Technical Trading

What happens after the stock market exhibits a streak of up or down weeks? To check, we use the S&P 500 Index as a proxy for the U.S. stock market and calculate average weekly returns and variabilities of these returns after streaks of positive or negative weekly returns. Using weekly closes of the S&P 500 Index for January 1950 through mid-August 2011, we find that: More…

What happens after big up days for the U.S. stock market? To ensure that a trader could have identified the days selected in real time and to accommodate volatility regime changes, we define a big up day as an advance of at least four standard deviations of the daily returns over the preceding four years (1,008 trading days). Using daily closes for the S&P 500 Index from January 3, 1950 through August 5, 2011, we find that: More…

What happens after big down days for the U.S. stock market? To ensure that a trader could have identified the days selected in real time and to accommodate volatility regime changes, we define a big down day as a decline of at least four standard deviations of the daily returns over the preceding four years (1,008 trading days). Using daily closes for the S&P 500 Index from January 3, 1950 through August 5, 2011, we find that: More…

Many studies rely on the first moment (mean) of historical asset return distributions and/or the second moment (variance or standard deviation) to predict future returns. Are the third (skewness, indicating left-right tail asymmetry) and fourth (kurtosis, indicating fat-tailedness) moments of return distributions useful for predicting returns? In the July 2011 update of their paper  entitled “Do Realized Skewness and Kurtosis Predict the Cross-Section of Equity Returns?”, Diego Amaya, Peter Christoffersen, Kris Jacobs and Aurelio Vasquez investigate whether decile sorts of individual stocks based on variance, skewness and kurtosis of intraday stock returns over the past week significantly predict returns the next week. Using past-week averages of daily realized volatility, skewness, and kurtosis computed from prices at five-minute intervals, and associated firm characteristics, for a broad sample of U.S. stocks over the period January 1993 through September 2008 (over two million firm-week observations), they find that: More…

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 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 market, style and sector ETFs. Using daily dividend-adjusted closes of 18 ETFs from the end of July 2000 (limited by data availability for two of the style ETFs) through July 2011 (11 years), we find that: More…

A reader asked: “I would love to see a backtest pitting a 10-month simple moving average (SMA) against a 200-day SMA for SPY. I assume trading costs would go through the roof on the latter, but do performance gains offset the additional costs?” Other readers asked about a 40-week SMA. Using monthly, weekly and daily dividend-adjusted closes for SPDR S&P 500 (SPY) from inception on 1/29/93 through 7/26/11, along with the contemporaneous daily 13-week Treasury bill (T-bill) yield, we find that: More…

A reader inquired about the complex strategy for trading stock index proxies and futures described in the March 2010 paper “MR Swing: A quantitative System for Mean‐reversion and Swing Trading in Market Regimes” by David Abrams and Scott Walker. This strategy posits that:

• The stock market switches between bull and bear states, with the bull or bear state in effect when current index level is above or below a channel generated by 200-day simple moving averages (SMA) of daily highs and lows. The channel buffers whipsaws.
• Different (not symmetrically opposite) trading approaches work best during these two states. Specifically, swing trading (short-term mean reversion) works in the bull (bear) state.
• Mean reversion and swing trading signal calculations must incorporate stock market volatility.
• The swing trading and mean reversion components must not produce serious drawdowns when the 200-day SMA indicator whipsaws between bull and bear states.

Using fairly recent daily data for the S&P 500 Index, SPDR S&P 500 (SPY), exchange-traded fund (ETF) proxies for several other stock market indexes and index futures, they find that: More…

Based on results from “Simple Sector ETF Momentum Strategy Performance”, “Does the Turn-of-the-Month Effect Work for Sectors?” and “Long-term SMA and TOTM Combination Strategy”, a subscriber proposed: “Have you ever thought of combining the three? When SPY is above a long term average, buy the best performing sector ETF using the TOTM strategy.” To investigate, we consider the nine sector exchange-traded funds (ETF) defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR), all of which have trading data back to December 1998:

Materials Select Sector SPDR (XLB)
Energy Select Sector SPDR (XLE)
Financial Select Sector SPDR (XLF)
Industrial Select Sector SPDR (XLI)
Technology Select Sector SPDR (XLK)
Consumer Staples Select Sector SPDR (XLP)
Utilities Select Sector SPDR (XLU)
Health Care Select Sector SPDR (XLV)
Consumer Discretionary Select SPDR (XLY)

We determine sector momentum based on total return over the past six months (6-1). We define bull-bear stock market state according to whether SPDR S&P 500 (SPY) is above-below its 200-day simple moving average (SMA). We define the turn-of-the-month (TOTM) as the eight-trading day interval from the close five trading days before the first trading day of a month to the close on the fourth trading day of the month. Using daily dividend-adjusted closes for the sector ETFs and SPY from 12/22/98 through 7/11/11 (151 months), we find that: More…

Does a strategy combining a long-term simple moving average and the turn of the month beat the market and its components? To investigate, we apply four strategies to S&P Depository Receipts (SPY) as a tradable proxy for the stock market that incorporates portfolio formation costs: (1) buy and hold SPY; (2) invest in SPY (cash) when SPY closes above (below) its 200-day simple moving average ( 200-day SMA); (3) invest in SPY from the close five trading days before through the close four trading days after the last trading day of each month and cash at all other times (TOTM); and, (4) invest in SPY when SPY closes above its 200-day SMA and otherwise use the TOTM strategy (SMA + TOTM). We explore sensitivities of these strategies to a range of trading frictions. Using daily dividend-adjusted closing levels of SPY from inception (1/29/93) through 7/11/11 and contemporaneous three-month Treasury bill (T-bill) yields, we find that: More…

Extended stock market index winning and losing streaks elicit speculation in the financial media about pending reversals. Does evidence support the what-goes-up-must-come-down view that likelihood of reversal grows with streak duration? To check, we examine the recent behaviors of the S&P 500 Index and NASDAQ Composite Index during the one, two and five trading days after winning and losing streaks of at least three days. Using daily closes for the S&P 500 Index and the NASDAQ Composite Index for January 2004 through (most of) June 2011 (1,881 trading days), we find that: More…