Re: -->To Mike --> Re: [amibroker] Re: Aronson Detrending Market {Was Detrending... log}, AmiBroker Email List Archive

2008/3/25, Mike <sfclimbers@xxxxxxxxx>:

Louis,

Yes, you are confused. Reread the end of the first chapter where
Aronson explains that your strategy must still be run against the
real market data (i.e. your Yahoo data, NOT the detrended data). You
do not optimize a script over detrended data, you *validate* a script
against detrended data.

All your optimization work should still be done exactly the way you
would normally do it. Once you have found a strategy that you are
happy with, only the resulting strategy *signal* is multiplied
against the detrended market data (i.e. either a -1 for short or a +1
for long).

If you study my second script example, you will see that all it does
is multiply the detrended data of the first script by a +1 or a -1
based on the signal of a strategy which was run against real market
data for the same period.

Look at the chart of the sample second script I gave and see that the
signal is produced when the close crosses the offset of a moving
average. That signal was produced on real market data!

Read the code and understand what every single line is doing. Put
aside what you think it *should* be doing, and understand what it
actually *is* doing. Only then will you be able to make any use of it.

In summary:

If the detrended data from the first script gives the following log
percent daily change series:

-.01
+.03
-.02

This represents "the detrended market" giving a daily average of (-
.01 + .03 - .02)/3 = 0.

If your strategy, as added to the second script and run against your
Yahoo real market data, has you going Short on the first day then
Long on each of the next 2 days, the resulting new detrended series
becomes:

-.01 * -1 (i.e. short) = +.01
+.03 * +1 (i.e. long) = +.03
-.02 * +1 (i.e. long) = -.02

This represents what your strategy would capture from "the detrended
market" giving a daily average of (+.01 + .03 - .02)/3 = .0067, which
is greater than zero.

The question now becomes; Is a value of .0067 significant? When you
have enough daily observations, a t-test will give you the answer.

Mike

--- In amibroker@xxxxxxxxxxxxxxx, "Louis Préfontaine"
<rockprog80@xxx> wrote:
>
> Hi Mike,
>
> I am not sure to understand if your two scripts can actually see
the results
> of the rule on a detrended market. Correct me if I am wrong, but
the first
> script allow to see the avg. log (ALR), and the second shows the
buy/sell
> signals on the "detrended" new quotes, but it still doesn't help me
to test
> the rule on the detrended market.
>
> Maybe I am confused, but I still don't see how I can backtest my
rule on the
> "detrended" quotes (which can't really be applied to a rule which
is looking
> at "High" values when the "High" value in this case is a
constant). Right
> now, even after reading you again and again, I am still stuck with
one on
> side the "detrended" quotes in which only the close matters and the
> buying/selling signals without any way to optimize and backtest the
actual
> rules.
>
> Can you help me with that?
>
> Thanks,
>
> Louis
>
>
>
>
>
> 2008/3/25, Mike <sfclimbers@xxx>:

