iggybacking is an efficient way to align trading
strategies with these relentless computer programs.
After identifying their signature early in the
session; sell all the rallies or buy all the dips,
as the case may be. Assume no reversal will take
place that day, as long as advance-decline number
stays on the far side of plus or minus 1200 on both
exchanges.
I know what you're thinking. But in reality, these
algorithms are easy for most traders to see in
action. In fact, I'm amazed that folks still ask me
to explain what they look like because their
intraday footprint is so heavy that it literally
makes the forest shake. In any case, here's a
down-and-dirty method to identify active computer
programs.
Start with a quote screen that includes the index
futures (or related ETFs) and a selection of liquid
equities across a wide variety of sectors. Add in
bid, ask, last price, and price change. Color-code
the numbers so the downticks are red and the
upticks are greens. Then sit back and watch the
first 90 minutes of the new trading day.
You'll quickly notice buying and selling waves
passing through the majority of instruments. These
can be extremely rapid pulses, lasting a few
seconds, or stomach churning air pockets that
persist for minutes. The main thing that will catch
your eye (and drive you crazy) will be lockstep
price action between dissimilar stocks and sectors.
Exchange-traded funds are primarily responsible for
this eye-popping alignment. Through these liquid
instruments, algorithms buy or sell huge baskets of
equities in microsecond bursts. The light-speed
activity then forces the stocks to get bought or
sold. Add in a half-dozen cross-markets, and you
have a typical program strategy.
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Have you noticed how market depth information,
commonly referred to as the Level II screen, has
turned into a blur of rapid pricing in the last
year, making it nearly useless for analysis of
short-term supply and demand? The culprit is SEC
Regulation NMS, also known as the trade-through
rule, which went into effect on March 5, 2007.