Blog - Investing Notes

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.

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

The Latest

July 2, 2009 - Regulatory Activity and Stock Returns

How does the U.S. Securities and Exchange Commission's (SEC) level of spending relate to U.S. stock market returns? Are expenditures reactive, growing after bear markets? Does higher spending boost investor confidence and subsequent stock returns? To investigate, we relate SEC outlays and the S&P 500 Index by federal fiscal year (October through September). Using agency outlay data for fiscal years 1990 through 2010 (estimates for the final two years) and S&P 500 closes for fiscal years 1986 through 2008, we find that:

The following chart plots for comparison SEC outlays and the S&P 500 Index for federal fiscal years since 1990 for SEC outlays and since 1986 for the stock index. SEC outlays for fiscal years 2009 and 2010 are estimates. Visual inspection offers a hint that SEC spending tends to ramp up after bear markets and moderate after bull markets.

For a closer look, we relate annual changes in SEC outlays and S&P 500 Index annual returns for various lead-lag scenarios.

The next chart plots Pearson correlations between the change in SEC outlays and the return on the S&P 500 Index by fiscal year based on the above data for lead-lag relationships ranging from SEC outlays lag stock returns by four years to SEC outlays lead stock returns by four years. Results suggest a negative correlation between stock returns and spending changes one to three years later. In other words, when the stock market declines (advances), SEC spending tends to rise (decline or flatten) over the following one to three years. There is no convincing relationship between SEC spending changes and same-year or future-year stock returns.

How convincing is the two-year lag scenario?

The following scatter plot depicts the relationship between S&P 500 Index returns and SEC spending changes two years later based on the above data. The plot is somewhat well-organized but the sample is small. The R-squared statistic for the relationship is 0.15, indicating that the stock market return for a given year explains 15% of the change in SEC fiscal year spending two years hence.

In summary, very limited evidence suggests that regulatory activity reacts to stock market returns with a lag of one to three years and has little or no effect on future stock market returns.

For related research, see Blog Synthesis: Politics and the Stock Market.

July 1, 2009 - Update: End-of-Quarter Effect

Does the U.S. stock market offer a predictable pattern of returns around the ends of calendar quarters? Do funds deploy cash to bid stocks up at quarter ends to boost portfolio values at the end of reporting periods (with subsequent reversals)? Or, do they sell stocks to raise cash for redemptions? Is the end-of-quarter effect the same as the turn-of-the-month effect? To investigate, we examine average daily stock market returns from 10 trading days before to 10 trading days after the ends of calendar quarters. We also compare these returns to those for turns of all calendar months. Using daily closes for the S&P 500 index for January 1950 through June 2009, we find that: More...

June 30, 2009 - Update: Measuring the Size Effect with Capitalization-based ETFs

Do popular capitalization-based exchange-traded funds (ETF) confirm the existence of an exploitable size effect? To investigate, we compare the difference in returns (small minus large) for the following matched pair of small-large ETFs:

iShares Russell 2000 Index (Smallcap) Index (IWM)
iShares Russell 1000 (Largecap) Index (IWB)

Using monthly adjusted closing prices (incorporating dividends) for these ETFs during May 2000 (the earliest month available for both) through June 2009 (110 months), we find that: More...

June 29, 2008 - Update: Measuring the Value Premium with Style-based ETFs

Do popular style-based exchange-traded funds (ETF) confirm the existence of an exploitable 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 adjusted closing prices (incorporating dividends) for these ETFs during September 2001 (the earliest quarter available for IWP-IWS) through June 2009 (94 months), we find that: More...

June 26, 2009 - Update: Biotech Seasonality?