> >
> > Louis,
> >
> > Forget the book for a minute. Just try to understand the
objective.
> > Until you understand what is trying to be accomplished, you will
not
> > get anywhere.
> >
> > Given two sets of daily changes, can you say with confidence that
the
> > daily changes did not come from the same strategy?
> >
> > If the average daily change from the first set of numbers is zero,
> > and the average daily change from the second set of numbers is NOT
> > zero. Then, is the strategy that generated the second set of daily
> > changes really better than the first? Or, was it just a lucky
sample
> > from a strategy whose true daily change really is equal to the
first
> > (i.e. really is zero after all).
> >
> > The hypothesis is that the two sets of daily changes came from
> > equivalent strategies (i.e. both zero predictive ability).
> >
> > The test is to calculate the probability of drawing a sample
(whose
> > average was the non zero average found in the second set of daily
> > changes), assuming that the true average for the second strategy
is
> > the same as the true average for the first strategy (i.e both true
> > averages equal to zero).
> >
> > If the probability is less than your cutoff (e.g. 5%), then reject
> > the hypothesis and conclude that the strategy that returned the
non
> > zero average daily change must be better than the one that
generated
> > the zero average daily change (i.e. the strategy generating non
zero
> > daily change has predictive ability).
> >
> > You may find the following link helpful:
> > http://www.socialresearchmethods.net/kb/stat_t.php
> >
> > The first script generates the first set of daily changes (log
> > percent change) for the period being studied. These changes were
not
> > generated by any strategy. They are just a detrended
representation
> > of what the market actually did.
> >
> > The second script generates the second set of daily changes based
on
> > the buy sell signal of your strategy as applied against the actual
> > detrended market changes. They are the results of what your
strategy
> > would capture from the detrended market.
> >
> > Running the second script will not give you a performance number
per
> > se. It will merely allow you to calculate the second detrended
> > average daily return (i.e. log percent change, presumably non
zero)
> > that must be compared to that of the first script (zero).
> >
> > If you want to see the actual performance of your strategy (e.g.
> > compounded average return), you still need to look at the
AmiBroker
> > backtest results.
> >
> > Also, if you go back and re-read my earlier comments. After
running
> > the first script, the High holds the total of all daily changes
for
> > the period, the Lo holds the number of bars in the period.
Dividing
> > the first by the second gives you the average daily change for the
> > period, which is then subtracted from the *individual* daily
changes,
> > giving the *detrended* daily changes in the _Close_ such that if
you
> > were to take the average of the Close you would get zero. The only
> > values you are interested in are the Close values. The rest are
just
> > intermediary values used to calculate the Close.
> >
> > The second script applies the strategy signal against the Close of
> > the first script to generate the second set of daily changes
(again,
> > in the Close), the average of which you want to compare to the
> > results of the first.
> >
> > I haven't run against the full 25 year period to compare against
the
> > book for any given strategy. Depending on data providers, you may
get
> > very different numbers. Particularly if Aronson used the actual
> > contents of the SP-500 for each year, as opposed to only the
> > survivors that currently appear in today's index.
> >
> > Mike
> >
> > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com>, "Louis
> > Préfontaine"
> > <rockprog80@> wrote:
> > >
> > > Hi Mike,
> > >
> > > I took a break from the detrending procedure because I thought I
> > had a lot
> > > to learn before been able to apply it. Now I think I am ready
for
> > some more
> > > testing. I know you took a lot of time to explain how you were
> > able to do
> > > build the detrending process, and so I will try not to make
> > yourself repeat
> > > yourself.
> > >
> > > I did exactly what Aronson did to try the method. I used the
> > S&P500 from
> > > November 1980 (November 1, 1980) to Junes 2005 (June 30, 2005)
and
> > used the
> > > 91 days channel breakout:
> > >
> > > Buy=C>Ref (HHV (C,91),-1);
> > > Sell= C< Ref (LLV (C,91),-1);
> > > Short=Sell;
> > > Cover=Buy;
> > >
> > > I used Yahoo data and used your detrend script:
> > >
> > > procedure Detrend(compositeName) {
> > > local range; range = Status("barinrange");
> > > local raw; raw = log(Ref(Open, 2)/Ref(Open, 1));
> > > local total; total = 0;
> > > local count; count = 0;
> > > local offset; offset = 0;
> > >
> > > for (i = 0; i < BarCount; i++) {
> > > if (range[i]) {
> > > if (NOT IsNull(raw[i])) {
> > > count++;
> > > total += raw[i];
> > > }
> > > }
> > > }
> > >
> > > if (count > 0) {
> > > AddToComposite(IIF(range, raw, Null), "~" + compositeName, "O",
> > > atcFlagDefaults | atcFlagEnableInBackTest);
> > >
> > > offset = total/count;
> > > raw = IIF(IsNull(raw), offset, raw);
> > >
> > > AddToComposite(IIF(range, raw - offset, Null), "~" +
> > > compositeName, "C", atcFlagDefaults | atcFlagEnableInBackTest);
> > > AddToComposite(IIF(range, total, Null), "~" +
compositeName, "H",
> > > atcFlagDefaults | atcFlagEnableInBackTest);
