Spot-market Rate Indexes: Truckload Transportation
Author: Andrew Bignell
Advisor: Dr. Christopher Caplice
Sponsor: Coyote Logistics
MIT SCM ResearchFest May 22-23, 2013
An index is a statistical measure of changes over time in a representative set of data points.
May 22-23, 2013 MIT SCM ResearchFest
Used as benchmark for:
• $10 trillion in loans
• $350 trillion in derivatives
Manipulated by several banks
from 1998-2008
$2.6 billion in fines (so far)
“This dwarfs by orders of magnitude any financial scams in the history of the markets” - Andrew Lo, Professor of Finance, MIT
LIBOR Scandal: The importance of index design
May 22-23, 2013 MIT SCM ResearchFest
268
40
229.5
25.5
Private
LTL
TL-contract(estimated)
TL-spot(estimated)
U.S. Trucking Industry: The spot market is a small component
Spot: Price is negotiated at (or near) the time of delivery
May 22-23, 2013 MIT SCM ResearchFest
U.S. Trucking Industry: Basic spot-market structure
May 22-23, 2013 MIT SCM ResearchFest
Shipper Shipper Shipper Shipper Shipper Shipper Shipper Shipper
Carrier Carrier Carrier Carrier Carrier Carrier Carrier Carrier
Broker
• Changes in spot-market rates experienced at Coyote have not tracked existing truckload transportation indexes.
• Accurate spot-market indexes could be useful for:
• Long-term, flexible contracts
• Derivatives
• Procurement planning and decision-making
Motivation
May 22-23, 2013 MIT SCM ResearchFest
• Review indexes from other industries to determine the characteristics of sound indexes.
• Review indexes from the trucking industry.
• Make recommendations for improving and/or developing spot-market truckload indexes.
Plan
1. Should be an accurate reflection of the real spot market
2. Should be rigorously computed and unbiased
3. Should be expressed in units familiar to the industry
4. Should be based on a sufficiently broad and balanced input
5. Should be transparent and simple
6. Should provide different levels of aggregated information in a
clear and calculable hierarchy
May 22-23, 2013 MIT SCM ResearchFest
Characteristics of sound freight indexes: Part 1: Index calculation and data collection
1. Should be an accurate reflection of the real spot market
2. Should be rigorously computed and unbiased
3. Should be expressed in units familiar to the industry
4. Should be based on a sufficiently broad and balanced input
5. Should be transparent and simple
6. Should provide different levels of aggregated information in a
clear and calculable hierarchy
May 22-23, 2013 MIT SCM ResearchFest
Characteristics of sound freight indexes: Part 1: Index calculation and data collection
Characteristics of sound freight indexes: Part 1: Index calculation and data collection
Route Rate #2
Route Rate #3
Route Rate #4
Route Rate #5
Route Rate #6
Route Rate #7
Route Rate #8
e.g. 52,000 dwt carrying grain from US gulf to Ned.
Baltic Dry Index
Baltic Supramax Index
Weightings: 2.5-20%
Baltic Capesize Baltic Panamax Baltic Handysize
Route rate #1
Weightings: 25% each
7. Should be published regularly and frequently
8. Should be audited and monitored by an independent body
9. Should have proper procedures for dealing with complaints
10. Should be low-cost
11. Should be supported by the major participants in the market
12. Should have procedures for updating and adjusting components or
index structure as market conditions change
May 22-23, 2013 MIT SCM ResearchFest
Characteristics of sound freight indexes: Part 2: Index management
Truckload Indexes – Oct. 2010 – Sept 2012
90
95
100
105
110
115
120
125
130
135
140
Lin
e-h
aul r
ate
s (O
cto
be
r 2
01
0 =
10
0)
Stephens Freight Index
May 22-23, 2013 MIT SCM ResearchFest
Truckload Indexes – Oct. 2010 – Sept 2012
90.0
95.0
100.0
105.0
110.0
115.0
120.0
125.0
130.0
135.0
140.0
Lin
e-h
aul r
ate
s (O
cto
be
r 2
01
0 =
10
0)
Cass Line-haul Rate Index Stephens Freight Index
May 22-23, 2013 MIT SCM ResearchFest
Truckload Indexes – Oct. 2010 – Sept 2012
90.0
95.0
100.0
105.0
110.0
115.0
120.0
125.0
130.0
135.0
140.0
Lin
e-h
aul r
ate
s (O
cto
be
r 2
01
0 =
10
0)
Cass Line-haul Rate Index Stephens Freight Index
DAT Spot Van Rates
May 22-23, 2013 MIT SCM ResearchFest
90.0
95.0
100.0
105.0
110.0
115.0
120.0
125.0
130.0
135.0
140.0
Lin
e-h
aul r
ate
s (O
cto
be
r 2
01
0 =
10
0)
Cass Line-haul Rate Index Stephens Freight Index
DAT Spot Van Rates Coyote Logistics
Truckload Indexes – Oct. 2010 – Sept 2012
May 22-23, 2013 MIT SCM ResearchFest
90.00
95.00
100.00
105.00
110.00
115.00
120.00
125.00
130.00
135.00
140.00
Lin
e-h
aul r
ate
s (O
cto
be
r 2
01
0 =
10
0)
DAT Spot Van Rates Coyote Logistics
Truckload Indexes – Oct. 2010 – Sept 2012
May 22-23, 2013 MIT SCM ResearchFest
Possible explanation: Geographic Distribution
Possible explanation: Tender Lead Time
May 22-23, 2013 MIT SCM ResearchFest
Approach:
May 22-23, 2013 MIT SCM ResearchFest
• Examine rate behavior in different geographies in the US.
