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<SPAN
class=018055914-14052004>Has anyone done anything MESA-like in AFL? Does anyone
know anything about MESA's internals beyond this?
<SPAN
class=018055914-14052004>
<SPAN
class=018055914-14052004> <A
href="">http://www.mesasoftware.com/#How%20MESA%20Works
<SPAN
class=018055914-14052004>
<SPAN
class=018055914-14052004>Dave
<SPAN
class=018055914-14052004>
<BLOCKQUOTE dir=ltr
>
FWIW, the following blurb from Ehlers website raises
some concerns about FFT. Charts regarding FFT are
on:
<A
href="">http://www.mesasoftware.com/#FFT%20Comparison
Bill
<FONT
color=#0000ff>MESA COMPARED TO FOURIER TRANSFORMS:
FFT is the acronym for Fast Fourier Transform. FFT is a
computer algorithm to perform the Fourier Transforms rapidly. The correct use
of Fourier Transforms is subject to several constraints. First, the data must
be stationary (non-shifting) over the observation period. Secondly, an integer
number of cycles must be used in the analysis. The Nyquist theory of sampled
data systems states that there must be at least two samples per cycle. These
constraints pose a dilemma for analysis of price data.
For example, if we have data consisting of 64 points (64 days
in the market), the longest cycle we can measure is 64 days. The next longest
cycle is 64/2=32 days. The next longest available cycle is 64/3=21.3 days. The
next cycle is 64/4=16 days, etc. The 64 day data simply does not provide good
resolution to identify the cycles because there is a 5 day gap between
measured results right in the most active cycle region. The only way to
increase resolution is to increase the data length. However, if the data
length is increased there is a significantly lower probability that the cycle
has not shifted over the entire data length. In fact, it is downright
unlikely.
Thus the use of FFTs
for trading is not advisable. MESA2002 accurately extracts
short term cycles using an adaptive short data length, and therefore MESA2002
should be your cycle measurement method.
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