Embed Size (px)
Citation preview
Passive Investors and Managed Money in Commodity Futures
Part 2:Liquidity
Prepared for:
The CME Group
Prepared by:
October, 2008
2
Table of Contents
Section Slide Number
Objectives and Approach 3
Findings
Corn 4-12
Soybeans 13-21
Chicago Wheat 22-30
KC Wheat 31-39
MN Wheat 40-48
Cotton 49-57
Natural Gas 58-66
Crude Oil 67-75
Summary 76-79
3
Objectives and Approach
The objective of this section is to examine the association, if it exists, between the market presence of passive and trend-following traders and liquidity in the studied markets.
The liquidity measure is plotted in time-series fashion to identify recent trends. Growth in volume and open interest is also presented.
A series of scatter diagrams are used to illustrate the relationship between market presence of each trader group and average liquidity.
For the purposes of this work, liquidity is measured as trading volume as a percentage of open interest during the last 200 trading days.
4
Findings - Corn
Overall, there has been at least a moderate increase in average liquidity for Corn contracts over the study period.
In 2005 and 2006, liquidity generally averaged between 13% and 19%.
From the beginning of 2007 onward, average liquidity per contract consistently ranges between 17% and 23%.
Liquidity is seasonal, being lowest for the September contract and highest for the May contract.
5
Findings - Corn
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
10%
12%
14%
16%
18%
20%
22%
24%
2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2008 2008
MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL
CONTRACT - YEAR
PE
RC
EN
T (
%)
6
50%
150%
250%
350%
450%
550%
650%
2003
0120
0303
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
50%
150%
250%
350%
450%
550%
650%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth - Corn
7
Findings - Corn
The correlation between the presence of Non-Commercials and liquidity in the studied corn contracts is the strongest and it is positive.
Correlations between the presence of Commercials and Indexers and liquidity were much weaker and negative.
Interestingly, liquidity appears to decline whenever small traders make up a larger percentage of the market.
8
Findings - Corn
Commercials, Corn
N8 K8
H8Z7
U7
N7K7
H7
Z6
U6
N6
K6
H6Z5
U5
N5
K5
H5
y = -0.11x + 0.22
R2 = 0.05
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
0.30
30% 35% 40% 45% 50% 55%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
9
Findings - Corn
Non-Commercials, Corn
H5
K5
N5
U5
Z5H6
K6
N6
U6
Z6
H7
K7N7
U7
Z7H8
K8N8y = 0.33x + 0.12
R2 = 0.34
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
10% 15% 20% 25% 30% 35%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
10
Findings - Corn
Indexers, Corn
H5
K5
N5
U5
Z5H6
K6
N6
U6
Z6
H7
K7N7
U7
Z7H8
K8N8y = -0.30x + 0.20
R2 = 0.12
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0% 2% 4% 6% 8% 10% 12% 14% 16% 18%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
11
Findings - Corn
Money Managers, Corn
H5
K5
N5
U5
Z5H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7H8
K8N8
y = 0.13x + 0.16
R2 = 0.04
0.12
0.14
0.16
0.18
0.20
0.22
0.24
2% 7% 12% 17% 22%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
12
Findings - Corn
Small Traders, Corn
H5
K5
N5
U5
Z5 H6
K6
N6
U6
Z6
H7
K7N7
U7
Z7H8
K8N8
y = -0.23x + 0.23
R2 = 0.12
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
15% 17% 19% 21% 23% 25% 27% 29% 31% 33% 35%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
13
Findings - Soybeans
There doesn’t appear to be a consistent, overall trend in average liquidity for Soybeans contracts over the study period.
Average liquidity per contract seems to have declined from the early to mid-2005 through mid-2006 and stabilized through 2007 before showing signs of an increase in 2008.
Overall, though, average liquidity has bounced between 22% and 36% per contract over the study period.
