Policy actions to mitigate the impact of highly volatile prices and income in commoditydependant

Transcription

1 Multi-year Expert Meeting on COMMODITIES AND DEVELOPMENT March 2011, Geneva Policy actions to mitigate the impact of highly volatile prices and income in commoditydependant countries by Mr. Jean-François Casanova, CEO, Strategic Risk Management, France "The views expressed are those of the author and do not necessarily reflect the views of UNCTAD"

2 Policy actions to mitigate the impact of highly volatile prices and income in commodity-dependant countries Multi-year expert Meeting on Commodities March 2011, Geneva

3 EXPERIENCE FROM THE LAST CRISIS 2

4 In crisis time, Oil exporters are taking the most severe hit because: They are more globally integrated/dependent to the world economy Oil export is the major source of revenue Oil price is very volatile Growth deceleration More than 3 % -2 to-3 % Zero to 1.9 % Increased growth between Source: African Economic Outlook, 2009

5 Strong dependence to the world economy and its financial markets will persist 4

6 HOW TO MITIGATE THE IMPACT OF HIGHLY VOLATILE PRICES AND INCOME ON COMMODITY-DEPENDANT COUNTRIES? 5

7 LONG TERM APPROACH 6

8 The macro LONG TERM economic way : Going down the value chain... 7

9 Worked very well in GCC 8

10 Percent of GDP & Bln $ With relatively stable Current account balances 9

11 SHORT TERM APPROACH 10

12 Similarity of behavior... Dealing with Oil price uncertainty requires you: Track invariance between present and past economic environment Analyze oil and financial markets behavior over a comparable environment but not sufficient for prediction Assign probabilities, the SCORES, to future market behavior to be used for Buy and Sell signals Design the level of price exposure acceptable within your own constraints Monitor and adjust your opinion to the environment changes Appendices :Examples of what we said over the last years

13 Now, and only now, you will implement your hedging strategy Collateral issues related to Hedging policies Higher Market Risk Hedging transforms market risk into counterparty risk 1 unhedged position 1' Direct hedging on organized markets transforms market risk into cash risk hedged position Higher counterparty risk 2 Neutral risk position CSA mitigates counterparty risk and generates cash risk hedged position with counterparty risk mitigation Higher Cash Risk 12

14 Example of liquidity issue associated with hedging with Future contracts Oil price 150$ 80$ A producer is required to hedge 30% of his production Margin calls 4,500 lots x 70$ = $315m Actual production 2,000 lots Turn over = $300m Cumulative Production profile 15,000 lots = 4,500 lots of hedge There is a point when margin calls are no longer covered by operating cash flows = One using Futures as a tool to manage the risk gets into liquidity issues Source:

15 Using SCORES for dynamically managing your hedging price exposure with Buy and Sell signals, enable to obtain this type of pro forma performance SCORES (probabilities) recognized nearly all major trends but not the short December 2008 Euro spike SCORES (probabilities) managed very well the up and down of the highly volatile Oil market

16 BUT regarding the fact that Dynamic Hedging is not riskless, is Dynamic Hedging wise? Making the choice of Dynamic hedging, you will have to face some important hurdles: Bureaucracy Personal Risk Complexity of the concepts Management qualifications Budget-Accounting dilemma Volatility of Risk 15

17 For avoiding too damaging personal risk, we advise you to use the following Toolkit Analyze the risk management implications Prepare political/cultural organization map Mobilize political support for risk management Identify and mobilize relevant talent Inform and reassure individuals/groups Select an approach appropriate to the realities of timing, resistance and power Utilize external help for diagnosis 16 16

18 Alternatively you can use banks structured products for securing your revenues stream Link funding costs to oil revenue Principal Linked to Oil Price Oil Producer issues USD amortising bond with 5-year maturity for which amortisation payments are indexed to oil price Credit spread over LIBOR will be reduced due to inherent credit mitigation of oil price risk Amortisation payments will be reduced in low crude price environment Indicative Terms and Conditions / Sample Issuer: Oil Producer Principal Amount: USD 300,000,000 Effective Date: March 2006 Maturity Date: 5 years after Effective Date Interest Rate: 3M USD LIBOR + 75 bppa Illustration of Amortization vs. Oil Price Tranches: payments XXX quarterly linear amortisation Amortisation Payment ($MM) $17 $16 $15 $14 $13 $ Oil ($/bbl) Oil Price ($/bbl) Amortisation Payment: Standard Amortisation + Oi Amortisation Standard Amortisation: USD 15,000,000 Oil Amortisation: Volume x { Max [Oil Price - $78/bbl, 0] - Max [Oil Price - $100/bbl, 0] - Max [$55/bbl Oil Price, 0] + Max [$40/bbl Oil Price, 0] } Volume: 100,000 bbl per quarterly Coupon Period Oil Price: Quarterly average of PLATTS mid prices for Dated Brent crude oil * Assumes Client standard funding at 100 bppa Oil Amortisation Payments Standard Payment Oil Price

19 ASSET ALLOCATION MODEL FOR MANAGING OIL WINDFALL FUNDS 18

20 Pro forma performance of individual asset class components of an example portfolio

21 Relative weight of every asset class used for the example of a portfolio voluntary over weighted in Oil and designed to managing Oil windfall revenues

22 Pro forma performance of an example portfolio using SCORES vs «Buy and hold» on different asset classes or asset classes mix 70/30 et 30/70

23 Based on Futures rollover with 0,5% of transaction fees on each trade, the model outperforms the risk return equation for all of its components Return Risk return of the example portfolio Volatility

24 In conclusion We DO believe that : Policy actions to mitigate the impact of highly volatile prices and income must be clear, easy to understand and to explain Hedging policies must take into account the economic environment, and the objectives and constraints of the commodity-dependant country or State owned oil company Dynamic Hedging using scenarios analysis and forecasted risk assessments are much more powerful decision-making tools than doing nothing or systematic hedging We DO NOT believe: In historical correlation for managing risks We DON T trust : either the independence of brokers and investment banks advisory services or free lunches

25 References French Treasury GE Capital EURONEXT Sal Oppenheim AREVA Thales Chargeurs SA Banques Populaires Sonatrach RTL Group Adisseo EDF Group OSEO Bank Aventis Winterthur International CSAM Efiposte / Post Bank SOCIETE GENERALE HSBC UNCTAD / UNO CDC Ixis Sonelgaz Calyon Renault SAS VINCI Credit Agricole Asset Management

26 STRATEGIC RISK MANAGEMENT 52, rue de Ponthieu, Paris +33 (0)

27 Very large Oil Price jumps and collapse over a short period of time are very frequent $34/b $147/b $25/b $102/b $60/b $11/b $19/b $34/b 26