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You asked me if 30-40% PA is really possible in EOD trading.
Enter that code to Formula Editor and run it as a backtest on YHOO -
use Yahoo data and test from 1997 - 2006 inclusive then look at the
backtest report - you will see that the return is ? PA%
The code buys on the Monday open and sells on the Friday close.
It's not a trading system - it is a trading lesson.
Where you find yourself is normal for new traders.
Everyone starts off with naive optimism.
Many continue on naively for as long as they trade, and get the
corresponding results.
Those who are making earnest enquiries into trading are eventually
confronted with some trading quandries - I could make a list of them -
how you resolve the difficult dilemnas of trading determines how
successful you will be.
You are confronting them early in the piece because you are lucky
enough to have received the help of the AB community.
brian_z
--- In amibroker@xxxxxxxxxxxxxxx, "Louis Préfontaine"
<rockprog80@xxx> wrote:
>
> Sorry Brian, I don"t understand what you mean...
>
> Louis
>
> 2008/4/10, brian_z111 <brian_z111@xxx>:
> >
> > Apologies.
> >
> > Better use the correct syntax.
> >
> > Buy = DayOfWeek() == 1;
> > Sell = DayOfWeek() == 5;
> >
> > BuyPrice = O;
> > SellPrice = C;
> >
> > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%40yahoogroups.com>,
> > "brian_z111" <brian_z111@> wrote:
> > >
> > > Is 20% PA EOD good?
> > >
> > > Run this on YHOO using Yahoo data - I have a 97 to 2006
database.
> > >
> > > Buy = DayOfWeek() == 1;
> > > Sell = DayOfWeek() == 5;
> > >
> > > BuyPrice == O;
> > > SellPrice == C;
> > >
> > > What PA% do you get (it is the first stock I picked to try)?
> > >
> > > Should I backtest?
> > >
> > > It gets rid of all of my bad ideas (a Dennisism!)
> > >
> > > If I can trade now, without a computer and backtesting, it is
only
> > > because of the thousands of hours of computer trading hours I
have
> > > under the belt.
> > >
> > >
> > >
> > > You have to generalise before you can specialise.
> > >
> > > brian_z
> > >
> > >
> > >
> > >
> > > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%40yahoogroups.com>,
> > "louisprefontaine" <rockprog80@>
> > > wrote:
> > > >
> > > > Hi everyone,
> > > >
> > > > I am not at home right now, and it's really a pleasure to read
> > you
> > > > while drinking this marvelous Côtes-du-Rhônes. I really
> > appreciate
> > > > all the ideas you shared with me (and the group).
> > > >
> > > > I must say that everyone seem to have different visions of the
> > > > problem, with people focusing on walk-forward optimizations,
> > others
> > > > on specific date backtesting and still others (someone who
> > > contacted
> > > > me in private) refuse to backtest and want to trade directly
with
> > > > easy to follow rules.
> > > >
> > > > For what I have read (and I will re-read tomorrow, at home), I
> > need
> > > > more data if I want to follow the « rule » of the 30 trades.
> > Right
> > > > now, my system is based on a major index and it issues only
about
> > 3-
> > > > 5 signals a year (which, at a 20% portfolio ratio is 15 to 25
> > > > trades), so I would need between 6 to 10 years of data, which
of
> > > > course is impossible to do because we all know the market 10
> > years
> > > > ago as nothing to do with what it is right now.
> > > >
> > > > On the other side, I could use minimal backtesting, but then
the
> > > > data-mining bias would increase, considering that my system
has
> > > only
> > > > a very limited of trades each year. Let's say that if I use
only
> > > > one year back-testing (a bull market, a sideway market, and a
> > bear
> > > > to sideway market), that would be about 3-5 trades. How can I
> > say
> > > > with certitude that the gains are not due to luck on such a
small
> > > > amount of signals on the major index? Even if I get 30 trades
> > from
> > > > buying the stocks linked to the index, this may still be only
> > data-
> > > > mining to the major index, as the stocks tend to follow that
> > > index.
> > > > (As an example, if I data-mine perfectly the Dow Jones,
chances
> > are
> > > > that buying the 30 companies in the index will give a good
> > > > result... I would have a lot more trades, but in fact they
would
> > > be
> > > > based only on the same data-mined Dow Jones index...) --BIG
> > > PROBLEM-
> > > > -
> > > >
> > > > Finally, there is the suggestion of going intraday. I'd like
to
> > do
> > > > this, butmy RT data provider only provides 1 year of intraday
> > > data.
> > > > Do you know other provider who gives more?
