Calendar Effects

A reader asked:

“Have you tested the Darlings of the Dow strategy developed by Larry Williams? He has modified his original strategy several times, and I wonder whether he made revisions because of new insight or because the original strategy proved not much better than the five cheapest Dogs of the Dow. What I find interesting is his timing of the Darlings with Sy Harding’s MACD timing method and his buying the Dow Jones Utilities for the remainder of the year.”

The original Darlings of the Dow strategy employs fundamentals to select the five most undervalued stocks in the Dow Jones Industrials Average and times entries and exits seasonally (enter in October and exit in April). The revised version chooses other entry and exit dates. To evaluate the strategy, we assume that the trading dates/returns for Darlings of the Dow stocks are as listed by Larry Williams and that returns while out of the Darlings are the adjusted returns for the iShares Dow Jones US Utilities (IDU). As benchmarks, we calculate returns based on adjusted closing values for S&P Depository Receipts (SPY) over the same intervals and average 90-day Treasury bill (T-bill) yields as an alternative to IDU returns. We use a test period of 2002-2007 (10/28/02-9/13/07) that is out-of-sample and post-publication with respect to the original strategy. We find that: Keep Reading

Cycles, whether empirical or tied to economic/political fundamentals, are a recurring theme in efforts to predict financial markets. Is there a two-year cycle for the stock market? In his August 2008 paper entitled “The Two-Year Effect”, Graham Bornholt investigates a two-year reversion effect in the U.S. equity market. He defines low and high stock market return years, from which reversion occurs, relative to a lagged 10-year moving average of annual market returns. Using value-weighted annual returns from broad samples of stocks during 1871-1925 for in-sample model specification and during 1926-2005 for out-of-sample testing, he concludes that: Keep Reading

Is an adaptive marketplace extinguishing the January effect? In their June 2008 paper entitled “The Persistence of the Small Firm/January Effect: Is it Consistent with Investors’ Learning and Arbitrage Efforts?”, Kathryn Easterday, Pradyot Sen and Jens Stephan investigate whether the stock market has adapted over time to diminish the small firm/January effect. Using returns and firm size data for a very large sample of stocks over three subperiods (1946-1962, 1963-1979, 1980-2007), they conclude that: Keep Reading

Do northern hemisphere seasonal variations impact stock market volatility and return by affecting aggregate investor/trader mood? In their April 2008 paper entitled “Seasonal Affective Disorder (SAD) and Perceived Market Risk”, Guy Kaplanski and Haim Levy test the effect of seasonal environmental factors (daylight hours, temperature and fall season) on perceived market risk as indicated by the Chicago Board Options Exchange Volatility Index (VIX). VIX, also known as the Fear Index, is a measure of the risk perceived by traders of S&P 500 index options. Using VIX and actual volatility data and environmental measurements (for latitude 41 degrees north, Chicago and New York) over the period 1990-2007, they conclude that: Keep Reading

Are there patterns to intraday stock returns and, if so, are they exploitable? In their March 2008 paper entitled “Intraday Patterns in the Cross-Section of Stock Returns”, Steven Heston, Robert Korajczyk and Ronnie Sadka examine the intraday behavior of stock prices. Using return data for 13 half-hour intervals during the trading day for all NYSE-listed stocks over the decimalized period of 2001-2005, they conclude that: Keep Reading

Do Treasury instruments exhibit a seasonal return pattern? If so, is the pattern related to that of stock returns? In their September 2007 paper entitled “Opposing Seasonalities in Treasury versus Equity Returns”, Mark Kamstra, Lisa Kramer and Maurice Levi investigate the calendar month dependence of returns for U.S. Treasuries and its relationship to that of U.S. stock returns. Using monthly returns for mid-term to long-term Treasury indexes and for a broad equal-weighted stock index over the period 1952-2004, along with contemporaneous economic data, they find that: Keep Reading

What part of the day offers the best stock returns? Does this sweet spot vary by day of the week, time of the month or calendar month? In their July 2007 paper entitled “Return Differences between Trading and Non-trading Hours: Like Night and Day”, Michael Cliff, Michael Cooper and Huseyin Gulen use transaction-level data to decompose returns for individual stocks and exchange-traded funds (ETF) into four time intervals: Night (4:00 PM to 9:30 AM), AM (9:30 AM to 10:30 AM), Mid-day (10:30 AM to 3:00 PM), and PM (3:00 PM – 4:00 PM). Using intraday price data for the period 1993-2006, they conclude that: Keep Reading

Do stocks have annual rhythms beyond the January effect? In their March 2007 paper entitled “Common Patterns of Predictability in the Cross-Section of International Stock Returns”, Steven Heston and Ronnie Sadka investigate cyclic patterns of return predictability for stocks in Canada, Japan and twelve European countries (chosen based on the number of firms available for analysis). Using monthly returns over the period January 1985 through June 2006 (258 months), they conclude that: Keep Reading

Does an opening stock price above or below the prior session close indicate price movement for the rest of the trading day? If so, is the indication tradable. In their September 2006 paper entitled “The Overnight Return: One More Anomaly”, Ben Branch and Aixin Ma investigate the relationships between overnight and adjacent intraday returns for individual stocks. Using NYSE, AMEX and NASDAQ data over the period 1994-2005, they find that: Keep Reading

Do hedge funds eliminate, or even reverse, seasonal effects in the returns of the stock market? In his September 2006 paper entitled “Seasonality in Hedge Fund Strategies”, Yan Olszewski investigates general seasonal effects for various hedge fund strategies. Using monthly excess return data during 1990-2005 for 30 of the 37 equally-weighted Hedge Fund Research strategy indexes encompassing over 1600 funds, he finds that: Keep Reading