14
Findings - Soybeans
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
10%
15%
20%
25%
30%
35%
40%
J AN MAR MAY J UL AUG SEP NOV J AN MAR MAY J UL AUG SEP NOV J AN MAR MAY J UL AUG SEP NOV J AN MAR MAY J UL
CONTRACT - YEAR
PE
RC
EN
T (
%)
15
50%
100%
150%
200%
250%
300%
350%
400%20
0301
2003
03
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
50%
100%
150%
200%
250%
300%
350%
400%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth - Soybeans
16
Findings - Soybeans
Correlation between the presence of any of the large trader groups and average liquidity was very weak for soybean futures.
The data do not indicate a strong correlation between the presence of either Indexers or Money Managers and liquidity.
The presence of small traders is negatively associated with liquidity.
17
Findings - Soybeans
Commercials, Soybeans
N8
K8
H8
F8X7
U7Q7N7
K7
H7F7
X6
U6
Q6
N6
K6
H6F6X5U5
Q5
N5
K5H5
y = 0.12x + 0.22
R2 = 0.05
0.15
0.17
0.19
0.21
0.23
0.25
0.27
0.29
0.31
0.33
0.35
25% 30% 35% 40% 45% 50% 55%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
18
Findings - Soybeans
Non-Commercials, Soybeans
H5K5
N5
Q5
U5X5 F6 H6
K6
N6
Q6
U6
X6
F7H7
K7N7
Q7U7
X7F8
H8
K8
N8y = -0.12x + 0.29
R2 = 0.04
0.15
0.17
0.19
0.21
0.23
0.25
0.27
0.29
0.31
0.33
0.35
10% 15% 20% 25% 30% 35%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
19
Findings - Soybeans
Indexers, Soybeans
H5 K5
N5
Q5
U5X5F6H6
K6
N6
Q6
U6
X6
F7H7
K7N7
Q7 U7
X7F8
H8
K8
N8y = 0.27x + 0.26
R2 = 0.06
0.15
0.17
0.19
0.21
0.23
0.25
0.27
0.29
0.31
0.33
0.35
0% 2% 4% 6% 8% 10% 12%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
20
Findings - Soybeans
Money Managers, Soybeans
H5K5
N5
Q5
U5X5F6H6
K6
N6
Q6
U6
X6
F7H7
K7N7
Q7U7
X7F8
H8
K8
N8
y = 0.16x + 0.25
R2 = 0.10
0.15
0.17
0.19
0.21
0.23
0.25
0.27
0.29
0.31
0.33
0.35
2% 7% 12% 17% 22% 27% 32%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
21
Findings - Soybeans
Small Traders, Soybeans
H5K5
N5
Q5
U5X5 F6H6
K6
N6
Q6
U6
X6
F7H7
K7N7
Q7U7
X7F8
H8
K8
N8
y = -0.23x + 0.33
R2 = 0.21
0.15
0.17
0.19
0.21
0.23
0.25
0.27
0.29
0.31
0.33
0.35
10% 15% 20% 25% 30% 35% 40% 45%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
22
Findings – Chicago Wheat
Average liquidity has increased over time in Chicago Wheat futures.
Average liquidity per contract moved between 14% and 22% during 2005 and 2006.
From early 2007 on, average liquidity has consistently been above 20% and peaked as high as 28%.
23
Findings – Chicago Wheat
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
10%
12%
14%
16%
18%
20%
22%
24%
26%
28%
30%
2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2008 2008
MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL
CONTRACT - YEAR
PE
RC
EN
T (
%)
24
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%20
0301
2003
03
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth – Chicago Wheat
25
Findings – Chicago Wheat
The presence of each of the major trading groups exhibits an extremely weak correlation to average liquidity for Chicago Wheat futures.
There is not enough evidence in the charts on the following pages to suggest that the market presence of any trading group has even a modest impact on liquidity.
