Technical Trading

Does the effectiveness of simple moving average (SMA) crossing signals vary with stock volatility? In the August 2011 update of their paper entitled “A New Anomaly: The Cross-Sectional Profitability of Technical Analysis”, Yufeng Han, Ke Yang and Guofu Zhou investigate the application of SMAs to portfolios of stocks sorted sorted based on realized volatility. Specifically, each year they sort stocks into deciles by volatility (standard deviation of daily returns over the past year). For each decile, they calculate a price index, an SMA for the index and daily returns based on initial equal weighting. When a decile portfolio is above (below) its SMA, they hold the portfolio (30-day Treasury bills), with a one-day delay for switches. They compare the returns for this timing strategy to buy-and-hold by decile. They focus on a 10-day SMA, but also test 20-day, 50-day, 100-day and 200-day SMAs. Using daily returns for a broad sample of U.S. stocks spanning 1963 through 2009, they find that: More…

A subscriber suggested comparing intrinsic momentum to simple moving average (SMA) as alternative signals for equity market entry and exit. To investigate, we compare the long run performances of entry and exit signals from intrinsic momentum over commonly used past intervals of 3, 6, 9 and 12 months and from the 10-month SMA (based on conclusions in “Is There a Best SMA Calculation Interval for Long-term Crossing Signals?”). We consider two cases for intrinsic momentum signals: in stocks (cash) when past return is positive (negative); and, (2) in stocks (cash) when average monthly past return is above (below) the average monthly risk-free rate over the same measurement interval. Using monthly data for the 13-week Treasury bill (T-bill) yield as the risk-free rate and the Dow Jones Industrial Average (DJIA) as a proxy for the U.S. stock market during January 1934 through November 2011 (about 78 years), we find that: More…

A reader observed and inquired:

“I frequently see a certain cliche in trading blogs…that, when the bond markets and the equity markets disagree, trust the bond markets. Do you know of any evidence for this? The article ‘What Leads to Market Bottoms?’ is one example out of dozens: ‘…possibly the most reliable indicator of a turn for the better in the fortunes of the stock market is the corporate bond market. Napier – who has published this research in the book Anatomy of the Bear: lessons from Wall Street’s four great bottoms (CLSA Books, 2005) – points out that corporate bonds have a superb track record of anticipating recovery.

• US corporate bonds bottomed in June 1921. US equities bottomed in August 1921.
• US corporate bonds bottomed in May 1932. US equities bottomed in July 1932.
• US corporate bonds bottomed in February 1982. US equities bottomed in August 1982.

Bond market investors aren’t stupid. There is good evidence that the bond market is altogether shrewder than the stock market.’”

Testing the hypothesis that bond market bottoms (bond yield tops) reliably anticipate stock market bottoms requires operational definitions of “top” and “bottom.” Consider definitions based on two conditions: (1) a top (bottom) must be the maximum (minimum) value over the preceding XX months; and, (2) this value must persist as the maximum (minimum) as this XX-month window rolls at least through the next YY months. Using monthly levels of Moody’s yield on seasoned Aaa corporate bonds for all industries and monthly closes of the Dow Jones Industrial Average (DJIA) during October 1928 through October 2011 (about 83 years) for two XX-YY scenarios, we find that: More…

Is there a reliable way to improve the performance of conventional moving average signals? In the October 2011 and November 2011 versions of their papers entitled “An Improved Moving Average Technical Trading Rule” and “An Improved Moving Average Technical Trading Rule II”, Fotis Papailias and Dimitrios Thomakos investigate a modification of the conventional moving average crossover trading strategy that add a dynamic trailing stop (long-only variation) or a dynamic trailing stop-and-reverse (long-short variation). In order to stay long after a moving average buy signal, the modification requires that the asset price must remain at least as high as the entry price. Specifically:

1. Price crossing above a moving average, or a short-interval moving average crossing above a long-interval moving average, signals initial entry.
2. After going long, switching to cash or a short position occurs only if the price falls below the reference entry price (ignoring conventional moving average sell signals).
3. While long, the reference entry price changes when the crossover signals a sell/switch and then a subsequent buy/re-switch.

