Blog - Investing Notes

For complete reverse chronological listings of blog entries, see:

• External (Secondary) Research for summaries of working papers and published articles written by others.
• Original (Primary) Research for summaries of original research.
• Reviews for a few discussions of books, web sites and products.
• Reader Q&A for interactions with readers that do not involve substantial analysis but may be of general interest.

Investing Demons provides a construct for synthesizing much of the research from past blog entries.

The Latest

February 9, 2010 - ETF Pair Trading Based on Relative Returns/Volatilities

Does pairs trading work for exchange-traded funds (ETF)? In their January 2010 paper entitled "Pairwise Asset Rotation Trading and Market Timing: An Anatomy to a New Trading Strategy", Panagiotis Schizas and Dimitrios Thomakos present a market timing strategy based on transforming the predictability of relative returns/volatilities between pairs of ETFs into weekly trading signals via simple rules. They choose S&P Depository Receipts (SPY), the Financial Sector Select SPDR (XLF), PowerShares QQQ (QQQQ) and Oil Services HOLDRs (OIH) to investigate three pairs: SPY-XLF, SPY-QQQQ and SPY-OIH. For robustness, they consider weeks ending on Monday, Wednesday and Friday (for a total of nine pair-endpoint combinations). They devise four trading models based on relative pair returns, relative pair (realized) volatilities and more complex characterizations of relative pair performance. Relative return/volatility predictions derive from a rolling historical window of 104 weeks. Using daily open-high-low-close prices for SPY, XLF, QQQQ and OIH to construct weekly metrics from earliest availability through April 4, 2008, they conclude that:

• In many cases, the models considered yield statistically significant sign predictions for pair relative returns and relative volatilities.
• Based on terminal wealth and weekly Sharpe ratio, rotation models outperform both buying and holding one asset in a pair and an equal weighting of both assets in a pair for eight of nine pair-endpoint combinations. Models based on predictions of pair relative returns are best for six of nine combinations.
• A very simple pair trading model based on a moving average of relative returns can outperform both benchmarks.
• More elaborate pair trading models may perform even better than the four considered.
• Pair trading models are generally riskier than equal weighting of both assets in a pair, but a priori less risky than buying and holding one asset in a pair.
• Trading frequencies (and therefore trading frictions) vary considerably across the four pair trading models.

In summary, evidence from limited tests suggests that ETF pair trading based on relative returns/volatilities may outperform simple passive benchmarks.

Exclusion of trading frictions limits the persuasiveness of findings with respect to economic significance. Data snooping bias inherent in experimentation with multiple models/sampling variations on the same dataset may be material. Assumptions about return distributions may be critical to conclusions about statistical significance.

For research on other potential trading signals, see Blog Synthesis: Some Trading Indicators. See especially the related research summarized in the blog entries of 1/27/09 and 8/13/08.

February 8, 2010 - The 2000s: A Market Timer's Decade?

Did the poor returns and high volatility of the U.S. stock market during 2000-2009 represent a tailwind for market timers? To check, we measure the performances of various simple market timing approaches (equal weighting with cash, 10-month simple moving average signals, momentum, and coin-flipping) over the decade. Using monthly closes for S&P Depository Receipts (SPY), a short-term interest rate composite and the S&P 500 index from December 1999 through December 2009 (and earlier for S&P 500 Index signal calculations), we find that: More...

February 5, 2010 - Update: The Stock Market and the Super Bowl

Investor mood affects the market. Sports affect investor mood. The biggest mood-mover among sporting events in the U.S. is the National Football League's Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super Bowl focusing and anxiety-relieving? (Presumably, post-game elation and depression cancel between respective fan bases.) Using past Super Bowl dates since inception and daily/weekly S&P 500 Index data for 1967-2009 (43 events), we find that: More...

February 4, 2010 - Important News Releases for Short Sellers

How do short sellers gain an informational advantage over other traders? On what news do they focus? Do they anticipate or react to news? In their January 2010 paper entitled "How are Shorts Informed? Short Sellers, News, and Information Processing", Joseph Engelberg, Adam Reed and Matthew Ringgenberg combine detailed data on short selling with data on news releases to investigate how short sellers use news. Using detailed information on short sales (daily short volume divided by total volume) for a broad sample of stocks and relevant news releases spanning January 3, 2005 through July 6, 2007, they conclude that: More...