In an August 2004 article entitled "Time is Right for These 7 Biotechs", Jim Jubak states: "...in most years, biotechs decline in the spring as investors anticipate a summer hiatus in the conferences where new clinical results are announced. They rally in the fall as the conference schedule and the volume of news increases." Is this conventional wisdom correct? To check, we examine the behavior of the AMEX Biotechnology Index (BTK) across the calendar year. Using monthly closing levels for BTK from its inception in January 1995 through most of June 2009 (14.5 years), and contemporaneous monthly returns for the S&P 500 Index for detrending, we find that: More...

June 25, 2009 - An Annual Worldwide Optimism Cycle (Sell in May)?

Does the conventional wisdom to "sell in May," with the average stock return during November-April far exceeding that for May-October, work for the world equity market? If so, why? In the November 2005 version of his paper entitled "The Optimism Cycle: Sell in May", flagged by a reader, Ronald Doeswijk examines the hypothesis that this seasonal pattern derives from an annual optimism cycle. Using monthly return data for markets, sectors and Initial Public Offerings (IPO) over the period 1970 through 2003 (34 years), he concludes that: More...

June 24, 2009 - Update: Trading Around Option Expiration Days

Does recent (post-1980s) data suggest any stock market return anomalies around the equity option expiration (OE) date (third Friday of each month)? To investigate, we examine close-to-close returns from five trading days before to five trading days after OE. Using daily closing prices for the S&P 500 index for January 1990 through June 2009 (233 OEs), we find that: More...

June 23, 2009 - Update: Any Recent Day-of-the-Week Anomalies?

Does recent (post-1980s) data suggest any day-of-the-week stock market return anomalies? To investigate, we examine close-to-close returns for the five trading days of the week during normal trading weeks (those having five trading days). In other words, we exclude 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 (847 normal weeks), we find that: More...

June 22, 2008 - Update: Stock Market Behavior Around the Mid-year Point

The middle of the year might be a time for funds to dress their windows and investors to review and revise portfolios. The 4th of July celebration might engender optimism among U.S. investors. Is there a reliable pattern to daily stock market returns around mid-year? To check, we analyze the historical behavior of the S&P 500 index from five trading days before through trading days after both the last trading day of June and the last trading day before the 4th of July. Using daily closing levels of the index for 1950-2008 (59 years), we find that... More...

June 18, 2009 - Do Investors Prefer an Idle Congress?

Our blog entry of 3/25/05 summarizes research finding that the U.S. stock market generates higher and less volatile when Congress is not in session. Is this finding robust to inclusion of recent data? To check, we examine average daily returns when the U.S. Senate is in session and out of session based on open-to-open market data (for alignment of daily Senate activity to potentially related daily trading). Using Senate in session data, party in power data and daily opening levels of the S&P 500 Index for 1978 through 2009 (partial through June 12), we find that... More...

June 17, 2009 - Inflation Forecast Update

We have updated the Inflation Forecast to incorporate actual data for May 2009. The actual total and core inflation rates for May 2009 are slightly lower than forecasted values, but the differences are so small that they do not materially change the projections of the Real Earnings Yield Model as shown at Stock Market Status (extended to June 2010).

June 16, 2009 - Revisiting Party in Power and Stock Returns

Past research relating U.S. stock returns to the party holding the Presidency mostly concludes that Democratic presidents are better for the stock market than Republican presidents. However, the President shares the power conferred by the electorate with Congress. Does historical data confirm than Democratic control of Congress is also better for stock returns than Republican control of Congress? Is control of the smaller Senate more decisive than control of the House of Representatives? To check, we relate annual stock returns to various combinations of party control of the Presidency, the Senate and the House of Representatives. Using party in power data and annual levels of the S&P 500 Index for 1950 through 2009 (partial), we find that... More...

June 12, 2009 - A Better Three-Factor Model?

