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, a fact that has played havoc with most schemes to exploit the market 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. New methods had to be invented to deal with the seeming mathematical absurdity in the notion of non-periodic cycles. |
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Frequency from Monthly Comb Filter
Representative Cycle (Trading Sessions) = 21.00
Sawtooth = 48.97
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 17.15 | 30.00 | 21.00 | 9.78 % | | Low | 17.31 | 31.00 | 21.00 | 9.20 % |
| Recent High | Price | Recent Low | Price | Cycle | | | Tuesday, August 24, 2010 | 71.61 | 35 | | Monday, August 09, 2010 | 77.77 | | | 34 | | | Tuesday, July 06, 2010 | 67.12 | 31 | | Monday, June 21, 2010 | 76.48 | | | 36 | | | Thursday, May 20, 2010 | 67.30 | 77 | | Thursday, April 29, 2010 | 76.92 | | | 27 | | Monday, March 22, 2010 | 73.31 | | | 49 | | | Friday, January 29, 2010 | 59.69 | 28 |
Fourier Transform after Digital Filter M | Cycle Length | Fourier Amplitude | | 12 | 0.52 | | 18 | 0.37 | | 20 | 0.37 | | 22 | 0.35 | | 16 | 0.35 | | 25 | 0.35 | | 37 | 0.25 | | 27 | 0.24 | | 31 | 0.22 | | 34 | 0.20 | | 29 | 0.20 |
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Frequency Analysis based on Quarterly Comb
Frequency from Quarterly Comb Filter
Representative Cycle (Trading Sessions) = 111.00
Sawtooth = 53.10
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 48.45 | 89.00 | 94.00 | 15.06 % | | Low | 51.17 | 85.00 | 111.00 | 13.05 % |
| Recent High | Price | Recent Low | Price | Cycle | | | Tuesday, July 06, 2010 | 67.12 | 108 | | Thursday, April 29, 2010 | 76.92 | | | 76 | | | Friday, January 29, 2010 | 59.69 | 60 | | Friday, January 08, 2010 | 67.13 | | | 254 | | | Monday, November 02, 2009 | 54.10 | 111 | | Tuesday, January 06, 2009 | 52.17 | | | 88 | | | Wednesday, May 27, 2009 | 44.32 | 55 | | Friday, August 29, 2008 | 80.61 | | | 64 |
Fourier Transform after Digital Filter Q | Cycle Length | Fourier Amplitude | | 14 | 0.28 | | 146 | 0.23 | | 17 | 0.21 | | 25 | 0.20 | | 21 | 0.19 | | 124 | 0.14 | | 37 | 0.14 | | 117 | 0.13 | | 65 | 0.13 | | 79 | 0.13 | | 34 | 0.13 |
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Frequency Analysis based on Yearly Comb
Representative Cycle (Trading Sessions) = 0.00
Sawtooth = 40.55
| 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 | | | Monday, March 09, 2009 | 32.70 | 648 | | Friday, August 29, 2008 | 80.61 | | | 593 | | | Wednesday, August 09, 2006 | 36.77 | 514 | | Monday, April 24, 2006 | 45.17 | | | 583 | | | Tuesday, July 27, 2004 | 24.82 | 346 | | Monday, December 29, 2003 | 31.00 | | | 460 | | | Wednesday, March 12, 2003 | 22.63 | 367 | | Monday, March 04, 2002 | 28.16 | | | 196 |
Fourier Transform on Raw Closing Prices | Cycle Length | Fourier Amplitude | | 683 | 4.71 | | 512 | 4.41 | | 585 | 4.32 | | 455 | 4.28 | | 819 | 4.01 | | 410 | 2.61 | | 273 | 2.51 | | 256 | 2.32 | | 293 | 2.26 | | 16 | 1.76 | | 241 | 1.71 |
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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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| UNP
Union Pacific Corporation
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Average Sawtooth based on Monthly Combo
| UNP
Union Pacific Corporation
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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. 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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