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Do popular capitalization-based exchange-traded funds (ETF) confirm the existence of a size effect? To investigate, we compare the difference in returns (small minus large) for the following pair of large-small ETFs:
iShares Russell 1000 Index (Largecap) Index (IWB)
iShares Russell 2000 (Smallcap) Index (IWM)
Using monthly adjusted closing prices (incorporating dividends) for these ETFs during June 2000 (the earliest month available for both) through July 2008, we find that: More...
Do popular style-based exchange-traded funds (ETF) confirm the existence of a value premium? To investigate, we compare the difference in returns (value minus growth) for each of the following three matched pairs of value-growth ETFs:
iShares Russell 2000 (Smallcap) Growth Index (IWO)
iShares Russell 2000 (Smallcap) Value Index (IWN)
iShares Russell Midcap Growth Index (IWP)
iShares Russell Midcap Value Index (IWS)
iShares Russell 1000 (Largecap) Growth Index (IWF)
iShares Russell 1000 (Largecap) Value Index (IWD)
Using monthly and quarterly adjusted closing prices (incorporating dividends) for these ETFs during October 2001 (the earliest quarter available for IWP-IWS) through June 2008, we find that: More...
The inflation rate forecast flyoff now incorporates 40 months of live testing for three granular (month-by-month or quarter-by-quarter) 12-month trailing consumer inflation rate forecasts, all freely available on the web: (1) the BMO Nesbitt Burns United States Economic Outlook; (2) our own simple extrapolation (CXO); and, (3) the Financial Trend Forecaster (FTF) Moore Inflation Predictor. The flyoff is for one-month-ahead accuracy only. Which model is winning? Using accumulated forecast and actual inflation data for 4/05-7/08, we find that: More...
Do presidential election polling data have any effect on stock returns? In other words, do investors act on the survey-indicated election prospects for the two major party candidates? Presumably, investors would tend to enter (exit) stocks if they thought the candidate with policies more (less) favorable for equity valuation were gaining ground. Using Gallup Daily polling data and contemporaneous daily closing levels of the S&P 500 index from June 6 (when the major party nominations solidified) through August 17 (49 trading days), we find that: More...
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 12/22/9-8/15/08, we find that: More...
Taking the same approach as used for the calendar year at Trading Calendar, what is the typical cumulative return profile for the U.S. stock market over the four-year presidential term? Using monthly closing levels of the S&P 500 index from December 1951 through July 2008 (13+ presidential terms), we find that: More...
To determine whether stocks are expensive or cheap, some stock market experts use value ratios, such as price-earnings ratio (P/E) or price/dividend ratio. These ratios reached unusually high levels during the Internet bubble and have been mostly falling since. Are value ratios still trending down or have they bottomed? Using price, earnings (operating and reported) and dividend actuals/estimates from the end of 1989 through July 2008 from the S&P 500 Earnings and Estimate Report of Standard and Poor's Quantitative Services, we find that: More...
In reaction to our blog entry of 7/29/08 on trading the relationship between natural gas and crude oil prices, a reader suggested that reversion in the relationship between PowerShares QQQ (QQQQ) and iShares Russell 2000 Index (IWM) may support short-term trading. To check, we consider: (1) the QQQQ-IWM ratio over the long term; (2) this ratio relative to its six-month moving average; and, (3) unusual daily divergences between these two exchange-traded funds. Using daily adjusted closing prices for QQQQ and IWM over the period 5/26/00 (the earliest available for IWM) through 7/29/08, we find that: More...
Reader Henry Bee of Vancouver, Canada asks:
"You have probably heard of the historical 6:1 crude oil/natural gas price ratio. This relationship is said to be mean reverting based on the thermal equivalence of the two commodities. Does this ratio have any predictive power for the future prices of oil or natural gas? If there is no predictive power for this ratio, then it could mean that the thermal equivalence itself shifts over time. And hedge funds who are long natural gas right now are making a huge fundamental mistake."
If there are relationships, we hypothesize that a high (low) crude oil-natural gas price ratio should predict future changes in the prices of natural gas of crude oil to decrease (increase) the ratio. Using the monthly composite U.S. refiner cost of crude oil (nominal dollars per barrel) and the monthly U.S. wellhead natural gas price (nominal dollars per thousand cubic feet) for January 1976 through April 2008 (388 months), we find that... More...
Our Test Strategy attempts to exploit the value premium, the size effect, the turn-of-the-month effect and the volatility premium embedded in index options. The strategy has outperformed buy-and-hold, achieving a small gain during a mostly declining market over the past 16 months. How has each premium/effect contributed to strategy performance? Using strategy account and benchmark data over the period 3/16/07 through 7/11/08, we find that: More...
Are prominent stock market bloggers in aggregate able to predict the market's direction? The Ticker Sense Blogger Sentiment Poll "is a survey of the web's most prominent investment bloggers, asking 'What is your outlook on the U.S. stock market for the next 30 days?'" (bullish, bearish or neutral) on a weekly basis. The site currently lists 21 active prognosticators. Participation has varied over time. Based on results from Guru Grades and other stock market sentiment studies, we hypothesize that blogger sentiment: (1) tends to react to what just happened in the stock market; and, (2) does not predict stock market behavior. Using the 102 aggregate measurements from the poll since inception, we find that... More...
A reader inquired about the validity of Martin Zweig's Four Percent Model Indicator, which states:
"The Four Percent Model Indicator uses the...weekly close of the Value Line Index. A buy signal is generated when the index rises four percent or more from the previous week. Similarly, a sell signal is indicated when the index falls four percent or more from the previous week."
Does the rule really work? Using weekly closes of the Value Line Arithmetic Index over the period 5/4/84 (the earliest available) through 7/11/08, we find that: More...
How stable are the quarterly aggregate operating earnings growth forecasts for the S&P 500? What has the trend in these forecasts been lately? Using the earnings forecasts published every one to two weeks by Standard and Poor’s (and by Reuters until recently discontinued) for the eight quarters of 2007 and 2008 over the period 5/15/06 through 7/9/08, we find that: More...