Entry and exit/switching times for the modified strategy therefore differ over time from those of a conventional moving average crossover strategy. In comparing modified and conventional strategy performance characteristics, they consider: simple, exponential and weighted moving averages; price crossovers of 5, 20, 50, 100 and 200-day moving averages; and, (5,20), (10,20), (20,50), (20,100) and (50,200) pairs of short-interval and long-interval moving average crossovers. They conservatively assume a delay of one trading day in signal implementation. Using daily prices for broad stock indexes, a variety of exchange-traded funds (ETF) and several currency exchange rates as available, they find that: More…

Is a 10-month simple moving average (SMA) the best SMA for long-term crossing signals (to exploit return momentum by capturing part of long uptrends while avoiding part of long downtrends)? If not, is there some other optimum SMA calculation interval? To check, we compare the average monthly returns and return variabilities from SMA crossing signals generated by SMA calculation intervals ranging from 3 to 48 trailing months, as applied to the Dow Jones Industrial Average (DJIA). Using monthly DJIA closes for January 1930 through August 2010 and monthly yields for 3-month Treasury bills (T-bills) for January 1934 through October 2011, we find that: More…

A reader asked: “Should the moving average crossover threshold be symmetrical, or does it make sense to try getting back in close to the bottom?” In other words, should we perhaps use a 200-day simple moving average (SMA) to stick with the typical long bull market grind upward and then switch to a 50-day SMA signal after crossing under the 200-day SMA so that we re-enter closer to a V-shaped bear market bottom? Using daily closes for the S&P 500 Index commencing 5/20/59, the 3-month Treasury bill (T-bill) yield commencing 1/4/60 and S&P Depository Receipts (SPY), adjusted for dividends, commencing 1/29/93, all through the end of October 2011, we find that: More…

A subscriber asked: “Is there value in buying any market after it has had three straight down years?” As a limited test on a market with a reasonably long history, we consider both down and up annual streaks for the Dow Jones Industrial Average (DJIA). We allow streaks to overlap. For example, a streak of three down years contains two streaks of two down years. Using DJIA annual returns (capital gain only) for 1929 through 2010 (81 years), we find that: More…

Does short-term (one-month) stock return reversal persist? If so, is there a best way to refine and exploit it? In the September 2011 version of their paper entitled “Decomposing the Short-term Return Reversal”, Zhi Da, Qianqiu Liu and Ernst Schaumburg decompose the total short-term reversal into an across-industry component (long prior-month loser industries and short prior-month winner industries) and a within- industry component (long prior-month loser and short prior-month winner stocks within each industry). They then further decompose the within-industry return reversal into three components related to: (1) variation in three-factor (market, size, book-to-market) expected stock returns; (2) underreaction/overreaction to within-industry cash flow news (relative to analyst forecasts); and, (3) a residual component attributable to discount rate news/liquidity shocks. Using monthly data for a broad sample of relatively large and liquid stocks accounting for about 75% of U.S. equity market capitalization over the period January 1982 through March 2009, they conclude that: More…

Can the forward-looking aspect of the S&P 500 Volatility Index (VIX) amplify technical analysis? In their September 2011 paper entitled “Using VIX Data to Enhance Technical Trading Signals”, James Kozyra and Camillo Lento apply nine simple technical trading rules (three each moving average crossovers, filters and trading range breakouts) to VIX to generate daily trading signals for the S&P 500 Index, the NASDAQ index and the Dow Jones Industrial Average. They reason that a relatively high (low) level of VIX indicates strong (weak) future stock index returns, so technical rules that separate daily levels of VIX into high and low regimes should aid trading. They compare results for VIX rule signals to those for signals generated by applying the rules to the indexes themselves. In all 27 cases (nine rules times three indexes), rule implementation assumes going long (short) an index on the day after buy (sell) signals. Estimated trading friction accounts for the bid-ask spread and a broker fee at the time of each trade. Using daily closes for VIX and the three indexes for January 1999 through July 2009, they find that: More…

Do U.S. stock market returns during the first and last hours of normal trading days reliably indicate what comes next? To investigate, we analyze average SPDR S&P 500 (SPY) returns during 9:30-10:30, 9:30-15:00, 9:30-16:00 and 15:00-16:00 for normal trading days during 2007 (bullish year) and 2008 (bearish year). Using a sample of SPY one-minute prices spanning 2007-2008, we find that: More…