> > > >
> > > > And finally finally... Are you sure Brian one can expect 40%
per
> > > > annumm on EOD data? This seem like very very good!
> > > >
> > > > My strategy right now is based on a very limited number of
trades
> > > > with extra-limited drawdowns (I need to thank a member of this
> > > board
> > > > who helped me with this... You know who you are... Thanks
> > again!).
> > > > So I can put maximum margin and boost the results. But with
> > extra-
> > > > little trades comes the problem of significance of the
results:
> > are
> > > > the results good because the system is good or are the results
> > good
> > > > be cause of good luck?
> > > >
> > > > That was the purpose of the first message, and so far I have
new
> > > > ideas but I am still wondering what I should do.
> > > >
> > > > Louis
> > > >
> > > >
> > > >
> > > > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com>,
> > "brian_z111" <brian_z111@>
> > > > wrote:
> > > > >
> > > > > > I agree that there is a serious problem when the only data
> > that
> > > > is
> > > > > >available
> > > > > > contains no period that is similar to what is expected in
the
> > > > > >future.
> > > > > >
> > > > >
> > > > > Getting enough data is an issue for EOD traders.
> > > > >
> > > > > A few possible solutions I have mentioned in the past (I
> > > > like 'live'
> > > > > work but the negative is that it doesn't persist - unlike a
> > book).
> > > > >
> > > > > - new traders should work in old EOD data, say 1995-2000,
until
> > > > they
> > > > > address all of the basic issues, like length of IS versus OS
> > etc.
> > > > >
> > > > > They should save up the best years (the current 5) until
they
> > > > start
> > > > > to get good == backtests > 30-40% per annum on OOS tests and
> > then
> > > > > move to fresh and/or bought data for confirmation/trading.
> > > > >
> > > > > (of course we know that a lot of ideals will never make it
to
> > > > common
> > > > > practice - some are just too hard to sell).
> > > > >
> > > > > - use other markets (that is why I highlighted the S&P
global
> > > 1200
> > > > in
> > > > > a UKB post) - a US trader could practice on the ASX top 20
for
> > > > > example - ASX market behaviour of the 20 most liquid stocks
is
> > > > > similar to the US top 100 or 200.
> > > > >
> > > > > - become an intraday trader (plenty of data then)
> > > > >
> > > > > - take a ten year history that included different market
> > > > conditions,
> > > > > filter it for liquid stock (for concept testing I like only
> > stock
> > > > > that trade everyday - no data holes - in real time I know
when
> > a
> > > > > stock isn't trading) - sort the data by 10 year performance
> > i.e.
> > > > 10
> > > > > year % return - assign them an ordinal number - then put
every
> > > > even
> > > > > stock in an IS testing watchlist and every odd stock in an
OOS
> > > > > testing watchlist.
> > > > >
> > > > > Now you have a 10 year IS and OOS database with a range of
> > > > conditions
> > > > > and equal numbers of bullish and bearish stock.
> > > > >
> > > > > I have done that with the most liquid stock in Jim's Yahoo
> > > > database
> > > > > and I am comfortable working with it like that.
> > > > >
> > > > > > Artificial data has no value.
> > > > >
> > > > > One exception is for training.
> > > > >
> > > > > I have learnt a lot using (crude) randomly generated data
as a
> > > > > training benchmark - I regard the Black Swan as my
adversary so
> > I
> > > > > have studied his/her habits in depth.
> > > > >
> > > > > The beauty of RGD is that, while it is not real, it is
> > > > lifelike,and
> > > > > more importantly, we know in advance what it's real
performance
> > > is
> > > > > (W/L ratio, %period returns).
> > > > >
> > > > > I can't recommend that type of synthetic trading highly
enough.
> > > > >
> > > > > In all other trading tests we never ever have certainty
about
> > > > those
> > > > > numbers - I love the certainty of simulated data for
comparing
> > > > real
> > > > > behaviour to theoretical behaviour (if they don't mactch
then I
> > > am
> > > > > not confident my theories will stand up in real life).
> > > > >
> > > > >
> > > > > brian_z
> > > > >
> > > > >
> > > > >
> > > > > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com>,
> > "Howard B" <howardbandy@>
> > wrote:
> > > > > >
> > > > > > Hi Louis --
> > > > > >
> > > > > > I agree that there is a serious problem when the only data
> > that
> > > > is
> > > > > available
> > > > > > contains no period that is similar to what is expected in
the
> > > > > future.
> > > > > >
> > > > > > Artificial data has no value.
> > > > > >
> > > > > > Using data that is earlier in time than the in-sample
period
> > > has
> > > > > limited
> > > > > > value. You can test earlier data, but you will over-
estimate
> > > the
> > > > > > performance that you can expect in the future.