Does the monthly ADP National Employment Report predict U.S. stock market returns? This report "was developed to help meet the need for additional timely and accurate estimates of short-term movements in the national labor market among economists, financial professionals, and government policy-makers. Because ADP pays 1-in-6 private sector employees in the United States every pay period across a broad range of industries, firm sizes, and geographies, it has a unique and significant perspective on the U.S. labor market." ADP releases the report for each month near the beginning of the following month. Using historical monthly ADP estimates of seasonally adjusted non-farm payrolls for December 2000 through June 2008 (91 months) and contemporaneous monthly S&P 500 index data, we find that: More...
For this sensitivity analysis of the short-term Real Earnings Yield (REY) model, we use the version based on core inflation rate because this version has been more accurate than that based on the total inflation rate in fitting the historical S&P 500 index over the past few years. We consider four S&P 500 operating earnings scenarios and two core inflation rate scenarios, with a tilt toward pessimistic inputs. Using projections through the middle of 2009, we find that... More...
Our blog entry of 6/12/08 summarizes a simple momentum trading strategy that trades each month into the one of nine sector exchange-traded funds (ETF) with the highest total return over the prior six months. The strategy outperforms the broad stock market since introduction of these ETFs. A reader comments and asks:
"Many value investors say they scan for 'new lows.' Would a similar methodology apply to ETFs? How do the bottom performers (lowest prior six-month return) work for this test? My guess is that the ranking period would have to be longer than six months (say, one year or three years) and that the holding period would have to be longer than one month to generate positive returns."
To investigate sector ETF reversion, we test two trading strategies on the following nine sector ETFs 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)
The first (6-1) reversion trading strategy starts with $10,000 and each month puts all funds into the one of the above ETFs that has the lowest total return over the prior six months. The second (12-6) reversion trading strategy also starts with $10,000 and every six months puts all funds into the one ETF with the lowest total return over the prior 12 months. Using monthly adjusted closing prices for these ETFs and for the S&P 500 index mimicking SPY (to represent the overall stock market) over the period 1/99-5/08 (113 months), we find that: More...
Do the emotions of presidential elections in the U.S. affect monthly stock returns, either elevating returns based on hope or suppressing them based on uncertainty? To check, we compare returns by calendar month for the Dow Jones Industrial Average (DJIA) during presidential election years to returns during non-election years. Using monthly adjusted closes for the DJIA over the period October 1928 through May 2008 (81+ years and 20+ presidential election years), we find that: More...
The middle of the year might be a time for investors to review and revise their portfolio allocations. It includes a turn of the month and the 4th of July celebration in the U.S. Is there a reliable pattern to daily stock market returns at mid-year? To check, we analyze the historical behavior of the S&P 500 index from ten trading days before to ten trading days after the June/July turn of the month. Using daily closing levels of the index for 1950-2007 (58 observations), we find that... More...
Does a simple momentum trading strategy applied to the major stock market sectors outperform the overall market? To investigate, we apply a simple six-month past total return momentum trading strategy to 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)
The simple trading strategy starts with $10,000 and each month puts all funds into the one of the above ETFs that has the highest total return over the prior six months. Using monthly adjusted closing prices for these ETFs and for the S&P 500 index mimicking SPY (to represent the overall stock market) over the period 1/99-5/08 (113 months), we find that: More...
Do investors/traders tend to overdo it during buying and selling frenzies, coming to their senses shortly thereafter? In other words, does the broad U.S. stock market tend to revert after extreme short-term moves up or down? To check, we test for short-term reversion of the S&P 500 index after its sharpest declines and advances since the beginning of 1990, hoping to identify reasonably frequent trading opportunities. Using daily closes of the S&P 500 index over the period 1/2/90 through 6/6/08 (4647 trading days), we find that... More...
Do any of the major stock market sectors systematically lead or lag the overall market, perhaps because of some underlying economic cycle? To investigate, we examine the behaviors of the nine sectors 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)
Using monthly adjusted closing prices for these exchange traded funds (ETF) and for the S&P 500 index mimicking SPY (to represent the overall stock market) over the period 1/99-5/08 (113 months), we find that: More...
One of the stock market anomalies we seek to exploit in our Strategy Test is the Turn-of-the-Month Effect, a significant concentration of excess stock market returns around the turns of calendar months. Has the strength of this effect changed over time? Does it (as asked by a reader) interact with the U.S. political cycle? Using daily closes for the S&P 500 index for the period January 3, 1950 through May 2, 2008 (700 months), we find that: More...
In our Trading Calendar, we construct full-year and monthly cumulative performance profiles for the overall stock market (S&P 500 index) based on its average daily behavior since 1950 and since 1990. How much do the corresponding monthly behaviors of the various stock market sectors deviate from an overall market profile? To investigate, we consider the nine sectors 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)
Using monthly adjusted closing prices for these exchange traded funds since inception, along with contemporaneous data for the S&P 500 index mimicking SPY as a benchmark, we find that: More...
In our Real Earnings Yield Model, we argue that inflation at the consumer level is fundamentally a wealth discount rate important in determining the value of equities to investors. Do investors therefore reliably react over the intermediate term to changes in CPI as a measure of the wealth discount rate? Using monthly historical CPI data (for all items, not seasonally adjusted) from the Bureau of Labor Statistics (BLS) and contemporaneous S&P 500 index data for the period January 1994 (the earliest for which release dates are available) through May 2008 (173 months), we find that: More...
Does the stock market react reliably and exploitably to the monthly announcements of the change in the Consumer Price Index (CPI) by the Bureau of Labor Statistics? To check, we examine the typical behavior of stocks during the five trading days before and the five trading days after CPI release dates. Using non-seasonally adjusted total and core CPI data, associated release dates and contemporaneous daily S&P 500 index data for the period 1/94-4/08 (171 announcements), we find that... More...
