|
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
__._,_.___
![]()
__,_._,___
|
