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, attempts to exploit the market cycles are foiled by the deviation from strictly periodic behavior required by ordinary analysis. 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. In order to determine the actual frequences in a particular case, we must conduct an new form of analysis that is better suited to deal with the oxymoronic condition of variable length cycles. |
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Frequency from Monthly Comb Filter
Representative Cycle (Trading Sessions) = 28.00
Sawtooth = 48.11
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 17.18 | 29.00 | 25.00 | 17.39 % | | Low | 16.88 | 31.00 | 22.00 | 22.19 % |
| Recent High | Price | Recent Low | Price | Cycle | | | Wednesday, October 06, 2010 | 20.47 | 25 | | Tuesday, August 10, 2010 | 22.02 | | | 19 | | | Tuesday, August 31, 2010 | 19.35 | 42 | | Wednesday, July 14, 2010 | 19.44 | | | 28 | | | Thursday, July 01, 2010 | 17.19 | 28 | | Thursday, June 03, 2010 | 21.75 | | | 24 | | | Friday, May 21, 2010 | 20.00 | 68 | | Thursday, April 29, 2010 | 24.88 | | | 28 |
Fourier Transform after Digital Filter M | Cycle Length | Fourier Amplitude | | 14 | 0.50 | | 17 | 0.40 | | 24 | 0.39 | | 21 | 0.30 | | 31 | 0.28 | | 28 | 0.23 | | 36 | 0.22 | | 34 | 0.19 | | 41 | 0.18 | | 49 | 0.13 | | 77 | 0.10 |
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Frequency Analysis based on Quarterly Comb
Frequency from Quarterly Comb Filter
Representative Cycle (Trading Sessions) = 78.00
Sawtooth = 44.49
| Peak Type | Avg. Cycle | Median Cycle | Cycle Mode | Cycle Amplitude | | High | 44.20 | 82.00 | 41.00 | 27.43 % | | Low | 47.29 | 96.00 | 78.00 | 40.70 % |
| Recent High | Price | Recent Low | Price | Cycle | | Tuesday, August 10, 2010 | 22.02 | | | 99 | | | Thursday, July 01, 2010 | 17.19 | 96 | | Friday, March 19, 2010 | 26.24 | | | 42 | | | Friday, February 12, 2010 | 22.33 | 78 | | Tuesday, January 19, 2010 | 26.71 | | | 87 | | | Wednesday, October 21, 2009 | 18.19 | 160 | | Monday, September 14, 2009 | 24.82 | | | 82 | | | Thursday, March 05, 2009 | 8.02 | 70 |
Fourier Transform after Digital Filter Q | Cycle Length | Fourier Amplitude | | 9 | 0.46 | | 12 | 0.30 | | 14 | 0.29 | | 17 | 0.23 | | 77 | 0.20 | | 24 | 0.19 | | 21 | 0.17 | | 146 | 0.16 | | 28 | 0.14 | | 80 | 0.14 | | 26 | 0.14 |
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Frequency Analysis based on Yearly Comb
Representative Cycle (Trading Sessions) = 0.00
Sawtooth = 38.98
| 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 | | Tuesday, January 19, 2010 | 26.71 | | | 582 | | | Thursday, March 05, 2009 | 8.02 | 395 | | Wednesday, September 26, 2007 | 62.36 | | | 415 | | | Thursday, August 09, 2007 | 51.12 | 178 | | | Tuesday, November 21, 2006 | 44.78 | 145 | | Wednesday, February 01, 2006 | 61.24 | | | 827 | | | Thursday, April 27, 2006 | 45.70 | 379 | | Friday, October 18, 2002 | 16.69 | | | 286 |
Fourier Transform on Raw Closing Prices | Cycle Length | Fourier Amplitude | | 585 | 3.04 | | 512 | 3.03 | | 819 | 2.55 | | 683 | 2.05 | | 9 | 1.72 | | 455 | 1.45 | | 14 | 1.14 | | 178 | 0.97 | | 171 | 0.94 | | 372 | 0.74 | | 256 | 0.72 |
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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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Coventry Health Care, Inc.
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Average Sawtooth based on Monthly Combo
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Coventry Health Care, 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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