|
PureBytes Links
Trading Reference Links
|
Great post, thank you Howard.
A single unique market pattern or anomaly can be traded with thousands of
different formulas; the formula is not unique, only the anomaly is. So while
we see thousands of system formulas many of those are actually trading the
very same market anomaly with various degrees of success. If we have a
million traders looking for the HG sooner or later the system will fail as
hundreds of different formulas are trading the same anomaly.
Many people think that it is unlikely that a system will fail due to
publicity and overtrading - because they think that each system formula
trades a different market anomaly and that there are unlimited anomalies to
trade. Due to the greed factor the most profitable trading system are the
first to fail.
just my opinion :-)
Thanks again for a stimulating post!
herman
-----Original Message-----
From: Howard Bandy [mailto:howardbandy@xxxxxxxxx]
Sent: Thursday, October 16, 2003 2:20 PM
To: amibroker@xxxxxxxxxxxxxxx
Subject: [amibroker] Optimization -- again
Greetings --
In my opinion, anything we do in development of trading systems involves a
search for a pattern than precedes a profitable trading opportunity. Any
time we examine the results of alternative systems, we are involved in
searching; and when we select the most promising of those alternatives, we
are optimizing. Only a system based on truly random entries and exits would
not be the result some optimization. So the question of "should we
optimize?" is moot -- we have no choice but to optimize. Consequently, we
should be aware of our optimization techniques.
Chuck referred to an optimization technique recommendation I made to the
company we both worked for in Denver a few years ago. This is a short
description of it.
The company is a Commodity Trading Advisor which traded futures, not
individual stocks, but the procedures are equally valid for both.
When I joined the company, they were using very long data series when
developing their models. They used a technique sometimes called folding or
jackknifing, where the data was divided into several periods -- say ten.
The modeling process made ten passes. During each pass, one period was held
back to be used as out-of-sample data, the other nine were used to select
the best parameter values. After all ten passes, the results were gathered
together and the parameter values that scored best overall were chosen.
There are several problems with this method. One is the difficulty with the
"ramp up" period at the start of each segment, another is that it is not
valid to use older data for out-of-sample testing than was used for
in-sample development, and another is that the data series were too long.
Chuck and I and others had many interesting discussions about how long the
in-sample data should be.
My background is strong in both the theory and the practice of modeling and
simulation, and includes a great deal of experience with analysis of
financial time series. I proposed the following method, which I continue to
believe is valid.
First, before any modeling begins. Using judgment of management and
comparison of trading profiles of many trading runs (real, simulated, or
imagined), pick an objective function by which the "goodness" of a trading
system will be measured. This is important, it is a personal or corporate
judgment, and it should not be subject to optimization.
Divide each data series into a sequence of in-sample and out-of-sample
periods. The length of the out-of-sample period is the "reoptimization"
period. Say there are about ten years of historical data available
(1/1/1993 through 1/1/2003. Set the in-sample period to two years and the
out-of-sample period to one year. Run the following sequence: Search /
optimize using 1993 and 1994; pick the "best" model for 1993-1994; forward
test this model for 1995 and save the results; step forward one
reoptimization period and repeat until all the full in-sample periods have
been used. The final optimization will have been 2001 and 2002, with no
out-of-sample data to test. Ignore all in-sample results!! Examine the
concatenated out-of-sample equity curve. If it is acceptable, you have some
confidence that the parameters select by the final optimization (2001 and
2002) will be profitable for 2003. No guarantees -- only some confidence.
How did I pick two years for in-sample and one year for out-of-sample? That
was just an example. The method is to set up an automated search where the
length of the in-sample period and the length of the out-of-sample period --
the reoptimization period -- are variables, and then search through that
space.
Trading systems work because they identify inefficiencies in markets. Every
profitable trade reduces the inefficiency until, finally, the trading system
cannot overcome the frictional forces of commission and slippage. This is
the same phenomenon that physicists talk about as entropy.