26
Findings – Chicago Wheat
Commercials, Chicago Wheat
N8
K8
H8
Z7
U7
N7
K7
H7
Z6
U6
N6
K6
H6
Z5
U5
N5
K5
H5
y = 0.06x + 0.17
R2 = 0.01
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
20% 25% 30% 35% 40% 45% 50%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
27
Findings – Chicago Wheat
Non-Commercials, Chicago Wheat
H5
K5
N5
U5
Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = -0.09x + 0.21
R2 = 0.02
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
5% 10% 15% 20% 25% 30%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
28
Findings – Chicago Wheat
Indexers, Chicago Wheat
H5
K5
N5
U5
Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = -0.14x + 0.21
R2 = 0.05
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
0.30
5% 10% 15% 20% 25% 30% 35%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
29
Findings – Chicago Wheat
Money Managers, Chicago Wheat
H5
K5
N5
U5
Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = 0.27x + 0.15
R2 = 0.09
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
5% 7% 9% 11% 13% 15% 17% 19% 21% 23% 25%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
30
Findings – Chicago Wheat
Small Traders, Chicago Wheat
H5
K5
N5
U5
Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = 0.04x + 0.18
R2 = 0.00
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
10% 12% 14% 16% 18% 20% 22% 24% 26% 28% 30%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
31
Findings – Kansas City Wheat
For Kansas City Wheat, average liquidity per contract has shown a rather strong down-trend over the study period.
In 2005 and 2006, average liquidity was consistently 15% or higher, peaking around 20%.
That steadily declined over time, and liquidity for recent Kansas City Wheat contracts has consistently been below 10%.
Recently, volume has declined faster than open interest.
32
Findings – Kansas City Wheat
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
0%
5%
10%
15%
20%
25%
2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2008 2008
MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL
CONTRACT - YEAR
PE
RC
EN
T (
%)
33
0%
50%
100%
150%
200%
250%
300%20
0301
2003
03
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
0%
50%
100%
150%
200%
250%
300%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth – Kansas City Wheat
34
Findings – Kansas City Wheat
Although the correlation is not very strong (R-squared = 0.27), the data suggests that the presence of Indexers may have a positive impact on liquidity in the Kansas City Wheat futures market.
Interestingly, the presence of Money Managers may have a very modest but negative impact on liquidity.
There are no strong or definitive patterns between market presence and liquidity for the Commercial, Non-Commercial and Small Trader groups.
35
Findings – Kansas City Wheat
Commercials, Kansas City Wheat
N8
K8
H8Z7
U7N7
K7H7
Z6
U6
N6 K6
H6
Z5
U5
N5
K5
H5
y = 0.11x + 0.07
R2 = 0.04
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
35% 40% 45% 50% 55% 60% 65%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
36
Findings – Kansas City Wheat
Non-Commercials, Kansas City Wheat
H5
K5
N5
U5
Z5
H6
K6N6
U6
Z6
H7K7
N7 U7
Z7H8
K8
N8
y = 0.07x + 0.11
R2 = 0.01
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
5% 10% 15% 20% 25% 30%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
37
Findings – Kansas City Wheat
Indexers, Kansas City Wheat
H5
K5
N5
U5
Z5
H6
K6N6
U6
Z6
H7K7
N7U7
Z7H8
K8
N8
y = 0.86x + 0.08
R2 = 0.27
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
2% 4% 6% 8% 10% 12% 14%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
38
Findings – Kansas City Wheat
Money Managers, Kansas City Wheat
H5
K5
N5
U5
Z5
H6
K6 N6
U6
Z6
H7K7
N7U7
Z7H8
K8
N8
y = -0.44x + 0.17
R2 = 0.23
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
5% 7% 9% 11% 13% 15% 17% 19% 21% 23%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
39
Findings – Kansas City Wheat
Small Traders, Kansas City Wheat
H5
K5
N5
U5
Z5
H6
K6 N6
U6
Z6
H7K7
N7U7
Z7 H8
K8
N8
y = -0.23x + 0.18
R2 = 0.06
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
15% 17% 19% 21% 23% 25% 27% 29% 31% 33% 35%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
40
Findings – Minneapolis Wheat
Average liquidity has varied widely over the study period for the Minneapolis Wheat futures market, ranging anywhere from 11% to 20%.
Although liquidity has varied more in recent months, the general trend has been toward modestly lower liquidity.
