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<FONT face=Arial color=#0000ff
size=2>Whew... at last someone asked the question.
<FONT face=Arial color=#0000ff
size=2>
Phsst
asked me: if you
really use non-split adjusted data, how do you account for stock splits in
yourbacktest results where a 2 for 1, or 3 for 2, or 4 for 5 stock split has
occurred. For example if your system generates a trade when the stock price is
at 50, and a 2 for 1 split occurs dropping the price to 25 (reducing your
position by one-half), how in the heck do you account for the price reduction
which did not REALLY account for a loss in your 'real life account' but which
devasted your backtest results?
<FONT
face="Courier New" color=#000000 size=3>
<FONT
face="Courier New" color=#000000 size=3>
I've
actually commented on this previously, but I always felt like the explanation
got lost in the shuffle.
<FONT face=Arial color=#0000ff
size=2>
For
filtering purposes, I use ACTUAL prices and ACTUAL volumes. To me,
anything else is a waste of time. I've given hundreds examples on
this board, but I will give some here for completeness:
<FONT face=Arial color=#0000ff
size=2>
DELL
was actually trading at $9.12 on 19880817. I'm sure you are showing
a price of $0.09 or somthing similar in your data.
<FONT face=Arial color=#0000ff
size=2>
YHOO
was actually trading at $33.00 on 19960412. I'm sure you are showing
a price of $2.75 or something similar in your data.
<FONT face=Arial color=#0000ff
size=2>
<FONT face=Arial color=#0000ff
size=2>Volumes, as shown in most data vendor's databases are off by the same
magnitude.
<FONT face=Arial color=#0000ff
size=2>
How
can anyone possibly use backadjusted prices and/or volumes for
filtering?
<FONT face=Arial color=#0000ff
size=2>
Now,
to answer your direct question. While I use actual prices and
volumes for filtering, I use backadjusted prices for all trading
calculations. As you suggest, that's the only way to compensate for
splits, dividends, cash payouts, etc. when calculating indicators and/or profit
and losses once you actually trade the stock.
<FONT face=Arial color=#0000ff
size=2>
Here
again, the accuracy of the data is paramount. Many stocks are backadjusted
to the point where most data suppliers might show a stock trading for $0.10 for
almost a month. Two decimal digits simply isn't accurate
enough. My database carries eight decimal digits for the
backadjusted data. That way, I can see that a stock went from
0.10000000 to 0.10600000 to 0.10900000, etc. These are huge
moves that disappear in the data of most data vendors.
<FONT face=Arial color=#0000ff
size=2>
Are
you aware, for instance, that VectorVest rounded backadjusted prices to the
nearest ten cents in some of its early data? It's bad enough that
the data is stored with only two decimal digits, but to the nearest ten
cents? Useless.
<FONT face=Arial color=#0000ff
size=2>
I hope
that answers your question and I'm relieved that someone actually asked
it. I'm afraid that I can not apologise for being so pedantic when
it comes to the accuracy of data.
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<BLOCKQUOTE
>
<FONT face="Times New Roman"
size=2>-----Original Message-----From: Phsst
[mailto:phsst@xxxxxxxxx]Sent: Saturday, June 21, 2003 12:24
AMTo: amibroker@xxxxxxxxxxxxxxxSubject: [amibroker] Re:
Historical volume filteringChuck,I've been
keeping 'grandkids on steroids' today, so I am a littlepunch-drunk. I've
read all the posts on this thread and have a coupleof
comments.Your database goes back to '85. As I relate to my own
situation, myaverage Positionsize in '85 was only a fraction of my
Positionsizetoday. I've been backtesting since the late 80's, and have
used VOLUMEfor two (2) purposes... (1) to gauge price action, and (2) to
gaugeliquidity as it related to MY POSITION SIZE. On the second count,
asmy personal positionsize increased, so did the average volume in
themarkets. As mentioned in subsequent posts on this subject, I've
filtered bothmy backtests and my actual trades based upon a volume
multiple of myPositionsize as opposed to x# of shares traded per day,
irrespectiveof price.You and I have both stated that we backtest
based upon 'fixed positionsize'. And yet other people are not able to
relate to that. They seemto think that everyone 'compounds' their trades
on a daily basisdepending upon their account size growth or demise as a
direct resultof trading results. The truth (for me) is a
compromise... As myaccount size grows(whether thru trade profits or
savings) I graduallyincrease my Positionsize, but it is not directly
proportional totrading success.So in my mind, increases in actual
market trading volume are justabout proportional to increases in my own
account size, and aretherefore a 'non-issue'.Another issue for me
is your multiple posts relating to preferingnon-split adjusted
data.Every time you've mentioned your preference for 'non-split
adjusteddata', I've chosen to ignore the subject rather than to open it up
asan issue.But it is time to ask the crucial question... if you
really usenon-split adjusted data, how do you account for stock splits in
yourbacktest results where a 2 for 1, or 3 dor 2, or 4 for 5 stock
splithas occurred. For example if your system generates a trade when
thestock price is at 50, and a 2 for 1 split occurs dropping the price
to25 (reducing your position by one-half), how in the heck do
youaccount for the price reduction which did not REALLY account for
aloss in your 'real life account' but which devasted your backtest
results?Just curious.Phsstgroups.com,
"Chuck Rademacher" <chuck_rademacher@x> wrote:> I was about to
send this email to "b", but I would welcome comments from> anyone else
interested in such historical work.> > At the risk of having
some of you ask why it matters, my backtesting> generally goes back to
1985. Just yesterday, I posted a messageto this>
group saying that I always use one set of parameters across allstocks
and> across all timeframes. One of the downsides of this
approach(perhaps) is> that volume has changed over
time. I suppose that one could argue that> volatility
changes over time as well. Volatility, however,
goesthrough> cycles and volume just keeps growing.> >
The question that I have involves volume filtering. To me, it
isessential> that volume filters be applied to actual volume and
not backadjustedvolume.> My concern, however, is that if I apply a
filter requiring an average of> 300,000 shares, I don't get very many
hits back in the late 80's andearly> 90's.> > I have
a solution in mind and would appreciate some input ordialogue on
the> subject. It seems to me that volume filtering
should be based on some> percentage of the total volume of all NYSE
stocks (for instance). I> haven't done my homework yet, but
let's say that the average volumetoday is> ten times more than it
was in 1985. If I decide to filter today at300,000>
shares, wouldn't it make sense to filter based on 30,000 shares
in1985. I> can probably answer that question myself by
saying that I don'tthink 30,000> would be an adequate filter in
1985. But I could scale it from100,000 to> 300,000
progressively between 1985 and 2003 based on mathematicalequation.>
> You may ask why backtesting to 1985 (or any other date) is
important.> There are dozens of reasons, but the most important reason
to me is that> prospective investors in any funds that I manage want to
see how aproposed> system would have performed over a statistically
meaningful periodof time.> You can argue about the relevance of
such information, but THEYEXPECT TO> SEE IT. For the
record, I also think that it is very important.> > I welcome
comments from anyone with an interest or knowledge in
thisarea.Send
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