> > > AddToComposite(IIF(range, offset, Null), "~" +
> > > compositeName, "L", atcFlagDefaults | atcFlagEnableInBackTest);
> > > AddToComposite(IIF(range, count, Null), "~" +
compositeName, "I",
> > > atcFlagDefaults | atcFlagEnableInBackTest);
> > > } else {
> > > AddToComposite(Null, "~" + compositeName, "X", atcFlagDefaults |
> > > atcFlagEnableInBackTest);
> > > }
> > > }
> > >
> > > Buy = Sell = Short = Cover = 0;
> > > Detrend(Name());
> > >
> > > The values I got (in the new file created by your script) are
the
> > following:
> > >
> > >
> > > Hi: 2.21199
> > > Lo: 0.000355397
> > >
> > > And that's why I am stuck.
> > >
> > > I tried to apply the 91-days channel breakout to the new file,
but
> > after
> > > reflexion it makes no sense because the Hi value in that file
is a
> > constant
> > > while in "real life" it isn't. So I am kind of stucked there,
still
> > > wondering how to apply the rule to the "detrended" data.
> > >
> > > If you could help me with that, I would appreciate a lot!
> > >
> > > Thanks,
> > >
> > > Louis
> > >
> > > p.s. For anyone actually trying to do this yourself without
having
> > read
> > > Aronson, Aronson says the result is +-4% annualized on detrended
> > data.
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > > 2008/3/3, Mike <sfclimbers@>:
> > > >
> > > > Louis,
> > > >
> > > > The first script (Detrend.afl) will detrend the market.
Nothing
> > more
> > > > to do. If you want to chart the results, open the symbol in a
> > chart
> > > > and plot the Close using line format (i.e. not bar or
> > candlesticks).
> > > > You will see what appears like an oscillator centered on zero,
> > since
> > > > all the values average out. Similarly, if you plotted a
> > histogram, of
> > > > the Close values, you would get a normal distribution
centered at
> > > > zero.
> > > >
> > > > You must code your own strategy into the second script,
replacing
> > the
> > > > example buy/sell/short/cover with your own logic.
> > > >
> > > > If you are not using a separate symbol to base your signals
on,
> > you
> > > > can remove the SetForeign/RestorePrice arrays. The parts that
are
> > > > most important are the setting of trade delays (since the
> > detrended
> > > > market data was produced with that assumption) and the
generating
> > of
> > > > a new composite.
> > > >
> > > > SetTradeDelays(1, 1, 1, 1);
> > > >
> > > > ...
> > > >
> > > > isLong = Flip(Buy, Sell);
> > > > isShort = Flip(Short, Cover);
> > > > market = Foreign("~" + Name(), "C", false);
> > > >
> > > > AddToComposite(IIF(isLong, 1 * market, 0), "~" + Name()
> > > > + "Return", "C", atcFlagDefaults | atcFlagEnableInBackTest);
> > > > AddToComposite(IIF(isShort, -1 * market, 0), "~" + Name()
> > > > + "Return", "C", atcFlagDefaults | atcFlagEnableInBackTest);
> > > >
> > > > Once your buy/sell/cover/short logic is in place, there is
nothing
> > > > more to do, the resulting composite (e.g. ~SP-500Return) will
> > already
> > > > have every thing you need. If you were to plot a histogram of
the
> > > > Close values, you want to see a normal distribution centered
on a
> > > > value greater than zero, indicating better than chance
results.
> > > >
> > > > Since the second script is *your* trading logic, yes, when
> > running it
> > > > the buy/sell signals and all AmiBroker performance data are
> > relevant.
> > > > If the system does not perform well based on your personal
> > criteria,
> > > > then you really don't care whether or not it is statistically
> > > > significant, because you wouldn't want to trade it anyway!
> > > >
> > > > The only thing that you need to do with the two composites is
to
> > > > compare the results.
> > > >
> > > > Take the mean of the detrended market (e.g. use excel to add
all
> > > > Close values found in ~SP-500 and divide by the number of
values)
> > and
> > > > compare it to the mean of your strategy results (again, add
all
> > Close
> > > > values of ~SP-500Results and divide by the number of values).
> > > >
> > > > If a t-test shows them to be statistically significant, you
> > *might*
> > > > be on to something. According to Aronson (by my
interpretation)
> > you
> > > > would then have to correct for data mining bias.
> > > >
> > > > Note that this is just one approach. Others prefer the much
> > simpler
> > > > walk forward analysis and visually evaluating the equity
curve.
> > Walk
> > > > forward and equity curve evaluation will rule out most of your
> > ideas
> > > > long before you ever need to start doing the statistical
> > validation.
> > > >
> > > > Delaying the statistics until after you've got a nice walk
forward
> > > > equity curve will get you on your way much quicker. Though, if
> > > > possible it would still be preferable to do the statistics at
that
> > > > time.
> > > >
> > > > Walk forward is built in to the most recent release of
AmiBroker,
> > and
> > > > also available in the free edition of Intelligent Optimizer
(see
> > IO
> > > > under Files section of this forum). My understanding is that
> > > > AmiBroker and IO treat the handling of trades accross
boundries
> > > > differently, so don't be surprised if you get slightly
different
> > > > results between them.
> > > >
> > > > Again, I'm no statistician, I wrote the code quickly in the
late
> > > > hours of the night, and I may not have understood correctly
the
> > > > process described in the book. So, use all of this as a
starting
> > > > point, but don't accept any of it as Gospel.
> > > >
> > > > Mike
> > > >
> > > > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%