The widely used Fama-French three-factor model explains stock returns based on aggregate market return, firm size (small versus large) and firm valuation (value versus growth). Since the Fama-French model does not explain the stock price momentum effect, researchers and investors often add momentum as a fourth factor to predict future stock returns. Might some other small set of factors (three) outperform the Fama-French model in explaining stock returns, obviating the need for a momentum factor and accounting for other stock return anomalies as well? In their June 2009 paper entitled "A Better Three-Factor Model That Explains More Anomalies", Long Chen and Lu Zhang argue that a three-factor model based on aggregate market return, level of firm investment relative to assets (low versus high) and return on assets (high versus low) substantially outperforms the Fama-French model in explaining stock returns. Using a wide range of firm and stock data for a broad sample of stocks over the period 1972-2006 to test this model, they conclude that: More...

June 11, 2009 - Is There a Best SMA Calculation Interval for Long-term Crossing Signals?

Is a 10-month simple moving average (SMA) the best SMA for long-term crossing signals (to exploit return momentum by capturing part of long uptrends while avoiding part of long downtrends)? If not, is there some other optimum SMA calculation interval? To check, we compare the average monthly returns and return variabilities from SMA crossing signals generated by SMA calculation intervals ranging from 3 to 48 months, as applied to the Dow Jones Industrial Average (DJIA). Using monthly DJIA closes for January 1930 through May 2009 and monthly yields for 3-month Treasury bills (T-bills) for January 1934 through May 2009, we find that: More...

June 10, 2009 - The Most Intriguing Gurus?

Which stock market experts intrigue investors and traders the most? For insight, we examine CXOadvisory.com log files for visits derived from web search engines based on search phrases associated with specific experts. We consider the top 50 search phrases for each of the last three years and consolidate similar searches (e.g., "jim jubak" and "jubak" or "ken fisher" and "fisher investments"). We also normalize results for each year by expressing relative interest in experts by dividing the number of searches for each by the total number of searches for all experts. Using the top 50 search phases arriving at CXOadvisory.com for each of 2007, 2008 and 2009 (to date), we find that: More...

June 8, 2009 - Update: Stock Market Valuation Ratio Trends

To determine whether the stock market is expensive or cheap, some experts use aggregate valuation ratios, either trailing or forward-looking, such as price-earnings ratio (P/E) and price-dividend ratio. Operating under a belief that such ratios are mean-reverting, most imminently due to movement of stock prices, these experts expect high (low) future stock market returns when the these ratios are low (high). Where are the ratios now? Using the S&P 500 index close for 6/5/09, actual and forecasted earnings and dividend data from Standard & Poor's as of 6/3/09 and our own Earnings Forecast as of 6/5/09, we find that: More...

June 4, 2009 - Performance Trend for Value Line's Timeliness Ranking

A reader observed and suggested:

"When I first started paying attention to markets in the 1980s and 1990s, one frequently cited argument against market efficiency was the Value Line anomaly - the fact that stocks with their best timeliness ranking had extraordinary returns over a long period. You can still find charts showing how well Group 1 has done versus Group 5 over a multi-decade period, but it seems that there has not been much cumulative performance separation among groups in recent years. Some raw data on their site shows that the predictive power of the ranking system seems to be missing from about 2000 onward. It might be interesting to look at what was once a widely discussed method of potential market outperformance."

The Value Line Timeliness Ranking System sorts stocks into five groups, with Group 1 (5) expected to exhibit the strongest (weakest) future performance. Value Line summarizes annual performance data for Groups 1 through 5 based on assumptions of both weekly and annual group re-sorting. Because the trading frictions of weekly re-sorting are likely high and difficult to estimate, we focus on performance by group for annual re-sorting. Specifically, we measure the Group 1 annual returns minus the Group 5 annual returns and the Group 2 annual returns minus the Group 4 annual returns. If the ranking system is persistently reliable, both sets of differences should be persistently positive, with the differences for the first set generally larger than those for the second set. Using the annual return data stated by Value Line for 1965 (partial year) through 2008 (nearly 44 years), we find that... More...

June 3, 2009 - Update: Blogger Sentiment Analysis

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 20 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 135 measurements from the poll since inception, we find that... More...