Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for September 2023 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for September 2023 (Final)
1st ETF 2nd ETF 3rd ETF

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.

Asset Class ETF Seasonalities?

Do exchange-traded funds (ETF) that track asset classes, such as those used in the Simple Asset Class ETF Momentum Strategy (SACEMS) and the Simple Asset Class ETF Value Strategy (SACEVS), exhibit reliable seasonalities? To check, we look at average return by calendar month for the following nine ETFs:

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

Using monthly dividend-adjusted returns for these ETFs over a common sample period during March 2006 (limited by DBC) through August 2023, 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, do abnormal returns concentrate 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 1928 through Jul 2023 (about 96 years and 24 presidential terms) and focusing on “political quarters” (Feb-Apr, May-Jul, Aug-Oct and Nov-Jan), we find that: Keep Reading

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 August 2023.

Stock Market 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 2022 (73 observations), we find that: Keep Reading

Robustness and Exploitability of Intraday Stock Return Prediction

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

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 in daily U.S. stock market returns around mid-year and the 4th of July? To check, we analyze 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 1950-2022 (73 years), we find that: Keep Reading

Live Test of the Stock Market Overnight Move Effect

Is the stock market overnight move effect exploitable? To investigate, we look at performances of two exchange-traded funds (ETF) designed to exploit the effect:

  1. NightShares 500 ETF (NSPY), which “seeks to return the night performance of a portfolio of 500 large cap U.S. companies.” The benchmark is SPDR S&P 500 ETF Trust (SPY).
  2. NightShares 2000 ETF (NIWM), which “seeks to return the night performance of a portfolio of 2000 small cap U.S. companies.” The benchmark is iShares Russell 2000 ETF (IWM).

Because available samples are very short, we focus on daily return correlation with the benchmark, average daily return, standard deviation of daily returns and daily reward/risk (average daily return divided by standard deviation of daily returns). We also look at compound annual growth rates (CAGR) and maximum drawdowns (MaxDD) based on daily data. Using daily total returns for NSPY, NIWM and benchmarks during June 28, 2022 through June 7, 2023, we find that: Keep Reading

Comparing Long-term Returns of U.S. Equity Factors

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:

Keep Reading

Does the Turn-of-the-Month Effect Work for Asset Classes?

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

Does the Turn-of-the-Month Effect Work for Sectors?

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

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