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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.

Survey of Seasonal Anomalies

In their February 2011 book chapter entitled “Seasonal Anomalies”, Constantine Dzhabarov and William Ziemba describe, update and assess several published U.S. stock market anomalies, most of which are directly or indirectly calendar-driven. They update using returns for stock index futures as a low-friction approach to exploiting calendar anomalies. They acknowledge the possible materiality of data mining/snooping bias in past findings and the difficulty of proving statistical significance even in large samples due to high return variability. Using returns for S&P 500 Index and Russell 2000 Index futures from February 1993 through December 2010 to update analyses of these anomalies, they find that: Keep Reading

Any Recent Day-of-the-Week Anomalies?

Does recent data suggest any reliable day-of-the-week U.S. stock market return anomalies? To investigate, we examine close-to-close stock market returns for the five trading days of the week, excluding trading days before and after market holidays and the day after the extended market disruption in September 2001. The intent of these exclusions is to suppress holiday effects on stock market returns. Using daily closing prices for the S&P 500 Index for 1981 through 2010 (7,301 daily returns, ranging from 1,382 Fridays to 1,546 Wednesdays), we find that: Keep Reading

Reversal, Momentum, Reversion and 12-month Echo Dependencies on January Returns

Are January returns important to the profitability of short-term reversal, intermediate-term momentum, long-term reversion and 12-month echo trading strategies? In her December 2010 paper entitled “Momentum, Seasonality and January”, Yaqiong Yao investigates the role of  January returns within these previously discovered anomalies. The study’s core methodology is to reform equally weighted hedge portfolios each month that are long/short stocks in extreme tenths (deciles) of  past returns over various intervals.  The one-month reversal strategy is long (short) losers (winners) based on prior month returns. Momentum strategies are long (short) winners (losers) based on past 11-month or 12-month returns, with a skip month before portfolio formation to avoid short-term reversal. The reversion strategy is long (short) losers (winners) based on past four-year returns, with a skip-year before portfolio formation to avoid intermediate-term momentum. The 12-month echo strategy is long (short) winners (losers) based on returns for the same month the prior one, two or three years. Using monthly returns for a broad sample of NYSE/AMEX stocks during 1926 through 2009, she finds that: Keep Reading

Persistently Effective Sector Selection Variables

What variables are persistently effective in picking equity sectors for tactical (monthly) trading? In their July 2010 paper entitled “Global Tactical Sector Allocation: A Quantitative Approach”, Ronald Doeswijk and Pim van Vliet investigate the effectiveness of seven variables for tactical trading of ten global equity sector indexes. They test effectiveness of these variables separately and in combination, and after their respective publication dates. The seven variables are: one-month return momentum, 12-1 return momentum (over the 11 months prior to the last month), earnings revision trend, long-term return (over the four years prior to the last year) reversion, aggregate dividend yield, Federal Reserve policy (expansive or contractive) and sell-in-May seasonal.  The ten sectors are energy, materials, industrials, consumer discretionary, consumer staples, health care, financials, information technology, telecommunication services and utilities.  Testing consists of monthly construction of equally weighted long-short portfolios based on variable conditions. For the first five variables, portfolios are long (short) the top (bottom) three sectors. The Federal Reserve policy and sell-in-May seasonal variables indicate whether to be long or short cyclical versus defensive sectors. The authors calculate net profitability based on a constant 0.60% round-trip trading friction. Using monthly sector index total returns and values for non-return variables mostly over the period 1970 through 2008, they find that: Keep Reading

Three Centuries of Calendar Effects

How well do calendar-based anomalies, such as the January and Halloween/Sell-in-May effects, hold up for data extending back three centuries? Do any new anomalies emerge from such a data set? In their October 2010 paper entitled “Are Monthly Seasonals Real? A Three Century Perspective”, Ben Jacobsen and Cherry Zhang examine an extremely long record of UK stock returns for evidence of calendar anomalies. Using 317 years of monthly UK stock index returns and risk-free rate proxies spanning 1693 through 2009, they find that: Keep Reading

The Lure of Trading at the Open?

Do naive investors, lured by news they encounter while the stock market is closed, bid up the prices of attention-getting stocks at the open? In their June 2010 paper entitled “Paying Attention: Overnight Returns and the Hidden Cost of Buying at the Open”, Henk Berkman, Paul Koch, Laura Tuttle and Ying Zhang examine whether attention-based trading by individual equity investors reliably causes temporary mispricing at the market open. Using intraday bid and ask price data for the 3,000 largest U.S. stocks over the period 1996-2008 (13 years), along with contemporaneous measures of retail investor attention to individual stocks and overall market sentiment, they conclude that: Keep Reading

A Daily Stock Return Cycle

Do the aggregate trading stimulants/habits of large players create short-term stock return patterns? In their June 2010 paper entitled “Are You Trading Predictably?”, Steven Heston, Robert Korajczyk, Ronnie Sadka and Lewis Thorson continue an investigation of daily patterns in stock returns by extending the sample period described in “Intraday/Daily Stock Return Patterns”. Using intraday bid and ask prices for 4,494 U.S. stocks spanning the post-decimalization period of January 2001 through December 2009 to calculate returns over 13 half-hour intervals each day, they find that: Keep Reading

Weekend Effect for Individual Stock Options?

Does reluctance of traders to hold naked short positions in individual stock options over weekends induce a weekend effect for option prices? In the February 2010 revision of their paper entitled “The Weekend Effect in Equity Option Returns”, Christopher Jones and Joshua Shemesh employ a portfolio approach to investigate a weekend effect for put and call options on U.S. stocks. They compute portfolio excess returns as the equally weighted average of individual option contract returns based on bid-ask midpoints, in excess of a short-term yield. Using price data for a filtered set of U.S. equity options and for the underlying stocks over the period January 1996 to June 2007, they conclude that: Keep Reading

The Real Calendar Effects?

Is it possible that some widely acknowledged calendar effects emerge from data only because of overlap with a few “real” calendar effects? In their December 2009 paper entitled “An Anatomy of Calendar Effects”,  Stefan Grimbacher, Laurens Swinkels and Pim Van Vliet examine interactions among five calendar effects: Halloween, January, turn-of-the-month, weekend and holiday. Specifically, they employ tests that control for all five effects simultaneously to determine whether any dominate or disappear in isolation. Using daily returns for the U.S. stock market in excess of the 30-day Treasury bill yield over the period July 1963 through December 2008, they conclude that: Keep Reading

Do Not Trade at the Open?

A reader noted and asked: “I frequently read that one should not trade at the open, because the smart traders manipulate opening prices to scalp the naive. Does it really help to wait a half hour (or whatever) before trading?” Keep Reading

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