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For complete reverse chronological listings of blog entries, see: External (Secondary) Research for summaries of research done by others; Original (Primary) Research for summaries of our own work; and, Reviews for a few discussions of books, web sites and products.
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:
Not being ECRI subscribers, we collect WLI data from various public web sources, such as DismalScientist. Note that ECRI releases a preliminary (revised) WLI with a one-week (two-week) lag.
The following chart depicts the raw data over the entire sample period. The shapes appear generally similar, but the degree to which WLI leads or lags stock market behavior is not obvious. Because stock market behavior is an input to the WLI, two series should display some similarity.
Does the alternative visualization of a scatter plot reveal more about the relationship between WLI and stocks?
The following scatter plot relates WLI and the S&P 500 index over the entire sample period, with an exponential best-fit curve. The data indicates that the two series have a general tendency to move up and down together. However, clustering of data suggests that the relationship sometimes adjusts (switches regimes). In other words, the sensitivity of aggregate stock valuation to composite economic outlook varies discontinuously over time.
Where might the regimes be within the sample period?
The next scatter plot breaks the stocks-WLI relationship into three regimes, each with a distinct best-fit exponential curve:
While all results indicate a positive relationship between stocks and WLI, it appears that investors tend to fall relatively out of step with the economic forecast when that forecast points to recession. The number of data points on this plot likely overstates reliability, because some inputs to WLI probably do not vary weekly.
For a more sensitive view of the relationship between WLI and stocks, we compare weekly changes.
The next scatter plot relates weekly change in the S&P 500 index to weekly change in WLI over the sample period. The Pearson correlation between these two series is 0.25, and the R-squared statistic 0.06, confirming that WLI and stocks tend to move in the same direction and suggesting that weekly changes in WLI explain 6% of the variation in contemporaneous stock market behavior.
But does WLI lead the stock market, or vice versa?
The final chart shows the Pearson correlations for various WLI-stocks lead-lag scenarios. As noted above, the coincident correlation (0 weeks lead-lag) between weekly changes in WLI and weekly changes in the S&P 500 index is 0.25. Offsetting the two series such that the weekly change in WLI leads the weekly change in the stock index by 1-13 weeks produces a series of correlations near zero. Offsetting such that weekly change in the stock index leads the weekly change in WLI by 1-13 weeks produces some small positive correlations, but all weaker than the coincident correlation. The argument that stocks lead WLI is a little stronger than the argument that WLI predicts stock market behavior, especially since ECRI releases WLI preliminary/revised readings with one-week/two-week lags.
In test whether WLI exhibits any cumulative and exploitable predictive power for stocks, we relate weekly change in WLI (as revised) to the change in the S&P 500 from initial release to four weeks later, from initial release to 13 weeks later and from initial release to 26 weeks later. The Pearson correlations for these three relationships are -.03, -.05 and -.03, respectively, suggesting no exploitable relationship between weekly changes in WLI and intermediate-term stock market behavior. If anything, these results suggest a slight (untradable) tendency for reversion.
In summary, ECRI WLI movements probably coincide with or slightly trail stock market behavior, offering no trading intelligence over the short or intermediate terms. This coincident/trailing connection may tend to break down during stock market declines.
See Blog Synthesis: The Economy and the Stock Market for other research on relationships between macroeconomic indicators and stock market behavior.
How strong and persistent are the effects of inflation rate and interest rate shocks on the stock market? In the May 2008 draft of their paper entitled "Inflation, Monetary Policy and Stock Market Conditions", Michael Bordo, Michael Dueker and David Wheelock quantify the extent to which various macroeconomic and policy shocks (industrial production, inflation, money supply growth, 10-year Treasury note yield and 3-month Treasury bill yield) explain the behavior of U.S. real stock prices and stock market conditions (trend) during the second half of the 20th century. Using monthly data for these variables and the S&P 500 index (as a proxy for stock prices) over the period August 1952 through December 2005, they conclude 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 forecasters. 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 93 aggregate measurements from the poll since inception, we find that... More...
Do the attention-grabbing past returns of high-flying stocks produce pre-earnings announcement buying frenzies? In the April 2008 version of their paper entitled "Limited Attention and the Earnings Announcement Returns of Past Stock Market Winners", David Aboody, Reuven Lehavy and Brett Trueman examine whether the limited time and resources of small investors explains a striking return pattern around the earnings releases of firms with extremely strong prior year price momentum. Using daily stock return data and earnings release/forecast news from the beginning of 1971 through the third quarter of 2005 for a broad sample of companies, they conclude that: More...
