Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
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Momentum Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
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Technical Trading

Does technical trading work, or not? Rationalists dismiss it; behavioralists investigate it. Is there any verdict? These blog entries relate to technical trading.

Price Impact of Turnover

Over the past two decades, stock trading frictions (transaction fees and bid-ask spreads) have dramatically decreased on a per-trade basis, but trading frequency (share turnover) has dramatically increased. Does turnover now dominate per-trade friction in impacting asset prices? In the June 2010 draft of their paper entitled “Trading Frequency and Asset Pricing: Evidence from a New Price Impact Ratio”, Chrisostomos Florackis, Andros Gregoriou and Alexandros Kostakis investigate the return-to-turnover ratio (monthly average of daily ratios of absolute stock return to volume as a percentage of shares outstanding) as a new measure of the price impact of trading. Using daily data for a broad sample of stocks listed on the London Stock Exchange over the period 1991-2008, they find that: Keep Reading

Selling Calls or Puts According to Trend

Are there predictable times when selling covered call options outperforms selling cash-covered put options? In his March 2010 paper entitled “Buy-Write or Put-Write, An Active Portfolio to Strike it Right” (the National Association of Active Investment Managers’ 2010 Wagner Award runner-up), George Yang investigates using trend signals to trigger switching between covered call and put writing. The test portfolio consists of: (1) a long position in the S&P 500 Total Return Index (SPTR); (2) cash (Treasury bills); and, (3) a short position equivalent to the value of (1) plus (2) in at-the-money, next-month call or put options on the S&P 500 Index. The Golden Cross/Black Cross Rule (the 50-day simple moving average crossing above/below the 200-day simple moving average) applied to SPTR triggers switches between calls (after black crosses) and puts (after golden crosses). Using daily closes for SPTR, the S&P 500 Buy-Write Index (BXM) and the S&P 500 Put-Write Index (PUT) during June 1988 through December 2009 (21.6 years), he finds that: Keep Reading

What About Long-Short-Timing.com?

A reader asked and commented: “Would you please check out Long-Short-Timing.com, which is free? I’ve done really well with these guys, and they ought to be reviewed.” Keep Reading

Short-term Reversal and Trading Friction

Can investors effectively exploit the short-term price reversal anomaly for individual stocks after trading friction? Is success limited to big players? In their May 2010 paper entitled “Another Look at Trading Costs and Short-Term Reversal Profits”, Wilma de Groot, Joop Huij and Weili Zhou investigate the net profitability of reversal trading with and without steps to suppress trading friction. Using market capitalization, return and trading data for a broad sample of U.S. stocks spanning 1990-2009, and two models of contemporaneous associated trading friction, they conclude that: Keep Reading

Technical Analysis of Market Bubbles and Anti-bubbles

Can technical (price) analysis usefully identify major bubbles and anti-bubbles in financial markets? In the May 2009 version of their paper entitled “A Consistent Model of ‘Explosive’ Financial Bubbles With Mean-Reversing Residuals”, Lin Li, Ruoen Ren and Didier Sornette model bubbles. In their March 2010 paper entitled “Diagnosis and Prediction of Market Rebounds in Financial Markets”, Wanfeng Yan, Ryan Woodard and Didier Sornette similarly model anti-bubbles. Using daily levels of various financial market indexes, they conclude that: Keep Reading

Industry/Asset Class Momentum Over the Long Run

Does the momentum anomaly hold for industries/asset classes over the long run? In his April 2010 draft paper entitled “Relative Strength Strategies for Investing”, Mebane Faber quantifies the effects on gross returns of applying simple momentum/trend following  rules to U.S. equity industry and global asset class portfolios. His “intent is to describe some simple methods that an everyday investor can use to implement momentum models in trading.” Momentum rankings derive from trailing total returns over intervals ranging from one to twelve months, as well as a combination of multiple intervals. Using monthly levels of ten value-weighted U.S. equity industries spanning July 1926 through December 2009 and of global asset classes spanning 1973-2009, he concludes that: Keep Reading

Technical Trading Thoroughly Tested on Emerging Currencies

Are “proven” technical trading rules reliable profit-makers, or artifacts of data snooping bias? In their April 2010 paper entitled “Illusory Profitability of Technical Analysis in Emerging Foreign Exchange Markets”, Pei Kuang, Michael Schröder and Qingwei Wang apply several tests to evaluate the decisiveness of data snooping bias in the past profitability of technical trading rules for ten emerging foreign exchange markets. These environments are arguably less intensively mined than many other financial markets. Using spot exchange rates in the selected markets over the period January 1994 to July 2007 to test 25,998 commonly used simple, pattern and complex trading rules (see the table below), they find that: Keep Reading

Review of The Mutual Fund Strategist Timing (Revised to Append Comment)

A reader requested: “Please analyze The Mutual Fund Strategist, written by Holly Hooper-Fournier. They seem to have done quite well.” While the web site for this newsletter does not explicitly describe its timing method, it does explain that: “All of our timing models are oriented towards the intermediate trend…a period between several weeks and several months in duration. Focusing on the intermediate trend allows us to control risk effectively without subjecting your invested capital to the wide price swings that are associated with major trend following systems, such as a 200-day moving average.” The newsletter makes publicly available a record of “MFStrategist US Growth” timing signals since 2/16/01, as verified by TimerTrac.com. Using these 48 signals, daily dividend-adjusted closing prices for S&P 500 SPDR (SPY) and the daily short-term Interest Rate Composite over the period May 2000 through March 2010, we find that: Keep Reading

Amplifying Momentum with Volume and Accounting Indicators

Can investors enhance momentum returns for individual stocks with combination strategies that incorporate other technical and accounting indicators? In the April 2010 draft of their paper entitled “Technical, Fundamental, and Combined Information for Separating Winners from Losers”, Cheng-Few Lee and Wei-Kang Shih investigate combined momentum strategies based on past stock returns, past trading volume and sets of fundamental (accounting) indicators. They consider two distinct sets of fundamentals: Piotroski’s FSCORE for value stocks and Mohanram’s GSCORE for growth stocks. Their combined strategy is long (short) past winners (losers) with weak (strong) past relationship between returns and trading volume and high (low) fundamental scores. Using stock return/volume and firm fundamentals data for a broad sample of NYSE and AMEX non-financial stocks spanning 1982-2007 (26 years), they find that: Keep Reading

Use Short-term Signals to Inform Rebalancing?

Can long-term investors who periodically rebalance their portfolios materially enhance performance by using short-term signals to “permit” rebalancing? In their April 2010 paper entitled “To Trade or Not to Trade? Informed Trading with High-Frequency Signals for Long-Term Investors”, Roni Israelov and Michael Katz test the effects of such a tactical “informed trading” twist on long-run portfolio performance, focusing on the net Sharpe ratio as the bottom line discriminator. As an example, they apply one-week reversal signals to rebalancing a value-momentum portfolio that selects high value (book-to-market), high momentum (12-month past return) country indexes from among developed markets. Using book-to-market and return data for 18 developed markets over the period 1980-2009 (30 years), they conclude that: Keep Reading

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