Do the favorite equity investments of stock market newsletter gurus reliably outperform the market? One way to answer this question is a test of the performance of the favorite investments identified in the historical reports at NewsletterAdvisors.com published from 11/1/05 to 11/1/07. In each of these seven reports, a group of "top investment gurus reveal their favorite investment ideas." NewsletterAdvisors.com is published by Business Financial Publishing, "a diversified publisher of investment news, research, and analysis for individual investors through paid subscription newsletters, free e-letters, and regular special reports." Using historical price data from Yahoo!Finance for the sample of 70 favorite investments in in the seven reports and contemporaneous S&P Depository Receipts (SPY) performance data for benchmarking, we find that: More...
Financial market experts sometimes cite the Economic Cycle Research Institute’s (ECRI) Weekly Leading Index (WLI) as an important economic indicator, implying that it is somehow predictive of future stock market performance. According to ECRI, WLI "has an average lead of 10 months at business cycle peaks and three months at business cycle troughs..." with the most recent value summarizing any shift in overall outlook as a result of "data through the previous week." Does this indicator usefully foretell the future of equities? Using WLI readings for 3/2/01 to 5/2/08 (376 weeks) and contemporaneous weekly S&P 500 index data, we find that: More...
A reader requested an extension of the analysis in our blog entry of 4/9/08, which tests a strategy that goes long (short) the stock market from Wal-Mart's (Alcoa's) earnings release until Alcoa's (Wal-Mart's) earnings release. The proposed follow-up employs a larger sample and a strictly calendar-based definition of earnings season, as follows: go long (short) the market at the close at the end of the sixth full week (first full week) of each calendar quarter, representing the end (beginning) of earnings season. The hypothesis is that the broad stock market does well outside of the specified earnings season and poorly during the specified earnings season. Using weekly closes of the S&P 500 index (as a proxy for the broad stock market) since the beginning of 1950, we find that... More...
The zero-sum S&P 500 futures market involves three categories of players: commercial hedgers; non-commercial traders (large speculators); and, non-reportable traders (small or retail speculators) representative of the public. The Commodity Futures Trading Commission collects and publishes their aggregate positions (short, long and spread) for each asset in a weekly Commitment of Traders report. Are the behaviors of these groups in trading S&P 500 index futures reliable indicators of future stock market direction? If so, is this predictive power stable over time? Using the Historical Commitments of Traders Reports Futures and Options Combined available from CFTC and corresponding S&P 500 index data from late March 1995 (the earliest available for futures) through March 2008 (a total of 675 weeks), we find that: More...
A reader asks:
"CNBC's Fast Money cited a 'seasonal' strategy noted in Barron's, as follows: Go long the market from Wal-Mart's (WMT) earnings release until Alcoa's (AA) earnings release and short the market from Alcoa's earnings release until Wal-Mart's earnings release (earnings season). Over last six years, the market has been up nicely during the former period and down an average 8% during the latter. Any testing on this?"
To test this proposition we assemble the earnings release dates for Wal-Mart and the earnings release dates for Alcoa since the beginning of 1997 (the earliest available from Alcoa's web site). We estimated the date for one missing Wal-Mart release. This sample of 45 quarters is nearly twice as large as that cited on Fast Money, potentially offering more reliable historical inference. Using these earnings release dates and daily closing S&P 500 index levels (as a proxy for the broad stock market) over the period 2/25/97 through 4/7/08, we find that... More...
In a post at TraderFeed, Brett Steenbarger noted that long-term changes in margin debt may signal major stock market turning points. Could margin debt serve as an intermediate-term indicator based on either momentum (with an increase in margin debt signaling a higher stock market) or contrarian reversion (with a change in margin debt indicating an opposing future stock market move)? To investigate, we compare the behavior of NYSE end-of-month margin debt with the monthly behavior of the S&P 500 index over the period January 1990 through February 2008. Based on experience with other investor sentiment measures, our hypotheses are that: (1) the stock market and margin debt move up and down together; and, (2) changes in margin debt do not reliably predict changes in the stock market. We find that... More...
A reader inquired: "Do copper futures reliably lead the market, as some believe." The hypothesis is that demand for copper is a reliable leading indicator of economic activity and therefore aggregate equity prices. In lieu of a long-run set of copper futures data, we use monthly prices for copper base scrap (not seasonally adjusted) from the "Metal and Metal Products" group of the Producer Price Index components. This series extends back to 1957, allowing comparing across multiple economic expansions and contractions. Comparing the behavior of quarterly copper base scrap prices to quarterly levels of the S&P 500 index for 1957-2007, we find that... More...
A reader posed the following question:
"What would be the current S&P 500 index target according to your model if expected earnings were flat? Could you provide some scenario analysis based on your model relative to different expected earnings growth rates (+5%, 0%, -5%, -10%) and different realized inflation rates (1.5%, 2.5%, 3.5%)?"
For this analysis, we use the short-term version of the Real Earnings Yield (REY) model based on total inflation rate because the REY model generally outperforms the Reversion-to-Value model in fitting historical data and because we have better total than core inflation rate forecast error data. We consider four S&P 500 operating earnings scenarios and five total inflation rate scenarios, with focus on the most optimistic and pessimistic combinations. Using projections through the end of 2008, we find that... More...
A reader posed the following question:
"What does recent outperformance of gold and steel mining sector and agricultural sector mean for the stock market in general and is there any correlation with other sectors in the following 3 to 12 months as common wisdom on the business cycle would suggest?"
To enable a sample that is long enough to support inference, we use the chemicals industry to represent agriculture and the precious metals and mining industry to represent gold and steel mining. We use the Fidelity Select Chemicals (FSCHX) fund as a tradable proxy for the chemicals industry and the Vanguard Precious Metals and Mining (VGPMX) fund as a tradable proxy for the precious metals and mining industry. To keep the analysis manageable, we relate the performances of these two funds to that of the S&P 500 index (and not the performances of other industries). Using daily return data for the funds and the index from 7/15/87 (the earliest all three are available) through 3/7/08, we find that... More...
