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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.

Combining Momentum and Moving Averages for Asset Classes

A reader wondered about the value of combining momentum and simple moving average signals for asset class allocation, as follows:

  • Each month calculate the average momentum of each asset class over the prior 3, 6 and 12 months
  • Hold the top positions as long as they are also trading above their 10-month SMA (otherwise go to cash)

We test these rules using exchange-traded funds (ETF) as easily tradable asset class proxies. However, many ETFs have very short histories, greatly restricting any such test. We use S&P Depository Receipts (SPY), iShares Barclays 20+ Year Treasury Bond (TLT) and iShares Russell 2000 Index (IWM) as available asset classes, with historical data limited to July 2002 (by TLT). We use the 13-week Treasury bill (T-bill) yield as a proxy for the return on cash. Each month, we allocate funds to the one asset class with the highest average momentum over the prior 3, 6 and 12 months, unless the momentum leader is below its lagged 10-month SMA, in which case we put all funds into T-bills. Using monthly values for SPY, TLT, IWM and the T-bill yield over the period July 2002 through April 2009 (82 months), we find that: Keep Reading

A Few Notes on The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets

In their 2009 book, The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets, Mebane Faber and Eric Richardson “profile the top endowments and then examine how an investor can hope to replicate their returns while avoiding bear markets. The focus [is] on practical applications that an investor can implement immediately to take control of their investment portfolio.” Mebane Faber “is the portfolio manager at Cambria Investment Management where he manages equity and global tactical asset allocation portfolios” and a co-founder of AlphaClone, an investing research web site. Eric Richardson is Chairman and founder of Cambria Investment Management. The book has a complementary web site that links to source materials. The principal messages of the book are: Keep Reading

Out-of-Sample Tests of Bullish Regime 2-day RSI Signals

A reader suggested: “It would be nice to see a study of a low 2-day Relative Strength Index (RSI) as a technical indicator as suggested by TradingMarkets.com. “We focus on exchange-traded funds (ETF) to perform two simple tests of 2-day RSI trading rules as described by TradingMarkets.com in “How to Trade ETFs: The 2-Period RSI and Entry Strategies for Traders” and “The Improved R2 Strategy: 84% Correct with Just 6 Rules”. For the test of the first set of rules, we arbitrarily select the Technology Select Sector SPDR (XLK). For the test of the second set of rules, we use SPDRs (SPY) as specified. Since the in-sample rule selection period described in the latter article extends through 2006, we conduct the tests with subsequent data to avoid data snooping bias. Using daily adjusted closing prices for XLK and SPY over the period 3/20/06 through 3/17/09 and the Stockcharts.com RSI template, we find that: Keep Reading

Stock Price as a Future Return Indicator

Do investors fool themselves into thinking a low share price means a cheap price? In other words, are the simple nominal prices of stocks predictive of their future returns? In their December 2008 paper entitled “Is Share Price Relevant?”, Soosung Hwang and Chensheng Lu investigate this question by measuring the performance of portfolios formed annually by sorting listed common stocks by nominal price into five ranges: less than or equal to $5, $5 to $10, $10 to $15, $15 to $20, and more than $20. Using delisting-adjusted price data for a broad sample of NYSE/AMEX/NASDAQ common stocks over the period July 1963 through December 2006, they conclude that: Keep Reading

Determinants of Pairs Trading Profitability

How do the returns from pairs trading (bets on the re-convergence of prices for similar stocks that have historically tracked but recently diverged) play out? Are there systematic ways to enhance pairs trading profitability? In the November 2008 version of their paper entitled “An Anatomy of Pairs Trading: the Role of Idiosyncratic News, Common Information and Liquidity”, Joseph Engelberg, Pengjie Gao and Ravi Jagannathan explore how news events and liquidity shocks relate to pairs trading profitability. Using daily prices for a broad set of stocks spanning January 1992 through June 2006 and related news items and trading data for January 1993 through December 2005, they conclude that: Keep Reading

A Few Notes on Short Term Trading Strategies That Work

In his 2008 book, Short Term Trading Strategies That Work, Larry Connors, CEO and Founder of The Connors Group, shares “more than two decades of research and trading knowledge.” He states in the introductory chapter:

Philosophically, I live in the world of reversion to the mean when it comes to trading. What that simply means is that something stretched too far will snap back. I didn’t come up with that idea. It’s been around for decades. What I have done though is an attempt to quantify it.

Most of the quantifying tests use daily data spanning 1995-2007 for a large sample of stocks and the S&P 500 index. Based on past reviews of hundreds of anomaly studies, here are a few observations on the analyses presented in this book: Keep Reading

Trading After 52-week Highs and Lows

Do 52-week highs and lows trigger unusual trading and returns for individual stocks? In their recent paper entitled “Volume and Price Patterns Around a Stock’s 52-Week Highs and Lows: Theory and Evidence”, Steven Huddart, Mark Lang and Michelle Yetman examine the evidence that past price extremes influence trading decisions, with focus on 52-week highs and lows. Using weekly volume and closing prices for a random sample of 2,000 stocks listed for at least a year during November 1982 through December 2006 (24 years), they conclude that: Keep Reading

Simple Test of Sector ETF Pair Trading

Do short-term relative mispricings of equity sectors offer a means to capture abnormal returns? To investigate, we measure the returns from trading potential “errors” in the relative price movements of a pair of sector exchange-traded funds (ETF) selected from the following:

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)

Using daily adjusted closing prices (incorporating dividends) for these ETFs during 12/22/98-8/15/08, we find that: Keep Reading

Classic Paper: Matched Pairs Trading

We occasionally select for retrospective review an all-time “best selling” research paper of the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the February 2006 version of the paper entitled “Pairs Trading: Performance of a Relative Value Arbitrage Rule” (download count over 14,500) by Evan Gatev, William Goetzmann and Geert Rouwenhorst. The study tests the trading of mismatches in the dividend-adjusted prices of pairs of stocks that historically move together. Specifically, when the price spread between such a pair widens, short the winner and buy the loser and hold until prices converge. Using daily stock prices for a broad sample of reasonably liquid stocks over the period 1962-2002, the authors conclude that: Keep Reading

Using Trailing Stop Losses to Reduce Risk

Do stop-loss orders (automated position exits based on a cumulative loss threshold) enhance returns and reduce risk? In their 2008 paper entitled “The Value of Stop Loss Strategies” Adam Lei and Huihua Li investigate whether traders using stop-loss strategies to exit losing positions in individual stocks outperform a comparable buy-and-hold strategy. They test the following strategy alternatives: holding periods of three months, six months or one year; stop-loss thresholds of 5, 10 or 20 daily return standard deviations; reinvestment of stopped out positions in either the S&P 500 index or the one-month Treasury bill; and, a fixed stop price or a trailing stop price that follows stock price upward (but not downward). Using historical and simulated daily return data for a broad sample of NYSE/AMEX-listed stocks and random buy dates over the period 1970-2005, they conclude that: Keep Reading

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