For internal use only Commodities Derivatives Trading Sridev Ramaswamy, Global Commodities, DB London

For internal use onlyFor internal use only

Commodities Derivatives TradingSridev Ramaswamy, Global Commodities, DB London

For internal use only

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

Demand production demand (raw materials) final consumption technological progress

Overview - The Commodities Landscape (I)Commodity Sectors and Market Influences

Sector Example

Energy Light CrudeHeating OilRBOB GasolineNatural Gas

Industrial Metals

AluminiumLeadCopperZincNickel

Precious Metals

GoldSilver

Agriculture CornWheatCoffeeSugarCocoaCoffeeSoybeans

Livestock Live CattleLean HogsFeeder Cattle

Commodity SectorsAsset Class Characteristics

2

For internal use onlySpeaker nameName of

Source: Bloomberg, 3 October 2011

16.6%

14.7%

8.2%

2.4%

-5.8%

-7.1%

-13.8%

-15.1%

-15.2%

-15.5%

-17.9%

-22.0%

-22.6%

-22.7%

-24.0%

-27.5%

-30.2%

-32.5%

-40% -30% -20% -10% 0% 10% 20%

Gold

Gas Oil

Heating Oil

Gasoline

Corn

Cof fee

Aluminium

WTI Crude Oil

Cocoa

Soybeans

Natural Gas

Wheat

Sugar

Lead

Zinc

Nickel

Copper

Cotton

Commodity Performance 2011 YTD

Overview - The Commodities Landscape (II)Performance of Selected Commodities

Commodity Scorecard 2011 YTD Commodity Scorecard 2010

Source: Bloomberg, Jan 2010 to Dec 2010

91.5%

76.9%

51.7%

46.7%

35.1%

34.0%

32.6%

29.1%

20.1%

20.0%

19.5%

19.2%

15.1%

11.5%

8.0%

-5.4%

-7.7%

-20.9%

-40% -20% 0% 20% 40% 60% 80% 100%

Cotton

Coffee

Corn

Wheat

Nickel

Soybeans

Copper

Gold

Heating Oil

Gas Oil

Gasoline

Sugar

WTI Crude Oil

Aluminium

Lead

Zinc

Cocoa

Natural Gas

Commodity Performance 2010

3


Commodities: Impressive Long-Run Returns

0%

100%

200%

300%

400%

500%

600%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

DBLCI MR Enhanced

DJ-UBSCI TR

U.S. Govt All

S&P 500

DB 3m T-Bill Index

Real Estate (UK IPD)

Inflation

Commodities (DBLCI MRE)

Commodities (DJ UBSCI)

Bonds (US Govt All)

Cash (3m T-Bills)

Equities (S&P 500)

Real Estate (UK IPD)

Inflation (CPI)

Total Return 11.68% 4.00% 6.06% 2.03% 0.19% 6.59% 2.44%Excess Return 9.65% 1.97% 4.03% 0.00% -1.84% 4.56% 0.41%

Source: Bloomberg, Data from 1 January 2001 to 3 October 2011

4


Performance Comparison vs. Alternatives

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6



Private Equity CTA FX Managers Hedge Funds Real Estate

Sharpe Ratio



Private Equity

CTAFX

ManagersHedge Funds

Real Estate

Total Return 12.07% 3.44% -0.47% 4.71% 2.19% 0.32% 0.32%Excess Return 10.06% 1.43% -2.48% 2.70% 0.18% -1.69% -1.68%Volatility 20.56% 19.52% 28.00% 7.57% 2.96% 4.12% 25.69%Sharpe ratio 0.49 0.07 -0.09 0.36 0.06 -0.41 -0.07

Source: Bloomberg, Data from 28 November 2003 to 3 October 2011

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

5


Growth of Commodities as an Asset Class

6

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.