Significant seasonality is present, with liquidity routinely peaking in the May contract.
Recently volume has fallen faster than open interest, causing the liquidity metric to decline.
41
Findings – Minneapolis Wheat
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
10%
11%
12%
13%
14%
15%
16%
17%
18%
19%
20%
2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2008 2008
MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL SEP DEC MAR MAY JUL
CONTRACT - YEAR
PE
RC
EN
T (
%)
42
0%
50%
100%
150%
200%
250%
300%20
0301
2003
03
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
0%
50%
100%
150%
200%
250%
300%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth – Minneapolis Wheat
43
Findings – Minneapolis Wheat
The following charts indicate that any correlation between the market presence of each trading group and liquidity in Minneapolis Wheat futures is extremely weak.
Indexers are conspicuously absent in this futures market.
44
Findings – Minneapolis Wheat
Commercials, Minneapolis Wheat
N8
K8
H8
Z7
U7
N7
K7
H7
Z6
U6
N6
K6
H6
Z5U5
N5K5
H5
y = 0.04x + 0.13
R2 = 0.02
0.10
0.11
0.12
0.13
0.14
0.15
0.16
0.17
0.18
0.19
0.20
40% 45% 50% 55% 60% 65% 70%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
45
Findings – Minneapolis Wheat
Non-Commercials, Minneapolis Wheat
H5
K5N5
U5
Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = 0.03x + 0.15
R2 = 0.00
0.10
0.11
0.12
0.13
0.14
0.15
0.16
0.17
0.18
0.19
0.20
2% 4% 6% 8% 10% 12% 14% 16% 18%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
46
Findings – Minneapolis Wheat
Indexers, Minneapolis Wheat
H5
K5N5
U5Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = -2.52x + 0.15
R2 = 0.18
0.10
0.11
0.12
0.13
0.14
0.15
0.16
0.17
0.18
0.19
0.20
0.0% 0.2% 0.4% 0.6% 0.8% 1.0% 1.2% 1.4%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
47
Findings – Minneapolis Wheat
Money Managers, Minneapolis Wheat
H5
K5N5
U5Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = -0.03x + 0.15
R2 = 0.00
0.10
0.11
0.12
0.13
0.14
0.15
0.16
0.17
0.18
0.19
0.20
2% 4% 6% 8% 10% 12% 14% 16% 18% 20%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
48
Findings – Minneapolis Wheat
Small Traders, Minneapolis Wheat
H5
K5N5
U5
Z5
H6
K6
N6
U6
Z6
H7
K7
N7
U7
Z7
H8
K8
N8
y = -0.04x + 0.16
R2 = 0.01
0.10
0.11
0.12
0.13
0.14
0.15
0.16
0.17
0.18
0.19
0.20
25% 30% 35% 40% 45% 50%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
49
Findings - Cotton
Liquidity was consistently above 10% and as much as 15% or higher during 2005.
For cotton, average liquidity per contract appears to be declining over time but this is heavily influenced by a substantial decline in liquidity during early 2008.
The sharp drop in the liquidity measure during early 2008 may have been driven by reduced future volumes as price limits became binding more frequently and volume appeared to shift toward the options market.
50
Findings - Cotton
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
0%
5%
10%
15%
20%
25%
2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2008 2008
MAR MAY JUL OCT DEC MAR MAY JUL OCT DEC MAR MAY JUL OCT DEC MAR MAY JUL
CONTRACT - YEAR
PE
RC
EN
T (
%)
51
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
2003
0120
0303
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth - Cotton
52
Findings - Cotton
The presence of Commercials exhibits a very modest positive correlation to liquidity.
A very modest negative correlation may exist between the presence of Non-Commercials and liquidity in this market.
The presence of Indexers and Money Managers displays a much weaker and positive correlation to liquidity.
