Frequency Analysis based on Monthly Comb
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It is obvious from inspection of price lines, that many seem to contain cycles that may persist in repeating for a long time. Through the years, technicians have expended much effort to measure and exploit these cycles. It would appear simple enough to do a frequency analysis on the time series. But the cycles or periods that seem so easy to see in the price data, have proven to be surprisingly difficult to measure by classical methods. The classical methods apply to stationary cycles of exactly regular period. We can easily remove the trends from historical price data to make the series stationary. However, the fluctuations seen in financial data are almost never exactly periodic, complicating most attempts to take advantage of these cycles. One factor in the behaviour of market fluctuations is "Anticipation". When speculators detect a cycle in prices, they will buy earlier before the peak, and sell earlier before the dip. This phenomena causes an increase in frequency, and eventually a breakup of the established cycle. Traditional frequency analysis methods such as the Fourier Transform, break down badly attempting to deal with these irregularities. Wilder estimated that there was an important period of about 28 trading sessions. The half cycle of this period (14 sessions) is a default factor in many of the technical indicators. We have found this to be a reasonable figure, even in today's markets, but there is significant variation between issues. Some companies just seem to have faster or slower cycles for one reason or another, and the indicators may be more accurate when fitted to the situation. The paradoxical condition of variable length periods forces the adoptation of some new forms of analysis. |
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Frequency from Monthly Comb Filter
Representative Cycle (Trading Sessions) = 31.00
Sawtooth = 51.11
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 16.68 | 27.00 | 16.00 | 13.00 % | | Low | 17.89 | 31.00 | 18.00 | 13.07 % |
| Recent High | Price | Recent Low | Price | Cycle | | Thursday, January 21, 2010 | 63.92 | | | 78 | | | Tuesday, September 08, 2009 | 44.18 | 41 | | Tuesday, September 29, 2009 | 55.32 | | | 25 | | | Friday, July 10, 2009 | 42.98 | 40 | | Monday, August 24, 2009 | 45.60 | | | 17 | | | Wednesday, May 13, 2009 | 43.70 | 46 | | Thursday, July 30, 2009 | 48.36 | | | 33 | | | Monday, March 09, 2009 | 44.03 | 30 |
Fourier Transform after Digital Filter M | Cycle Length | Fourier Amplitude | | 9 | 0.56 | | 11 | 0.41 | | 20 | 0.38 | | 14 | 0.31 | | 26 | 0.27 | | 24 | 0.17 | | 37 | 0.17 | | 31 | 0.15 | | 51 | 0.14 | | 39 | 0.14 | | 108 | 0.12 |
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Frequency Analysis based on Quarterly Comb
Frequency from Quarterly Comb Filter
Representative Cycle (Trading Sessions) = 39.00
Sawtooth = 43.48
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 49.31 | 84.00 | 39.00 | 19.83 % | | Low | 49.38 | 84.00 | 40.00 | 15.95 % |
| Recent High | Price | Recent Low | Price | Cycle | | | Tuesday, September 08, 2009 | 44.18 | 41 | | Thursday, July 30, 2009 | 48.36 | | | 77 | | | Friday, July 10, 2009 | 42.98 | 40 | | Thursday, April 09, 2009 | 50.83 | | | 39 | | | Wednesday, May 13, 2009 | 43.70 | 118 | | Thursday, February 12, 2009 | 48.83 | | | 109 | | | Thursday, November 20, 2008 | 35.72 | 77 | | Monday, September 08, 2008 | 53.62 | | | 58 |
Fourier Transform after Digital Filter Q | Cycle Length | Fourier Amplitude | | 9 | 0.37 | | 12 | 0.25 | | 14 | 0.19 | | 17 | 0.18 | | 20 | 0.17 | | 26 | 0.16 | | 158 | 0.15 | | 85 | 0.15 | | 137 | 0.15 | | 79 | 0.14 | | 89 | 0.13 |
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Frequency Analysis based on Yearly Comb
Representative Cycle (Trading Sessions) = 0.00
Sawtooth = 57.94
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 0.00 | 0.00 | 0.00 | 0.00 % | | Low | 0.00 | 0.00 | 0.00 | 0.00 % |
| Recent High | Price | Recent Low | Price | Cycle | | | Thursday, November 20, 2008 | 35.72 | 252 | | Monday, June 16, 2008 | 57.08 | | | 290 | | | Wednesday, November 21, 2007 | 40.39 | 212 | | Monday, April 23, 2007 | 61.45 | | | 289 | | | Monday, January 22, 2007 | 48.00 | 153 | | Monday, February 27, 2006 | 63.46 | | | 293 | | | Monday, June 12, 2006 | 46.74 | 284 | | Tuesday, December 28, 2004 | 60.76 | | | 246 |
Fourier Transform on Raw Closing Prices | Cycle Length | Fourier Amplitude | | 341 | 2.64 | | 293 | 2.18 | | 158 | 1.96 | | 9 | 1.92 | | 683 | 1.90 | | 512 | 1.70 | | 256 | 1.53 | | 228 | 1.43 | | 11 | 1.37 | | 137 | 1.28 | | 186 | 1.27 |
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| Breaking News: Wednesday, March 10, 2010: We have news on Philip Morris, ticker symbol MO. Some signs of an over-sold condition have become evident.
Also, there are breaking events concerning PNC Financial Services and NiSource Inc..
From the News Archive: (3/10/2010 ) Bad news came from CenterPoint Energy, Inc., Vulcan Materials Company, Best Buy Co., Inc., and Avon Products, Inc..
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Average Sawtooth based on Monthly Combo
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Average Sawtooth based on Bi-weekly Combo
A comparison of the average distance (in time) from each periodic high to to next periodic low, against the distance to the following high point, yields the Sawtooth Statistic. The mid-point, corresponding to a perfect sine wave, is 50 percent. Values less than this indicate the sell slope is steeper than the buy slope, while values over 50 percent show the opposite. The Sawtooth Statistic gives a clue to the general mood of the markets, functioning as a sort of sentiment indicator. The chart represents the sawtooth percentage of (approximately) monthly cycles over the past year, and of the (approximately) bi-weekly cycles, averaged over the past six months.
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