40yahoogroups.com><amibroker%

> > 40yahoogroups.com>, "Louis
> > > > Préfontaine"
> > > > <rockprog80@> wrote:
> > > > >
> > > > > Hi again Mike,
> > > > >
> > > > > Ok I tried the formula without the "setbacktestmode" and it
> > seems
> > > > to work.
> > > > > I did use the first formula to get the log results of spx.xo
> > (S&P
> > > > 500) from
> > > > > January 9 2007 to December 31, 2007. Then I added all the
> > results
> > > > and
> > > > > divided by the number of days. -->But what do I do with this
> > > > number then?
> > > > > (I know it's the number I want to substract from each day
> > result,
> > > > but od I
> > > > > have to do it manually?)
> > > > >
> > > > > Then I applied the second formula to the same spx.xo for the
> > same
> > > > days.
> > > > > When clicking on "backtesting" buying/selling orders were
> > issued.
> > > > Are those
> > > > > relevant, or do I simply need to look at what's in the new
> > > > ~spx.xoReturn?
> > > > > (I changed DTX--X for spx.xo everywhere in the formula). And
> > when
> > > > I open
> > > > > this ~spx.xoReturn I get the detrended results but how to
use
> > them
> > > > with the
> > > > > actual stock? I mean: I get all those 0. 000x numbers; how
can I
> > > > actually
> > > > > use my trading system to test my positive/negative bias with
> > this?
> > > > >
> > > > > Thank you a lot for your help. Your formulas really rock.
> > Thanks!
> > > > >
> > > > > Louis
> > > > >
> > > > >
> > > > >
> > > > > 2008/3/2, Mike <sfclimbers@>:
> > > > > >
> > > > > > I've provided an example of how to use it below. I'm still
> > > > working on
> > > > > > this myself, so take all of this with a measure of
caution. I
> > have
> > > > > > not yet gone through all results to verify that there
aren't
> > any
> > > > > > bugs...
> > > > > >
> > > > > > If I understand Aronson correctly, after you have have
> > detrended
> > > > the
> > > > > > market for the desired period, you then apply your trading
> > > > strategy
> > > > > > to generate new log daily returns by multiplying your
system
> > state
> > > > > > (+1 for long, -1 for short) by the detrended log daily
> > returns.
> > > > You
> > > > > > then take the mean log daily return generated by your
> > strategy and
> > > > > > compare it to the mean log daily return of the detrended
daily
> > > > > > returns (i.e. zero).
> > > > > >
> > > > > > The purpose is to remove the "conjoint effect of position
> > bias and
> > > > > > trend" from your strategy results.
> > > > > >
> > > > > > If the two means are found to be different (i.e. your
strategy
> > > > > > generates non zero mean) with statistical significance
(e.g.
> > using
> > > > > > student's t-test), then you may conclude* that the returns
> > > > generated
> > > > > > by the strategy are not purely by chance.
> > > > > >
> > > > > > I use a "*" there because Aronson continues to say that a
> > simple
> > > > t-
> > > > > > test is NOT sufficient if you have used data mining to
produce
> > > > your
> > > > > > strategy. In that case, your results will still include a
data
> > > > mining
> > > > > > bias that must be removed by applying the Bootstrap method
> > with
> > > > > > White's reality check, or else the Monte Carlo analysis.
> > > > > >
> > > > > > Now for what you're really looking for, a concrete
example :)
> > > > > >
> > > > > > Still in Chapter 1 of the book, Aronson refers to an
example
> > of
> > > > > > taking signals based on the Dow Jones Transportation
Average
> > (DTX-
> > > > -X
> > > > > > by my data provider), and applying those signals to trade
the
> > SP-
> > > > 500.
> > > > > > The strategy has a long bias and is defined as follows:
> > > > > >
> > > > > > Draw a moving average of DTX--X
> > > > > > Draw an upper band 3% above the moving average
> > > > > > Draw a lower band 3% below the moving average
> > > > > > Short the SP-500 when the DTX--X crosses below the lower
band.
> > > > > > Long the SP-500 at all other times.
> > > > > >
> > > > > > I believe that I have captured these rules and added
> > backtesting
> > > > > > support in the script below. After running the backtest,
a new
> > > > symbol
> > > > > > will be added to your system holding the returns in the
Close
> > > > field
> > > > > > (e.g. ~SP-500Returns).
> > > > > >
> > > > > > Aronson does not say what the moving average should be.
It is
> > > > > > actually a bit of a challenge to find a period where the
> > above is
> > > > > > profitable! However, after optimizing for the moving