In our blog entries of 3/3/08 and 3/4/08, we test the usefulness of the Relative Strength Index (RSI) and the Moving Average Convergence/Divergence (MACD), respectively, for anticipating abnormal returns of a broad market index as proxied by S&P Depository Receipts Trust (SPY). In this entry, we combine RSI and MACD signals from those prior analyses in search of more concentrated abnormal returns. Using those signals and daily dividend-adjusted SPY closing prices from 1/29/93 (the earliest available) through 2/29/08, we find that... More...
In this entry, we perform a simple test of the Moving Average Convergence/Divergence (MACD), as calculated using the Exponential Moving Average (EMA) template at StockCharts.com, on a tradable proxy for the S&P 500 index. MACD is the difference between the 26-day EMA price and the 12-day EMA price for an asset. A bullish (bearish) crossover occurs when MACD moves above (below) its 9-day EMA. To reduce the number of very short-term MACD trades, we filter out "close calls" by requiring MACD to reach a level 25% above or below its 9-day EMA before triggering a trade. Using daily dividend-adjusted closing prices for the S&P Depository Receipts Trust (SPY) from 1/29/93 (the earliest available) through 2/29/08, we find that... More...
Reader Dennis Page of Beverly Hills MI sent the following question:
"Jason Kelly from the Kelly Newsletter posted this remark in January 2008: 'A good way to judge trading opportunities on indexes is by watching their MACD and RSI scores. Both together, along with the price chart, give good indications as to whether the odds favor rising or falling from here.' Is this true?"
In this entry, we perform a simple test of the 14-day Relative Strength Index (RSI), as calculated by the template at StockCharts.com, on a tradable proxy for the S&P 500 index. Note that this indicator measures the strength of price for an asset relative to its own recent past, not relative to other assets. We use the conventional interpretation that values of RSI below 30 (above 70) indicate oversold (overbought) conditions ripe for reversion. Using daily dividend-adjusted closing prices for the S&P Depository Receipts Trust (SPY) from 1/29/93 (the earliest available) through 2/29/08, we find that... More...
After reviewing our blog entry of 1/29/08 that finds no evidence supporting Charles Nenner's belief in a relationship between sunspots and the stock market, reader Henry Bee of Vancouver, Canada asks:
"Sunspot activity does have a direct relationship to weather. Could one speculate on the natural gas market or the agriculture market using the sunspot cycles?"
Using monthly sunspot counts and monthly U.S. wheat prices for January 1950 through November 2007 (695 months) and monthly U.S. wellhead natural gas prices for January 1976 through November 2007 (383 months), we find that... More...
A reader asks:
"Have you had the opportunity to evaluate Charles Nenner as an equity and commodities forecaster?"
Charles Nenner is self-described as "the talk of Wall Street in 2006 with his 'triple call' on the market." However, we found hardly any references to him in the online business media. We therefore listened to a Bloomberg-sponsored presentation/discussion of his methods. Dr. Nenner cites in that presentation a specific key indicator for equity returns, sunspot activity, that we can test. Using monthly sunspot counts from the National Geophysical Data Center (NGDC) and contemporaneous monthly S&P 500 index data for January 1950 through November 2007 (695 months), we find that... More...
A reader asks about the implications of the currency carry trade (with attractiveness indicated, for example, by the yen/euro exchange rate trend) for U.S. stock returns (as measured via the S&P 500 index). Specifically, does the yen/euro exchange rate trend predict the degree to which large players borrow yen to buy U.S. stocks? Using currency exchange rate data from the Federal Reserve Bank of New York and contemporaneous S&P 500 index data for 1999-2007, we find that... More...
What categories of information are of broadest interest to readers of this web site, who might be characterized as fairly sophisticated investors and traders? Using a listing of the Top 50 most visited directories for all of 2007, we find that... More...
Does systematic measurement of the level of investor optimism provide a clue to the future direction of the stock market? Or, does investor sentiment merely respond to market ups and downs? UBS and Gallup conduct a monthly poll of American investors ("head of a household or a spouse in any household with total savings and investments of $10,000 or more") to assess their aggregate level of optimism. Polling takes place during the first half of each month, with results reported near the end of the month. Comparing historical UBS/Gallup investor optimism data to contemporaneous monthly S&P 500 index over the period February 1999 through December 2007, we find that... More...
Many stock market experts cite the year (1, 2, 3 or 4) of the U.S. presidential term cycle as a useful indicator of U.S. stock market returns. Game theory suggests that presidents deliver bad news immediately after being elected and do everything in their power to create good news just before ensuing biennial elections. Are some presidential term cycle years reliably good or bad? If so, are these abnormal returns concentrated in certain quarters? Finally, what does the stock market do in the period immediately before and after a national election? Using S&P 500 index data from 1950 through 2007 (58 years) and focusing on "political quarters" (Feb-Apr, May-Jul, Aug-Oct and Nov-Jan), we find that: More...
How do aggregate corporate operating earnings behave over the long run? Does the earnings growth rate predictably revert to some mean value? Using actual and estimated S&P 500 earnings data from Standard and Poor’s for 1990-2008, we find that: More...
Are there any systematic, marketwide return or volatility patterns associated with the expiration of U.S. stock options on the third Friday of each month? Using equity option expiration dates and daily closes for the S&P 500 index for 1/2/90-12/24/07, we find that: More...
Do family visits, gifts and personal resolutions around the year-end holidays inject a dose of optimistic forward thinking into U.S. stock investors? To investigate, we analyze the historical returns of the S&P 500 index from one trading day before through 10 trading days after Christmas. Using daily closing levels for 1950-2006 (57 events), we find that... More...
In reaction to our blog entry of 11/30/07, a reader offered the following observation and question:
"For many market observers, the 200-day moving average is the point of being in or out of the market. Does being above or below the 200-day moving average make a material difference with respect to missing the the best/worst 10, 20 or 100 days?"
