Transcript Commodities Master Presentation

Commodities Derivatives Trading
Sridev Ramaswamy, Global Commodities, DB London
For internal use only
Overview - The Commodities Landscape (I)
Commodity Sectors and Market Influences
Asset Class Characteristics

Commodity Sectors
The commodities asset class is made up of
very distinct sectors
 Energy
 Metals (precious and industrials)
 Agriculture (livestock and grains)

Contrary to financial assets, commodities
are physical assets. The market will be
affected by
Supply
 farming capacity
 exploitation capacity
 discovery of new exploitation sites
 weather and climate
Sector
Example
Energy
Light Crude
Heating Oil
RBOB Gasoline
Natural Gas
Industrial
Metals
Aluminium
Lead
Copper
Zinc
Nickel
Precious
Metals
Gold
Silver
Agriculture
Corn
Wheat
Coffee
Sugar
Cocoa
Coffee
Soybeans
Livestock
Live Cattle
Lean Hogs
Feeder Cattle
Demand
 production demand (raw materials)
 final consumption
 technological progress
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Overview - The Commodities Landscape (II)
Performance of Selected Commodities
Commodity Scorecard 2011 YTD
Commodity Scorecard 2010
Cotton -32.5%
Copper
Nickel
Zinc
Natural Gas
-30.2%
-27.5%
Commodity Performance 2011 YTD
-24.0%
Zinc
-22.7%
Aluminium
Sugar
-22.6%
WTI Crude Oil
-22.0%
Natural Gas
-17.9%
-7.7%
Commodity Performance 2010
-5.4%
Lead
Lead
Wheat
-20.9%
Cocoa
8.0%
11.5%
15.1%
Sugar
19.2%
Gasoline
19.5%
Soybeans
-15.5%
Gas Oil
20.0%
Cocoa
-15.2%
Heating Oil
20.1%
WTI Crude Oil
-15.1%
Gold
Aluminium
Cof f ee
-5.8%
Heating Oil
Gas Oil
14.7%
Gold
16.6%
-10%
0%
10%
46.7%
Corn
8.2%
-20%
35.1%
Wheat
2.4%
-30%
34.0%
Nickel
Gasoline
-40%
32.6%
Soybeans
-7.1%
Corn
29.1%
Copper
-13.8%
20%
51.7%
Coffee
76.9%
Cotton
-40%
91.5%
-20%
0%
20%
40%
60%
80%
100%
Source: Bloomberg, Jan 2010 to Dec 2010
Source: Bloomberg, 3 October 2011
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Commodities: Impressive Long-Run Returns
600%
500%
400%
DBLCI MR Enhanced
DJ-UBSCI TR
300%
U.S. Govt All
S&P 500
200%
DB 3m T-Bill Index
Real Estate (UK IPD)
100%
Inflation
0%
2001
2002
2003
2004
2005
2006
Commodities Commodities
(DBLCI MRE) (DJ UBSCI)
Total Return
Excess Return
11.68%
9.65%
4.00%
1.97%
2007
2008
Bonds (US
Govt All)
6.06%
4.03%
2009
2010
2011
Cash
Equities Real Estate
(3m T-Bills) (S&P 500)
(UK IPD)
2.03%
0.00%
0.19%
-1.84%
6.59%
4.56%
Inflation
(CPI)
2.44%
0.41%
Source: Bloomberg, Data from 1 January 2001 to 3 October 2011
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Performance Comparison vs. Alternatives
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
-0.5
Sharpe Ratio
Commodities
(DBLCI MRE)
Commodities
(DJ UBSCI)
Private Equity
Commodities Commodities
(DBLCI MRE) (DJ UBSCI)
Total Return
Excess Return
Volatility
Sharpe ratio
12.07%
10.06%
20.56%
0.49
3.44%
1.43%
19.52%
0.07
CTA
FX Managers
Hedge Funds
Real Estate
Private
Equity
CTA
FX
Managers
Hedge
Funds
Real
Estate
-0.47%
-2.48%
28.00%
-0.09
4.71%
2.70%
7.57%
0.36
2.19%
0.18%
2.96%
0.06
0.32%
-1.69%
4.12%
-0.41
0.32%
-1.68%
25.69%
-0.07
Private Equity: S&P Listed Private Equity Index - CTA: Newedge CTA Index - FX Managers: PBCI PGS Currency Managers Index - Hedge Funds: HFRX Global Hedge Fund
Index - Real Estate: S&P REIT Index Period is different as all data was available together only from Nov 2003
Source: Bloomberg, Data from 28 November 2003 to 3 October 2011
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Growth of Commodities as an Asset Class
Commodity ETF AUM
100.0
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In light of the superior risk-adjusted returns,
diversification benefits and inflation protection,. there
has been a significant increase in interest in
commodities as an asset class,,
A very significant portion of this interest has come from
pension funds and multi-asset funds in Europe and the
US
Investor interest in commodities is likely to persist as
the continuing presence of physical producers and
consumers leads to continuing opportunities for
investors
Commodity indices are mostly based on futures
replication. Investors use predominantly indices to
express their views, and close out their futures positions
prior to contract expiry.
Producers and consumers are normally on the other
side of these positions and are able to take physical
delivery.
Given the inability of investors to take physical delivery,
the market is dominated by physical producers and
consumers.
Europe
US
80.0
AUM(US$ bn)

60.0
40.0
20.0
0.0
Feb-05
200
Feb-06
Feb-07
Feb-08
Feb-09
Feb-10
Index investment flows by sector (US market, USD bn)
Livestocks
160
Softs
Grains
Precious & Base Metals
120
Energy
80
40
0
Dec-07
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Jun-08
Dec-08
Jun-09
Dec-09
Jun-10
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… for both vanilla and structured risk management solutions
Examples of Vanilla Products
Fixed / Floating Swaps
Floating / Floating Swaps
(Basis Swaps)
Heat Rate Options
‘Crack’ Spread Swaps
‘BTU’ Swaps
Load Shape
Asian Options
European Options
Collars
(Min / Max’s)
Correlation Transactions
Examples of Structured Products
Barrier Options
(Knock-in/out)
Trigger Swaps
(Curve Locks)
Swaptions
(Extendibles)
Range Swaps
Extendable
Collars
Producer Net Revenue Hedges
Examples of Complex Products
Credit Facilities for
Commodity Hedging
Correlation
Commodity and Asset Financing
M & A Structuring and Hedging
Monetization
Term
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Hybrids
Functions of a Trader
 Pricing
 Risk Management
 Infrastructure & Analytics
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Trade Development Context
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Need for exposure
Vehicle for exposure
Models of product behaviour
Robustness to externalities
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Trade Development Process
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Idea Generation
Evaluation Filters
Infrastructure feasibilities
Profit potential and costs of operation
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Role of Financial Mathematics
 Tool for
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Idea generation and evaluation for trade ideas (Stochastic calculus)
Algorithmic or automatic trading
Game theoretic stress tests
Technical indicator and rule based trading
News and event based impact analysis
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