Dec

2

 In honor of our new spec and Larry, I hypothesize that like Pascal's Law, that a small move in a big market will cause probabilistically, a large move in a smaller market. I'll give 1,000 bucks to the personage that comes up with the best predictive relation on that theme.

Mr. Isomorphisms replies: 

I would start looking in smaller markets that are dependent on the larger one. Eg, look at a town where >50% of the workers are employed at one company. The decline of various parts of Detroit's supply chain could fit this story. Or Iceland/Scotland with their large banking sectors relative to within-country wealth.

Steve Ellison writes: 

Chair: "I hypothesize that like pascal's law, that a small move in a big market will cause probabilistically, a large move in a smaller market."

Let us first get an idea of which markets are big and small. Glancing at the futures contract listings in the newspaper, here are some rough estimates of open interest:

3-month Eurodollar 10,000,000
S&P 500 e-mini        3,100,000
10-year US Treasury 3,000,000
Crude oil                  1,300,000
Soybeans                   670,000
Euro                           465,000
Gold                           400,000
Wheat                         360,000
Cocoa                         175,000
Copper                        155,000
Silver                          150,000
Palladium                      31,000
Oats                               8,500
Lumber                           5,000

Next, I would like to introduce the bullwhip effect. Most goods have a "supply chain" that begins with raw materials, progresses to components and finished goods, and may include warehouses and stores. The bullwhip effect posits that, the farther "back" in the supply chain an operation is (farther away from the end customer), the greater the swings in production and inventory will be in response to fluctuations in end customer demand. Here is an article on the subject.

During the dot-com crash in October 2000, stocks briefly rallied on a glowing earnings report by JDS Uniphase. The CNBC screamer correctly noted that JDSU was a component supplier, farther back in the supply chain, and its record sales had probably just bloated the inventories of companies such as Cisco Systems that had already reduced forward guidance.

From this perspective, lumber seems a good candidate for a Pascal's Law study. It is a raw material that must go through additional processing before reaching most customers, and its futures market is very small. The S&P 500 is a large market that theoretically is based on the whole economy and should be more sensitive to final sales.

Using 3 months as a rough rule of thumb for total lead time in a typical supply chain, I compared quarterly net changes in the S&P 500 with net changes one quarter later in the lumber price.

LUMBER                        S&P 500
          Adjusted  Net              Adjusted   Net
Date      Close     change   Date    Close      change
                           09/30/11   1048.50
  12/30/11   291.1         12/30/11   1180.75  132.25
  03/30/12   283.0   -8.1  03/30/12   1337.50  156.75
  06/29/12   294.8   11.8  06/29/12   1297.50  -40.00
  09/28/12   311.3   16.5  09/28/12   1382.00   84.50
  12/31/12   391.4   80.1  12/31/12   1373.75   -8.25
  03/29/13   407.6   16.2  03/28/13   1521.50  147.75
  06/28/13   310.2  -97.4  06/28/13   1563.75   42.25
  09/30/14   355.7   45.5  09/30/13   1645.50   81.75
  12/31/13   365.7   10.0  12/31/13   1818.75  173.25
  03/31/14   334.4  -31.3  03/31/14   1849.25   30.50
  06/30/14   340.3    5.9  06/30/14   1944.50   95.25
  09/30/14   338.0   -2.3  09/30/14   1965.50   21.00

There were only 11 data points since 2012, not enough for significance. In a regression, the t score was -1.55, and the R squared was 0.21.

The quarterly changes in lumber were a little larger in percentage terms (about 8% mean absolute change) than in the S&P 500 (about 6% mean absolute change).

Victor Niederhoffer writes: 

Excellent. You win the prize. Everything a report should be. (A little weak on the predictivity but not your fault.) If it was easy, we would all be wealthy men. 


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2 Comments so far

  1. Diego Joachin on December 2, 2014 3:20 pm

    Connect the T-bond with the local currency of my country. Sharp decline in the TNX led to local enterprises (1st time in their life) to issue corporate bonds. Those extra dollars moved the exchange rate between the Quetzal vs the USD down. The reverse would also apply in the moment the yield curve moves back.

  2. douglas roberts dimick on December 4, 2014 5:58 pm

    Smaller Big or Little?

    Assuming Steve’s report, how would you all address the quantitative relativity of state transitions, such as China’s new status as No 1…”

    See…

    http://finance.yahoo.com/news/official-america-now-no-2-150936444.html

    It would seem that how one quantifies “smaller markets” determines the predictive relationship to the “big market” but for the probability of the resulting move itself.

    Those high priests of Fibonacci correlations to markets come to mind here.

    dr

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