February 3, 2010 - Simple Sector ETF Momentum Strategy Robustness/Sensitivity Tests (Updated 2/3/10 with a reader comment)

Readers have requested sensitivity testing of the ranking interval for the simple sector momentum trading strategies described in the blog entry of 12/22/09. These strategies generally reallocate funds monthly, based on highest past return, to one of the nine sectors defined by the Select Sector Standard & Poor's Depository Receipts (SPDR) exchange-traded funds (ETF):

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)

As noted in that prior analysis, available data is so limited that sensitivity test results may well be misleading. With that reservation, here are two additional robustness/sensitivity tests: (1) additional benchmarking of prior results against an equally weighted portfolio of sector ETFs; and, (2) comparison of ranking intervals ranging from one to 12 months applied to a narrowed XLK-XLP-XLU set of sectors. Using monthly adjusted closing prices for the sector ETFs and S&P Depository Receipts (SPY) over the period 1/99-11/09 (126 months), we find that: More...

February 2, 2010 - Variation in Long-run Stock Market Predictability

Is there a steady, zero or varying supply of stock market return predictability? In their January 2010 paper entitled "Stock Return Predictability and the Adaptive Markets Hypothesis: Evidence from Century Long U.S. Data", Jae Kim, Kian-Ping Lim and Abul Shamsuddin employ a battery of tests to evaluate the evolution of U.S. stock market return predictability over the last century and determine whether this evolution is consistent with the Adaptive Markets Hypothesis. Using monthly Dow Jones Industrial Average (DJIA) return data, along with various indicators of market conditions and economic fundamentals, for 1900 through 2009, they conclude that: More...

February 1, 2010 - A Market Volatility Factor Model

How much of the variation in stock returns flows from actual (realized or backward-looking) and implied (forward-looking) market volatilities? In the January 2010 version of his paper entitled "Option Implied Volatility Factors and the Cross-Section of Market Risk Premia", Junye Li investigates the effectiveness of a three-factor model of stock returns based on market return (beta), diffusion volatility (moderate and persistent component) and jump volatility (large and mean-reverting component). The author also examines how the value premium and size effect relate to the two volatility factors and how relying only on realized market volatility affects results. Using weekly (Wednesday) data for the S&P 500 Index, S&P 500 Index options (filtering out options with extremely long/short durations, extreme moneyness and low activity) and the S&P 500 Volatility Index (VIX) spanning January 1997 through September 2008 (608 weeks), he concludes that: More...

January 30, 2010 - Impossibly Good?

A reader asked: "The performance on Swing-Trading.net must have 200 trades, and no losers. How is that possible?"

The returns presented at Swing-Trading.net appear to be theoretical gains based on perfect foresight and perfect execution (and no trading frictions), assuming exit at the maximum price (minimum price for short sales) during the ten days after entry.

The probability of achieving such perfection is vanishingly small (in other words, zero). Such information does not represent a realistic way to evaluate performance and places a large burden on prospective subscribers to determine whether the trade advice is good or bad. Determination would require development of realistic trade exit rules, modeling of realistic trading frictions and collection of detailed historical price data for each trade.

See "Steve Sarnoff's Advice at the 'Options Hotline'" for a sense of how hard it is to get a realistic read on such information.

January 29, 2010 - Updates of Earnings Forecast, Stock Market Status and Stock Market Models

We have updated: (1) the Earnings Forecast both to simplify calculations and to incorporate early actuals for the fourth quarter of 2009; (2) Stock Market Status to reflect the revised Earnings Forecast; and, (3) the Real Earnings Yield Model and the Reversion-to-Value Model to reflect data collected over the past several months.

January 29, 2010 - The Return on Art

Do works of art provide a good return compared to equities, or do they carry an aesthetic discount? Can investors use art to hedge equities? In their July 2009 paper entitled "Art as an Investment: the Top 500 Artists", Roman Kraeussl and Jonathan Lee employ public auction prices from Artnet.com to construct and analyze a Top 500 Art Market index based on historical prices of artworks by the top 500 artists in the world (as ranked by Artprice.com). They relate art returns to those for commodities, corporate bonds, 10-year U.S. Treasury notes, hedge funds, private equity, real estate, global stocks and U.S. Treasury bills. Using prices for nearly 100,000 art transactions and contemporaneous quarterly levels of indexes for other asset classes over the period January 1985 through March 2009 (as available), they conclude that: More...