53
Findings - Cotton
Commercials, Cotton
N8
K8
H8
Z7V7
N7
K7
H7
Z6
V6
N6K6
H6Z5
V5
N5
K5
H5
y = 0.21x + 0.01
R2 = 0.19
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
35% 40% 45% 50% 55% 60% 65%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
54
Findings - Cotton
Non-Commercials, Cotton
H5
K5
N5
V5
Z5H6
K6N6
V6
Z6
H7
K7
N7
V7Z7
H8
K8
N8
y = -0.27x + 0.16
R2 = 0.22
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
5% 10% 15% 20% 25% 30% 35%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
55
Findings - Cotton
Indexers, Cotton
H5
K5
N5
V5
Z5H6
K6N6
V6
Z6
H7
K7
N7
V7Z7
H8
K8
N8
y = 0.18x + 0.10
R2 = 0.04
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0% 2% 4% 6% 8% 10% 12% 14% 16%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
56
Findings - Cotton
Money Managers, Cotton
H5
K5
N5
V5
Z5H6
K6N6
V6
Z6
H7
K7
N7
V7Z7
H8
K8
N8
y = 0.28x + 0.09
R2 = 0.11
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
57
Findings - Cotton
Small Traders, Cotton
H5
K5
N5
V5
Z5H6
K6N6
V6
Z6
H7
K7
N7
V7Z7
H8
K8
N8
y = -0.27x + 0.15
R2 = 0.19
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
5% 10% 15% 20% 25% 30% 35% 40%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
58
Findings – Natural Gas
For Natural Gas contracts, liquidity was steady – possibly even declining slightly – from early 2005 through early 2007.
From there, average liquidity increased sharply and peaked in mid-2007 only to retreat to previous levels before rebounding again into and through 2008.
While liquidity once averaged between 15% and 25%, it has regularly been above 25%, and even up to 40%, since the middle of last year.
59
Findings – Natural Gas
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
10%
15%
20%
25%
30%
35%
40%
45%
JAN
2005
FE
B20
05M
AR
2005
AP
R20
05M
AY
2005
JUN
2005
JUL
2005
AU
G20
05S
EP
2005
OC
T20
05N
OV
2005
DE
C20
05JA
N20
06F
EB
2006
MA
R20
06A
PR
2006
MA
Y20
06JU
N20
06JU
L20
06A
UG
2006
SE
P20
06O
CT
2006
NO
V20
06D
EC
2006
JAN
2007
FE
B20
07M
AR
2007
AP
R20
07M
AY
2007
JUN
2007
JUL
2007
AU
G20
07S
EP
2007
OC
T20
07N
OV
2007
DE
C20
07JA
N20
08F
EB
2008
MA
R20
08A
PR
2008
MA
Y20
08JU
N20
08JU
L20
08A
UG
2008
CONTRACT - YEAR
PE
RC
EN
T (
%)
60
0%
50%
100%
150%
200%
250%
300%20
0301
2003
03
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
0%
50%
100%
150%
200%
250%
300%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth – Natural Gas
61
Findings – Natural Gas
There appears to be little or no correlation between the market presence of the trader groups and average liquidity in this market.