To check, we return to the data set for our blog entry of 12/03/07, which identifies the 40 biggest up days (daily return > 3.50%) and the 40 biggest down days (daily return < -3.09%) for the S&P 500 index during January 1950 through November 2007. Calculating the 200-day moving average (MA) at the close for each day just before these 80 biggest up/down days, we find that: More...
The differences between the aggregate stock forward earnings yield and the yields on Treasury instruments are at present extraordinarily large. What are the current outputs of the the Fed Model based on these differences? To calculate Fed Model valuation benchmarks, we use daily data for the 13-week Treasury bill (T-bill) yield, the 10-year Treasury note (T-note) yield and the S&P 500 forward operating earnings yield (E/P) derived from our Real Earnings Yield Model over the period 1/2/90-12/5/06. To generate projections, we use the current Standard and Poor’s S&P 500 operating earnings forecast for the fourth quarter of 2007 through the third quarter of 2008. Using these data series, we find that: More...
In reaction to our blog entry of 11/30/07, a reader posed the following question:
"Do big up days tend to occur during down trends as counter-move rallies (meaning that big down days and big up days tend to cluster during downtrends)?"
To check for clustering, we compare the dates of big up and down days for U.S. stock market averages. To check whether these dates tend to occur during downtrends, we examine returns during the 63 trading days before and the 63 trading days after these dates. Using daily returns for the Dow Jones Industrial Average (DJIA) during October 1928 through November 2007 and the S&P 500 index during January 1950 through November 2007, we find that: More...
Suppose we take the current intermediate-term (notionally 3-9 month) stock market outlooks of the experts covered in Guru Grades and weight these outlooks according to current calculated guru forecast accuracies. Would the current accuracy-weighted aggregate opinion be bullish or bearish? Here's another update on weighting guru stock market outlooks. More...
Does the Thanksgiving holiday, a time of families celebrating plenty, signal any unusual return effects by injecting optimism into U.S. stock investors? To investigate returns around Thanksgiving, we analyze the historical behavior of the S&P 500 index during the three trading days before and the three trading days after the holiday. Using daily closing levels for 1950-2006 (57 events), we find that... More...
Which stock market experts intrigue investors and traders the most? To gain some insight regarding this question, we examine cxoadvisory.com log files over the past six months for visits derived from search engine inputs and for counts of visits to specific Guru Grades directories. Using the the top 50 log file results for these two approaches over the period 5/7/07-11/6/07, we find that: More...
In our blog entry of 11/1/07, we examine the hypothesis that growth (value) stocks tend to do relatively better when interest rates are rising (falling). A reader inquires:
"Ken Fisher did a statistical study in his book, The Only Three Questions That Count: Investing by Knowing What Others Don't, which states that growth (value) is in favor when the yield curve flattens (steepens). Any truth to this?"
To test this hypothesis, we compare the performances of paired growth and value indexes/funds as the spread between the yields on the 10-year Treasury Note (T-note) and the 90-day Treasury Bill (T-bill) varies. Using monthly and quarterly adjusted (for dividends) return data for a pair of growth-value indexes and a pair of growth-value mutual funds, along with contemporaneous T-note and T-bill yield data, we find that: More...
In our blog entry of 10-23-07, we identify the worst and best calendar days of the year on average for the U.S. stock market. In this entry, we take a different perspective to envision average daily returns and average daily close-to-close volatility across the calendar year. Using daily closes for the S&P 500 index during 1/3/50-10/19/07, we find that... More...
In his 2007 book The Little Book That Makes You Rich: A Proven Market-Beating Formula for Growth Investing, expert Louis Navellier hypothesizes that growth (value) stocks tend to do relatively better when interest rates are rising (falling). Growth stocks benefit from the economic expansions associated with rising rates. Value stocks benefit from refinancing opportunities as interest rates fall. To test this hypothesis, we compare the performances of paired growth and value indexes/funds as interest rates, proxied by the 10-year Treasury Note (T-note) yield, vary. Using monthly and quarterly return data for a pair of growth-value indexes and a pair of growth-value mutual funds, along with contemporaneous T-note yield data, we find that: More...
Do individuals whose stock market forecasting records are good (bad) gain (lose) attention? The "pro" argument is that investors/traders, seeking a market timing edge, eventually flock to good forecasters and ignore bad ones. The "con" arguments are that loud noise (for example, marketing-related or entertainment-driven) swamps information, and/or investors/traders do not or cannot measure accuracy, and/or investors/traders are more interested in ideas than forecasts. As a simple, partial test these arguments, we use two data series: (1) the stock market forecasting accuracies of the 43 named gurus in Guru Grades; and, (2) the attention paid to these same individuals as defined by the number of matches found by a Google query on ("[guru name]" "stock market"), with the "stock market" term intended to filter out potential namesakes and relate each name to the forecasted variable. We find that: More...
In our blog entry of 10-23-07, we identify the worst and best calendar days of the year on average for the U.S. stock market. In this entry, we widen the aperture to find the worst and best five-day trading periods on average by the calendar. Using daily closes for the S&P 500 index during 1/3/50-10/19/07, we find that... More...
The unreal deal, as found in the cyber-alleys off Wall Street... More...
The Trading Calendar maps the average behavior of the S&P 500 index by trading day of the year since the beginning of 1990. Are there particular calendar days of the year that are especially bad or good for U.S. stocks? Using daily closes for the S&P 500 index during 1/3/50-10/19/07, we find that... More...
Since 1990, the Federal Reserve Bank of Philadelphia has conducted a quarterly Survey of Professional Forecasters. The American Statistical Association and the National Bureau of Economic Research conducted the survey from 1968-1989. Among other things, the survey solicits from experts on the economy the probabilities of recession in each of the next four quarters. The "Anxious Index" is the probability of recession in the next quarter. When professional forecasters are relatively pessimistic (optimistic) about the economy, does the stock market go down (up) over the coming months? Using raw survey results and quarterly S&P 500 index data from the third quarter of 1968 through the second quarter of 2007 (156 surveys), we find that: More...
