Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for April 2024 (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.

Turn-of-the-Month Effect Applied to SSO

Referring to “Turn-of-the-Month Effect Persistence and Robustness”, a subscriber asked about applying the Turn-of-the-Month (TOTM) effect to ProShares Ultra S&P500 (SSO).  As in the referenced research, we define TOTM as the interval from the close five trading days before to the close four trading days after the last trading day of the month (a total of eight trading days, centered on the monthly close). We compare a strategy of holding SSO only during TOTM to buying and holding SSO. We initially assume 0.1% 1-way SSO-cash switching frictions and look at sensitivity of findings to variation in the assumed level of frictions. Using daily dividend/split-adjusted prices for SSO during late June 2006 through early April 2024, we find that: Keep Reading

Live Test of the Stock Market Overnight Move Effect (Final)

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 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 July 31, 2023, we find that: Keep Reading

“Sell in May” Update

How has the simple Sell in May strategy worked in the modern U.S. equity market, defined as the time since introduction of SPDR S&P 500 ETF Trust (SPY)? To investigate, we:

  • Calculate 6-month SPY returns from the ends of April and October.
  • Find yields for 6-month U.S. Treasury bills (T-bills) at the end of each April, and the yield for 3-month T-bills at the end of January 1993 for the initial interval.
  • Generate returns for a strategy that holds SPY during November through April and T-bills during May through October, with switches at the ends of April and October.

We assume 0.1% frictions when switching between SPY and T-bills. We ignore tax implications of trading. The benchmark is buy-and-hold SPY. Using the specified data from the end of January 1993 through March 2024, 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 March 2024.

Stock Market Returns Around Holidays in Aggregate

Is the behavior of the U.S. stock market around exchange holidays consistent enough to generate an aggregate pattern? To investigate, we look at daily S&P 500 Index returns from three trading days before a holiday through three trading days after for the following holidays (adding the Super Bowl) as available since 1950:

New Year’s Day (74 observations, including 2024)
Super Bowl (58 observations, including 2024)
Good Friday (74 observations)
Memorial Day (53 observations)
4th of July (74 observations)
Labor Day (74 observations)
Thanksgiving (74 observations)
Christmas (74 observations)

The total number of observations is 555. Using daily closes of the S&P 500 Index during the specified intervals around holidays, we find that: Keep Reading

Stock Returns Around Easter

Does the seasonal shift marked by the Easter holiday, with the U.S. stock market closed on the preceding Good Friday, produce anomalous returns? To investigate, we analyze the historical behavior of the S&P 500 Index before and after the holiday. Using daily closing levels of the S&P 500 index for 1950-2023 (74 events), 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 Feb 2024 (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

Predictable Monthly Pattern for TLT?

Does iShares 20+ Year Treasury Bond ETF (TLT) exhibit a predictable monthly pattern due to beginning-of-month dividends and mid-month U.S. government consumer and producer inflation releases? To investigate, we calculate average cumulative return for TLT across the month (from trading day 1 through trading day 23). We also investigate exploitability of findings. Using daily raw and dividend-adjusted levels of TLT from the end of July 2002 (inception) through January 2024 (21.5 years), we find that: Keep Reading

Long-term SMA and TOTM Combination Strategy

“Turn-of-the-Month Effect Persistence and Robustness” indicates that average absolute returns during the turn-of-the-month (TOTM) are strong for both bull and bear markets. Does a strategy of capturing all bull market returns and TOTM returns only during bear markets perform well? To investigate, we apply four strategies to SPDR S&P 500 ETF Trust (SPY) as a tradable proxy for the stock market:

  1. SPY – buy and hold SPY.
  2. SMA200 – hold SPY (cash) when SPY closes above (below) its 200-day simple moving average (SMA200) the prior day.
  3. TOTM – hold SPY from the close five trading days before through the close four trading days after the last trading day of each month and cash at all other times (TOTM).
  4. SMA200 or TOTM – hold SPY when SPY closes above its 200-day SMA the prior day and otherwise use the TOTM strategy.

We explore sensitivities of these strategies to a range of one-way SPY-cash switching frictions, with baseline 0.1%. Using daily dividend-adjusted SPY from the end of January 1993 through early January 2024 and contemporaneous 3-month Treasury bill (T-bill) yields as the return on cash, we find that: Keep Reading

Turn-of-the-Month Effect Persistence and Robustness

Is the Turn-of-the-Month (TOTM) effect, a concentration of relatively strong stock market returns around the turns of calendar months, persistent over time and robust to different market conditions. Does it exist for all calendar months? Does it persist throughout the U.S. political cycle? Does it work for different equity indexes? To investigate, we define TOTM as the interval from the close five trading days before to the close four trading days after the last trading day of the month (a total of eight trading days, centered on the monthly close). Using daily closes for the S&P 500 Index since January 1928 and for the Russell 2000 Index since mid-September 1987, both through early January 2024, we find that: Keep Reading

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