average,
> > I
> > > > found
> > > > > > that the period 4/27/1998 - 12/31/2000 will show you fully
> > > > invested
> > > > > > for the entire range with a 13.69% CAR.
> > > > > >
> > > > > > Applying my Detrend.afl script (posted in my last note)
> > against
> > > > the
> > > > > > SP-500 over those dates will give a mean log daily return
of
> > > > 2.40265E-
> > > > > > 10 (i.e. zero).
> > > > > >
> > > > > > You can compute the mean log daily return by opening the
Quote
> > > > Editor
> > > > > > (e.g. select ~SP-500 in symbols tree, then use Symbol |
Quote
> > > > > > Editor... menu item) and copying all the data into Excel,
then
> > > > > > summing all the Close values for the given date range and
> > > > dividing by
> > > > > > the number of quotes in that range (678 in this example).
> > > > > >
> > > > > > Running the script below against the SP-500 for the same
dates
> > > > will
> > > > > > will give a mean log daily return of 0.000428057
> > > > > >
> > > > > > Again, copy ~SP-500Returns from Quote Editor into Excel
and
> > > > compute
> > > > > > the mean from the Close data.
> > > > > >
> > > > > > Peforming a Student's T-Test over the two sets of log
daily
> > > > returns,
> > > > > > assuming a shared variance and hypothesizing a shared
mean of
> > > > zero,
> > > > > > returns a one tailed p-value of 0.272346792. This is well
> > above
> > > > 0.05
> > > > > > (the p-value required to reject the hypothesis with 95%
> > > > confidence)
> > > > > > and so we cannot reject the hypothesis.
> > > > > >
> > > > > > In other words, despite a 13.69% CAR over the period
tested,
> > the
> > > > > > strategy is no better than chance alone and thus should
not be
> > > > traded.
> > > > > >
> > > > > > If the p-value had been .05 or less, we still could not
> > conclude
> > > > > > (according to Aronson) that the strategy was any good
because
> > I
> > > > used
> > > > > > Optimization (MA period ranging from 5 to 200 increments
of
> > 5) to
> > > > > > find the best rule (data mining bias) and because I used
the
> > 3%
> > > > band
> > > > > > width suggested in the book (snooping bias - have no idea
how
> > much
> > > > > > optimization was applied to reach that number). Applying
Monte
> > > > Carlo
> > > > > > analysis would remove the data mining bias (my next
effort).
> > > > There's
> > > > > > no getting around the snooping bias.
> > > > > >
> > > > > > 1. Copy paste the script below to a file on your machine
(say
> > > > > > c:\Program Files\AmiBroker\Formulas\Custom\Results.afl).
Make
> > sure
> > > > > > that you correct any formatting that gets messed up from
this
> > > > post,
> > > > > > such that AmiBroker likes everything. Use the Tools |
Verify
> > > > Syntax
> > > > > > menu from the code editor.
> > > > > >
> > > > > > 2. Open a chart on the symbol that you want to detrend.
For
> > > > example;
> > > > > > Aronson used the SP-500 for all his tests.
> > > > > >
> > > > > > 3. Open the Automatic Analysis Window
> > > > > >
> > > > > > 4. Click the "Pick" button and select the script that you
just
> > > > saved
> > > > > > (i.e. Results.afl).
> > > > > >
> > > > > > 5. Select "current symbol" for the Apply To.
> > > > > >
> > > > > > 6. Select "from" for the Range, and enter a from date and
a to
> > > > date
> > > > > > (e.g. from 4/27/1998 to 12/31/2000).
> > > > > >
> > > > > > 7. Click on Backtest
> > > > > >
> > > > > > A new symbol will be added to your system having the same
> > name as
> > > > the
> > > > > > original, but prefixed with a "~" and appended
with "Return",
> > for
> > > > > > example "~SP-500Return". This symbol will appear in Market
> > 253 and
> > > > > > contain detrended performance results for the range
selected
> > and
> > > > > > zeros for all other dates.
> > > > > >
> > > > > > For each bar in the detrended symbol, the information
will be
> > > > > > arranged as follows:
> > > > > >
> > > > > > Close: The detrended log daily return of the strategy
(i.e.
> > Pos0
> > > > x log
> > > > > > (Open2/Open1) - ALR).
> > > > > >
> > > > > > Note: As per Aronson, Pos0 refers to the strategy signal
(+1
> > for
> > > > > > long, -1 for short), Open2 refers to the Open two days
from
> > now,
> > > > > > Open1 refers to the Open one day from now, ALR refers to
the
> > > > average
> > > > > > log daily return of the market (not your strategy results)
> > over
> > > > the
> > > > > > period being detrended.
> > > > > >
> > > > > > As always, comments, corrections and enhancements are