January 28, 2010 - How About Barron's "Daily Stock Alert"?

A reader asked: "Have you done an analysis of the Barron's 'Daily Stock Alert' service?" More...

January 28, 2010 - Earnings Surprises and Future Stock Market Returns

As espoused by many market commentators, do positive (negative) earnings surprises in fact predict upward (downward) stock market movement? In their January 2010 paper entitled "Aggregate Market Reaction to Earnings Announcements", William Cready and Umit Gurun investigate the relationship between earnings announcement surprises and market returns, focusing on the days surrounding earnings news. Using quarterly earnings announcements for a broad sample of firms spanning January 3, 1973 through June 21, 2006 (413,687 announcements) and contemporaneous values of a combined NYSE/AMEX index, they find that: More...

January 27, 2010 - Guru Grades Insignificant?

A reader comments and asks: "Guru Grades has 4586 "measurable forecasts" as of 1/1/2010 and only 2199 are graded "essentially right." The Excel formula <=BINOMDIST(2199, 4586, 50%, FALSE)> indicates that there is only a 0.29% chance that the gurus could have forecasted worse, given a 50-50 coin-flip ratio of forecasts being reviewed as right or wrong. There are three possible explanations of this strikingly low probability:

1. The gurus on your list are extraordinarily poor forecasters.
2. You are biased and tend to punish the forecasters.
3. The forecasters may be poor at calling the direction, but their ability to forecast magnitude (i.e., how large a market swing will be) may be better, and this ability has not been reviewed, thus indicating that your guru list is of little interest for real-life investors whose returns are determined by hit ratio times magnitude of market swing.

If reality is a mix of these three points, it could be that the guru stats are of no statistical significance. Have you considered your guru stats in light of these points?" More...

January 27, 2010 - Unadmired Stocks Beat Admired Ones?

Are the most admired companies the best investments? Or, is current state of admiration a contrarian indicator for future returns? In their January 2010 paper entitled "Stocks of Admired Companies and Spurned Ones", Deniz Anginer and Meir Statman use Fortune magazine's yearly survey-based lists of "America's Most Admired Companies" to answer these questions by measuring the returns (April 1 through March 31) of two portfolios reformed annually: admired companies (upper half of survey scores), and unadmired companies (lower half of survey scores). Survey respondents are senior executives, directors and securities analysts, and the questions asked seemingly relate indirectly or directly to the investment value of the companies named. Using these lists for April 1983 (survey inception) through March 2007 and associated stock return data, they conclude that: More...

January 26, 2010 - Timothy Sykes: Penny Stock Pump-and-Dump Detective?

A reader requested a review of the trading methodology presented at TimothySykes.com ("Short Selling Penny Stocks"), which essentially uses price-volume analyses in attempts to detect in real time penny stocks being pumped and ride the ensuing downside (dump). Timothy Sykes, author of the An American Hedge Fund, is a former hedge fund manager and founder of BullShip Press LLC. His bio states: "Since the beginning of 2008, Timothy has been the #1 trader/investor, out of 25,000+ on Covestor.com." Using the record of 296 trades spanning 2/1/08 through 1/22/10 (including those previously posted for October 2009, but now missing) and some recent clarifications from Timothy Sykes, we find that: More...

January 25, 2010 - Dishonesty and Fraud?

In response to "The TimingCube Market Timing Advisory Service", a reader commented: "TimingCube's home page claims a 37% annualized return. In prior years, they advertised 100%+ returns. For the first year I followed them (2003), they did great. I told everyone about it. Their subsequent failure starting in 2004 though has taught me a lesson. You have to give a system two full years at least to see if will work. I wish I had done that. Every single person to whom I recommended TimingCube has left them. If you look at TimingCube's results page, you will see pure fiction. These are not the actual signals they put out, but instead the 'revised' signals that they backtested after the system failed a few times. I am surprised they are still in business. The SEC doesn't respond to complaints very well. Why? There are lots of TimingCubes out there. It would be like reporting a dishonest used car salesman... Dishonesty and fraud is what TimingCube is about. ...I wish you or someone would dig a little deeper and expose guys like this who misrepresent their results." More...

