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Putting Recent Volatility into Historical Perspective

(Guest Commentary By Bill Rempel – April 3, 2008)

Dear Subscribers and Readers,

For those who had wanted to learn more about individual stocks, the art of stock selection, and model-based trading/investing, it is again time to see what one of our regular guest commentators, Bill Rempel, has to say.  Bill is a prolific writing on the stock market and individual stocks and is the author of a very active market blog at: http://billrempel.com (“The Rempel Report”).

In this commentary, Bill is going to put the current volatility in the stock market (namely the Dow Industrials and the S&P 500) in historical perspective – as well as discuss the predictive value of such volatility.  There are many charts and statistics in this commentary, but I assure you that this would be a worthwhile read.  Without further ado, following is a biography of Bill:

Bill Rempel (aka nodoodahs) is an active poster on the MarketThoughts forum as well as a few others around the web. Bill is a regular, monthly guest commentator on our website (see “Selecting Municipalities for Investment” for his last guest commentary). Bill graduated from Caddo Magnet High School (a high school for nerds) back in 1985 and proceeded to learn the hard way when he drank his way out of a scholarship to Tulane later that year. After a few years of sweating for a living, he decided to go back to school, and graduated from LSU-Shreveport in 1995 with a Bachelors in Mathematics - all the while working the overnight shift stocking shelves in a grocery store.

Post-college, Bill has been in the P&C insurance industry as an actuary, product manager, and pricing manager. Bill and his wife Millie are amateur investors with a variety of holdings, but they prefer to buy and hold value investments. In typical "value" style, they live cheap, driving old cars and preferring to save or invest instead of buying fancy "stuff."

Disclaimer: This commentary is solely meant for education purposes and is not intended as investment advice.  Please note that the opinions expressed in this commentary are those of the individual author and do not necessarily represent the opinion of MarketThoughts LLC or its management.


I don't know about y'all, but I haven't been able to read much market commentary without coming across somebody talking about how VOLATILE the markets have been in 2008.  Like, it's a shock!  Oooh, markets are volatile!  Scary!  It made me wonder just how the recent action stacks up on a historical basis, and I decided to share that research today.

There are just a couple of definitions I need to present before I dive in; it's a bit chart- and table-heavy, so this will help. 

  • I will refer to the Year Ending First Quarter, or "YrEnd1Q," to mean the 12 months ending with March 31 of the year listed.  For example, the data point for 1988 is the 12 months ending March 1988, so that "1988 YrEnd1Q" data point includes the 1987 crash.  I did it this way so that we can put the last twelve months in perspective, compared to other full years.

  • I refer to the standard deviation of daily percentage returns in the index as "DailyStDev."  The Aggie Stat Notes may help if you need a refresher.  By taking the standard deviation of daily percentage returns, I can equalize different years.

  • The percentage of days in the year, for which the index moved 2% or more from close to close, either up or down, is labeled "2%Days."  Those big 200-point Dow days in modern 12K Dow levels will be compared in percentage terms to big 2% movers of the past.

  • The "EZ Trend" is based on the 100-day and 180-day Exponential Moving Average, applied to the index.  If the shorter moving average is above the longer moving average, the EZ Trend is UP and the market is Bullish, and vice versa.  Long-term readers are familiar with this simple, slow market-timing concept.

Now that the definitions are out of the way, it's time to charge into the analysis.

During the year ending March 31 of 2008 (YrEnd1Q 2008), the S&P 500 had an average daily percentage standard deviation (DailyStDev) of 1.20%, and the percentage of days where the index moved 2% or more in either direction (2%Days) was 11.16%.  For the Dow Jones Industrials, these numbers were 1.10% and 9.20%, reflecting the fact that crisis was in financial stocks, which are light in the Dow.  How does this compare to previous years?

S&P 500 Index historic average daily percentage standard deviation and the percentage of days where the index moved 2% or more in either direction

In the history I have for the S&P 500, going back to 1950, the most recent year ranked 8th.  Fairly impressive.  But in the history of the Dow from 1901, it's nowhere near as impressive. 

Dow Jones Industrials historic average daily percentage standard deviation and the percentage of days where the index moved 2% or more in either direction

There were 29 other years with higher daily percentage standard deviations, and most of them had a much higher percentage of days with 2% moves in either direction.  Would you have hated, or loved, to trade in the early 1930s?  Would you have checked your account every 15 minutes online (if you could have, back then)?

Because of its longer history, I will focus on the Dow Industrials, but the DailyStDev and 2%Days in the Dow and S&P (during the period when they both existed) have R-Squareds of 96.3% and 94.5% to each other (Aggie Stat Notes), so they're very comparable.

Dow Industrials - Daily Standard Deviations of Percentage Movement 

Dow Industrials - Percentage of 2% Days, Either Up or Down 


It's also pretty plain to see that the two measures of volatility are fairly equivalent.  Indeed, the R-Squared between DailyStDev and 2%Days is 93.9% for the Dow since 1901, and 87.8% for the S&P 500 since 1950.

The upshot of this analysis is that the volatility we've just seen, over the last 12 months, isn't really all that bad, comparatively speaking.  It looks bad only because we don't have a good historical perspective.

There is also some truth to the platitude that "bear markets are chaotic," because if we define a bear market as a period where the EZ Trend is DOWN, we can see that there's a negative correlation, not especially strong, between the EZ Trend and the volatility of the market.  Years in which the majority of the time had EZ Trend UP tend to have fewer extremes of daily price swings, and vice versa.

