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
