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I think proper exits with money management are key to success. Am
trying something with ATR...but this is a toughie.
--- In amibroker@xxxxxxxxxxxxxxx, "Dave Merrill" <dmerrill@xxxx>
wrote:
> I've been working on a new (to me) way of evaluating possible entry
methods,
> as distinct from exit methods. I've got code in the works, but I
thought I'd
> run the concept by folks here for some feedback while I finalize
it. here's
> the basic idea:
>
>
> on the long side, profits come from selling at a higher price than
you
> bought. so, a good entry signal is one where the stock frequently
rises
> reasonably soon after a buy signal occurs. with the exception of a
permanent
> down-trend or individual stock fatalities, *everything* goes up
eventually,
> so the question really is, how soon after buys does price rise, and
how far?
>
> this exploration makes two assumptions, after Steve Karnish: 1) a
relatively
> tight stoploss is needed to limit risk and mental pain, and 2)
we're looking
> for short term signals, to generate a statistically meaningful
number of
> trades, and to limit the opportunity cost of continuing to hold a
position
> that's treading water. specifically, we'll sell anything that hits
a 13%
> stoploss or is still held after 15 days. these aren't the only
possible
> assumptions, but they're what's used here.
>
> given those assumptions, the quality of an entry signal can be
evaluated as
> the peak percentage rise in price, after commissions, before one of
those
> two basic exit conditions occurs. to actually trade the signal
profitably,
> you might well need to exit before the loss or time stops took you
out, and
> the design and testing of an exit signal specific to a given entry
model is
> beyond the scope of this effort. however, unless price reaches a
healthy
> profit fairly often before those basic stop exits happen, the entry
signal
> itself isn't useful; you could do better with random entries.
>
> peak price rise before those time or loss stops are hit can be
evaluated for
> any bar, not just when there's a buy signal. the efficiency of a
buy signal
> can then be expressed as the percentage ratio of the average peak
rise on
> buy bars to that of all bars. greater than 100% means it entered on
bars
> with higher than average gain before stopping out, less than 100%,
lower
> than average.
>
> to design a system using this idea, you'd need to select a set of
issues and
> a date range to test, evaluate a variety of entry methods on this
basis,
> then test a variety of exit signals with the top entry methods and
choose
> the best combination.
>
>
> make sense? is this a known concept that others have explored? other
> thoughts?
>
> dave
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