Calendar Effects

A subscriber requested a test of holding Invesco QQQ Trust (QQQ) during November through April and idle cash during May through October. Informed by the Trading Calendar, we consider four strategies:

1. QQQ – buy and hold QQQ.
2. QQQ Seasonal (Idle Cash) – hold QQQ during November through April and idle cash during May through October, as requested.
3. QQQ No-even (Idle Cash) – hold QQQ during odd years and idle cash during even years (avoiding stocks during years with U.S. federal elections).
4. QQQ No-even (1-year T-note) – hold QQQ during odd years and 1-year U.S. Treasury notes (T-note) bought at the beginning of the year during even years.

We consider average monthly return, standard deviation of monthly returns, monthly reward/risk (average return divided by standard deviation), compound annual growth rate (CAGR) and maximum drawdown (MaxDD). We ignore frictions and tax implications of trading once or twice a year. Using monthly dividend-adjusted returns for QQQ during March 1999 (inception) through October 2023, we find that: Keep Reading

Are intraday stock market exchange-traded funds (ETF), stock sector ETFs and individual stock returns exploitably predictable at short horizons? In their June 2023 paper entitled “Intraday Stock Predictability Everywhere”, Fred Liu and Lars Stentoft study intraday U.S. equity return predictability using machine learning methods. Specifically, they:

• Consider the market portfolio represented by SPDR S&P 500 ETF (SPY), sector portfolios represented by the nine Select Sector SPDR ETFs and individual S&P 500 constituent stocks. For portfolios, return predictors are lagged returns of the portfolio itself and its constituents. For individual stocks, return predictors are the lagged returns of SPY and its constituents.
• Consider intraday return horizons of 1, 5, 10, 15 and 30 minutes.
• Train 17 machine learning methods based initially on the first ten months of data, validate on the next month and evaluate out-of-sample predictive power on the ensuing month. Each month, they repeat these steps by rolling all data by one month (142 test months).
• Test statistical significance via the power of predictions to explain actual future stock returns (R-squared).
• Test gross economic value of predictions via portfolios that buy and sell assets according to predicted returns.
• Test net economic value of predictions by trading only when predicted long or short returns exceed trading frictions (estimated as the bid-ask spread) and debiting frictions from actual returns.

Using intraday transaction data for the specified ETFs and S&P 500 stocks during February 2004 through October 2016, they find that: Keep Reading

What characteristics of U.S. equity factor return series are most relevant to respective factor performance? In his May 2023 paper entitled “The Cross-Section of Factor Returns” David Blitz explores long-term average returns and market alphas, 60-month market betas and factor performance cyclicality for U.S. equity factors. He also assesses potentials of three factor rotation strategies: low-beta, seasonal and return momentum. Using monthly returns for 153 published U.S. equity market factors, classified statistically into 13 groups, during July 1963 through December 2021, he finds that:

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Does the Turn-of-the-Month Effect, a concentration of positive stock market returns around the turns of calendar months, work across a broad set of asset classes. To investigate, we measure turn-of-the-month (TOTM) returns for the following nine asset class exchange-traded funds (ETF) used in the “Simple Asset Class ETF Momentum Strategy” and the “Simple Asset Class ETF Value Strategy”:

• Invesco DB Commodity Index Tracking Fund (DBC)
• iShares MSCI Emerging Markets Index (EEM)
• iShares JPMorgan Emerging Markets Bond Fund (EMB) 
• iShares MSCI EAFE Index (EFA)
• SPDR Gold Shares (GLD)
• iShares Russell 2000 Index (IWM)
• iShares iBoxx $ Investment Grade Corporate Bond (LQD)
• SPDR S&P 500 ETF Trust (SPY)
• iShares Barclays 20+ Year Treasury Bond (TLT)
• Vanguard REIT ETF (VNQ)

We define TOTM as the eight-trading day interval from the close five trading days before the first trading day of a month to the close on the fourth trading day of the month. Using daily dividend-adjusted closes for these ETFs from their respective inceptions (ranging from February 1993 for SPY to December 2007 for EMB) through early May 2023, we find that: Keep Reading

