New research on the power of pullbacks


In my last article and on my research blog, I posted evidence for what I
called countertrend equivalence. When we have seen a distinct trending
move over a period of time, the S&P 500 has tended to reverse this move in
the next time period. Since 2003, we have seen such counter trending after
periods ranging from five hours to five weeks.

If the market is actually reversing prior movement, perhaps trading
retracements is the way to go. I decided to study this by focusing on the
Dow Jones Industrial Average, whose large cap stocks are prominent in the
baskets of stocks used for arbitrage. If, indeed, such program trading is
dampening market trending, then perhaps these issues will provide us with
promising vehicles for countertrend trading.

As a basic countertrend trade, I focused on the market’s tendency to return
to the prior day’s average trading price. I defined the average simply as
the mean of the day’s open-high-low-close. A trending market, in general,
should depart from this average; a counter trending market should return to it.

Going back to March, 2003 (N = 773), I found 491 instances of retracement to
the prior day’s mean. This means that today’s market returns to
yesterday’s average price just shy of two-thirds of the time.

I then divided the sample in half, based on the prior day’s volatility
(high-low range). When the previous day was volatile (N = 387), the next
day touched the prior day’s average price 56% of the time. When the market
was relatively non-volatile (N = 386), the next day touched the prior day’s
average 71% of the time.

Going further, I looked at the current day’s opening price relative to the
previous day’s average. I divided the sample in thirds, which gave me
occasions when the open was much above the prior day’s opening price; occasions
when the open was near the average price; and occasions in which the open was
far below the average price. When today’s open was much above yesterday’s
average price (N = 258), we revisited that average price during today’s session
only 46% of the time. When today’s open was near yesterday’s average price
(N = 258), we returned to that average a whopping 85% of the time.
Interestingly, when today’s close was well below yesterday’s average price (N =
257), we still hit that average 60% of the time.

Finally, I investigated occasions in which the prior day was low in
volatility and we opened today near yesterday’s average price (N =
129). We returned to the previous day’s mean in such situations a whopping
90% of the time.

This little exercise just happened to use yesterday as a prior range and
today as the next range. If, indeed, we see countertrend equivalence
across multiple time scales, we should see similar odds governing returns to
prior average prices for a variety of ranges. It may be that this market
is tradable; we just need to look backward instead of forward!

Brett N. Steenbarger, Ph.D. is Associate Clinical
Professor of Psychiatry and Behavioral Sciences at SUNY Upstate Medical
University in Syracuse, NY and author of
The
Psychology of Trading
(Wiley, 2003). As Director of Trader Development
for Kingstree Trading, LLC in Chicago, he has mentored numerous professional
traders and coordinated a training program for traders. An active trader of the
stock indexes, Brett utilizes statistically-based pattern recognition for
intraday trading. Brett does not offer commercial services to traders, but
maintains an archive of articles and a trading blog at www.brettsteenbarger.com
and a blog of market analytics at www.traderfeed.blogspot.com.
His book on the topic of trader development, Enhancing Trader Performance,
is due for publication this fall (Wiley).