By Susan C. Walker, Elliott Wave International
November 12, 2007
When you're caught in the middle of a bad storm, you don't really care whether it's a tropical depression or a full-strength hurricane. You just know you're hanging on for dear life. The same idea applies to financial markets. When a market is trending up strongly, it's hard to tell whether it's just a bull market or a more dangerous financial mania.
The recent tremendous ride up for global and U.S. financial markets, including the Dow, looks and feels more like a mania than a mere bull, says Elliott Wave International analyst Peter Kendall. This distinction is important to recognize in the rising stage, because manias always result in a crash that takes them back beneath their starting point.
Kendall recently published his research into current financial manias throughout the world in SFO (Stocks, Futures and Options) magazine. The article, titled "Financial Manias and the Trade of a Lifetime," suggests an even more stunning finish for the current manias: "The speed and global scope of the unfolding credit crisis suggest that most of the fast-rising markets of the last decade will crash in unison," he writes.
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Editor's note: Elliott Wave International invites you to read the full five-page article with charts from the October 2007 SFO magazine by Elliott Wave International's Pete Kendall called "Financial Manias and the Trade of a Lifetime."
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As co-editor of The Elliott Wave Financial Forecast, Kendall searches for trends that help traders to move in and out of markets. By comparing other historic manias with the impressive rise of the DJIA since the late 1970s, he focuses on the skyscraper pattern that they all have in common. The four historical manias are the Dutch Tulip mania of the 1630s, the South Sea bubble of 1720, the U.S. stock crash of 1921-1932 and the dot.com bust of the 1990s and early 2000s. Once you can see the similarities, you will be better prepared to face the music when the crash comes. As Kendall writes, "once the belief that the markets will always rise becomes widespread, it actually signals the start of a price swing that tends to be a career-breaker for any trader who tries to oppose it."
He also discusses current manias, such as the Nikkei, which has yet to return to its start after a manic rise to its all-time high in December 1989, and the Dow, which reversed from its rise in 2000 but made a U-turn in 2002. The starting point for the Dow's mania as shown in the chart included in the article is at the 1000 level.
Kendall, who is also writing a book about financial manias, titled The Mania Chronicles, describes five telltale signs that help an investor to tell the difference between a regular bull market and a mania. It's a mania if:
1. There is no upside resistance, and rising prices seem to be perpetual.
2. Everyone in the market looks like an expert.
3. There is a flight from quality investments to riskier investments.
4. As financial bubbles pop in one area, they bubble up in others.
5. The crash after the peak takes back all the gains the mania made.
No. 5 can be viewed only with hindsight. But the first four signs provide essential clues to what's shaping up in the markets.
"By studying past mania experiences, traders can gain valuable insight into the collective emotions that drive their markets," writes Kendall. "It's possible to make significant money in the advancing stages of a mania with no knowledge of its existence. But there is nothing like recognizing a mania for what it is in real time to help a trader keep those gains and deal with the relentless crash after it peaks."
In the last part of the SFO article, he asks the key question, Are we at the peak yet? Find out his answer by reading the whole article for yourself.
Susan C. Walker writes for Elliott Wave International, a market forecasting and technical analysis company. She has been an associate editor with Inc. magazine, a newspaper writer and editor, an investor relations executive and a speechwriter for the Federal Reserve Bank of Atlanta. Her columns also appear regularly on FoxNews.com.
Tuesday, November 13, 2007
Friday, November 9, 2007
Linear Regression Changes In Trends
The previous post covered using a linear regression line with standard deviation channels. This is helpful to define the trend and to statistically define where the underlying stock or index is in relation to the trend. Below is a three day chart with the same linear regression and standard deviation lines used previously.
MER - Merrill Lynch & Co.(click charts to enlarge)
In this chart the red line running up the center is the linear regression line(377 period). The blue lines are one standard deviation above and below the regression line. The yellow lines represent two standard deviations. Two standard deviations should include 95% of prices. Any price outside this area should be looked at as an extreme in relation to the trend, and should revert back to the mean. If prices stay outside these areas, it signals a change in trend.
As can be seen, one standard deviation acted as support for most prices. Recently prices broke through this area and went straight to the two standard deviation line, where prices paused before breaking strongly lower. This is a great visual picture of the change in the state of affairs for companies with exposure to the sub-prime lending issues. Below is the same chart of Merrill Lynch except it is a daily chart as opposed to the three day chart.
MER - Merrill Lynch & Co.
The daily chart shows more volatile price movement. The three day chart takes some of the noise out of the price movement and smooths the data. The daily chart is helpful for looking for entry points for those who trade more actively.