A reader inquired whether the Turn-of-the-Month Effect, a concentration of positive stock market returns around the turns of calendar months, works for U.S. stock market sectors. To investigate, we measure turn-of-the-month (TOTM) returns for the nine sector exchange-traded funds (ETF) defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR), all of which have traded since 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)

We define TOTM as the eight-trading day interval from the close five trading days before the first trading day of a month to the close on the fourth trading day of the month. Using daily dividend-adjusted closes for the sector ETFs and for SPDR S&P 500 ETF Trust (SPY) as a benchmark from December 1998 through early May 2023, we find that: Keep Reading

A subscriber asked about the performance of the 50-50  Simple Asset Class ETF Value Strategy (SACEVS) Best Value-Simple Asset Class ETF Momentum Strategy (SACEMS) Equal-Weighted (EW) Top 2 in combination with “Sell in May”. To investigate, we compare three alternatives:

1. Best Value – EW Top 2 – holds 50-50 SACEVS Best Value-SACEMS EW Top 2 during all months.
2. “Sell in May” – holds 50-50 SACEVS Best Value-SACEMS EW Top 2 during November through April and 3-month U.S. Treasury bills (T-bills) during May through October.
3. “Opposite” – holds 50-50 SACEVS Best Value-SACEMS EW Top 2 during May through October and 3-month U.S. Treasury bills (T-bills) during November through April.

Using monthly returns for SACEVS Best Value and SACEMS EW Top 2 and monthly T-bill yield during July 2006 (limited by SACEMS) through April 2023, we find that: Keep Reading

A subscriber requested review of a strategy that seeks to exploit “Sell in May” by switching between risk-on assets during November-April and risk-off assets during May-October, with assets specified as follows:

• Risk-on – SPDR S&P 500 (SPY), iShares Russell 2000 Index (IWM) and Invesco DWA Technical Leaders (PDP).
• Risk-off – iShares Barclays 20+ Year Treas Bond (TLT) and Invesco S&P 500 Low Volatility (SPLV).

On each portfolio switch date, assets receive equal weight with 0.25% overall penalty for trading frictions. We focus on compound annual growth rate (CAGR), maximum drawdown (MaxDD) measured at 6-month intervals and Sharpe ratio measured at 6-month intervals as key performance statistics. As benchmarks, we consider buying and holding SPY, IWM or TLT and a 60%-40% SPY-TLT portfolio rebalanced frictionlessly at the ends of April and October (60-40). Using April and October dividend-adjusted closes of SPY, IWM, PDP, TLT and SPLV as available during October 2002 (first interval with at least one risk-on and one risk-off asset) through April 2023, and contemporaneous 6-month U.S. Treasury bill (T-bill) yield as the risk-free rate, we find that: Keep Reading

A subscriber asked whether the Simple Asset Class ETF Momentum Strategy (SACEMS) exhibits monthly calendar effects. In investigating, we also look at the Simple Asset Class ETF Value Strategy (SACEVS)? We consider the Best Value (most undervalued asset) and Weighted (assets weighted by degree of undervaluation) versions of SACEVS. We consider the Top 1, equal-weighted (EW) Top 2 and EW Top 3 versions of SACEMS, which each month holds the top one, two or three of nine ETFs/cash with the highest total returns over a specified lookback interval. We further compare seasonalities of these strategies to those of their benchmarks: for SACEVS, a monthly rebalanced 60% stocks-40% bonds portfolio (60-40); and, for SACEMS an equal-weighted and monthly rebalanced portfolio of the SACEMS universe (EW All). Using monthly gross total returns for SACEVS since August 2002 and for SACEMS since July 2006, both through March 2023, we find that:

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Investor mood may affect financial markets. Sports may affect investor mood. The biggest mood-mover among sporting events in the U.S. is likely the National Football League’s Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super Bowl focusing and anxiety-relieving? Presumably, post-game elation and depression cancel between respective fan bases. Using past Super Bowl dates since inception and daily/weekly S&P 500 Index levels for 1967 through 2022 (56 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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