> > welcomed.
> > > > > >
> > > > > > Again, I'm a software developer, not a statistics guy, and
> > this
> > > > is my
> > > > > > interpretation of the book. Do your own research before
> > accepting
> > > > > > taking this as acurate.
> > > > > >
> > > > > > If anyone else has done any work in this area, I would
very
> > much
> > > > like
> > > > > > to hear if their approach agrees with my interpretation.
> > > > > >
> > > > > > Thanks,
> > > > > >
> > > > > > Mike
> > > > > >
> > > > > > SetTradeDelays(1, 1, 1, 1); // All trades on next Open
after
> > > > > > EOD signal
> > > > > > SetBacktestMode(backtestRegular); // One symbol, no
redundant
> > > > signals
> > > > > > SetOption("InitialEquity", 100000);
> > > > > > SetOption("AccountMargin", 100);
> > > > > >
> > > > > > Plot(Close, "Close", colorBlue, styleLine);
> > > > > >
> > > > > > SetForeign("DTX--X");
> > > > > > center = MA(Close, Optimize("MA", 40, 5, 200, 5));
> > > > > > upper = 1.03 * center;
> > > > > > lower = .97 * center;
> > > > > >
> > > > > > Buy = Cross(Close, lower);
> > > > > > Sell = Cross(lower, Close);
> > > > > > Short = Sell;
> > > > > > Cover = Buy;
> > > > > >
> > > > > > Plot(Close, "DTX--X Close", colorYellow, styleLine);
> > > > > > Plot(upper, "DTX--X Upper", colorGreen, styleDashed);
> > > > > > Plot(center, "DTX--X MA", colorPink, styleLine);
> > > > > > Plot(lower, "DTX--X Lower", colorRed, styleDashed);
> > > > > >
> > > > > > RestorePriceArrays();
> > > > > >
> > > > > > BuyPrice = SellPrice = ShortPrice = CoverPrice = Open;
> > > > > >
> > > > > > PlotShapes(shapeUpArrow * Buy, colorGreen, 0, Close, -30);
> > > > > > PlotShapes(shapeDownArrow * Sell, colorRed, 0 , Close, -
30);
> > > > > > PlotShapes(shapeHollowDownArrow * Short, colorRed, 0 ,
> > Close, -
> > > > 40) ;
> > > > > > PlotShapes(shapeHollowUpArrow * Cover, colorGreen, 0,
Close, -
> > 40);
> > > > > >
> > > > > > isLong = Flip(Buy, Sell);
> > > > > > isShort = Flip(Short, Cover);
> > > > > > market = Foreign("~" + Name(), "C", false);
> > > > > >
> > > > > > AddToComposite(IIF(isLong, 1 * market, 0), "~" + Name()
> > > > > > + "Return", "C", atcFlagDefaults |
atcFlagEnableInBackTest);
> > > > > > AddToComposite(IIF(isShort, -1 * market, 0), "~" + Name()
> > > > > > + "Return", "C", atcFlagDefaults |
atcFlagEnableInBackTest);
> > > > > >
> > > > > > --- In amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com><amibroker%
> > 40yahoogroups.com><amibroker%
> > > > 40yahoogroups.com>, "Louis
> > > > > > Préfontaine"
> > > > > > <rockprog80@> wrote:
> > > > > > >
> > > > > > > Hi again,
> > > > > > >
> > > > > > > I've searched thru the manual and I think that += is
simply
> > a
> > > > > > shortcut. I
> > > > > > > wrote total = total+ raw[i]; instead and there is no
more
> > error!
> > > > > > >
> > > > > > > I did exactly as you said and got the sign with those
huge
> > bars
> > > > all
> > > > > > topping
> > > > > > > at 0.267615. I think I understand what you say, but
what is
> > OI?
> > > > > > >
> > > > > > > The thing is: I am not sure how to use this. I think
what I
> > need
> > > > > > is to make
> > > > > > > an average of all this data and then subtract this
average
> > from
> > > > > > each day log
> > > > > > > of the actual stock to detrend. Am I correct? Would you
be
> > kind
> > > > > > enough to
> > > > > > > give me some tips about how to use this new information
to
> > > > actually
> > > > > > backtest
> > > > > > > one of my rules and see how it performs when it is
> > detrended?
> > > > > > >
> > > > > > > Thanks a lot!
> > > > > > >
> > > > > > > Louis
> > > > > > >
> > > > > > > 2008/3/2, Louis Préfontaine <rockprog80@>:
> > > > > > > >
> > > > > > > > Hi Mike,
> > > > > > > >
> > > > > > > > Thank you so much for your reply!
> > > > > > > >
> > > > > > > > This is EXACTLY what I am looking for, from the
Aronson's
> > > > book!
> > > > > > > >
> > > > > > > > I can't wait to make it work... Right now there is a
small
> > > > > > problem with
> > > > > > > > the formula... I get an error message for this parti
> > total +=
> > > > raw
> > > > > > [i]; Ln12:
> > > > > > > > col:8:Error 30. Syntax error.
> > > > > > > >
> > > > > > > > I tried to change the += for = "" == and it works...
Is it
> > > > > > possible that
> > > > > > > > the AB version that I have doesn't recognize the +=?
Or
> > maybe
> > > > > > there is an
> > > > > > > > error with the +=? Is it possible to get to the same
> > result in
> > > > > > any other
> > > > > > > > way?