> > > > > >
> > > > > > Are there other tickers that are closely related that have
> > data
> > > > for
> > > > > the
> > > > > > periods you would like to test?
> > > > > >
> > > > > > In the end, you will need to make a decision on whether to
> > > place
> > > > > actual
> > > > > > trades. And that decision must be based on your
> > understanding
> > > > of
> > > > > and
> > > > > > confidence in your system. The only way to gain that
> > > confidence
> > > > is
> > > > > by
> > > > > > observing the transitions from in-sample testing to out-
of-
> > > > sample
> > > > > simulated
> > > > > > trading.
> > > > > >
> > > > > > Thanks,
> > > > > > Howard
> > > > > > On Tue, Apr 8, 2008 at 10:37 PM, Mike <sfclimbers@> wrote:
> > > > > >
> > > > > > > Howard's comments are consistent with those of Robert
> > Pardo
> > > > (The
> > > > > > > Evaluation and Optimization of Trading Strategies, Wiley
> > > > 2008),
> > > > > with
> > > > > > > respect to training periods.
> > > > > > >
> > > > > > > Pardo recognizes that there is a tradeoff between more
> > robust
> > > > > > > strategies which require longer in sample training
periods,
> > > > > require
> > > > > > > fewer reoptimizations, trade for longer out of sample
> > periods
> > > > and
> > > > > are
> > > > > > > generally less profitable, vs. more responsive
strategies
> > > which
> > > > > > > require shorter in sample training periods, require more
> > > > frequent
> > > > > > > reoptimizations, can only trade for shorter out of
sample
> > > > periods
> > > > > and
> > > > > > > are generally more profitable.
> > > > > > >
> > > > > > > Pardo suggests that strategies generating more frequent
> > > > signals
> > > > > can
> > > > > > > use shorter in sample training windows since they
generate
> > the
> > > > > > > minimum 30+ trades sooner than strategies that generate
> > less
> > > > > frequent
> > > > > > > signals. But, that in any case, one should try to use
an in
> > > > sample
> > > > > > > period sufficiently long to capture bull, bear, and
> > sideways
> > > > > markets.
> > > > > > >
> > > > > > > Further, when first trying to evaluate the worth of the
> > > > strategy,
> > > > > > > Pardo suggests backtesting the in sample history in
> > segments
> > > > > rather
> > > > > > > than one shot (e.g. 10 year history divided into five 2
year
> > > > > > > segments). This gives you better insight as to whether
the
> > > > results
> > > > > > > are due to a single segment or are consistent accross
> > > > segments,
> > > > > and
> > > > > > > provides insight to your eventual in sample/out of
sample
> > > > periods
> > > > > for
> > > > > > > Walk Forward Optimization.
> > > > > > >
> > > > > > > Finally, Pardo suggests that regardless of whether a
long
> > or
> > > > short
> > > > > > > training period is used, a rule of thumb for in sample
vs.
> > > out
> > > > of
> > > > > > > sample is for out of sample to be between 1/8 to 1/3 of
the
> > > in
> > > > > sample
> > > > > > > period (e.g. 24/8 = 3 and 24/3 = 8, so it would
be "safe"
> > to
> > > > trade
> > > > > > > out of sample for 3 - 8 months based on a system
backtested
> > > > over
> > > > > 24
> > > > > > > months.
> > > > > > >
> > > > > > > Yet another good book covering the topic. I reccomend
it.
> > > > > > >
> > > > > > > Mike
> > > > > > >
> > > > > > >
> > > > > > > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com><amibroker%
> > > > > 40yahoogroups.com>, "Howard B"
> > > > > > > <howardbandy@> wrote:
> > > > > > > >
> > > > > > > > Hi Louis, and all --
> > > > > > > >
> > > > > > > > I know David Aronson, respect him, and like and
recommend
> > > > his
> > > > > book.
> > > > > > > >
> > > > > > > > My view is that the in-sample period should be as
short as
> > > > > > > practical. My
> > > > > > > > thought is that: the system we are testing / trading
is
> > > > trying
> > > > > to
> > > > > > > recognize
> > > > > > > > the signal from among the noise; and the signal
patterns
> > are
> > > > > > > changing over
> > > > > > > > time. So the length of the in-sample period is a
> > tradeoff --
> > >
> > > > > short
> > > > > > > to be
> > > > > > > > able to change as the characteristics of the
underlying
> > > > market
> > > > > > > change, but
> > > > > > > > not so short that the system is over-fit to the noise
> > > rather
> > > > > than
> > > > > > > learns the
> > > > > > > > signal.
