Seasonality for Stocks and Treasuries?”, are bonds better than stocks during the “Sell-in-May” months of May through October? Are behaviors of government, corporate investment grade and corporate high-yield bonds over this interval similar? To investigate, we test seasonal behaviors of:

SPDR S&P 500 (SPY)
Vanguard Intermediate-Term Treasury (VFITX)
Fidelity Investment Grade Bond (FBNDX)
Vanguard High-Yield Corporate Bond (VWEHX)

Using dividend-adjusted monthly prices for these funds during January 1993 (limited by SPY) through January 2020, we find that: Keep Reading