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.
August 5, 2010 - Technical Trading
A reader inquired about the predictive powers of bullish and bearish engulfing candlesticks, defined as: Bullish – a down day followed by an up day, with the latter having a higher intraday high and lower intraday low and closing in the top quarter of the daily range; and, Bearish – an up day followed by a down day, with the latter having a higher intraday high and lower intraday low and closing in the bottom quarter of the daily range. Using daily high, low and closing levels for the S&P 500 Index from January 1962 (the earliest available with intraday data) through July 2010, we find that: Keep Reading
August 5, 2010 - Technical Trading
In his 2010 book entitled Harmonic Trading: Volume Two Advanced Strategies for Profiting from the Natural Order of the Financial Markets, author Scott Carney “offers unprecedented strategies that identify the areas where overall trend divergence and harmonic pattern completions define the most critical technical levels. In addition, the new ideas presented in this material advance the basic theory of price pattern recognition by requiring other technical conditions to exist to validate potential opportunities with improved accuracy. Specifically, the advancement of the RSI BAMM separates the minor reactive moves from the more substantial trading opportunities and provides extensive technical information regarding the future potential direction of the price action. …Essentially, the integration of other measures has resulted in even more accurate projected reversal points for trade executions and hence, more reliable technical information regarding the state of potential price action. …The advanced techniques outlined in this book incorporate only the most pertinent technical measures that substantially increase the accuracy of harmonic patterns to identify the critical turning points in the financial markets.” On a chapter-by-chapter basis, key points from the book are: Keep Reading
August 4, 2010 - Technical Trading
In his 2010 book entitled Harmonic Trading: Volume One, Profiting from the Natural Order of the Financial Markets, author Scott Carney presents “an important advancement of the gamut of technical trading strategies that seek to define opportunities in the financial markets through the identification of price patterns and the analysis of market structure. …Most important, Harmonic Trading possesses unique and effective technical measurement strategies that define critical new patterns and expound upon the existing knowledge base of general Fibonacci and price pattern theories to establish precise guidelines and extremely effective predictive tools to define and analyze market trends.” Focusing on the first three chapters, which provide background on the harmonic trading methodology, key points from the book are: Keep Reading
July 22, 2010 - Technical 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
July 13, 2010 - Technical Trading
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
June 25, 2010 - Momentum Investing, Technical Trading
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
June 24, 2010 - Technical Trading
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
May 28, 2010 - Equity Options, Technical Trading
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
May 26, 2010 - Technical Trading
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
May 17, 2010 - Technical Trading
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