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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.

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

Gold Seasonality Drivers

Does seasonal fear of stock market weakness or demand for jewelry drive gold prices? In his January 2012 paper entitled “The Seasonality of Gold – Jewelery Demand and Investor Behavior”, Dirk Baur examines calendar month seasonality of the price of gold. Using daily gold bullion spot prices (London fixing) and COMEX gold futures prices during 1981 through 2010 (30 years), along with contemporaneous stock market index and gold jewelry demand data, he finds that: Keep Reading

Value Premium Concentration in January

Is the value premium seasonal? In their 2012 paper entitled “Is the Value Effect Seasonal? Evidence from Global Equity Markets”, Praveen Kumar Das and Uma Rao investigate the intersection of the January effect and the value premium in stock market indexes around the world. They consider market capitalization-weighted value and growth stock portfolios for the following indexes: Asia Pacific; Europe, Australasia and Far East (EAFE); Europe, with and without UK; Scandinavian countries; UK; U.S.; and, Japan. They define value (growth) stocks as the 30% with the highest (lowest) book-to-market ratios within their respective market indexes. Using monthly stock prices and lagged annual book-to-market ratios for stocks in these markets during 1975 (or inception if unavailable that early) through 2007, they find that: Keep Reading

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