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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.

Success Factors for High-frequency Pairs Trading

What factors drive profitability for trading price divergences and convergences of pairs of similar stocks based on high-frequency data? In their March 2010 paper entitled “High Frequency Equity Pairs Trading: Transaction Costs, Speed of Execution and Patterns in Returns”, David Bowen, Mark Hutchinson and Niall O’Sullivan examine the characteristics of a high-frequency pairs trading strategy that takes a long (short) position in the relatively underpriced (overpriced) stock of a normally tracking pair upon divergence in price and closes positions upon convergence. They use overlapping 264-hour formation periods to identify the top five and top 20 trading pairs, followed by 132-hour trading periods for those pairs triggered by price divergence of two or three historical standard deviations. Using 60-minute return intervals calculated from tick by tick trade data for a sample of FTSE 100 stocks over calendar year 2007, they find that: Keep Reading

Stock Synchronicity and Future Returns

Does the degree to which a stock tracks the market and its industry predict its future performance. In their July 2010 paper entitled “R2: Does It Matter for Firm Valuation?”, John Stowe and Xuejing Xing investigate how the coefficient of determination (R-squared statistic) relating individual stock returns to market/industry returns affects the stock’s market valuation and future returns. They calculate R-squared for a stock’s returns using weekly data by firm fiscal year (and apply a logarithmic transformation). Using weekly stock returns and associated firm fundamentals/characteristics for a broad sample of U.S. stocks and weekly market and industry returns (excluding financials and utilities) over the period 1970-2007, they find that: Keep Reading

Past Performance Consistency and Future Returns

What are the momentum and reversion patterns for stocks that have been consistent past winners or losers? In his June 2010 paper entitled “Does Bad Economic News Play a Greater Role in Shaping Investors’ Expectations than Good Economic News?”, Abdulaziz Alwathainani investigates the relationship between the consistency of past monthly stock performance and future returns. He defines consistent past winners (losers) as those ranking in the top (bottom) 30% of monthly returns for at least six of the last 12 months. He defines stocks ranking in the middle 40% for at least six of the last 12 months as a consistently moderate benchmark. Using monthly return and characteristics data for a broad sample of U.S. stocks spanning 1963-2007, he finds that: Keep Reading

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

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