Commodity Risk Management - DACT – DACT - …€¦ · Commodity Risk Management ......
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Transcript of Commodity Risk Management - DACT – DACT - …€¦ · Commodity Risk Management ......
1. How to determine your specific Commodity Risks2. Understand the basics3. What affects your costs and by which percentage4. Risk management5. Forward curves & price dynamics6. Volatility of FX and Interest Rates
Agenda
Introduction KYOS CCAPart I
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7. Volatility of Commodities8. Correlation & co-integration9. Value-at-Risk (VAR)10. Credit Risk (Potential Future Exposure)11. Documentation (ISDA) 12. Accounting IFSR - IAS39
Commodity “Formula Assistant“Portfolio & Risk Management Tool
Part II
Introduction KYOS CCA
Background
� Active since 1997 as Maycroft, since 2008 transformed into KYOS
� Strong focus on energy & commodity markets: trading, valuation, risk management
� Core competence: combine quantitative background with practical solutions
� Experienced and dedicated expert team
Activities
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� Modelling
Apply quantitative financial techniques to Commodity markets
� Consulting
Advise on commodity trading, valuation and risk management
� Training ( procurement & treasury )
Combine theory with real life examples
� Power plant valuation
� Gas storage and swing pricing
� Value long term tolling agreements
� Commodity price modelling based on fundamental co-integration
Introduction KYOS work & customers
Recent ProjectsRecent Projects CustomersCustomers
� Asphalt/Bitumen price formulas
� Energy % in Cement Bricks Glass
� Development “VAR” and capital allocation framework
� Credit Risk Exposure ( PFE’s)
� Metal hedging advice in terms of Cash flow-at-risk (CfAR)
4Our advice is a result of thorough understanding of your business….
• Construction Cement, Asphalt/Bitumen, Steel, Glass , Diesel.. …aluminium
• Cable/wire Copper, Lead & Plastics …olefins
• Beverage Steel / Aluminium cans …packaging
• Transport Diesel/JetFuel / GasOil …trains
• Chemicals Electricity, Steam, Naphta, Benzene, Xylene …aromatics
• Energy Coal, Coke, Natural Gas, Oil, carbon …electricity
• ….
• Steel, Food, Glass, Cement, Brick, Sugar, Automotive, Retail, Pharmaceutical……
Hedging is an end stage….what is your risk ?
• Steel, Food, Glass, Cement, Brick, Sugar, Automotive, Retail, Pharmaceutical……
Your sector is exposed to commodities, energy is often one of them
Commodity exposures can be quantified either direct or indirect…..
Treasury involvement
� Combine FX and Interest Rate exposures with Commodity exposures
� Discover differences in volatility & liquidity compared to FX & IR
� Discover the overlap of financial hedging opportunities of commodity risks
� Analyze sensitivity of hidden currency components
� Quantify value-at-risk ( or : cashflow-at-risk )
� Determine an optimal risk profile in line with FX and IR
..treasurer & risk manager….what is your task ?
� Determine an optimal risk profile in line with FX and IR
� Use your “wallet” to invite the proper banks to compare physical suppliers
� Introduce quantified Credit Risk (Potential Future Exposure)
� Think global but act local….
KYOS CCA can quantify direct or in-direct Commodity Exposures
…back to the basics and develop insight…
Barrel crudeAbbr. “bbl”
…a construction company consumes bitumen….
Understanding the production processwill certainly lead to a better understanding of the costs of :
• NYNAS
Question: Are you able to calculate the effect on your P&L of fast moving “commodity” prices…..
• NYNAS• Petroplus• Total• Shell• ExxonMobil
…..we all consume OLEFINS and AROMATICS….
• Committee of chief risk officers (US): www.ccro.org
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…know where your product fits in the circle …..
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Gather the correct information.....
…understanding the cost structure of suppliers…
Analyze your suppliers:
� Balance sheet
� P&L statement
� EBITDA
� Cost structure
� Profit & margin breakdown
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Breakdown of Commodity costs
� Cement
� Materials
� Clay
� ......
Breakdown of Energy costs
� Coal
� Natural gas
� ......
…leads to improved predictability of your costs…
20%
28%
12%
9%
9%
12%
10%
Float Glass Production Costs
Raw Materials
Energy
Prime Labour
Overhead
Depreciation
Transport
Other
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How about the predictability of your costs ?
� Metals
� Glass
� Transport
� Plastics
� Cement/Bricks
� .........
Other
Exposure Price Change
Cashflow-at-Risk
….from basics towards Risk Management
Treasurer questions: Funding horizon ?Hedging horizon ?Fix Floating mixture ?
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Market Credit Operational
Risk
Other
…how to organise “Risk Management“…..
? ? ?
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Credit Exposure:
Measure for the loss of market / replacement value in case of default
Credit Exposure
Current Exposure
Potential
Loss, if default
occurs now.
“Worst case” loss,
…… counterparty risks……
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Potential Future
Exposure
“Worst case” loss,
if default occurs at
a future point in time.
Is the supplier with the best price also the best choice ?
Treasurer question : how do you “rate” your counterparties ?
Treasurer task - Search in Reuters for CDS market Rexam versus CrownCork
Physical Exposure: Secured physical requirements Volumetric constraintsLiquidity issues
Price Exposure: Floating or FIX Benchmark (EURIBOR ?)Currency ( USD or EUR)
…combine physical & financial markets…
Market
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Cashflow-at-risk: what is the risk ?