Below is a chart of Roper Industries Inc. It might look like a pretty boring chart, but is one that has been very profitable.
ROP - Roper Industries Inc.
Applying linear regressions to Exchange Traded Funds can be a helpful tool in identifying leaders. Below are charts of the XLE Energy ETF and the XLB Basic Materials ETF.
XLE
XLB
MER - Merrill Lynch & Co.(click charts to enlarge)
In this chart the red line running up the center is the linear regression line(377 period). The blue lines are one standard deviation above and below the regression line. The yellow lines represent two standard deviations. Two standard deviations should include 95% of prices. Any price outside this area should be looked at as an extreme in relation to the trend, and should revert back to the mean. If prices stay outside these areas, it signals a change in trend.As can be seen, one standard deviation acted as support for most prices. Recently prices broke through this area and went straight to the two standard deviation line, where prices paused before breaking strongly lower. This is a great visual picture of the change in the state of affairs for companies with exposure to the sub-prime lending issues. Below is the same chart of Merrill Lynch except it is a daily chart as opposed to the three day chart.
MER - Merrill Lynch & Co.
The daily chart shows more volatile price movement. The three day chart takes some of the noise out of the price movement and smooths the data. The daily chart is helpful for looking for entry points for those who trade more actively.
Below is a chart of Roper Industries Inc. It might look like a pretty boring chart, but is one that has been very profitable.
ROP - Roper Industries Inc.
Applying linear regressions to Exchange Traded Funds can be a helpful tool in identifying leaders. Below are charts of the XLE Energy ETF and the XLB Basic Materials ETF.
XLE
XLB
Tuesday, November 6, 2007
Smoothing Data and Using Linear Regressions
Linear regression analyzes the relationship between two variables, X and Y. For each subject (or experimental unit), you know both X and Y and you want to find the best straight line through the data. In some situations, the slope and/or intercept have a scientific meaning. In other cases, you use the linear regression line as a standard curve to find new values of X from Y, or Y from X.
In most instances when it comes to trading it is best to keep things as simple as possible. It is possible to write intricate formulas for analyzing and back-testing data with linear regressions. Through personal experience it seems best to focus on the time frame or the length of the linear regression and the overall slope of the regression line. Below is a chart of the S&P 500 with a longer term linear regression line. This regression line is shown as the red straight line that bisects the prices over the past 377 days. On either side of this red line are lines which show one standard deviation (blue lines) and two standard deviations (yellow lines). These lines run parallel to the linear regressions and act as channels.
S&P 500 Index
This is a longer term view of the market, but it does help in showing when the market is at mathematical extremes. It can help in knowing when not to fight a trend and when to expect support to possibly help adding to a position. It is important to note that the entire slope of the linear regression is positive. Creating long positions when the market is 2 standard deviations above this line could prove to be positive, but looking for better entries on pull-backs to the regression line or to the one standard deviation line could be significantly safer.
The chart below further smooths the data by using a three day chart. This is a custom time frame that is longer than a daily chart, but is shorter than a weekly chart. When using the 3day chart, most of the data will stay within one standard deviation of our linear regression line.
S&P 500 Index 3 Day Chart
Looking back to the late 90's, it is possible to see how the market reacted to these levels as the trend changed. This chart below is a three daily chart with the same linear regression line.
S&P 500 Index 1997-2002
In most instances when it comes to trading it is best to keep things as simple as possible. It is possible to write intricate formulas for analyzing and back-testing data with linear regressions. Through personal experience it seems best to focus on the time frame or the length of the linear regression and the overall slope of the regression line. Below is a chart of the S&P 500 with a longer term linear regression line. This regression line is shown as the red straight line that bisects the prices over the past 377 days. On either side of this red line are lines which show one standard deviation (blue lines) and two standard deviations (yellow lines). These lines run parallel to the linear regressions and act as channels.
S&P 500 Index
This is a longer term view of the market, but it does help in showing when the market is at mathematical extremes. It can help in knowing when not to fight a trend and when to expect support to possibly help adding to a position. It is important to note that the entire slope of the linear regression is positive. Creating long positions when the market is 2 standard deviations above this line could prove to be positive, but looking for better entries on pull-backs to the regression line or to the one standard deviation line could be significantly safer.
The chart below further smooths the data by using a three day chart. This is a custom time frame that is longer than a daily chart, but is shorter than a weekly chart. When using the 3day chart, most of the data will stay within one standard deviation of our linear regression line.
S&P 500 Index 3 Day Chart
Looking back to the late 90's, it is possible to see how the market reacted to these levels as the trend changed. This chart below is a three daily chart with the same linear regression line.
S&P 500 Index 1997-2002
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