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.

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Simple Tests of Sy Harding’s Seasonal Timing Strategy

Several readers have inquired about the performance of Sy Harding’s Street Smart Report Online, which includes the Seasonal Timing Strategy. This strategy combines “the market’s best average calendar entry [October 16] and exit [April 20] days with a technical indicator, the Moving Average Convergence Divergence (MACD).” According to Street Smart Report Online, applying this strategy to a Dow Jones Industrial Average (DJIA) index fund generated a cumulative return of 213% during 1999 through 2012, compared to 93% for the DJIA itself. As a robustness test, we apply this strategy to the SPDR S&P 500 (SPY) exchange-traded fund since its inception. Using daily dividend-adjusted closing prices for SPY and daily 13-week Treasury bill (T-bill) yields during 1/29/93 (inception of SPY) through 9/30/14, we find that: Keep Reading

Kaeppel’s Sector Seasonality Strategy

A reader suggested looking at the strategy described in “Kaeppel’s Corner: Sector Seasonality” (from November 2005) and updated in “Kaeppel’s Corner: Get Me Back, Clarence” (from October 2007). The steps of this calendar-based sector strategy are:

  1. Buy Fidelity Select Technology (FSPTX) at the October close.
  2. Switch from FSPTX to Fidelity Select Energy (FSENX) at the January close.
  3. Switch from FSENX to cash at the May close.
  4. Switch from cash to Fidelity Select Gold (FSAGX) at the August close.
  5. Switch from FSAGX to cash at the September close.
  6. Repeat by switching from cash to FSPTX at the October close.

Does this strategy materially and persistently outperform? To investigate, we compare results for three alternative strategies: (1) Kaeppel’s Sector Seasonality strategy (Sector Seasonality); (2) buy and hold Vanguard 500 Index Investor (VFINX) as an investable broad index benchmark (VFINX); and, (3) a simplified seasonal strategy using only VFINX from the October close through the May close and cash otherwise (VFINX /Cash). Using monthly dividend-adjusted closing levels for FSPTX, FSENX, FSAGX, the 13-week Treasury bill (T-bill) yield as the return on cash and VFINX over the period December 1985 through September 2014 (almost 29 years), we find that: Keep Reading

Recent Intraday U.S. Stock Market Behavior

“Intraday U.S. Stock Market Behavior” examines behavior of the S&P 500 Index at 15-minute intervals over the trading day during each of 2007 (bullish year) and 2008 (bearish year), finding slight tendencies for market weakness during mid-afternoon and market volatility at the beginning and the end of the trading day. Does recent data confirm these findings? To investigate, we calculate average cumulative returns and standard deviations of returns for both the S&P 500 Index and SPDR S&P 500 (SPY) measured at 5-minute intervals during the trading day over the last six months. Using 5-minute levels/prices for the S&P 500 Index and for SPY during 9:30-16:00 over the period August 2012 through September 2014, we find that: Keep Reading

Models, Trading Calendar and Momentum Strategy Updates

We have updated the S&P 500 Market Models summary as follows:

  • Extended Market Models regressions/rolled projections by one month based on data available through September 2014.
  • Updated Market Models backtest charts and the market valuation metrics map based on data available through September 2014.

We have updated the Trading Calendar to incorporate data for September 2014.

We have updated the the monthly asset class momentum winners and associated performance data at Momentum Strategy.

Turn-of-the-Month Effect in Stock Markets Around the World

Is the Turn-of-the-Month (TOTM) effect globally ubiquitous and persistent? In his August 2014 paper entitled “The Turn-of-The-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model”, Eleftherios Giovanis examines the TOTM effect in 20 country stock markets spanning the Americas, Australia, Europe and Asia. He defines TOTM as the interval including the last trading day of each calendar month through the third trading day of the next calendar month. He applies complex techniques to account for potential autocorrelation, heteroskedasticity and volatility clustering in daily market returns. His samples vary in start date by country, from as early as January 1950 (for the U.S.) to as late as January 2001 (for Australia). He considers full samples from the beginning of each country series through 2013 and two subsamples: (1) from the beginning of each country sample through 2007; and, (2) the financial crisis of 2008 through 2009. Using daily closes for the 20 country stock market indexes as described, he finds that: Keep Reading

Turn-of-the-Quarter Effect on Stock Momentum

Does the stock momentum anomaly interact with the quarterly financial cycle? In his August 2014 paper entitled “Seasonal Patterns in Momentum and Reversal in the U.S. Stock Market: The Consequences of Tax-Loss Sales and Window Dressing”, David Brown examines whether tax-loss selling and window dressing at the ends of calendar quarters affect U.S. stock momentum strategy returns. Each month, he ranks stocks by returns over the last 12 months, skipping the last month to avoid reversal, and then forms a momentum hedge portfolio that is long (short) the capitalization-weighted tenth of stocks with the highest (lowest) past returns, making the long and short sides of the portfolio equal in magnitude. He then measures how this portfolio performs by calendar month to check for end-of-quarter effects. He also investigates whether the level of capital losses among stocks in the portfolio affects performance. Using monthly returns for NYSE, AMEX and NASDAQ common stocks, along with contemporaneous risk-free rates and Fama-French model risk factor returns, during January 1927 through December 2013, he finds that: Keep Reading

Stock 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 2013 (64 observations), we find that: Keep Reading

Optimal Monthly Cycle for Sector ETF Momentum Strategy?

In response to “Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?”, a subscriber asked about the optimal monthly cycle for “Simple Sector ETF Momentum Strategy”, which each month allocates all funds to the one of the following nine Select Sector Standard & Poor’s Depository Receipts (SPDR) exchange-traded funds (ETF) with the highest total return over the past six months :

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)

To investigate, we compare 21 variations of the strategy based on shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM). For example, an EOM+5 cycle ranks assets based on closing prices five trading days after EOM each month. Using daily dividend-adjusted closes for the sector ETFs from mid-January 1999 through mid-July 2014 (about 186 months), we find that:

Keep Reading

Effects of Execution Delay on Simple Asset Class ETF Momentum Strategy

“Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?” investigates whether using a monthly cycle other than end-of-month (EOM) to determine the winning asset improves performance of the “Simple Asset Class ETF Momentum Strategy”. This strategy each month allocates all funds to the one of the following eight asset class exchange-traded funds (ETF), or cash, with the highest total return over the past five months:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

In response, a subscriber asked whether sticking with an EOM cycle for determining the winner, but delaying signal execution, affects strategy performance. To investigate, we compare 23 variations of the strategy that all use EOM to determine the winning asset but shift execution from the contemporaneous EOM to the next open or to closes over the next 21 trading days (about one month). For example, an EOM+5 Close variation uses an EOM cycle to determine winners but delays executions until the close five trading days after EOM. Using daily dividend-adjusted opens and closes for the asset class proxies and the yield for Cash from the end of July 2002 (or inception if not available then) through the end of July 2014 (144 months), we find that: Keep Reading

Stock Returns During and Between Earnings Seasons

Does intensity of firm quarterly earnings releases affect stock market behaviors? A reader proposed the following stock market timing strategy based on a strictly calendar-based definition of earnings season: go short (long) the market at the close at the end of the first full week (sixth full week) of each calendar quarter, representing the beginning (end) of earnings season. The hypothesis is that the broad stock market performs poorly during earnings season and well outside of earnings season. Using weekly closes for the S&P 500 Index since January 1950 and for the S&P 500 Implied Volatility Index (VIX) since January 1990, both through June 2014, we find that: Keep Reading

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