Whenever a trend in the dollar-euro exchange rate develops, the experts start theorizing. A weak dollar is good because U.S. exports boom and domestic employment rises. Or, a weak dollar is bad because capital flees the U.S., and import prices spur inflation. What does the state of the dollar, as indicated by the dollar-euro exchange rate, mean for U.S. stocks? "Theories" collide, so perhaps empirical data can enlighten. In this entry, we examine the relationship between the dollar-euro exchange rate and the behavior of the U.S. stock market over the short and intermediate terms. Specifically, using historical data from 5/1/02-10/15/07, we relate recent trends in the exchange rate to returns for the S&P 500 index over the next 5, 21 and 63 trading days. We find that: More...
Does the stock market react reliably and exploitably to the monthly announcements of the change in non-farm employment based on Bureau of Labor Statistics surveys of employers? To check, we examine the typical behavior of stocks during the five trading days before and the five trading days after release dates. Using the unrevised non-farm employment releases and contemporaneous daily S&P 500 index data for the period 2/94-9/07 (164 announcements), we find that... More...
With reversal of the easy lending practices of 2003-2005, U.S. home sales and homebuilder stock prices have fallen dramatically (as frequently and loudly reported in the media). Does the behavior of homebuilder stocks portend doom for the overall equity market? To check, we first assemble a simple measure of the performance of homebuilder stocks as the equally-weighted average monthly return for the stocks of Centex, DR Horton, Hovnanian, KB Homes, Lennar, Ryland and Pulte, starting with Centex and Pulte in August 1985 and adding the others as they are listed. Comparing these returns with monthly returns for the S&P 500 index data for 8/85-9/07 (266 months), we find that: More...
After reviewing our update of the relationship between crude oil price and overall stock market behavior, a reader requested a similar analysis of the relationship between crude oil price and an energy sector Exchange-Traded Fund (ETF) such as Energy Select Sector S&P Depository Receipts (XLE). The reader's hypothesis is that energy ETFs follow crude oil spot price fairly well. Comparing the weekly crude oil spot price for the U.S. with the weekly close for XLE for over the period 1/99-8/07, we find that... More...
Does the stock market offer a predictable pattern of returns around the ends of calendar quarters? Do funds deploy cash to bid stocks up before quarter ends to boost portfolio values at the end of reporting periods (with subsequent reversal)? Or, do fund liquidity needs tend to drive stock prices lower before ends of quarters? Is the end-of-quarter effect the same as the turn-of-the-month effect? To address these questions, we examine daily stock market returns from 10 trading days before to 10 trading days after the ends of calendar quarters. We also compare daily returns with those for turns of calendar months. Using daily closes for the S&P 500 index since 1/3/50, we find that... More...
Some market commentators cite the price of crude oil as an important indicator of future stock market behavior. Is expensive crude oil a sign of future inflation or a drag on aggregate corporate earnings, or is it a proxy for general economic strength? Does a local peak (valley) in the price of crude oil portend a falling (rising) overall stock market? Comparing the weekly crude oil spot price for the U.S. with the weekly level of the S&P 500 index for the period 1/97-8/07, we find that... More...
How do stocks behave in the few days around announcements of a change in the Federal Funds Rate (FFR)? Does evidence support the conventional expectation that a cut (boost) precipitates an immediate positive (negative) reaction by equities? To investigate, we analyze the historical behavior of the S&P 500 index from five trading days before through five trading days after the announcement dates for a change in the FFR during 1990-2006 (36 decreases and 31 increases). Using daily closing levels of the index, we find that... More...
Mark Hulbert's 9/5/07 column addresses the 9-to-1 up day event, a bullish technical signal publicized by Martin Zweig in a 1986 book. It occurs when at least 90% of daily NYSE volume belongs to advancing issues. When the signal occurs in multiples over short periods, as it has recently, prospects for equities are "quite bullish" according to Mark Hulbert. A reader comments and inquires:
"A statistician [David Aronson, author of Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals] confirms the significance of Zweig's original observation. I don't know whether he considered all possible confounding factors, such as low volume days, effect of externalities on the market, and others I can't think of. This analysis sounds like so much epidemiological research, finding associations but never proving causality. For example, in the decade of the 1980s, alternate papers found that coffee consumption (greater than three cups per day) is and is not associated with increased risk of cancer of the pancreas. How much credence do you place in Hulbert's article?"
Using S&P 500 index data for 1942-2006 (67 years), David Aronson finds an average return of about 5.2% in the 60 trading days after double 9-to-1 up days, significantly greater than the average return of about 1.1% during intervals of 60 trading days when there has not been such a signal. To follow up, we pose some questions to David Aronson and then consider strategies an investor might employ to exploit double 9-to-1 up day signals, as follows: More...
Does the Labor Day holiday, marking the end of summer vacations, signal any unusual return effects by refocusing U.S. stock investors on the market? By its definition, this holiday brings with it any effects from three-day weekends and the turn of the month. To investigate returns around Labor Day, we analyze the historical behavior of the S&P 500 index during the three trading days before and the three trading days after the holiday. Using daily closing levels for 1950-2006 (57 observations), we find that... More...
Suppose we take the current intermediate-term (notionally 3-9 month) stock market outlooks of the experts covered in Guru Grades and weight these outlooks according to current calculated guru forecast accuracies. Would the current accuracy-weighted aggregate opinion be bullish or bearish? Here's another update on weighting guru stock market outlooks. More...
Stock prices have recently fallen, and 13-week Treasury bill (T-bill) yields have plunged. We hypothesize that:
During a crisis, investors overreact in reallocating funds from risky assets (stocks) to safe ones (T-bills). Stock prices and T-bill yields consequently fall together. Once the crisis abates, investors correct their overreaction by moving funds back from T-bills to stocks. Stock prices and T-bill yields then rise together.