My feeling -- and it may be different than Chuck's -- is that the market is
not only non-stationary, but that the probability that it will return to a
previous state is near zero.
Being non-stationary means that market conditions change with respect to our
trading systems. If I am modeling a physical process, such as a chemical
reaction, I can count on a predictable modelable output for a given set of
inputs. If I am modeling a financial time series, the output following a
given set of inputs changes over time. If a market were stationary with
respect to an RSI oscillator system, I could always buy a rise of the RSI
through the 20 percent line, to use a very simplistic example.
I feel that the introduction of microcomputers, trading system development
software, inexpensive individual brokerage accounts, and discussion groups
such as this one have permanently changed the realm of trading. One,
everyone who is interested can afford to buy a computer, run AmiBroker, and
design and test trading systems. Two, if someone develops a profitable
system and trades it, the profits it takes reduce the potential profits
available to anyone else who trades it. Consequently, the characteristics
of the market change in a way that moves the market away from that model
until that trading system is no longer profitable enough to overcome
commission and slippage. Three, a new person beginning to study trading
system development typically tests a lot of old systems. If one is found to
be profitable and they start trading it, the market moves back to being
efficient. Consequently, trading systems that used to work, but no longer
work, are very unlikely to ever work again.
So, I feel that the in-sample period should be short so that the market
conditions do not change much over that period. That is, I am looking for a
data series that is stationary relative to my model. The stationary
relationship must extend beyond the in-sample period far enough that the
model will be profitable when used for trading in the out-of-sample data.
The length of the extension determines the reoptimization period. It could
be years, months, or even one day. Note that the holding period of a
typical trade is very much related to the length of both the in-sample and
out-of-sample periods. The typical trade should be much shorter than the
in-sample period and somewhat shorter than the out-of-sample period.
The important point in all this is that the only results being analyzed are
the concatenated out-of-sample trades.
As with all model development, every time I look at the out-of-sample
results in any way, I reduce the probability that future trading results
will be profitable. That means that I should not perform thousands of tests
of model parameters, in-sample periods, and out-of-sample periods, on the
same data series and then pick the best model base on my examination of
thousands of out-of-sample results. In effect, I will have just converted
all those out-of-sample results into in-sample data for another step in the
development. That is legitimate, just be aware of what is happening.
Thanks for listening,
Howard
Send BUG REPORTS to bugs@xxxxxxxxxxxxx
Send SUGGESTIONS to suggest@xxxxxxxxxxxxx
-----------------------------------------
Post AmiQuote-related messages ONLY to: amiquote@xxxxxxxxxxxxxxx
(Web page: http://groups.yahoo.com/group/amiquote/messages/)
--------------------------------------------
Check group FAQ at:
http://groups.yahoo.com/group/amibroker/files/groupfaq.html
Your use of Yahoo! Groups is subject to http://docs.yahoo.com/info/terms/
------------------------ Yahoo! Groups Sponsor ---------------------~-->
Buy Ink Cartridges or Refill Kits for your HP, Epson, Canon or Lexmark
Printer at MyInks.com. Free s/h on orders $50 or more to the US & Canada.
http://www.c1tracking.com/l.asp?cid=5511
http://us.click.yahoo.com/mOAaAA/3exGAA/qnsNAA/GHeqlB/TM
---------------------------------------------------------------------~->
Send BUG REPORTS to bugs@xxxxxxxxxxxxx
Send SUGGESTIONS to suggest@xxxxxxxxxxxxx
-----------------------------------------
Post AmiQuote-related messages ONLY to: amiquote@xxxxxxxxxxxxxxx
(Web page: http://groups.yahoo.com/group/amiquote/messages/)
--------------------------------------------
Check group FAQ at: http://groups.yahoo.com/group/amibroker/files/groupfaq.html
Your use of Yahoo! Groups is subject to http://docs.yahoo.com/info/terms/
|