62
Findings – Natural Gas
Commercials, Natural Gas
Q8
N8M8
K8J8
H8G8 F8
Z7
X7
V7U7
Q7N7
M7
K7
J7
H7
G7
F7
Z6
X6
V6
U6
Q6N6
M6
K6
J6
H6 G6F6
Z5X5
V5
U5Q5N5
M5
K5
J5
H5
G5
y = 0.04x + 0.16
R2 = 0.00
0.05
0.10
0.15
0.20
0.25
0.30
15% 20% 25% 30% 35% 40% 45%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
63
Findings – Natural Gas
Non-Commercials, Natural Gas
G5
H5
J5
K5
M5
N5Q5U5
V5X5
Z5F6
G6 H6
J6
K6
M6
N6 Q6
U6
V6
X6
Z6
F7
G7
H7
J7
K7
M7
N7Q7
U7V7
X7
Z7F8 G8
H8
J8K8
M8N8
Q8
y = -0.24x + 0.20
R2 = 0.03
0.05
0.10
0.15
0.20
0.25
0.30
5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
64
Findings – Natural Gas
Indexers, Natural Gas
G5
H5
J5
K5
M5
N5Q5
U5
V5
X5Z5
F6
G6 H6
J6
K6
M6
N6Q6
U6
V6
X6
Z6
F7
G7
H7
J7
K7
M7
N7Q7
U7V7
X7
Z7F8 G8
H8
J8
K8
M8N8
Q8
y = 0.23x + 0.14
R2 = 0.05
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
9% 11% 13% 15% 17% 19% 21% 23% 25%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
65
Findings – Natural Gas
Money Managers, Natural Gas
G5
H5
J5
K5
M5
N5Q5
U5
V5
X5Z5
F6
G6 H6
J6
K6
M6
N6Q6
U6
V6
X6
Z6
F7
G7
H7
J7
K7
M7
N7Q7
U7V7
X7
Z7F8G8
H8
J8
K8
M8N8
Q8
y = -0.12x + 0.21
R2 = 0.07
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
20% 25% 30% 35% 40% 45% 50% 55%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
66
Findings – Natural Gas
Small Traders, Natural Gas
G5
H5
J5
K5
M5
N5Q5
U5
V5
X5Z5
F6
G6H6
J6
K6
M6
N6Q6
U6
V6
X6
Z6
F7
G7
H7
J7
K7
M7
N7Q7
U7V7
X7
Z7F8 G8
H8
J8
K8
M8
N8
Q8
y = 0.27x + 0.14
R2 = 0.11
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
5% 7% 9% 11% 13% 15% 17% 19% 21% 23% 25%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
67
Findings – Crude Oil
Average liquidity was consistently around 40% during 2005 and 2006.
After a sudden upward shift, liquidity averaged mostly between 50% and 60% from early 2007 into 2008.
Liquidity for the July and August 2008 contracts soared to more than 70%, however.
It’s safe to say that Crude Oil futures have seen a marked increase in liquidity over the study period.
68
Findings – Crude Oil
VOLUME / OPEN INTEREST FROM 200 DAYS TO EXPIRATION
10%
20%
30%
40%
50%
60%
70%
80%
90%
JAN
2005
FE
B20
05M
AR
2005
AP
R20
05M
AY
2005
JUN
2005
JUL
2005
AU
G20
05S
EP
2005
OC
T20
05N
OV
2005
DE
C20
05JA
N20
06F
EB
2006
MA
R20
06A
PR
2006
MA
Y20
06JU
N20
06JU
L20
06A
UG
2006
SE
P20
06O
CT
2006
NO
V20
06D
EC
2006
JAN
2007
FE
B20
07M
AR
2007
AP
R20
07M
AY
2007
JUN
2007
JUL
2007
AU
G20
07S
EP
2007
OC
T20
07N
OV
2007
DE
C20
07JA
N20
08F
EB
2008
MA
R20
08A
PR
2008
MA
Y20
08JU
N20
08JU
L20
08A
UG
2008
CONTRACT - YEAR
PE
RC
EN
T (
%)
69
0%
50%
100%
150%
200%
250%
300%
350%
400%20
0301
2003
03
2003
0520
0307
2003
0920
0311
2004
0120
0403
2004
0520
0407
2004
0920
0411
2005
01
2005
0320
0505
2005
0720
0509
2005
1120
0601
2006
0320
0605
2006
0720
0609
2006
1120
0701
2007
03
2007
0520
0707
2007
0920
0711
2008
0120
0803
2008
0520
0807
2008
0920
0811
Avg
. D
aily
Vo
lum
e A
s P
ct o
f 20
02
0%
50%
100%
150%
200%
250%
300%
350%
400%
Op
en I
nte
rest
as
Pct
of
2002
Avg Daily Volume
Avg Open Interest
Volume and Open Interest Growth – Crude Oil
70
Findings – Crude Oil
As the following charts suggest, the presence of Indexers, as a trading group, does have some positive correlation with liquidity in Crude Oil futures.
The presence of the other major trading groups exhibits much weaker correlation with liquidity.