To test this model of investor behavior, we examine relationships between overall stock market returns and T-bill yield changes during and after dramatic declines in the T-bill yield for past and future intervals of 10, 21 and 63 trading days. Using daily closes for the S&P 500 index and T-bill yield from 1/4/60 through 8/20/07 (11,864 days when both traded), we find that: More...
When the market close is strong (weak), does it indicate pent-up buying (selling) demand? Should a trader follow the trend of the close the next day, position for a reversal or look for a better indicator? To investigate, we compare the position of the daily close for a broad market index relative to same-day high and low to the next-day return for the index. We also compare the five-day and ten-day average relative closes to the index return for the next five and ten days, respectively. Using daily high, low and close levels of the S&P 500 index for the period 7/15/83 (the earliest without obvious errors available) through 8/15/07 (6077 trading days), we find that: More...
Reader David Zaitzeff poses the following question:
"In the last several weeks, there have been several times when the Dow Jones Industrial Average (DJIA) was down a lot, and Asian stock markets followed it down the next day. How reliably do Asian stock markets follow sharp drops in the U.S. stock market?"
To answer this question, we first examine the overall relationship between the U.S. stock market (DJIA) and Asian stock markets (Hang Seng and Nikkei 225). Then, we focus on what happens in Asian stock markets the day after sharp drops in the U.S. market. Using daily closing levels of the DJIA, the Hang Seng index and the Nikkei 225 index for 12/31/86-8/9/07 (roughly 5300 trading days), we find that: More...
But the market is just unsafe at any speed... More...
But other people were forecasting even higher... More...
Predicting Risk analyzing stormy weather...
More...
Taking a break... More...
Reader Bob Tait of Houston suggested a review of the free Decision Moose asset allocation framework of William Dirlam. "Decision Moose is an automated framework for making intermediate-term investment decisions." Decision Moose focuses on asset class momentum, as augmented by monetary policy, exchange rate and interest rate indicators. Its signals tell followers when to switch from one index fund to another among nine encompassing a broad range of asset classes, including equity indexes for several regions of the globe. The trading system presented is a long-only approach that allocates 100% of funds to the index "having the highest probability of price appreciation." The site includes a history of switch recommendations since the end of August 1996. Mr. Dirlam provides background on the site and the Decision Moose framework via FAQs. To evaluate the framework, we assume that the 44 switches and trading returns are as described (out of sample, not backtested) and compare the returns to those for the S&P 500 index over the same trading intervals (with open positions closed as of 7/20/07). We find that: More...
Can investors beat the market by buying when a stock index crosses above a moving average and selling when it crosses below? In other words, do such crossovers and crossunders signal economically important market turning points? Using daily closes for the S&P 500 index for 1/2/90-7/17/07 (and 1/2/62-7/17/07 for one analysis), we find that: More...
Reader David Zaitzeff requested a test of the TradingMarkets 5% VIX rule, which states:
"Do not buy stocks (or the market) anytime the VIX is 5% below its moving average. Why? Because since 1989, the S&P 500 cash market has "lost" money on a net basis 5 days following the times the VIX has been 5% below its 10 day ma."
"Since 1989, whenever the VIX has been 5% or more above its 10 day ma, the S&P 500 has achieved returns which are better than 2 1/2 to 1 compared to the average weekly returns of all weeks."
David also asks whether one can improve the signal by using a 4% or 6% threshold rather than 5%, or by using a holding interval longer or shorter than five days. We first reproduce the results claimed by TradingMarkets, then investigate whether the signals are of economic value to traders, and finally test sensitivity of results to parameter changes. Using daily CBOE Volatility Index (VIX) and S&P 500 index data for 1/2/90-7/11/07 (4415 trading days), we find that: More...
When the dollar weakens, large capitalization U.S. firms benefit from their international footprints, generating substantial revenues around the globe in local currencies and converting those revenues into an increased number of dollars on their income statements. Investors should therefore shift toward (away from) large capitalization stocks when the dollar is weak (strong). To test this hypothesis, we compare the performance of the Dow Jones Industrial Average (DJIA) (representing large capitalization stocks) and the Russell 2000 Index (representing small capitalization stocks) as the dollar fluctuates against the euro. Using daily data since introduction of the euro in October 2003 (937 trading days), we find that: More...
Are Bollinger Bands valuable tools for discovering overbought/oversold conditions in the aggregate stock market? Can traders build trading strategies around them? To check, we analyze the historical behavior of three sets of Bollinger Bands around the 21-trading day (one month) simple moving average of the S&P 500 index. The three sets of bands correspond to 1.5, 2 and 2.5 standard deviations for the moving windows of analysis. When the daily price crosses above (below) the upper (lower) Bollinger Band, we designate that day a SELL (BUY) at the close, holding the position for the next 21 trading days. Using S&P 500 index daily closing levels for January 1950 through June 2007 (about 688 independent 21-trading day windows), we find that... More...
Reader David Zaitzeff inquired about the predictive powers of bullish and bearish engulfing candlesticks, which he defines as:
Bullish: A down day followed by an up day, with the latter having a higher intraday high and lower intraday low and closing in the top quarter of the daily range.
Bearish: An up day followed by a down day, with the latter having a higher intraday high and lower intraday low and closing in the bottom quarter of the daily range.
We test these signals on the S&P 500 index using average daily returns for each of the 20 trading days immediately after a signal. Using daily high, low and closing levels for the index from January 1962 (the earliest available with intraday data) through June 2007, we find that: More...
Is a bad week or month in the stock market an indicator of further immediate deterioration, a sign of lost mojo? Using weekly and monthly S&P 500 index closing levels since 1950 (2,998 weeks and 689 months), we find that: More...
A reader recently suggested that we might be able to improve the fit of the Real Earnings Yield (REY) Model by including a second order inflation effect. The model presently uses only a first order effect, the 12-month trailing inflation rate (either total inflation or core inflation) as derived from the 12-month change in the Consumer Price Index (CPI). We consider two second order effects:
Testing these effects with CPI data and monthly S&P 500 index closing levels for estimated or actual CPI release dates during January 1990 through June 2007 (210 months), we find that: More...