0

40

80

120

160

200

Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10

Index investment flows by sector (US market, USD bn)

Livestocks

Softs

Grains

Precious & Base Metals

Energy

0.0

20.0

40.0

60.0

80.0

100.0

Feb-05 Feb-06 Feb-07 Feb-08 Feb-09 Feb-10

AU

M(U

S$

bn)

Commodity ETF AUM

Europe US


… for both vanilla and structured risk management solutions

‘BTU’ Swaps‘BTU’ Swaps‘Crack’ Spread Swaps‘Crack’ Spread Swaps

Collars (Min / Max’s)

Collars (Min / Max’s)

Asian OptionsEuropean Options

Asian OptionsEuropean Options

Floating / Floating Swaps (Basis Swaps)

Floating / Floating Swaps (Basis Swaps)Fixed / Floating SwapsFixed / Floating Swaps

Examples of Vanilla Products

Swaptions(Extendibles)Swaptions

(Extendibles)Barrier Options (Knock-in/out)

Barrier Options (Knock-in/out)

Producer Net Revenue HedgesProducer Net Revenue HedgesExtendableCollars

ExtendableCollarsRange SwapsRange Swaps

MonetizationMonetizationCommodity and Asset FinancingCommodity and Asset FinancingCredit Facilities for Commodity HedgingCredit Facilities for Commodity Hedging

Trigger Swaps(Curve Locks)Trigger Swaps(Curve Locks)

Examples of Structured Products

Examples of Complex Products

Load ShapeLoad Shape

Heat Rate OptionsHeat Rate Options

TermTermM & A Structuring and HedgingM & A Structuring and Hedging

Correlation Transactions

CorrelationCorrelation HybridsHybrids


Functions of a Trader

8

Pricing Risk Management Infrastructure & Analytics


Trade Development Context

9

Need for exposure Vehicle for exposure Models of product behaviour Robustness to externalities


Trade Development Process

10

Idea Generation Evaluation Filters Infrastructure feasibilities Profit potential and costs of operation


Role of Financial Mathematics

11

Tool for

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


Disclaimer

12

MARKETING MATERIALThis document is intended for discussion purposes only and does not create any legally binding obligations on the part of Deutsche Bank AG and/or its affiliates (“DB”). Without limitation, this document does not constitute an offer, an invitation to offer or a recommendation to enter into any transaction. When making an investment decision, you should rely solely on the final documentation relating to the transaction and not the summary contained herein. DB is not acting as your financial adviser or in any other fiduciary capacity with respect to this proposed transaction. The transaction(s) or products(s) mentioned herein may not be appropriate for all investors and before entering into any transaction you should take steps to ensure that you fully understand the transaction and have made an independent assessment of the appropriateness of the transaction in the light of your own objectives and circumstances, including the possible risks and benefits of entering into such transaction.

For general information regarding the nature and risks of the proposed transaction and types of financial instruments please go to www.globalmarkets.db.com/riskdisclosures. You should also consider seeking advice from your own advisers in making this assessment. If you decide to enter into a transaction with DB, you do so in reliance on your own judgment.

The information contained in this document is based on material we believe to be reliable; however, we do not represent that it is accurate, current, complete, or error free. Assumptions, estimates and opinions contained in this document constitute our judgment as of the date of the document and are subject to change without notice. Any projections are based on a number of assumptions as to market conditions and there can be no guarantee that any projected results will be achieved. Past performance is not a guarantee of future results.

This material was prepared by a Sales or Trading function within DB, and was not produced, reviewed or edited by the Research Department. Any opinions expressed herein may differ from the opinions expressed by other DB departments including the Research Department. Sales and Trading functions are subject to additional potential conflicts of interest which the Research Department does not face. DB may engage in transactions in a manner inconsistent with the views discussed herein. DB trades or may trade as principal in the instruments (or related derivatives), and may have proprietary positions in the instruments (or related derivatives) discussed herein. DB may make a market in the instruments (or related derivatives) discussed herein. Sales and Trading personnel are compensated in part based on the volume of transactions effected by them. The distribution of this document and availability of these products and services in certain jurisdictions may be restricted by law. You may not distribute this document, in whole or in part, without our express written permission.

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For internal use only Commodities Derivatives Trading Sridev Ramaswamy, Global Commodities, DB London