Does any broad measure of the state of the economy meaningfully predict financial market returns? In their May 2008 paper entitled "Time-Varying Risk Premia and the Output Gap", Ilan Cooper and Richard Priestley investigate the output gap as a direct link between future stock returns and economic fundamentals. They define output gap as the deviation of the log of industrial production from a trend constructed from both linear and quadratic components. Using unrevised industrial production data, aggregate U.S. stock market returns and Treasury bill yields (to calculate excess returns) for the period 1948-2005, they conclude that: More...
A reader asked about Robert Drach's "Basic Timing" Model Portfolio, which presents several hundred trades commencing 5/5/95. The objective of the portfolio is to demonstrate that market timing can beat the S&P 500 index, not to present an optimum trading strategy. The self-assessment of this portfolio as of 5/1/08 reports 370 closed positions with a 90.8% win rate. The average closed position yields a 9.19% gain over 202 days for an annualized return of 15.5%. The cumulative portfolio gain is 201%, compared to 199% for the DJIA and 170% for the S&P 500 index. These cumulative returns "...are reflective as to capital capture and market price of current holdings... They do not include cash dividends, interest earned on cash balances, transaction costs, or anything else." Robert Drach is publisher of the "Drach Weekly Research Report" (no web site). As explained in an article by Jon Markman, "he scales into stocks only when he believes there is a 95% likelihood of a successful result. ...He focuses on buying only from a master list of 80 large stocks [with decent earnings predictability] that hasn't changed much over the years." Do Robert Drach's results demonstrate market timing ability? We can answer this question approximately by measuring the correlation of his cash position (from his Cash Balance Ledger) with future stock market returns. Using this cash data and contemporaneous S&P 500 index data for the period 5/5/95-5/2/08, we estimate 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...
Do the big commodity futures speculators make money? If so, how? In their April 2008 draft paper entitled "Returns to Speculators in Commodity Futures Markets: A Comprehensive Revisit", Christof Sigl-Grüb and Dirk Schiereck investigate the performance and performance drivers for large speculators in 22 commodity markets over the last 15 years. Using aggregate position data for non-commercial traders (large speculators) from the weekly Commodity Futures Trading Commission Commitments of Traders (COT) reports and contemporaneous daily futures price data over the period 10/1/92 to 3/6/07, they conclude that: More...
Is the Fed Model an artifact of bad investor behavior (money illusion) or rational response? In the April 2008 draft of their paper entitled "Inflation and the Stock Market: Understanding the "Fed Model", Geert Bekaert and Eric Engstrom carefully re-examine mechanisms that might explain why the Fed Model "works." Using quarterly inputs for bond yield, S&P 500 index level and dividend yield, the economic forecast and a consumption-based measure of risk aversion spanning the fourth quarter of 1968 through 2007, they conclude that: More...
Robert Bendekgey of AlphaKing requested inclusion in the list of gurus at Guru Grades based on the service's market predictions. "The AlphaKing Research Project was started in 1999 to answer once and for all the age old question of what is the best way to risk one's capital in the stock market." This research culminated in the AlphaKing Trading Indicator (based on Nasdaq Composite index behavior), claimed to encapsulate the following conclusion: "Great fundamentals, when used in conjunction with specific targeted chart patterns, along with targeted beta leverage, while using active defensive and offensive money management techniques on individual stocks once entered, while timing portfolio entry and exit based on stock market trends has proven to provide maximum returns with the least amount of volatility..." Because this indicator is explicit and mechanical, we evaluate AlphaKing as a method and not as a guru. Using the record of the AlphaKing Trading Indicator and contemporaneous daily opening levels for the Nasdaq Composite index over the live out-of-sample period 3/27/06 through 3/28/08 (505 trading days), we find that... More...
We occasionally select for retrospective review an all-time "best selling" research paper from the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the June 2007 paper entitled "The Fundamentals of Commodity Futures Returns" (download count over 2,500) by Gary Gorton, Fumio Hayashi and Geert Rouwenhorst. Commodity futures are derivative, short-maturity claims on real assets. In this paper, the authors apply the theory of storage to investigate relationships between the physical inventories of these assets and the returns to traders in the associated commodity futures. Using monthly data for over 30 commodity futures and associated physical inventories as available between 1969 and 2006 and data from the weekly Commodity Futures Trading Commission Commitments of Traders (COT) reports, they conclude that: More...