January 25, 2010 - A Few Notes on Put Option Strategies for Smarter Trading

In his 2010 book Put Option Strategies for Smarter Trading: How to Protect and Build Capital in Turbulent Markets, author Michael Thomsett "explains all the put-based strategies [for individual stocks] in detail and shows how even a troubled market presents great opportunities to keep you in control. The worst aspect of volatile markets is a sense of not having control over events, and puts can be used to offset this apprehension. You have probably heard that astute traders can earn profits in all types of markets. Puts are among the best devices to accomplish that goal." Some notable points about the book are: More...

January 24, 2010 - Apply the Breakout Detection Model to the Euro?

A reader suggested: "You might test the Bollinger Band- Keltner Channel breakout detection model on the euro. Equity indexes generally have performed anti-trend (reversion to the mean) whereas currencies have trended." More...

January 23, 2010 - Guru Age Versus Performance?

A reader asked: "Is there a correlation between guru success and age. I ask this because: (1) Nassim Taleb talks about the success of younger traders (prior to blowing up at some point); and, (2) pessimism increases with age, or so it seems, and older traders are therefore likely to miss uptrends." More...

January 22, 2010 - Performance of Buy-Write Strategies for Australian Stocks

Do buy-write strategies, wherein investors buy stocks and simultaneously sell matched out-of-money call options, generally outperform their underlying stocks? In other words, do option premiums more than compensate for any sacrifice of capital gains? In their January 2010 paper entitled "The Efficiency of the Buy-Write Strategy: Evidence from Australia", Tafadzwa Mugwagwa, Vikash Ramiah and Tony Naughton examine the performances of buy-write strategies on the Australian Stock Exchange for portfolios formed monthly, quarterly and yearly at different levels of call option out-of-the-moneyness. They test the profitability of buy-write strategies during weak and strong markets. They measure the effects on buy-write returns of underlying stock liquidity (turnover ratio), dividend yield, firm size, book-to-market ratio, earnings per share and price-earnings ratio. Using prices, firm fundamentals and out-of-the-money call option prices (actual and modeled) for 179 stocks over the period January 1995 through October 2006, they conclude that: More...

January 21, 2010 - Stock Returns and Changes in Implied Volatility

Are there reliable and exploitable predictive relationships between stock returns and changes in implied volatility? In the January 2010 version of their paper entitled "The Joint Cross Section of Stocks and Options", Andrew Ang, Turan Bali and Nusret Cakici investigate the relationship between changes in implied volatility and stock returns for individual stocks. Using monthly implied volatilities and associated stock prices and firm fundamentals for a broad sample of U.S. stocks over the period January 1996 through September 2008 (153 months), they conclude that: More...

January 20, 2010 - Success Factors for Futures Traders

Does the profitability of futures traders depend on risk-taking, private information or luck? In the January 2010 revision of their paper entitled "Determinants of Trading Profits of Individual Traders: Risk Premia or Information", Michaël Dewally, Louis Ederington and Chitru Fernando investigate success factors for traders in the crude oil, gasoline and heating oil futures markets. They exploit detailed daily open interest data for specific large and mid-size traders (from the Commodity Futures Trading Commission, as augmented by the Department of Energy) accounting for about 70% to 80% of these three futures markets. This detailed data enables analytical segmentation of traders into eleven types, consolidated into four categories: (1) hedgers, (2) speculators, (3) market makers and (4) others. Using detailed data for a final sample of 382 traders over the period June 1993 through March 1997 (46 months), they conclude that: More...

January 19, 2010 - Update: Any Stock Market Anomalies Around Three-day Weekends?

A reader asked: "Is there any data on what typically happens after a three-day weekend?" Some stock market experts hypothesize that more traders than usual move to the sidelines before long weekends to avoid the risk of bad news during the extra long downtime. Assuming most traders are long, such selling would depress stock prices before three-day weekends and elevate them afterward as traders re-enter positions. To investigate, we analyze the historical behavior of the S&P 500 Index during the three trading days before and the three trading days after three-day weekends. Using daily closing levels of the S&P 500 Index for 1950-2009 (60 years and 337 three-day weekends), we find that... More...

