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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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 eight asset class exchange-traded funds (ETF) used in the “Simple Asset Class ETF Momentum Strategy”:

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)

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 2006 for DBC to May 2000 for IWB) through February 2015 (109-178 months), 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 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)

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 S&P Depository Receipts (SPY) as a benchmark from December 1998 through February 2015 (195 months), we find that: Keep Reading

Turn-of-the-Month Effect Persistence and Robustness

Is the Turn-of-the-Month (TOTM) effect, a concentration of positive 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 interact with the U.S. political cycle? Does it work for different 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 during February 1950 through February 2015 (782 TOTMs) and for the Russell 2000 Index during October 1987 through February 2013 (330 TOTMs), we find that: Keep Reading

Interactions among Stock Size, Stock Price and the January Effect

Is there an exploitable interaction between a stock’s market capitalization and its price? In their February 2015 paper entitled “Nominal Prices Matter”, Vijay Singal and Jitendra Tayal examine the relationship between stock prices and returns after: (1) controlling for market capitalization (size); (2) isolating the month of January; and, (3) excluding very small stocks. They each year perform double-sorts based on end-of-November data first into ranked tenths (deciles) by size and then within each size decile into price deciles. They calculate returns for January and for the calendar year with and without January. Using monthly prices and end-of-November market capitalizations for the 3,000 largest U.S. common stocks during December 1962 through December 2013, quarterly institutional ownership data for each stock during December 1980 through December 2013, and actual number of shareholders for each stock during 2004 through 2012, they find that: Keep Reading

Year-end Global Growth and Future Asset Class Returns

Does fourth quarter global economic data set the stage for asset class returns the next year? In their February 2015 paper entitled “The End-of-the-year Effect: Global Economic Growth and Expected Returns Around the World”, Stig Møller and Jesper Rangvid examine relationships between level of global economic growth and future asset class returns, focusing on growth at the end of the year. Their principle measure of global economic growth is the equally weighted average of quarterly OECD industrial production growth in 12 developed countries. They perform in-sample tests 30 countries and out-of-sample tests for these same 12 countries (for which more data are available). Out-of-sample tests: (1) generate initial parameters from 1970 through 1989 data for testing during 1990 through 2013 period; and, (2) insert a three-month delay between economic growth data and subsequent return calculations to account for publication lag. Using global industrial production growth as specified, annual total returns for 30 country, two regional and world stock indexes, currency spot and one-year forward exchange rates relative to the U.S. dollar, spot prices on 19 commodities, total annual returns for a global government bond index and a U.S. corporate bond index, and country inflation rates as available during 1970 through 2013, they 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 February 2015.
  • Updated Market Models backtest charts and the market valuation metrics map based on data available through February 2015.

We have updated the Trading Calendar to incorporate data for February 2015.

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

Interaction of Calendar Effects with Other Anomalies

Do stock return anomalies exhibit January and month-of-quarter (first, second or third, excluding January) effects? In his February 2015 paper entitled “Seasonalities in Anomalies”, Vincent Bogousslavsky investigates whether the following 11 widely cited U.S. stock return anomalies exhibit these effects:

  1. Market capitalization (size) – market capitalization last month.
  2. Book-to-market – book equity (excluding stocks with negative values) divided by market capitalization last December.
  3. Gross profitability – revenue minus cost of goods sold divided by total assets.
  4. Asset growth – Annual change in total assets.
  5. Accruals – change in working capital minus depreciation, divided by average total assets the last two years.
  6. Net stock issuance – growth rate of split-adjusted shares outstanding at fiscal year end.
  7. Change in turnover – difference between turnover last month and average turnover the prior six months.
  8. Illiquidity – average illiquidity the previous year.
  9. Idiosyncratic volatility – standard deviation of residuals from regression of daily excess returns on market, size and book-to-market factors.
  10. Momentum – past six-month return, skipping the last month.
  11. 12-month effect – average return in month t−k*12, for k = 6, 7, 8, 9, 10.

Each month, he sorts stocks into tenths (deciles) based on each anomaly variable and forms portfolios that are long (short) the decile with the highest (lowest) values of the variable. He updates all accounting inputs annually at the end of June based on data for the previous fiscal year. Using accounting data and monthly returns for a broad sample of U.S. common stocks during January 1964 to December 2013, he finds that: Keep Reading

VIX-VXX Seasonality

Does the S&P 500 Implied Volatility Index (VIX) exhibit exploitable seasonality? To check, we calculate average monthly change in VIX and and average iPath S&P 500 VIX Short-Term Futures ETN (VXX) monthly return by calendar month. Using monthly closes of VIX since January 1990 and monthly reverse split-adjusted closes for VXX since January 2009, both through December 2014, we find that: Keep Reading

Momentum Happens at Night?

Are overnight trading motivations systematically different from those that drive trading during normal trading hours? In the January 2015 version of their paper entitled “Tug of War: Overnight Versus Intraday Expected Returns”, flagged by a subscriber, Dong Lou, Christopher Polk and Spyros Skouras (1) decompose abnormal returns associated with well-known stock return predictors into overnight and intraday components and (2) investigate whether differences between institutional and other traders account for differences. Using return, firm characteristic and institutional ownership data for a broad sample of U.S. stocks (excluding low-priced and the smallest fifth of stocks) during 1993 through 2013, they find that: Keep Reading

Stock Market and the Super Bowl

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 2014 (48 events), we find that: Keep Reading

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