Both the academic community and practitioners generate large numbers of studies, formal and informal, analyzing and forecasting financial markets. In this blog, we offer an organization of financial markets research by topics such as The Value Premium and Buybacks and Secondaries. Are there other organizing principles that might convey a more fundamental understanding? Reflecting on the hundreds of studies we have reviewed and the limitations of this research with regard to practical application, here is another framework for thinking about financial markets research: More...
Reader David Zaitzeff inquired about the usefulness of James Altucher's QQQQ Crash Trade Triggers, which signals:
BUY PowerShares QQQ (QQQQ) when the daily close is more than 1.5 standard deviations below the average low over the past ten (trading) days, and
SELL at the next close that is higher than the BUY price or at the close after 20 (trading) days, whichever comes first.
In testing this scheme, we assume that any BUY must clear with a SELL before executing another BUY (multiple concurrent positions not allowed). In other words, our mechanical investor is all in or all out of the market. We assume that all BUYs and SELLs occur at closing prices. We also assume round trip trading costs of $20 and an initial stake of $100,000 to calculate trade returns and cumulative returns. Using QQQQ daily low and closing prices for 3/10/99 (the earliest available) through 6/13/07, we find that: More...
Reader Richard Beddard, editor of Interactive Investor, inquired about the relationship between home prices and stock prices, citing concern that weakness in UK and US residential real estate markets will adversely affect stocks. Does weakness in home prices portend a decline in the stock market? Using annual median home price data from RealEstateABC.com (1968-2004) and the National Association of Realtors (2004-2006) and contemporaneous annual S&P 500 index data for 1968-2006 (39 years), we find that: More...
Readers recently requested evaluations of two different retail investment managers. Our reviews involve simply putting the information the firms make available on their web sites into the context of broad stock market research. Our findings for the two firms are similar, as follows: More...
Reader David Zaitzeff notes that many experts are focused on the recent sharp rise in the 10-year Treasury note (T-note) yield, often asserting that such large positive yield shocks are bad for stocks. He asks what the historical data say about the relationship between short-term shocks in T-note yield and future stock returns. Using daily closing T-note yields and daily closing prices for the S&P 500 index since the beginning of 1990, we find that: More...
David Zaitzeff, a futures broker at Peregrine Financial Group, Inc. follows up on our review of possible three-day weekend anomalies:
"For regular five-day weeks, does Thursday tend to yield poor returns; and Tuesday, good returns? Also, there is conventional wisdom among traders about reversal Tuesdays. If Monday is up (down), what percentage of Tuesdays are down (up) and by how much?"
To investigate these questions, we examine returns and volatilities for the five trading days of the week during normal trading weeks, which we define as those having five trading days. In other words, we exclude abnormal weeks which have at least one day during which U.S. stock exchanges are closed all day. We do not exclude normal weeks adjacent to abnormal weeks. so a normal week occasionally follows or precedes a three-day weekend. Using daily closing prices for the S&P 500 index since the beginning of 1990, we find that: More...
Reader and blogger Bruce Hong asks: "Is there any data on what typically happens after a three-day weekend?" Some stock market experts claim that traders move to the sidelines before long weekends to avoid the risk of bad news while the market is closed. Assuming most traders are long, such selling might depress stock prices before extended weekends and elevate them afterward as traders re-enter positions. To test this hypothesis, we perform a modest event study examining returns and volatility for the three trading days before and after three-day weekends. Using daily closing prices for the S&P 500 index since the beginning of 1990, we find that: More...
Which stock market experts do investors/traders want to know about most often? To develop a partial answer to this question, we examine the search engine inputs to the activity log of cxoadvisory.com. Using the the top 100 key word searches for the site over the period 5/24/06-5/23/07, we find that: More...
The top ten reactions, from the bottom... More...
In our blog entry of 5/8/07, we found that the Chicago Board Options Exchange (CBOE) daily total exchange put-call ratio is not a useful predictor of future stock market behavior. A reader proposed that the International Securities Exchange (ISE) put-call data is a more focused measure of investor sentiment. "The ISE Sentiment Index (ISEE) is designed to show how investors view stock prices. The ISEE only measures opening long customer transactions on ISE. Transactions made by market makers and firms are not included in ISEE because they are not considered representative of market sentiment due to the often specialized nature of those transactions. Customer transactions, meanwhile, are often thought to best represent market sentiment because customers, which include individual investors, often buy call and put options to express their sentiment toward a particular stock." Is this alternative put-call data a useful indicator of future stock market behavior? Using ISEE historical data and contemporaneous daily S&P 500 index closing levels from 10/1/02 (the earliest ISEE data available) through 5/4/07, we find that: More...
Many stock market experts cite the the ratio of the volume of put options to the volume of call options (the put-call ratio) as an important indicator of investor sentiment, with a low (high) value indicating excessive optimism (pessimism). They assert, therefore, that this ratio is a useful contrarian indicator for future stock market behavior. Is it? In this entry, we test the value of the Chicago Board Options Exchange (CBOE) daily total exchange put-call ratio (put/call) as an indicator of future stock market returns. Using put/call data and contemporaneous daily S&P 500 index closing levels from 9/27/95 (the earliest put/call data available) through 5/4/07, we conclude that: More...
Using our traffic logs from 1/1/07-4/28/07, we have identified and listed below web sites that have sent a significant number of users here. We have excluded the following kinds of sites: search engines, Wikipedia pages, completely password-controlled and non-English. There are probably like minds at the originating sites. If these sites are unfamiliar, you might want to take a look. More...
Suppose we take the current intermediate-term (notionally 3-9 month) stock market outlooks of the experts covered in Guru Grades and weight these outlooks according to current calculated guru forecast accuracies. Would the current accuracy-weighted aggregate opinion be bullish or bearish? Here's another update on weighting guru stock mar
