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.

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Annual Stock Market Streaks

Are annual stock market winning and losing streaks informative about future market performance? To investigate, we consider up and down annual streaks for the Dow Jones Industrial Average (DJIA). We look at streaks in two ways:

  1. Retrospective (non-overlapping). We know the total duration of each streak.
  2. Experienced (real-time and partially overlapping). We know each year how long a streak has lasted, but we don’t know when it will end.

Using DJIA annual returns for 1929 through 2014 (86 years), we find that: Keep Reading

Profit Drivers of Actual Short-term Algorithmic Trading?

What drives the profitability of algorithmic long-short statistical arbitrage trading (such as pairs trading) of liquid U.S. stocks? In their September 2015 paper entitled “Performance v. Turnover: A Story by 4,000 Alphas”, Zura Kakushadze and Igor Tulchinsky examine portfolio turnover and portfolio volatility as potential net return drivers for such trading. Their data source is 4,002 randomly selected portfolios (essentially synonymous with “alphas” in their lexicon) from a substantially larger survivorship bias-free pool of real trading accounts. Position holding periods for sampled portfolios range from 0.7 to 19 trading days. The authors exclude 366 portfolios with negative performance and then remove 347 portfolios as outliers for a residual sample of 3,289 portfolios. Using daily closing prices for holdings in these portfolios over an unspecified sample period, they find that: Keep Reading

High-Frequency Technical Trading of Gold and Silver?

Does simple technical analysis based on moving averages work on high-frequency spot gold and silver trading? In their August 2015 paper entitled “Does Technical Analysis Beat the Market? – Evidence from High Frequency Trading in Gold and Silver”, Andrew Urquhart, Jonathan Batten, Brian Lucey, Frank McGroarty and Maurice Peat examine the profitability of 5-minute moving average technical analysis in the gold and silver spot markets. They consider simple moving average (SMA), exponential moving average (EMA) and weighted moving average (WMA) crossing rules. These rules buy (sell) when a fast moving average crosses above (below) a slow moving average. They start with four commonly used parameter settings, all using a fast moving average of one interval paired with a slow moving average of 50, 100, 150 or 200 intervals [(1-50), (1-100), (1-150) or (1-200)]. They then test all combinations of a fast moving average ranging from 1 to 49 intervals and a slow moving average ranging from 50 to 500 intervals, generating a total of 66,297 distinct rules. To compensate for data snooping bias, they specify in-sample and out-of-sample subperiods and test whether the most successful in-sample rules work out-of-sample. They also use bootstrapping as an additional robustness test. Using 5-minute spot gold and silver prices during January 2008 through mid-September 2014, they find that: Keep Reading

SMA Signal Effectiveness Across Stock ETFs

Simple moving averages (SMA) are perhaps the most widely used and simplest market regime indicators. For example, many investors estimate that a stock index or exchange-traded fund (ETF) or individual stock priced above (below) its 200-day SMA is in a good (bad) regime. Do SMA signals/signal combinations usefully and consistently identify good and bad regimes across different kinds of U.S. stock ETFs? To investigate, we apply the regime indications of 50-day, 100-day and 200-day SMAs and some combinations of these SMAs to a variety of broad equity market (DIASPYIWBIWM and QQQ), equity style (IWDIWFIWN and IWO) and equity sector (XLBXLEXLFXLIXLKXLPXLUXLV and XLY) ETFs. As an ancillary test, we also consider three individual stocks: Apple (AAPL), Bershire Hathaway (BRKB) and Wal-Mart (WMT). Using daily dividend-adjusted closes of these 18 ETFs and three stocks from the end of July 2000 (limited by data availability for IWN and IWO) through August 2015 (about 15 years), we find that: Keep Reading

Optimal Cycle for Monthly SMA Signals?

A reader commented and asked:

“Some have suggested that the end-of-the-month effect benefits monthly simple moving average strategies that trade on the last day of the month. Is there an optimal day of the month for long-term SMA calculation and does the end-of-the-month effect explain the optimal day?”

