Here’s the edge you have trading stocks instead of the S&P 500
September, 2001 was a historic occasion for the
stock market, but not for the obvious reason.
It was then that trending behavior in the S&P 500
Index officially died. What follows is an autopsy you might find revealing.
My TradingMarkets article earlier this week
dealing with traders’ recent struggles brought more mail–all of it positive,
thankfully–to my inbox than any previous piece. It seemed to strike a chord
among traders who realized that market movement just isn’t what it used to be.
Inspired by a
recent
article by Fred Goodman, I decided to investigate the issue further and
study the historical trending behavior of the S&P 500 Index. What I found blew
me away.
I went back to January, 1966 and investigated
250-day periods in the market–periods amounting to roughly one year of data. I
counted each occasion in which the market was either up following an up day or
down following a down day. These I called two-day trends. My goal was to
determine the percentage of occasions in a moving 250-day period that qualified
as two-day trends.
Before we examine the data, let’s think about
this logically. If the odds of the market rising or falling on a particular day
are 50/50, then we should see roughly one-quarter of all occasions displaying
two-day uptrends; one half of all occasions showing no trend; and one-quarter of
all occasions exemplifying two-day downtrends. So, all in all, we should
see–in any moving 250-day period–about 125 trending occasions. If we see many
more trending occasions, then we have a directional bias: market direction is
likely to persist. If we see many fewer trending occasions than 125, then we
are displaying anti-persistence: the market is biased toward reversing prior
movement.
Here’s the chart from 1966 to the present:
What we see is that market
trendiness is trending, and it’s trending down! Indeed, we are at the lowest
level of trendiness in the roughly 20 year period, and we are well below that
average point of 125. Note that early in the sample–the late 1960s and early
1970s–we saw consistently elevated levels: Gains or losses on day one tended to
carry over to day two. Now, however, we see the reverse: Gains or losses on day
one are more likely to reverse on day two.
And that September, 2001 date?
That’s the last time we had a reading of 125 (though we have come close late in
2004 and early in 2005).
While we’re at it, here’s another
piece of evidence that I recently posted to
my site: simple
technical trading systems aren’t working.
The
Barchart market service has an interesting
feature for subscribers that tracks the performance of all stocks across an
array of technical trading systems. Those systems, such as moving average
crossovers, are momentum-based and trend following; that is, they buy strength
and sell weakness. The systems generate signals formed over a variety of
periods, from a few days to several months. The website tracks the winning and
losing trades and overall profitability of each system for each stock over a
three year period.
When I entered Google
(
GOOG |
Quote |
Chart |
News |
PowerRating) as my stock,
all of the systems were profitable. When I entered
(
SPY |
Quote |
Chart |
News |
PowerRating)–the exchange-traded
fund for the S&P 500 Index–none of the systems were profitable.
Not one.
What I believe the Barchart site is
really tracking is trendiness. It provides a useful assessment of trendiness
because it taps price-persistent behavior across multiple time frames. Google
was trending over multiple timeframes: it was following strength with strength,
weakness with weakness. The S&P 500 was not trending on any timeframe. That is
significant.
It also helps to explain why it has
been so difficult to make money in the stock index. It is human nature to
extrapolate the future from the recent past. If we see something shoot up, we
want to buy it and vice versa. That is exactly what hasn’t worked in the
S&P, as traders have learned.
There is a silver lining in all of
this, however. As my experience with Barchart suggests, it is possible to find
individual stocks that display trending behavior even as the market languishes.
Measuring their performance against benchmark technical trading systems of
varying durations might be a useful way to derive an index of trendiness for
stock pickers. A different strategy would be to identify individual stocks that
are likely to benefit from market anti-persistence; i.e., that are most likely to
rise after a fall or dip after a bounce. My sense is that the TradingMarkets
PowerRatings, as well as the trading strategies in Larry Connors’ book
How
Markets Really Work, pursue this latter strategy.
The important thing is to clearly
identify where there is opportunity in markets. My best estimate–and it’s
hardly an original conjecture–is that the market indices and individual stocks
that are most frequently included in arbitrage trading are those that are
showing the greatest loss of trendiness. Explorations in the small cap and
micro-cap worlds for trending issues might prove fruitful. Alternatively, it
might be possible to find an edge by waiting for market moves to occur in the
most arbitraged sectors and then fade these. I will be exploring these–and
other–strategies on my site.
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. He is currently writing a book on the topics
of trader development and the enhancement of trader performance due for
publication this fall (Wiley).