Objective research to aid investing decisions

Value Investing Strategy (Read Overview)

Allocations for January 2020 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Read Overview)

Allocations for January 2020 (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.

January Effect Over the Long Run

Does long term data support belief in the January effect, exceptionally strong performance by the U.S. stock market during the month of January? Robert Shiller’s long run sample, which calculates monthly levels of the S&P Composite Stock Index since 1871 as average daily closes during calendar months, offers data for testing. Using monthly levels of the S&P Composite Stock Index for January 1871 through December 2013 (143 years), monthly closes of the S&P 500 Index for January 1950 through December 2013 (64 years), we find that: Keep Reading

Testing Earnings Season (Alcoa to Wal-Mart) Trading Strategies

Five years ago, a reader noted and asked: “CNBC’s Fast Money cited a ‘seasonal’ strategy described in Barron’s, as follows: Go long the market from Wal-Mart’s (WMT) earnings release until Alcoa’s (AA) earnings release and short the market from Alcoa’s earnings release until Wal-Mart’s earnings release (earnings season). Over the last six years, the market has been up nicely during the former period and down an average 8% during the latter. Any testing on this?” To test this strategy, we assemble AA earnings release dates and WMT earnings release dates since the beginning of 1997 (the earliest available for AA), estimating the date for one missing WMT release. This sample period is much longer than that cited. Using these earnings release dates, daily dividend-adjusted closes for S&P 500 SPDR (SPY) and ProShares Short S&P500 (SH) and the daily 13-week Treasury bill (T-bill) yields over the period 2/25/97 (6/21/06 for SH) through 10/8/13 (67 quarters), we find that: Keep Reading

Halloween Indicator Out-of-sample Test

Does the Halloween effect (sell in May) still hold? In the June 2013 version of their paper entitled “Are Stock Markets Really so Inefficient? The Case of the ‘Halloween Indicator'”, Hubert Dichtl and Wolfgang Drobetz investigate whether true out-of-sample results confirm that the Halloween effect persists for five total return indexes: S&P 500, DAX 30, FTSE 100, CAC 40 and Euro Stoxx 50. They consider both regression tests to compare average monthly returns and simulated trading strategies based on bootstrapping. They consider three sample periods for each index: (1) the total available sample period; (2) the subperiod since availability of a liquid investment proxy (such as a mutual fund or exchange-traded fund) to exploit the Halloween effect; and, (3) the subperiod starting January 2003 (after publication of the seminal international study of the effect). For simulated trading strategies, they assume switches from stocks to cash at the end of April and cash to stocks at the end of October incur trading friction of 0.5%. Using monthly total returns of the specified indexes as available (starting years ranging from 1965 to 1988) through December 2012, and contemporaneous one-month local interest rates as the return on cash, they find that: Keep Reading

Stock Market Performance by Month Worldwide

Are there worldwide anomalies with regard to equity market returns by calendar month? In his June 2013 paper entitled “Stock Market Performance: High and Low Months”, Vichet Sum examines stock market performance in 70 countries to determine which months generate relatively high and low returns. He weights country stock markets equally in calculating worldwide statistics. Using monthly returns as available (with many series beginning in the 1980s and 1990s) mostly through May 2012, he finds that: Keep Reading

Halloween Effect Pervasiveness

Is the outperformance of stocks during November-April compared to May-October pervasive worldwide and over time? In their October 2012 paper entitled “The Halloween Effect: Everywhere and All the Time”, Ben Jacobsen and Cherry Zhang test the “Halloween” or “Sell-in-May” effect for all stock markets worldwide using the full histories of indexes available for these markets (excluding dividends). Using 55,425 monthly observations for 108 stock market indexes (24 developed, 21 emerging, 31 frontier and 32 rarely studied) during 1693 through 2011 (319 years), they find that: Keep Reading

Distinctive Biotech Seasonality?

In an August 2004 article entitled “Time is Right for These 7 Biotechs” (apparently no longer available on MSN Money), Jim Jubak states: “…in most years, biotechs decline in the spring as investors anticipate a summer hiatus in the conferences where new clinical results are announced. They rally in the fall as the conference schedule and the volume of news increases.” Does empirical data support belief in these observations? To check, we examine the behavior of the AMEX Biotechnology Index (BTK) across the calendar year. Using monthly closing levels for BTK from its inception in January 1995 through August 2012 (over 17 years), and contemporaneous monthly returns for the S&P 500 Index for detrending, we find that: Keep Reading

Combine Long-term SMA, TOTM and Sector Momentum?

Based on results from “Simple Sector ETF Momentum Strategy Performance”, “Does the Turn-of-the-Month Effect Work for Sectors?” and “Long-term SMA and TOTM Combination Strategy”, a subscriber proposed: “Have you ever thought of combining the three? When SPY is above a long term average, buy the best performing sector ETF using the TOTM strategy.” To investigate, we consider 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 determine sector momentum based on total return over the past six months (6-1). We define bull-bear stock market state according to whether SPDR S&P 500 (SPY) is above-below its 200-day simple moving average (SMA). We define the turn-of-the-month (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 SPY from 12/22/98 through 8/10/12 (164 months), we find that: Keep Reading

“Sell in May” Still Working?

Does the conventional wisdom of avoiding stocks during May through October work in recent years? In their July 2012 paper entitled “‘Sell in May and Go Away’ Just Won’t Go Away”, Sandro Andrade, Vidhi Chhaochharia and Michael Fuerst test the sell-in-May anomaly (or Halloween effect) based on data unambiguously available only after publication of the anomaly. They compute returns in adjacent six-month periods, the beginning of May to end of October and the beginning of November to end of April. They also test a trading strategy that: (1) from the end of April through the end of October, invests a fraction k (for k equals 3/4, 1/2, 1/3 and 0) of the portfolio in the stock market index and the balance in one-month Treasury bills (T-bills); and, (2) from the end of October through the end of April, invests 2-k in the stock market index by borrowing 1-k at the T-bill rate. Using total returns for 37 country stock market index and the MSCI World Index during during May 1970 through October 1998 (replicating prior research) and November 1998 through April 2012 (new data), along with contemporaneous T-bill yields for the latter, they find that: Keep Reading

Deconstructing the Size Effect

What calendar and technical factors drive the size effect? In the June 2012 version of his paper entitled “Predictable Dynamics in the Small Stock Premium”, Valeriy Zakamulin explores the interaction of the size effect with the January effect and both prior-month and prior-year stock market returns. He defines the size effect based on the Small-Minus-Big (SMB) factor of the Fama-French three-factor model of stock returns. A positive (negative) value for the effect means that small (big) stocks outperform big (small) stocks. Using market factor and SMB factor returns from the library of Kenneth French and National Bureau of Economic Research (NBER) business cycle dates during 1927 through 2011 (85 years), he finds that: Keep Reading

VIX Day-of-the-Week Effects

Does the S&P 500 implied volatility index (VIX) exhibit systematic behaviors by day of the week? In their February 2012 paper entitled “Day of the Week Effect on the VIX: A Parsimonious Representation”, Maria Gonzalez-Perez and David Guerrero apply methodologies that minimize sensitivity to outliers to examine VIX day-of-the-week patterns. Using daily closes of VIX and the S&P 500 Index during 2004 through 2008, they find that: Keep Reading

Login
Daily Email Updates
Filter Research
  • Research Categories (select one or more)