To investigate, we compare 21 variations of a 10-month simple moving average (SMA10) timing strategy based on shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM) and applied to SPDR S&P 500 (SPY) as a tradable proxy for the U.S. stock market. Using daily dividend-adjusted and unadjusted closes for SPY from inception (end of January 1993) through August 2015 and contemporaneous three-month Treasury bill (T-bill) yields, we find that: Keep Reading

Technical vs. Fundamental Investment Recommendations

Are expert technicians or fundamentalists better forecasters of short-term and intermediate-term asset returns? In the August 2015 version of their paper entitled “Talking Numbers: Technical versus Fundamental Recommendations”, Doron Avramov, Guy Kaplanski and Haim Levy assess the economic value of dual technical and fundamental recommendations presented simultaneously on “Talking Numbers”, a CNBC and Yahoo joint broadcast… “featuring fundamental and technical recommendations before and during the market open. Dual recommendations are made by highly experienced analysts representing prominent institutions.” Recommendations address both individual stocks and asset classes, including U.S. and foreign broad equity indexes, sector/industry equity indexes, bonds, commodities and exchange rates. Using 1,000 dual recommendations on 262 stocks and 620 dual recommendations on other assets, along with associated price data, during November 2011 through December 2014, they find that: Keep Reading

RSP/SPY as a Stock Market Breadth Indicator

A reader proposed: “I recently found something interesting while analyzing the ratio of the equal-weighted S&P 500 Index to its market capitalization-weighted counterpart. Whenever this ratio declines (out of an uptrend), the market crashes (July 2007, September-October 2008, July 2011). Also, when this ratio starts rising, the recovery commences (April 2009). The indicator seems to warn of problematic times ahead. …Perhaps this ratio provides insight into whether money is moving into the market (ratio rising) or out of the market (ratio falling). Could you take a look at this to see whether this ratio is a great indicator?” To investigate, we employ S&P 500 SPDR (SPY) and Rydex S&P 500 Equal Weight (RSP) as tradable proxies for the capitalization-weighted and equal-weighted S&P 500 Index, respectively. Using weekly and monthly dividend-adjusted values of SPY and RSP from the end of April 2003 (limited by data for RSP) through July 2015 (641 weeks), we find that: Keep Reading

U.S. Stock Market Death Crosses and Golden Crosses

A subscriber requested tests exploring whether a recent death cross for the Dow Jones Industrial Average (DJIA) portends an index crash. To investigate, we consider two ways of evaluating DJIA performance after death crosses and conversely defined golden crosses:

  1. Behavior of the index during the 126 trading days (six months) after death and golden crosses.
  2. Behavior of the index between converse crosses (death cross-to-golden cross, and golden cross-to-death cross).

We focus on distributions of average returns and maximum drawdowns during specified periods. We also check robustness by repeating DJIA tests on the S&P 500 Index. Using daily DJIA closes during October 1928 through mid-August 2015 and daily S&P 500 Index closes during January 1950 through mid-August 2015, we find that: Keep Reading

DJIA-Gold Ratio as a Stock Market Indicator

A reader requested a test of the following hypothesis from the article “Gold’s Bluff – Is a 30 Percent Drop Next?”: “Ironically, gold is more than just a hedge against market turmoil. Gold is actually one of the most accurate indicators of the stock market’s long-term direction. The Dow Jones measured in gold is a forward looking indicator.” To test this assertion, we examine relationships between the spot price of gold and the level of the Dow Jones Industrial Average (DJIA). Using monthly data for the spot price of gold in dollars per ounce and DJIA over the period January 1971 through July 2015 (535 months), we find that: Keep Reading

Combining Annual Fundamental and Monthly Trend Screens

Stock return anomaly studies based on firm accounting variables generally employ annually reformed portfolios that are long (short) the tenth of stocks expected to perform well (poorly). Does adding monthly portfolio updates based on technical stock price trend measurements boost anomaly portfolio performance? In the June 2015 version of their paper entitled “Anomalies Enhanced: The Use of Higher Frequency Information”, Yufeng Han, Dayong Huang and Guofu Zhou test eight equal-weighted long-short portfolios that combine annual screening based on a predictive accounting variable with monthly screening based on a simple moving average (SMA)-based stock price trend rule. The eight accounting variables (screened in June based on prior December data) are: (1) book-to-market ratio; (2) gross profitability; (3) operating profitability; (4) asset growth; (5) investment growth; (6) net stock issuance; (7) accruals; and, (8) net operating assets. The price trend screen excludes from the long (short) side of the portfolio any stock for which 50-day SMA is less than (greater than) 200-day SMA at the end of the prior month. Using accounting and daily price data for a broad sample of U.S. stocks during July 1965 through December 2013, they find that: Keep Reading

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