R-Square to PosEZtrend 15.50%
Dow Jones Industrial Average
YrEnd1Q PosEZtrend DailyStDv 2%Days
1901 0.00% 0.94% 4.20%
1902 43.50% 1.19% 6.10%
1903 10.00% 0.78% 2.70%
1904 0.00% 1.30% 13.70%
1905 70.90% 0.89% 2.30%
1906 100.00% 0.97% 5.60%
1907 86.40% 1.12% 5.30%
1908 0.00% 1.21% 11.20%
1909 89.00% 0.83% 2.30%
1910 88.10% 0.78% 2.70%
1911 0.00% 0.87% 4.70%
1912 30.40% 0.64% 2.00%
1913 78.60% 0.69% 1.30%
1914 15.00% 0.66% 1.00%
1915 52.40% 1.04% 4.70%
1916 98.00% 1.19% 10.20%
1917 89.70% 1.19% 7.30%
1918 0.00% 1.23% 10.60%
1919 69.70% 0.81% 2.00%
1920 87.50% 1.32% 12.50%
1921 0.00% 1.09% 6.00%
1922 33.00% 0.89% 3.70%
1923 100.00% 0.76% 1.30%
1924 42.50% 0.86% 4.00%
1925 78.40% 0.80% 2.70%
1926 100.00% 0.90% 4.00%
1927 87.00% 0.76% 1.70%
1928 100.00% 0.74% 1.00%
1929 100.00% 1.16% 7.90%
1930 62.70% 2.20% 16.90%
1931 0.00% 1.97% 24.50%
1932 0.00% 3.13% 43.70%
1933 0.00% 3.32% 43.80%
1934 90.80% 2.42% 28.10%
1935 63.10% 1.30% 9.30%
1936 100.00% 0.93% 3.60%
1937 100.00% 0.92% 3.70%
1938 34.70% 1.85% 19.00%
1939 64.80% 1.53% 17.30%
1940 57.30% 1.16% 7.00%
1941 12.90% 1.25% 6.30%
1942 17.60% 0.82% 2.00%
1943 47.50% 0.70% 1.00%
1944 100.00% 0.63% 1.00%
1945 100.00% 0.51% 0.00%
1946 100.00% 0.82% 1.40%
1947 43.60% 1.10% 6.40%
1948 47.90% 0.72% 1.40%
1949 52.50% 0.73% 1.80%
1950 57.40% 0.55% 0.00%
1951 100.00% 0.91% 3.20%
1952 100.00% 0.59% 0.00%
1953 100.00% 0.45% 0.00%
1954 50.80% 0.54% 0.40%
1955 100.00% 0.67% 2.40%
1956 100.00% 0.78% 1.60%
1957 74.50% 0.67% 0.00%
1958 34.40% 0.80% 3.20%
1959 76.80% 0.58% 0.40%
1960 98.80% 0.66% 0.40%
1961 24.30% 0.66% 0.40%
1962 100.00% 0.55% 0.00%
1963 30.30% 1.01% 4.00%
1964 100.00% 0.55% 0.80%
1965 100.00% 0.40% 0.00%
1966 100.00% 0.52% 0.40%
1967 13.10% 0.76% 0.80%
1968 82.10% 0.59% 0.00%
1969 88.80% 0.60% 0.90%
1970 23.50% 0.70% 0.40%
1971 32.20% 0.93% 4.30%
1972 85.80% 0.72% 0.80%
1973 100.00% 0.65% 0.00%
1974 7.90% 1.20% 8.70%
1975 0.00% 1.45% 18.30%
1976 96.50% 0.98% 4.30%
1977 90.90% 0.69% 0.40%
1978 0.00% 0.68% 0.40%
1979 34.00% 0.91% 2.40%
1980 76.30% 0.82% 3.60%
1981 76.60% 0.96% 4.00%
1982 40.70% 0.83% 3.20%
1983 53.50% 1.20% 9.10%
1984 99.60% 0.83% 1.60%
1985 55.20% 0.85% 3.60%
1986 100.00% 0.70% 2.00%
1987 100.00% 0.99% 6.70%
1988 63.40% 2.24% 18.50%
1989 45.60% 0.95% 4.80%
1990 100.00% 0.93% 3.20%
1991 60.20% 1.08% 7.20%
1992 100.00% 0.80% 2.40%
1993 100.00% 0.66% 0.80%
1994 100.00% 0.56% 1.20%
1995 100.00% 0.64% 0.80%
1996 100.00% 0.66% 1.60%
1997 100.00% 0.77% 2.40%
1998 100.00% 1.17% 7.50%
1999 89.70% 1.31% 10.70%
2000 100.00% 1.14% 9.10%
2001 52.60% 1.24% 10.80%
2002 15.40% 1.29% 8.90%
2003 18.60% 1.69% 23.70%
2004 78.30% 0.82% 2.40%
2005 100.00% 0.65% 0.00%
2006 96.40% 0.64% 0.80%
2007 100.00% 0.65% 1.60%
2008 83.20% 1.10% 9.20%

Although that fact can give us comfort; that the volatility increases when EZ Trend is down, it's not really predictive of anything.  Can a recently-passed year of high or low volatility tell us something about the returns for next year?

Dow Industrials - Next Year's Return by This Year's Percentage of 2% Days 

Um, nope.  Not even for the more recent period covered by the S&P 500?

S&P 500 - Next Year's Return by This Year's Percentage of 2% Days 

Nah.  Regardless of what the permabears may say about the recent volatility, it ain't the harbinger of doom or Hell on Earth, it's just … volatility.

To recap:

  • The recent market volatility, while unpleasant, isn't unusual.  This kind of thing happens in the stock market.

  • Periods when the EZ Trend is DOWN ("bear markets?") tend to have higher volatility, but the correlation isn't perfect.

  • Current volatility doesn't give us any real clue as to whether the long-term movement of the market will be up or down.  To use volatility for that, we need to include sentiment analysis as well.

 

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