Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for February 2023 (Final)

Momentum Investing Strategy (Strategy Overview)

Allocations for February 2023 (Final)
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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.

Abnormal Returns from Providing Liquidity After Hours?

Can traders reliably turn a profit by providing liquidity to anxious after-hours counterparts and then closing the trade at the open? In his September 2009 paper entitled “The Cost of Illiquidity: Evidence from After-Hours Trading”, Brian Walkup quantifies price reversal/momentum when the market opens for stocks experiencing price movements during preceding after-hours trading. Using a large sample of after-hours trades from the three major U.S. stock exchanges during 2006, he concludes that: Keep Reading

Optimally Exploiting the January Barometer

The January Barometer (as goes January, so goes the rest of the year) seems persistent for U.S. stocks. Is there a best way to exploit it? In their July 2009 paper entitled “What’s the Best Way to Trade Using the January Barometer?”, Michael Cooper, John McConnell and Alexei Ovtchinnikov update their prior analysis of the January Barometer through 2008 and explore how an investor can best exploit its signal. Specifically, they consider five alternative strategies (all ignoring trading costs and taxes): (1) long stocks all the time; (2) long stocks in all Januaries and long (short) stocks during February-December when the return for January is positive (negative); (3) long stocks in all Januaries and long stocks (Treasury bills) during February-December when the return for January is positive (negative); (4) long Treasury bills all the time; and, (5) long stocks in all Januarys and long Treasury bills the rest of all years. Using monthly U.S. stock returns and one-month Treasury bill (or equivalent) yields over the period 1857-2008 (152 years), they conclude that: Keep Reading

An Annual Worldwide Optimism Cycle (Sell in May)?

Does the conventional wisdom to “sell in May,” with the average stock return during November-April far exceeding that for May-October, work for the world equity market? If so, why? In the November 2005 version of his paper entitled “The Optimism Cycle: Sell in May”, flagged by a reader, Ronald Doeswijk examines the hypothesis that this seasonal pattern derives from an annual optimism cycle. Using monthly return data for markets, sectors and Initial Public Offerings (IPO) over the period 1970 through 2003 (34 years), he concludes that: Keep Reading

Turn-of-the-Month, Options Expiration and Trend

We previously found that Russell 2000 Index returns have tended to be negative during the interval from options expiration (OE) to the turn of the month (TOTM), strongly positive during TOTM and near zero from TOTM to OE. Might the index trend leading up to these segments, defined by the index being over or under a simple moving average (SMA), discriminate the strength of monthly segment effects? Are the results robust? Using daily opening and closing levels of the Russell 2000 index over the period September 1987 through April 2009 (259 complete months), we find that: Keep Reading

Turn-of-the-Month Effect and Option Strategy Losses

The Strategy Test presently focuses on iteratively selling put options on the Russell 2000 Index with less than one month to expiration to capture the volatility risk premium. The test strategy seeks to exploit the turn-of-the-month (TOTM) effect to enhance this capture. Are there characteristics of index returns from options expiration (OE) to TOTM, during TOTM and from TOTM to OE that might inform options moneyness and position adjustment decisions? Using daily opening and closing levels of the Russell 2000 Index over the period September 1987 through April 2009 (259 complete months), we find that: Keep Reading

Stock Price as a Future Return Indicator

Do investors fool themselves into thinking a low share price means a cheap price? In other words, are the simple nominal prices of stocks predictive of their future returns? In their December 2008 paper entitled “Is Share Price Relevant?”, Soosung Hwang and Chensheng Lu investigate this question by measuring the performance of portfolios formed annually by sorting listed common stocks by nominal price into five ranges: less than or equal to $5, $5 to $10, $10 to $15, $15 to $20, and more than $20. Using delisting-adjusted price data for a broad sample of NYSE/AMEX/NASDAQ common stocks over the period July 1963 through December 2006, they conclude that: Keep Reading

Spectral Analysis of Stock Market Cyclicality

Are there reliable periodicities in U.S. stock returns tied to national election cycles? In their October 2008 paper entitled “Financial Astrology: Mapping the Presidential Election Cycle in US Stock Markets”, Wing-Keung Wong and Michael McAleer apply spectral analysis to identify and quantify cycles in U.S. stock market returns, including a presidential election cycle. Using weekly S&P 500 index data for the period 1965-2003, they conclude that: Keep Reading

The January Barometer Retested

As goes January, so goes the rest of the year? In the November 2008 update of their paper entitled “The Illusionary Market Timing Ability of the Other January Effect”, Ben Marshall and Nuttawat Visaltanachoti examine the ability of January returns to predict February-December returns and support a market timing strategy in the U.S. and other equity markets. They consider multiple robustness tests to determine the statistical and economic significance of this January Barometer based on both equally weighted and value weighted returns. Using U.S. stock return data spanning 1925-2007 (focusing on 1940-2007) and stock return data for 18 other countries and the world spanning 1970-2007, they conclude that: Keep Reading

Darlings of the Dow Strategy

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

A Two-Year Reversion Effect?

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

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