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.
Stock Returns Around Memorial Day May 21, 2013
Does the Memorial Day holiday signal any unusual return effects? By its definition, this holiday brings with it any effects from three-day weekends and sometimes the turn of the month. Prior to 1971, the U.S. celebrated Memorial Day on May 30. Effective in 1971, Memorial Day became the last Monday in May. To investigate the possibility of short-term effects on stock market returns around Memorial 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 2012 (63 observations), we find that: More…
Recent Intraday U.S. Stock Market Behavior May 2, 2013
“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 April 2013, we find that: More…
Earnings Forecast, Models, Trading Calendar and Momentum Strategy Updates April 30, 2013
We have updated the Earnings Forecast to incorporate Standard & Poors data for the first quarter of 2013. This data is not complete (some earnings are still estimates), so revisions are likely.
We have updated the Market Models summary as follows:
- Extended regressions/rolled projections by one month based on data available through April 2013.
- Updated backtest charts and the market valuation metrics map based on data available through April 2013.
We have updated the Trading Calendar to incorporate data for April 2013.
We have updated the the monthly asset class momentum winners and associated performance data at Momentum Strategy.
Continuation and Reversal Months? April 18, 2013
Are some calendar months more likely to exhibit stock market continuation (momentum) or reversal than others? To check, 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 from December 1949 (using the January open for 1949) through March 2013 and the Russell 2000 index from September 1987 through March 2013, we find that: More…
Test of Seasonal Risk Adjustment Strategy April 2, 2013
A subscriber requested review of a strategy that seeks to exploit “Sell in May” (the “Halloween Effect”) by switching between risk-on assets during November-April and risk-off assets during May-October. The risk-on assets are SPDR S&P 500 (SPY), iShares Russell 2000 Index (IWM) and PowerShares DWA Technical Leaders (PDP). Risk-off assets are iShares Barclays 20+ Year Treas Bond (TLT) and PowerShares S&P 500 Low Volatility (SPLV). At each portfolio switch date, specified assets receive equal weight. Using April and October dividend-adjusted closes of SPY, IWM, PDP, TLT and SPLV as available during October 2002 (the first interval for which at least one risk-on and one risk-off asset are available) through October 2012, plus the February 2013 close as an endpoint for a partial interval, we find that: More…
“Sell in May” Over the Long Run April 1, 2013
Does the conventional wisdom to “Sell in May” (and “Buy in November”, hence also termed the “Halloween Effect”) work over the long run, perhaps due to biological/psychological effects of seasons (such as Seasonal Affective Disorder)? To check, we turn to the long run data set of Robert Shiller. This data set includes monthly levels of the S&P Composite Index, calculated as average of daily closes during the month. This method of calculation deviates from that most often used for return calculations, but arguably suppresses noise in daily data. 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 Treasury notes) from the Shiller data set spanning April 1871 through October 2012 (283 six-month returns), we find that: More…
Stock Returns Around Easter March 22, 2013
Does the seasonal change marked by the Easter holiday, with the U.S. stock market closed on the preceding Good Friday, tend to 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 1950-2012 (63 events), we find that: More…
Style Performance by Calendar Month February 19, 2013
The Trading Calendar presents full-year and monthly cumulative performance profiles for the overall stock market (S&P 500 Index) based on its average daily behavior since 1950. How much do the corresponding monthly behaviors of the various size and value/growth styles deviate from an overall equity market profile? To investigate, we consider the the following six exchange-traded funds (ETF) that cut across capitalization (large, medium and small) and value versus growth:
iShares Russell 1000 Value Index (IWD) – large capitalization value stocks.
iShares Russell 1000 Growth Index (IWF) – large capitalization growth stocks.
iShares Russell Midcap Value Index (IWS) – mid-capitalization value stocks.
iShares Russell Midcap Growth Index (IWP) – mid-capitalization growth stocks.
iShares Russell 2000 Value Index (IWN) – small capitalization value stocks.
iShares Russell 2000 Growth Index (IWO) – small capitalization growth stocks.
Using monthly dividend-adjusted closing prices for the style ETFs and S&P Depository Receipts (SPY) over the period August 2001 through January 2013 (139 months, limited by data for IWS/IWP), we find that: More…
Sector Performance by Calendar Month February 12, 2013
The Trading Calendar presents full-year and monthly cumulative performance profiles for the overall stock market (S&P 500 Index) based on its average daily behavior since 1950. How much do the corresponding monthly behaviors of the various stock market sectors deviate from an overall market profile? To investigate, we consider the nine sectors defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR), all of which have trading data back to 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)
Using monthly adjusted closing prices for these exchange traded funds (ETF) since inception, along with contemporaneous data for Standard & Poor’s Depository Receipts (SPY) as a benchmark, for December 1998 through January 2013 (171 months), we find that: More…
Stock Market and the Super Bowl January 25, 2013
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 data for 1967 through 2012 (46 events), we find that: More…

