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let me throw the discussion of optimization in another direction for a sec,
into equity feedback, something I've been looking at a lot lately.
just to be clear what I mean, the idea is to pick your trades from among the
stocks (or whatever) that have historically done the best at that same
method, or something as similar to it as possible. for example (don't put
money on this!), say you went long or short when MACD(13, 21) crossed zero,
but picked stocks with the most strongly positive returns to date by that
method.
in a sense, this amounts to automatic optimization, by the most seemingly
relevant means possible: grading performance under the same system. another
way to look at it is that it automatically selects a universe of stocks to
run on, including only the ones that perform best with the strategy used.
given those general mechanics, you'd think this would produce good results
frequently, with a variety of common indicators, over many time frames and
universes of equities. my experience is that this isn't the case. on the
contrary, for example, it's hard to find system that are juicily profitable
from '92 to present on the NASDAQ 100. works better on the whole NASDAQ, I
think because a larger total universe has a better chance of containing some
stellar choices, but it's still hard to do outstandingly well.
what does it mean if a strategy doesn't perform well when managed like this?
seems like one of two things: either not very many tradable stocks
(sufficient liquidity and price etc) perform well with the strategy, or,
past performance with the strategy doesn't correlate well with future
performance.
if not many stocks do well with the strategy, it's just not that generally
applicable. perhaps it has parameters that need to be tailored more to each
individual stock or time frame, more than the algorithm itself does. if so,
the next direction to pursue might be more auto-compensating metrics within
the strategy. OTOH, the more complex and rube goldberg things get, the more
they seem like fragilely over-optimized special cases, unlikely on principle
to be robust beyond the specific conditions under which they were tested.
on the other hand, what if past performance doesn't predict future
performance? maybe some other metrics would, but how would you know? any
backtests you did to find that out couldn't be relied on to predict the
future themselves.
is there a third hand? or have I screwed up my equity feedback code, and
everyone else here has tons of highly profitable systems like this that
they're not talking about?
thoughts?
dave
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