Jim,
Static cycles are not my favorite or
special.
The real question is a fundamental one:
how to verify any trading strategy, based on anything.
10 years ago I have participated in a
big research project. Its purpose was to test and verify different trading
systems based on methods of technical analysis. Our group has found that
the application of methods of classical statistics to the stock market
analysis is an extremely dangerous thing.
Let me explain it better on this
example.
Let say we have found a system that
provides 70 winning signals from 100. The university's course of statistics
says that this fact is not occasional with the probability of 99.5% (Chi
Square=20x20/50=400/50=8 => P=99.5%) It means that we can assume
that there is a high possibility that this system will work well in the
future as it does in the present. And somebody may decide that the Holy Grail
is found finally. But - it is not true. Statistics of the real stock market
and the market's logic are different from this one. If the system works
good enough for 100 current examples, it does not mean that it will work the
same for other samples.
Jim, I want to emphasize that I do not
name here the models that we used for the research. My group tried
different things: TA indicators, risk/money management, arbitrage systems,
then different math models (like Spectrum, autoregression), astro cycles
as well. This problem still presents for all of them.
I believe that this problem is described
well in these books:
1) "The (Mis)behavior of Markets" of Benoit
Mandelbrot;
and 2) "Chaos and Order in the Capital Markets: A New View of
Cycles, Prices, and Market Volatility" of Edgar E. Peters.
In financial analysis, we have to work
with big data samples.
Best
regards,
Sergey
PS. Jim, it seems to me that you are
mixing two different things: fixed (or static) cycles and dominant cycles. As
an example, I would not believe if somebody states that the 20-days cycle is
found that has worked for 20 years. From another side, if somebody states that
withing the last 100 days the 20-days cycle has been found, it is quite
possible.
Next 100 days there might be some other
cycle (27-days, for example). It is closer to MESA and wavelet analysis, not
to normal fixed cycles analysis.
----- Original Message -----
Sent: Monday, December 08, 2008 4:27
PM
Subject: [Bulk] Re: [Bulk] [RT] A note
on Forecasting
Sergey,
The inability of a methodology to return
reliable and consistent performance is an indication that the underlying
hypothesis is flawed. For example, methods based on static cycles or
projections based on static cycles will have inconsistent performance over
different stretches of time because static cycles are not fundamentally
correct model of market activity.
There are characteristics of market movement
and trader psychology that do not change over time and methods based on
these will exhibit consistent performance. be it 100 or 700
samples.
Jim
----- Original Message -----
Sent: Monday, December 08, 2008 11:52
AM
Subject: Re: [Bulk] [RT] A note on
Forecasting
Hello, Jim
Actually, the question about
financial statistics is a tricky one. The important things there are not
only win/loss ratios, the intervals where these ratios are calculated
should be considered as well. I have had many cases when a trading
strategy worked very well for a half a year. And then it died
forever.
As an example, see this intermediate
backtesting result for huge intraday data:
The system provided 65% good signals
(469 win./ 247 los.) during some perios (several
months).
After that 53% only, and then
59%.
100 trades is not enough to get the
reliable statistics (we use at least 500 trades, in this example 700
trades).
One of this forum's participants is
Robert Pardo, he can comment this better than me.
Best regards,
Sergey
----- Original Message -----
Sent: Monday, December 08, 2008
12:31 PM
Subject: [Bulk] [RT] A note on
Forecasting
My pivot trading methodology depends on anticipating and trading as
close to the pivot
points as possible. My argument is that trades near the pivot
points are the lowest risk and highest reward points to trade. I operate
my trading as a business - I buy inventory and sell to capture a
minimum profit margin. I have spent most of my trading career studying
the characteristics of markets at turning points (pivots) and
constructing trading tools to anticipate and trade near those points.
These tools deliver consistent reliability of profitable trades between
70% and 80%.
I document my trading concepts by forward testing, not computer
generated back testing. In other words I trade the tools in real time
and record the results. For example, my latest application to the ESZ08
has generated about 78% profitable trades on a five minute chart over
the past 6 weeks.
One of the issues I have with the people that post forecast on this
list is that they do not provide reliability measures of their
techniques. Failed forecasts are rarely addressed and specific
application details are not provided. Consequently I usually delete them
without consideration - after all - a stopped clock is right twice a
day.
So I recommend that anyone who posts a forecast provide the
statistics documenting the same performance of technique over at least
100 applications. For example my techniques are good within one bar of
the forecast 70% to 80% of the time depending on market. With that
information, readers can better judge the value of the post.
Jim White
Pivot Research & Trading
Co.
PivotTrader.com
