Frequency Analysis based on Monthly Comb
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Even a casual examination of historical price lines seems to reveal cycles or regular short term fluctuations that continue repeating. 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) = 28.00
Sawtooth = 51.97
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 16.48 | 30.00 | 24.00 | 18.99 % | | Low | 16.78 | 30.00 | 32.00 | 33.93 % |
| Recent High | Price | Recent Low | Price | Cycle | | Wednesday, October 13, 2010 | 4.96 | | | 28 | | | Thursday, September 23, 2010 | 4.52 | 29 | | Thursday, September 02, 2010 | 5.10 | | | 86 | | | Thursday, August 12, 2010 | 2.78 | 19 | | | Friday, July 16, 2010 | 3.47 | 28 | | Monday, May 03, 2010 | 6.80 | | | 49 | | | Monday, June 07, 2010 | 4.67 | 34 | | Monday, February 22, 2010 | 8.35 | | | 31 |
Fourier Transform after Digital Filter M | Cycle Length | Fourier Amplitude | | 14 | 0.55 | | 18 | 0.45 | | 21 | 0.36 | | 24 | 0.32 | | 26 | 0.29 | | 29 | 0.22 | | 39 | 0.21 | | 31 | 0.20 | | 33 | 0.19 | | 35 | 0.16 | | 53 | 0.16 |
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Frequency Analysis based on Quarterly Comb
Frequency from Quarterly Comb Filter
Representative Cycle (Trading Sessions) = 86.00
Sawtooth = 40.10
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 49.18 | 86.00 | 46.00 | 29.38 % | | Low | 49.58 | 71.00 | 54.00 | 40.39 % |
| Recent High | Price | Recent Low | Price | Cycle | | Thursday, September 02, 2010 | 5.10 | | | 222 | | | Thursday, August 12, 2010 | 2.78 | 176 | | | Monday, November 30, 2009 | 9.05 | 61 | | Thursday, October 15, 2009 | 13.15 | | | 87 | | | Wednesday, September 02, 2009 | 8.90 | 40 | | Friday, June 12, 2009 | 12.35 | | | 107 | | | Wednesday, July 08, 2009 | 9.45 | 85 | | Thursday, January 08, 2009 | 13.45 | | | 159 |
Fourier Transform after Digital Filter Q | Cycle Length | Fourier Amplitude | | 12 | 0.32 | | 14 | 0.32 | | 18 | 0.24 | | 205 | 0.20 | | 24 | 0.20 | | 21 | 0.18 | | 53 | 0.16 | | 29 | 0.16 | | 89 | 0.15 | | 93 | 0.14 | | 55 | 0.13 |
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Frequency Analysis based on Yearly Comb
Representative Cycle (Trading Sessions) = 0.00
Sawtooth = 0.00
| 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, October 15, 2009 | 13.15 | | | 353 | | | Friday, March 06, 2009 | 5.20 | 283 | | Thursday, May 22, 2008 | 48.20 | | | 259 | | | Tuesday, January 22, 2008 | 32.20 | 687 | | Monday, May 14, 2007 | 53.25 | | | 326 | | | Thursday, April 28, 2005 | 16.15 | 695 | | Wednesday, January 25, 2006 | 28.60 | | | 292 | | | Thursday, July 25, 2002 | 2.55 | 979 |
Fourier Transform on Raw Closing Prices | Cycle Length | Fourier Amplitude | | 819 | 25.04 | | 683 | 10.50 | | 585 | 8.43 | | 8 | 8.27 | | 12 | 6.77 | | 512 | 6.09 | | 17 | 4.87 | | 25 | 4.03 | | 341 | 3.88 | | 315 | 3.77 | | 19 | 3.64 |
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| Breaking News: Friday, November 12, 2010: We have news on Cree, Inc., ticker symbol CREE. Signs of an over-bought condition have become noticable.
Also, there are breaking events concerning Intel and PetSmart, Inc.
From the News Archive: (11/11/2010 ) Favorable events happened at Exxon Mobil, Ingersoll-Rand Company Limited, and Concur Technologies, Inc.. Meanwhile, bad news came from International Game Technology.
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Dynegy Inc.
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Average Sawtooth based on Monthly Combo
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Dynegy Inc.
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Average Sawtooth based on Bi-weekly Combo
The Sawtooth statistic measures the time from each periodic high to the next periodic low, in comparison to the time from that low to the next high point . 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. Bullish or bearish moods may be reflected in the steepness of the buying and selling slopes, particularly as they change through time. 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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