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Apologies.
Better use the correct syntax.
Buy = DayOfWeek() == 1;
Sell = DayOfWeek() == 5;
BuyPrice = O;
SellPrice = C;
--- In amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@xxx> 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, "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, "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, "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>, "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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