> > > > > > > >
> > > > > > > > You can test this in AmiBroker. Have your system
ready to
> > > > buy
> > > > > and
> > > > > > > sell. In
> > > > > > > > the Automatic Analysis window, use Settings and set up
> > the
> > > > Walk
> > > > > > > Forward
> > > > > > > > parameters. Try an in-sample period of 10 years, an
out-
> > of-
> > > > > sample
> > > > > > > period of
> > > > > > > > 6 months or 1 year. Run Optimize > Walk Forward and
look
> > at
> > > > the
> > > > > in-
> > > > > > > sample
> > > > > > > > and out-of-sample equity curves. Shorten the length of
> > the
> > > > in-
> > > > > > > sample period
> > > > > > > > to 9, then 8, then 7, ... then 1 year, keeping the
out-of-
> > > > sample
> > > > > > > period
> > > > > > > > unchanged. Depending on your system and the market it
is
> > > > > trading,
> > > > > > > you may
> > > > > > > > find that there is a sweet spot in the length of the
in-
> > > > sample
> > > > > > > data. If so,
> > > > > > > > that is the amount of data that allows your system to
> > > > recognize
> > > > > the
> > > > > > > signal
> > > > > > > > without being overwhelmed by the noise.
> > > > > > > >
> > > > > > > > Thanks,
> > > > > > > > Howard
> > > > > > > >
> > > > > > > >
> > > > > > > > On Tue, Apr 8, 2008 at 8:56 AM, Louis Préfontaine
> > > > <rockprog80@>
> > > > > > >
> > > > > > > > wrote:
> > > > > > > >
> > > > > > > > > Hi,
> > > > > > > > >
> > > > > > > > > I've been thinking a lot lately, and here is
something
> > I
> > > > would
> > > > > > > like to
> > > > > > > > > have your opinion on.
> > > > > > > > >
> > > > > > > > > I've been introduced to automated systems by a trend
> > > > following
> > > > > > > book which
> > > > > > > > > related how some trend followers built their
systems in
> > > > the
> > > > > 70s
> > > > > > > or 80s and
> > > > > > > > > got rich with them, and how their system did not
really
> > > > change
> > > > > > > all this
> > > > > > > > > time. They didn't change their system because they
say
> > the
> > > > > > > market does NOT
> > > > > > > > > change. They looked at historic market data from the
> > > 1800s
> > > > and
> > > > > > > the market
> > > > > > > > > was as it is right now. So they say.
> > > > > > > > >
> > > > > > > > > On the other side, lately I have been introduced to
the
> > > > > concept of
> > > > > > > > > ever-changing markets and have had a hard time
trying
> > to
> > > > > build my
> > > > > > > system.
> > > > > > > > > Got a very promising start with a system getting
around
> > > 15-
> > > > 20%
> > > > > > > average for
> > > > > > > > > April 2007 to April 2008 (with little drawdown,
which
> > > mean
> > > > > that
> > > > > > > with
> > > > > > > > > leverage I can boost this a lot). In any variation
over
> > > > > > > thousands of stocks
> > > > > > > > > the results were nearly all positives. But then, I
> > tested
> > > > that
> > > > > > > same system
> > > > > > > > > for the years 2000 to 2008, and that was
disappointing.
> > > > Even
> > > > > more
> > > > > > > > > disappointing from 2001 to 2003, another troubled
> > market
> > > > like
> > > > > the
> > > > > > > one we are
> > > > > > > > > in right now.
> > > > > > > > >
> > > > > > > > > So here I am, wondering where to go from now.
Aronson's
> > > > > > > excellent book
> > > > > > > > > talk about the importance of having a very large
sample
> > > of
> > > > > data.
> > > > > > > But the
> > > > > > > > > problem is: the larger the data, the
more "historic" it
> > > > gets
> > > > > and
> > > > > > > the less it
> > > > > > > > > seems to work.
> > > > > > > > >
> > > > > > > > > Is my system not working, or did the markets really
> > > > change?
> > > > > Do I
> > > > > > > need to
> > > > > > > > > make it more robust (that is, it MUST make profit
even
> > > > from
> > > > > 2001
> > > > > > > to 2003),
> > > > > > > > > or can I have complete faith in what happened in the
> > last
> > > > > year?
> > > > > > > > >
> > > > > > > > > All those questions... Would be nice to read what
you
> > > think
> > > > > > > about this.
> > > > > > > > >
> > > > > > > > > Louis
> > > > > > > > >
> > > > > > > > >
> > > > > > > >
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > >
> > > > >
> > > >
> > >
> >
> >
> >
>
------------------------------------
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