January 18, 2010 - Inflation Forecast Update

The Inflation Forecast now incorporates the actual inflation rate for December 2009, which is slightly higher than predicted. This mismatch will cause slight downward adjustments in the outputs of the Real Earnings Yield Model at the end of January.

January 15, 2010 - Quantitative Versus Qualitative Hedge Funds

Do quants outperform quals? In his January 2010 preliminary draft paper entitled "A Comparison of Quantitative and Qualitative Hedge Funds", Ludwig Chincarini compares the performance characteristics of quantitative and qualitative hedge funds. Using return data and strategy descriptions spanning a total of 6,352 hedge funds over the period January 1970 through June 2009 and risk factor adjustment data for a January 1994 through March 2009 subperiod, he concludes that: More...

January 14, 2010 - Testing a Complex Breakout Indicator

A reader, citing a technical indicator recommended in Mastering the Trade by John Carter, inquired about the usefulness of watching for times when certain Bollinger Bands (upper and lower bounds two standard deviations from a 20-day simple moving average) converge within a certain Keltner Channel (upper and lower bounds 1.5 times the 20-day average range from a 20-day average typical price). Breakouts from this condition are supposedly reliable for both indexes and individual securities, meaning that price continues in same direction for a while without material reversal, because the condition represents true "consolidation." There is no specification for trend duration after these "reliable" breakouts. Using daily high, low and unadjusted closing prices for S&P Depository Receipts (SPY) for band/channel calculations, and adjusted closing prices for return calculations, over the period 1/29/93 through 1/8/10 (nearly 17 years), we find that: More...

January 13, 2010 - Does the Turn-of-the-Month Effect Work for Sectors?

A reader inquired whether the Turn-of-the-Month Effect, a significant concentration of positive stock market returns around the turns of calendar months, works for stock market sectors. To investigate, we measure turn-of-the-month (TOTM) returns for 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)

In an additional (shorter) test, we add measurement of TOTM returns for SPDR Gold Shares (GLD) as a proxy for gold. We define TOTM (per the Strategy Test) 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 for S&P Depository Receipts (SPY) as a benchmark from 12/22/98 through 1/8/10 (133 months) and for GLD from 11/18/04 through 1/8/10 (62 months), we find that: More...

January 12, 2010 - Is Phil Erlanger's Research Exploitable?

A reader asked about Phil Erlanger Research: the Art of the Squeeze Play for institutional investors, which offers "research focused on delivering...advanced technical and sentiment research and data," and the companion Erlanger Squeeze Play for private investors, which identifies "short-term trading opportunities in both long and short squeeze plays." The core elements of this research are "short intensity and technical strength." The performance data on the two sites are identical, but more up to date at Phil Erlanger Research. Should investors expect that portfolios built on this research will substantially outperform the market? Based on weekly self-reported performance data and contemporaneous weekly data for S&P Depository Receipts (SPY) spanning 3/8/02 through 10/9/09, we find that: we find that: More...

January 11, 2010 - Update: Using Commitments of Traders Reports to Time Asset Allocations

Is the aggregate sentiment of futures traders predictive for asset returns? In the June 2008 update of their paper entitled "How to Time the Commodity Market", Devraj Basu, Roel Oomen and Alexander Stremme investigate whether information in the weekly Commodity Futures Trading Commission's Commitments of Traders (COT) reports enable successful timing of U.S. equities and commodities markets. These reports aggregate the size and direction of the positions taken by different categories of futures traders in different assets. "Commercial" traders use futures contracts for hedging, "non-commercial" traders use them for other types of speculation and "non-reportable" traders operate below the reporting threshold. The study seeks to exploit "hedging pressure" (the fraction of positions that are long) for each of six liquid commodities (crude oil, gold, silver, copper, soybeans and sugar) and for the S&P 500 Index. Each Friday, the six trading strategies studied: (1) take a long position in a commodity if hedging pressure for both the commodity and the S&P 500 Index are below their 52-week averages; or, (2) take a long position in the S&P 500 Index if hedging pressure for both the commodity and the S&P 500 Index are above their 52-week averages; or, (3) hold 3-month U.S. Treasury bills. Using COT reports and associated weekly futures prices for October 1992 through December 2006, they conclude that: More...