• “Corridor”
• 1 origin region to 1 destination region • 100-250 miles in diameter
• 8,400 corridors with volume
• 5.2% of corridors account for 50% of dollars spent
• Selected 10 corridors that represented high-volumes and various regions
• Examine the relationship between tender lead time and rates
0
0.5
1
1.5
2
2.5
3
3-O
ct-1
0
3-N
ov-
10
3-D
ec-1
0
3-J
an-1
1
3-F
eb
-11
3-M
ar-1
1
3-A
pr-
11
3-M
ay-1
1
3-J
un
-11
3-J
ul-
11
3-A
ug-
11
3-S
ep
-11
3-O
ct-1
1
3-N
ov-
11
3-D
ec-1
1
3-J
an-1
2
3-F
eb
-12
3-M
ar-1
2
3-A
pr-
12
3-M
ay-1
2
3-J
un
-12
3-J
ul-
12
3-A
ug-
12
3-S
ep
-12
We
ekl
y av
era
ge li
ne
-hau
l rat
e (
$/m
ile)
Corridor 1
Corridor 2
Corridor 3
Corridor 4
Corridor 5
Corridor 6
Corridor 7
Corridor 8
Corridor 9
Corridor 10
Average weekly rates - by corridor
May 22-23, 2013 MIT SCM ResearchFest
0
50
100
150
200
250
300
3-O
ct-1
0
3-N
ov-
10
3-D
ec-1
0
3-J
an-1
1
3-F
eb
-11
3-M
ar-1
1
3-A
pr-
11
3-M
ay-1
1
3-J
un
-11
3-J
ul-
11
3-A
ug-
11
3-S
ep
-11
3-O
ct-1
1
3-N
ov-
11
3-D
ec-1
1
3-J
an-1
2
3-F
eb
-12
3-M
ar-1
2
3-A
pr-
12
3-M
ay-1
2
3-J
un
-12
3-J
ul-
12
3-A
ug-
12
3-S
ep
-12
We
ekl
y av
era
ge li
ne
-hau
l rat
e
(lan
e a
vera
ge =
10
0)
Corridor 9
Corridor 4
Rate stability - by corridor
0
50
100
150
200
250
300
3-O
ct-1
0
3-N
ov-
10
3-D
ec-1
0
3-J
an-1
1
3-F
eb
-11
3-M
ar-1
1
3-A
pr-
11
3-M
ay-1
1
3-J
un
-11
3-J
ul-
11
3-A
ug-
11
3-S
ep
-11
3-O
ct-1
1
3-N
ov-
11
3-D
ec-1
1
3-J
an-1
2
3-F
eb
-12
3-M
ar-1
2
3-A
pr-
12
3-M
ay-1
2
3-J
un
-12
3-J
ul-
12
3-A
ug-
12
3-S
ep
-12
We
ekl
y av
era
ge li
ne
-hau
l rat
e
(lan
e a
vera
ge =
10
0)
Corridor 9
Corridor 10
Seasonal patterns – by corridor
May 22-23, 2013 MIT SCM ResearchFest
Annual rate change - by corridor
May 22-23, 2013 MIT SCM ResearchFest
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
1 2 3 4 5 6 7 8 9 10
Conclusion #1
To be useful, a spot market index should measure each corridor independently.
May 22-23, 2013 MIT SCM ResearchFest
Relationship between lead time and rate
May 22-23, 2013 MIT SCM ResearchFest
• High rate premium for same-day pick-ups
• Beyond 3 days, rates are stable
Impact of lead time by season
May 22-23, 2013 MIT SCM ResearchFest
0%
5%
10%
15%
20%
25%
30%
Corridor 6 Corridor 9 Corridor 2 Corridor 10 Corridor 5
Peak
Low
• During peak seasons, same-day loads had higher rate premiums than during slower seasons.
% difference between same-day and next-day rates
Conclusion #2
To be useful, a spot market index should specify a lead time.
May 22-23, 2013 MIT SCM ResearchFest
Ongoing challenges
May 22-23, 2013 MIT SCM ResearchFest
Ongoing challenges
May 22-23, 2013 MIT SCM ResearchFest
Key Findings
May 22-23, 2013 MIT SCM ResearchFest
• Indexes should provide information at different levels of aggregation
• Corridors, regional, national, etc.
• DAT uses this approach
• An index of spot-market truckload transportation should specify a lead time
• No existing indexes do this
• Indexes can only provide partial understanding of rates
• Each transaction has a set of unique characteristics
“… individual experiences may vary…”
May 22-23, 2013 MIT SCM ResearchFest
Thank you!
May 22-23, 2013 MIT SCM ResearchFest
Q & A
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