> > > > > > > >
> > > > > > > > Thanks a lot!
> > > > > > > >
> > > > > > > > Louis
> > > > > > > >
> > > > > > > > 2008/3/2, Mike <sfclimbers@>:
> > > > > >
> > > > > > > > >
> > > > > > > > > Hi,
> > > > > > > > >
> > > > > > > > > Based on your formula, I assume that you are
referring
> > to
> > > > > > Chapter 1
> > > > > > > > > of David Aronson's book: Evidence Based Technical
> > Analysis.
> > > > > > > > >
> > > > > > > > > That being the case, I am providing a script below.
> > > > > > > > >
> > > > > > > > > However, I believe that the formula that you
originally
> > > > posted
> > > > > > is not
> > > > > > > > > correct. Aronson's formula calls for multiplying
your
> > > > boolean
> > > > > > > > > strategy signal (i.e. +1 for long vs. -1 for short)
by
> > the
> > > > > > detrended
> > > > > > > > > daily returns, *not* the Close by the returns!
> > > > > > > > >
> > > > > > > > > Also, the book does not go into detail for tri-state
> > > > strategies
> > > > > > (i.e.
> > > > > > > > > long/neutral/short) nor for long/neutral or
> > short/neutral
> > > > > > strategies.
> > > > > > > > > I'm assuming that plugging in a signal value of 0
would
> > be
> > > > > > acceptable
> > > > > > > > > for a neutral position, but haven't researched that
> > yet. So,
> > > > > > just be
> > > > > > > > > careful how you use the data once you've detrended
it.
> > > > > > > > >
> > > > > > > > > Anyway, here is a script that I believe will
detrend the
> > > > market
> > > > > > > > > returns as per the book. Currently, the script is
> > intended
> > > > for
> > > > > > > > > detrending a single symbol. I have not yet got
around to
> > > > making
> > > > > > it
> > > > > > > > > work against a watchlist of symbols (coming soon).
> > > > > > > > >
> > > > > > > > > 1. Copy paste the script below to a file on your
machine
> > > > (say
> > > > > > > > > c:\Program
Files\AmiBroker\Formulas\Custom\Detrend.afl).
> > > > Make
> > > > > > sure
> > > > > > > > > that you correct any formatting that gets messed up
from
> > > > this
> > > > > > post,
> > > > > > > > > such that AmiBroker likes everything. Use the Tools
|
> > Verify
> > > > > > Syntax
> > > > > > > > > menu from the code editor.
> > > > > > > > >
> > > > > > > > > 2. Open a chart on the symbol that you want to
detrend.
> > For
> > > > > > example;
> > > > > > > > > Aronson used the SP-500 for all his tests.
> > > > > > > > >
> > > > > > > > > 3. Open the Automatic Analysis Window
> > > > > > > > >
> > > > > > > > > 4. Click the "Pick" button and select the script
that
> > you
> > > > just
> > > > > > saved
> > > > > > > > > (i.e. Detrend.afl).
> > > > > > > > >
> > > > > > > > > 5. Select "current symbol" for the Apply To.
> > > > > > > > >
> > > > > > > > > 6. Select "from" for the Range, and enter a from
date
> > and a
> > > > to
> > > > > > date
> > > > > > > > > (e.g. from 1/1/2007 to 12/31/2007).
> > > > > > > > >
> > > > > > > > > 7. Click on Backtest
> > > > > > > > >
> > > > > > > > > A new symbol will be added to your system having the
> > same
> > > > name
> > > > > > as the
> > > > > > > > > original, but prefixed with a "~", for example "~SP-
> > 500".
> > > > This
> > > > > > symbol
> > > > > > > > > will appear in Market 253 and contain detrended
market
> > > > > > information
> > > > > > > > > for the range selected (e.g. all of 2007 as above)
and
> > zeros
> > > > > > for all
> > > > > > > > > other dates.
> > > > > > > > >
> > > > > > > > > For each bar in the detrended symbol, the
information
> > will
> > > > be
> > > > > > > > > arranged as follows:
> > > > > > > > >
> > > > > > > > > Open: The unadjusted log daily return (i.e. log
> > > > (Open2/Open1)).
> > > > > > > > >
> > > > > > > > > High: The total sum of all unadjusted log daily
returns.
> > > > > > > > >
> > > > > > > > > Low: The average of all unadjusted log daily returns
> > (i.e.
> > > > ALR).
> > > > > > > > >
> > > > > > > > > Close: The detrended log daily return (i.e. log
> > > > (Open2/Open1) -
> > > > > > ALR).
> > > > > > > > >
> > > > > > > > > OI: The number of bars over which the data has been
> > > > detrended.
> > > > > > > > >
> > > > > > > > > Note: As per Aronson, Open2 refers to the Open two
days
> > from
> > > > > > now,
> > > > > > > > > Open1 refers to the Open one day from now, ALR
refers
> > to the
> > > > > > average
> > > > > > > > > log return over the period being detrended.
> > > > > > > > >
> > > > > > > > > Note: I have used the natural logarithm in my code
