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| Trading Places (Image via RottenTomatoes.com) |
It is New
Year’s Eve. The Harrisburg Express speeds from Philadelphia to New York
City. It thunders down the rails carrying passengers Inga from Sweden,
Naga Eboko from Cameroon, Lionel Joseph, an Irish priest, a gorilla and
Beeks, with his briefcase. The case contains the crop report for orange
juice.
Possibly every single reader of Futures
can remember every major scene from the iconic movie "Trading Places."
Indeed, it made many of us take up trading futures and commodities.
We’ve all likely said some variation of the great line: "Pressure? Here
it’s kill or be killed. Make no friends and take no prisoners. One
minute you’re up half a million, the next — boom! — your kids don’t go
to college and you’ve lost the Bentley!"
"Trading Places" culminates in a wonderful
scene in the frozen concentrated orange juice futures pit in New York.
Back in the old days, all trading was pit trading. It was hectic and
exciting. How exciting? There were times in the 1980s when, in an effort
to get an edge, the runners were on roller skates.
The upshot in the movie was the main
characters, Winthorpe and Valentine, waiting until Wilson drove the
price of orange juice way, way up. They then sold into the market, the
Secretary of Agriculture announced the real crop report and the price
plummeted. Our heroes cover their shorts and make millions, putting the
Dukes into the poorhouse at the same time. It’s a fun story that defined
trading for a generation. The movie never gets old.
It also has some good lessons, particularly
for the orange juice trader. One topic is the issue of volatility and
some widely held beliefs. Does orange juice really swing wildly in
January because of the crop report? More important, if such volatility
does exist, can we use it to our benefit?
To answer these questions, the monthly
range of orange juice prices was recorded starting with January 1996.
The monthly range is defined as the high price of the month minus the
low price. The closing prices were disregarded for the purposes of this
test. Through Nov. 30, 2011, there were 191 pieces of data. The highest
trade during the sample period was $2.0940, observed during the month of
March 2007. The lowest price paid was $0.5420 in May 2004. The range of
the orange juice contract, therefore, is $2.095 – $0.542, or $1.553. In
percentage terms, the high is an increase of 286.7% over the low price.
In performing this test, it is important to
make uniform comparisons. A 10¢ range with a low of 70¢ is not the same
as a 10¢ range when the market is trading at $1.65. The former is a
14.28% range, which is far more volatile than the 6.06% range of the
latter. Consequently, all of the range values were converted into
percentages by dividing the range by the low price to normalize them
across the sample universe. With these data, it now is possible to
construct a meaningful statistical test.
If the calendar plays a significant role in
orange juice price volatility, we would expect certain months to have
much more volatility than others. To test this, we use an Analysis of
Variance with an F-test statistic. The null hypothesis is, there is no
effect.
For those whose statistics knowledge is a
bit rusty, the F test examines different dependent values and assumes
there is no significant difference between them based upon the
observation of independent values. In other words, all of the fixed
variables (that is, the different calendar months) will produce
essentially the same dependent observations (that is, the average
volatility during the month). The null hypothesis of the test is there
will be no statistically significant difference between the mean
volatilities of any of the months. The alternate hypothesis is that,
yes, there is. Although the F statistic measures the variance, if the
variance is low, it follows the means are essentially similar. If the
variance is high, the mean volatility must be significantly different
among the 12 months.
The Analysis of Variance test has 12
independent variables and 16 observations in each month. (Although
December is missing for 2011, it is easy to perform this slightly
unbalanced test using any statistical software package.) The F statistic
will have 11 and roughly 180 degrees of freedom. This is a powerful
test for discovering patterns, and we can have much confidence in its
results.
The average volatility for each month is
shown in "O.J. monthly" (below). The results of our Analysis of Variance
test was p<0.00001. Essentially, there is virtually no significant
chance that the means of the months are equal. We can conclude with
great confidence that the calendar does indeed play a major role in the
average volatility experienced in the orange juice market over time.
Click to enlarge
It is essential to realize that this does
not prevent high volatility from taking place in any month. The test
simply compares the averages and finds there is more variation between
the months than within the given months.
In a blow to Hollywood, and perhaps running
against the assumptions of most orange juice traders, the "Trading
Places" months of December and January were not the top of the
volatility list. Examining the table, it is easy to discern that
October, August, January and December experience greater than average
volatility, but October is much higher than December. Those four months
account for 17.17% of the volatility of the orange juice market.
March, April and November are relatively
quiet months by comparison, experiencing only 12.3% of the volatility.
It may be concluded that the best trading opportunities are likely to be
presented when volatility is greatest. It might also be concluded that
the greatest risk occurs at those times as well. Short-term traders
might find lots of trading opportunity in orange juice during October or
August. March and April may be too quiet, but also present less risk.
On average, volatility throughout the
year is 14.64%. As a side note, we can examine if extremely low
volatility has been a harbinger of any movement. Indeed, it turns out it
is, statistically speaking. When volatility in any month dropped below
7.25%, the market often changed direction within the three months
thereafter. Often, the low volatility immediately preceded a major
market shift.
For example, in December 2006, the monthly
low was $1.96 and the high was $2.0940 (see "Calm before the storm,"
below). This range of 13.4¢ was only a 6.8% swing for the month. Given
December is expected to be a pretty wild month, the volatility was less
than 45% of what we might normally see. January 2007 saw a major drop in
the market, with volatility falling to 13.35%. The all-time high was
hit only two months later in March 2007, and then the orange juice
market dropped precipitously, falling to $1.1060 in the next six months.
Similarly, in April 2004, the volatility
dropped to 4.42% and the market low for the month was $0.5580. The
following month, orange juice bottomed at $0.5420 before beginning its
wild climb into the 2007 high. Several other examples of such predictive
low-volatility activity may be found.
The lessons of the orange juice market may
be extrapolated to other markets and shorter time frames. The trader
easily can test different hours of the trading day to see if certain
periods present higher volatility than others. Similarly, it may be
tested to see if sudden contraction in the range of any time bar vs. its
historical norm predicts a sudden change in market direction. After
all, the goal, as Valentine and Winthorpe say at the end of the movie
is: "Looking good; feeling good!"
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