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Chuck,
I've been keeping 'grandkids on steroids' today, so I am a little
punch-drunk. I've read all the posts on this thread and have a couple
of comments.
Your database goes back to '85. As I relate to my own situation, my
average Positionsize in '85 was only a fraction of my Positionsize
today. I've been backtesting since the late 80's, and have used VOLUME
for two (2) purposes... (1) to gauge price action, and (2) to gauge
liquidity as it related to MY POSITION SIZE. On the second count, as
my personal positionsize increased, so did the average volume in the
markets.
As mentioned in subsequent posts on this subject, I've filtered both
my backtests and my actual trades based upon a volume multiple of my
Positionsize as opposed to x# of shares traded per day, irrespective
of price.
You and I have both stated that we backtest based upon 'fixed position
size'. And yet other people are not able to relate to that. They seem
to think that everyone 'compounds' their trades on a daily basis
depending upon their account size growth or demise as a direct result
of trading results. The truth (for me) is a compromise... As my
account size grows(whether thru trade profits or savings) I gradually
increase my Positionsize, but it is not directly proportional to
trading success.
So in my mind, increases in actual market trading volume are just
about proportional to increases in my own account size, and are
therefore a 'non-issue'.
Another issue for me is your multiple posts relating to prefering
non-split adjusted data.
Every time you've mentioned your preference for 'non-split adjusted
data', I've chosen to ignore the subject rather than to open it up as
an issue.
But it is time to ask the crucial question... if you really use
non-split adjusted data, how do you account for stock splits in your
backtest results where a 2 for 1, or 3 dor 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?
Just curious.
Phsst
groups.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 message
to this
> group saying that I always use one set of parameters across all
stocks 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, goes
through
> cycles and volume just keeps growing.
>
> The question that I have involves volume filtering. To me, it is
essential
> that volume filters be applied to actual volume and not backadjusted
volume.
> 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 and
early
> 90's.
>
> I have a solution in mind and would appreciate some input or
dialogue 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 volume
today is
> ten times more than it was in 1985. If I decide to filter today at
300,000
> shares, wouldn't it make sense to filter based on 30,000 shares in
1985. I
> can probably answer that question myself by saying that I don't
think 30,000
> would be an adequate filter in 1985. But I could scale it from
100,000 to
> 300,000 progressively between 1985 and 2003 based on mathematical
equation.
>
> 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 a
proposed
> system would have performed over a statistically meaningful period
of time.
> You can argue about the relevance of such information, but THEY
EXPECT 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 this
area.
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