(i.e.
> > > > ln), as
> > > > > > > > > opposed to the base 10 logarithm (i.e. log10). I
don't
> > know
> > > > if
> > > > > > that
> > > > > > > > > makes a difference.
> > > > > > > > >
> > > > > > > > > Note: To find your detrended strategy results, you
still
> > > > must
> > > > > > write
> > > > > > > > > your own code to calculate which of the detrended
daily
> > > > returns
> > > > > > your
> > > > > > > > > strategy would pick up, and which sign to use (+/-)
when
> > > > > > multiplying
> > > > > > > > > by the detrended return for that day.
> > > > > > > > >
> > > > > > > > > Note: I ran this script against SP-500 for the
entire
> > year
> > > > of
> > > > > > 2007.
> > > > > > > > > With my data source, the average detrended log daily
> > return
> > > > > > (i.e. all
> > > > > > > > > the Close values of ~SP-500 divided by 251 actual
> > trading
> > > > days)
> > > > > > ended
> > > > > > > > > up being -6.00797E-10 which is effectively zero.
So, I'm
> > > > > > assuming
> > > > > > > > > that it works.
> > > > > > > > >
> > > > > > > > > Corrections and enhancements welcomed :)
> > > > > > > > >
> > > > > > > > > Mike
> > > > > > > > >
> > > > > > > > > procedure Detrend(compositeName) {
> > > > > > > > > local range; range = Status("barinrange");
> > > > > > > > > local raw; raw = log(Ref(Open, 2)/Ref(Open, 1));
> > > > > > > > > local total; total = 0;
> > > > > > > > > local count; count = 0;
> > > > > > > > > local offset; offset = 0;
> > > > > > > > >
> > > > > > > > > for (i = 0; i < BarCount; i++) {
> > > > > > > > > if (range[i]) {
> > > > > > > > > if (NOT IsNull(raw[i])) {
> > > > > > > > > count++;
> > > > > > > > > total += raw[i];
> > > > > > > > > }
> > > > > > > > > }
> > > > > > > > > }
> > > > > > > > >
> > > > > > > > > if (count > 0) {
> > > > > > > > > AddToComposite(IIF(range, raw, Null), "~" +
> > > > compositeName, "O",
> > > > > > > > > atcFlagDefaults | atcFlagEnableInBackTest);
> > > > > > > > >
> > > > > > > > > offset = total/count;
> > > > > > > > > raw = IIF(IsNull(raw), offset, raw);
> > > > > > > > >
> > > > > > > > > AddToComposite(IIF(range, raw - offset, Null), "~" +
> > > > > > > > > compositeName, "C", atcFlagDefaults |
> > > > atcFlagEnableInBackTest);
> > > > > > > > > AddToComposite(IIF(range, total, Null), "~" +
> > > > > > compositeName, "H",
> > > > > > > > > atcFlagDefaults | atcFlagEnableInBackTest);
> > > > > > > > > AddToComposite(IIF(range, offset, Null), "~" +
> > > > > > > > > compositeName, "L", atcFlagDefaults |
> > > > atcFlagEnableInBackTest);
> > > > > > > > > AddToComposite(IIF(range, count, Null), "~" +
> > > > > > compositeName, "I",
> > > > > > > > > atcFlagDefaults | atcFlagEnableInBackTest);
> > > > > > > > > } else {
> > > > > > > > > AddToComposite(Null, "~" + compositeName, "X",
> > > > atcFlagDefaults |
> > > > > > > > > atcFlagEnableInBackTest);
> > > > > > > > > }
> > > > > > > > > }
> > > > > > > > >
> > > > > > > > > Buy = Sell = Short = Cover = 0;
> > > > > > > > > Detrend(Name());
> > > > > > > > >
> > > > > > > > > --- In amibroker@xxxxxxxxxxxxxxx<amibroker%
40yahoogroups.com><amibroker%
> > 40yahoogroups.com><amibroker%
> > > > 40yahoogroups.com><amibroker%40yahoogroups.com>,
> > > > > > > > > "louisprefontaine" <rockprog80@>
> > > > > > > > > wrote:
> > > > > > > > > >
> > > > > > > > > > Anybody can help?
> > > > > > > > > >
> > > > > > > > > > Thanks,
> > > > > > > > > >
> > > > > > > > > > Louis
> > > > > > > > > >
> > > > > > > > > > --- In amibroker@xxxxxxxxxxxxxxx<amibroker%
40yahoogroups.com><amibroker%
> > 40yahoogroups.com><amibroker%
> > > > 40yahoogroups.com><amibroker%
> > > > > > 40yahoogroups.com>, "Louis
> > > > > > > > > Préfontaine" <rockprog80@>
> > > > > > > > > > wrote:
> > > > > > > > > > >
> > > > > > > > > > > I am trying to build a formula to "detrend" the
> > market.
> > > > > > > > > > >
> > > > > > > > > > > What I want to set is something like this
> > > > > > > > > > >
> > > > > > > > > > > Close of day 0 * ( log (open day2/open day 1) -
> > average
> > > > log
> > > > > > > > > > return of
> > > > > > > > > > > every day of the data available.
> > > > > > > > > > >
> > > > > > > > > > > Anybody can do that?
> > > > > > > > > > >
> > > > > > > > > > > Thanks,
> > > > > > > > > > >
> > > > > > > > > > > Louis
> > > > > > > > > > >
> > > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > >
> > > > > > > >
> > > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > >
> > > >
> > > >
> > > >
> > >
> >
> >
> >
>