71
Findings – Crude Oil
Commercials, Crude OilQ8
N8
M8
K8
J8
H8
G8
F8
Z7
X7
V7
U7
Q7
N7
M7
K7J7
H7 G7
F7
Z6
X6
V6 U6
Q6 N6
M6
K6
J6
H6 G6
F6
Z5
X5V5U5Q5
N5M5 K5
J5H5 G5
y = -0.34x + 0.51
R2 = 0.06
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
30% 35% 40% 45% 50% 55%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
Regression Equation: Liquidity = a + b x Market Presence
R2 = the correlation coefficient squared.
72
Findings – Crude Oil
Non-Commercials, Crude Oil
G5H5J5
K5 M5N5
Q5U5V5X5
Z5
F6
G6 H6
J6
K6
M6
N6 Q6
U6 V6
X6
Z6
F7
G7 H7
J7 K7
M7
N7
Q7
U7
V7
X7
Z7
F8
G8
H8
J8
K8
M8
N8
Q8
y = -0.09x + 0.38
R2 = 0.00
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
8% 10% 12% 14% 16% 18% 20% 22% 24%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
73
Findings – Crude Oil
Indexers, Crude Oil
G5 H5J5
K5M5N5
Q5U5V5X5
Z5
F6
G6 H6
J6
K6
M6
N6 Q6
U6V6
X6
Z6
F7
G7H7
J7K7
M7
N7
Q7
U7
V7
X7
Z7
F8
G8
H8
J8
K8
M8
N8
Q8y = 0.57x + 0.22
R2 = 0.35
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
10% 15% 20% 25% 30% 35% 40% 45%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
74
Findings – Crude Oil
Money Managers, Crude Oil
G5 H5 J5
K5 M5N5
Q5U5 V5X5
Z5
F6
G6H6
J6
K6
M6
N6Q6
U6V6
X6
Z6
F7
G7 H7
J7K7
M7
N7
Q7
U7
V7
X7
Z7
F8
G8
H8
J8
K8
M8
N8
Q8
y = -0.50x + 0.43
R2 = 0.13
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0% 5% 10% 15% 20% 25% 30%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
75
Findings – Crude Oil
Small Traders, Crude Oil
G5H5J5
K5M5N5
Q5U5V5X5
Z5
F6
G6H6
J6
K6
M6
N6Q6
U6V6
X6
Z6
F7
G7H7
J7 K7
M7
N7
Q7
U7
V7
X7
Z7
F8
G8
H8
J8
K8
M8
N8
Q8
y = -0.74x + 0.41
R2 = 0.12
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
2% 4% 6% 8% 10% 12% 14% 16% 18%
Market Presence
Liq
uid
ity
(Vo
l/O
I)
76
Summary
Overall, it appears that liquidity increased over the study period (2005 through mid-2008) for Corn, Chicago Wheat, Natural Gas, and Crude Oil.
The most pronounced increase in liquidity was in Crude Oil futures.
Liquidity has declined over time in Kansas City Wheat, Minneapolis Wheat and Cotton.
Liquidity has been relatively stable in Soybean futures with little change over time.
77
Summary
The strongest observed positive associations were the Non-Commercials trading in the corn futures market and the Indexers trading Kansas City wheat and crude oil futures.
In all three instances, however, we observed R-square statistics that were no higher than 0.35, suggesting a relatively weak correlation by most guidelines for statistical analysis.
78
Summary
Liquidity tends to be seasonal in many contracts, with certain months “favored” over others. In corn, Dec liquidity is almost always higher than in Sep.
This seasonality may mask trends in liquidity to some degree.
If there were enough data we would have preferred to isolate by contract month (e.g., only compare Dec contracts with other Dec contracts). Unfortunately, there were only three years of data available.
79
Summary
Overall, there is little evidence to suggest that any one particular trader group has a strong impact on liquidity—either positive or negative.
It is more likely that, in markets where liquidity gains have occurred, all of the trader groups contributed in some manner. The factors that fostered increased trading for one group, likely did so for all of them.
We must remember that correlation does not imply causation. However, the lack of correlation makes a strong case for the absence of causation.
