A different kind of market indicator — time
As I recently noted on TraderFeed, my research
blog, most market indicators identify the presence of a particular market
condition. A different kind of indicator takes an expectable market event and
counts how many days have elapsed since that event has last occurred. This
makes time itself a market measure that can be applied to any trading
instrument. For example, my TraderFeed analysis found that, the longer the time
that elapses before we see a five-day price high in SPY, the more positive are
the short-term S&P 500 Index returns. Conversely, when we finally make a
five-day high, near-term returns are subnormal.
For this analysis, we’ll take a different
expectable market event: The number of stocks making 20-day new highs exceeding
the number that are making 20-day new lows. This measures breadth of strength in
the market, as I include all operating companies in the NYSE, NASDAQ, and AMEX
in the calculation.
What we find is that, since March, 2003 (N = 821
trading days), when we’ve had 11 or more days without new 20-day highs
outnumbering new 20-day lows (N = 50), the next five days in SPY average a gain
of .56% (37 up, 13 down). That is meaningfully stronger than the average
five-day gain of .25% (434 up, 337 down) for the remainder of the sample.
On the other hand, if 20-day new highs already
outnumber new 20-day lows (N = 552), the next five days in SPY display a
somewhat subnormal set of returns going forward. Specifically, the next five
days in SPY average a gain of .18% (307 up, 245 down) vs. an average five-day
gain of .44% (164 up, 105 down) when 20-day lows outnumber new highs.
This accords with my earlier finding: the longer
it takes for a bullish event to occur, the more bullish the near-term market
outlook. Once the bullish event does occur, returns tend to be subnormal going
forward. It is in this way that the market confounds human nature, which tends
to overweight recent events in making judgments. The tendency to become more
bullish as bullish events occur and more bearish as bearish events accumulate
almost ensures losing performance over time.
I will be following this up with further
time-based studies on the research
blog. A daily count of 20-day new highs and lows is available on the
Trading Psychology Weblog.
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, Enhancing Trader Performance,
is due for publication this fall (Wiley).