Floating - price could rise - how much ?Fix - price could fall - how much ?BenchmarkCurrency
Treasurer question: Normal EURUSD move in a single day ( in $ pips )
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Pri
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….different curves & price dynamics than FX….
“Contango” “Backwardation”
“Seasonality”
Commodity curves examples
Power Base Peak NatGas Base
EUR/MWh EUR/Mwh
nov-09 47.98 66.85 nov-09 11.945
dec-09 45.33 61.55 dec-09 13.085
jan-10 49.83 69.04 jan-10 14.338
feb-10 50.42 69.86“Seasonality”
spot vs 5 yr
• Aluminium 1800 ……
• Copper 6200 ……
( both quoted in $/MT )
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feb-10 50.42 69.86
Mar-10 45.46 60.64 Q1-10 14.196
apr-10 41.12 55.69 Q2-10 13.921
Q1-10 48.51 66.28 Q3-10 13.709
Q2-10 40.74 55.07 Q4-10 19.088
Q3-10 44.24 61.40 Sum-10 13.814
Q4-10 54.78 78.54 Win-10 20.081
Q1-11 59.46 85.88 Sum-11 18.919
Q2-11 44.83 63.38 Win-11 22.568
Cal-10 47.08 65.35 Cal-10 15.238
Cal-11 52.75 76.29 Cal-11 20.198
Cal-12 56.12 81.25 Cal-12 21.865
Cal-13 60.94 89.02
Cal-14 65.89 92.73
Correct estimation is complicated because:Volatility is not directly observable
We need to forecast future volatility levels, but can only measure in the past
Volatility is generally heteroskedastic – i.e. changes over time
Volatility of commodities can bear seasonality
Depends on time to maturity
… what is the volatility …. know the basic rules…
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But we need volatility to:Estimate the short term risk of positions (VAR)
Estimate the long term risk of positions (CFAR, PFE*) and assets
Value options and flexible assets
* PFE = Potential Future (Credit) Exposure
A B A C U S Advisory
Volatility = Annualized standard deviation of returns
Calculation Steps
1. Take time series of pricesduring a sample period:
price sample = {p , … , p } 300
400
500
600
700
800
…how to calculate volatility….
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price sample = {p0, … , pN}
2. Calculate returns:
A B A C U S Advisory
0
100
200
300
Mar-99
Jul-99
Nov-9
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Mar-00
Jul-00
Nov-0
0
Mar-01
Jul-01
Nov-0
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Mar-02
Jul-02
Nov-0
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Mar-03
Jul-03
Nov-0
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Mar-04
)pln()pln(p
ppr tt
t
tt
t 1
1
−− −≈
−=
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
Mar-
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Jul-99
Nov-9
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Mar-
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Jul-01
Nov-0
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Mar-
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Jul-02
Nov-0
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Mar-
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Nov-0
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Mar-
04Dail
y r
etu
rn
Calculation Steps Continued
3. Estimate standard deviation of returns
∑=
−−
=N
t
t
est )rr(N 1
2
1
1σ
….what is the probability of the returns….
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-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
Mar-
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Jul-99
Nov-9
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Mar-
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Jul-00
Nov-0
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Mar-
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Jul-01
Nov-0
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Mar-
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Jul-02
Nov-0
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Mar-
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Jul-03
Nov-0
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Mar-
04Dail
y r
etu
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Probability density of returnsTime series of returns
StandardDeviation
Calculation Steps Continued
returnacalculatetouseddays)trade(ofnumber
yearperdays)trade(ofnumberFactorionAnnualizat =
4. Calculate annualization factor
5. Rescale standard deviation to 1-year holding period
…and use Volatility for next year‘s budget …
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Mean ± 1 Standard Deviation
0
0,5
1
1,5
2
0 1 2 3 4 5 6 7 8 9 10 11 12
time in months
68% probability
5. Rescale standard deviation to 1-year holding period
volatility = standard deviation of returns * annualization factor
“Square Root of Time Rule”
Treasurers question Volatility %
1 months EURUSD ……….
3 months EURIBOR ….……
Treasurer: are you familiar with “your“ volatility….
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3 months EURIBOR ….……
A B A C U S Advisory
...theory starts to grow into a practical approach...
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Correlation for different scatter plots
…are you familiar with correlation ?
…is your commodity related to another commodity ?…
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Source: Wikipedia
How to measure correlation?
Normalize covariance: Divide by standard deviations
[ ]
∑∑
∑=
−−
−−−
==NN
N
t
t,t,
est
r
est
r
estest
r,r
)rr(*)rr(
)rr(*)rr(N
*
)r,r(cov
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1
2211
2
21
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1
1
1
21 σσρ
…can you quantify this movement….
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Correlation = 1: The returns of the prices for the two products havethe same sign, but not necessarily the same size.
Correlation = -1: The returns of the prices for the two products haveopposite signs , but not necessarily the same size.
Correlation = 0: Return pairs can be any combination.
A B A C U S Advisory
∑∑==
−−
−− t
t,
t
t, )rr(N
*)rr(N 1
22
1
11
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Co-integration
Correlation: ‘Commonality’ of two series of (daily) price changes
Cointegration: ‘Commonality’ of two series of (log) price levelsCointegration can be seen as “mean reversion of price spreads”, wherethe underlying prices contribute to the predictable adjustment to a different degree. Examples:
…better ways to quantify this price behaviour…
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• National Income and National Savings
• Power price and Fuel prices
• Zeebrugge and TTF gas prices
The concept was developed by Clive Granger and Robert Engle (Nobel prize 2003)
How to model co-integration
Equilibrium relationship:
In case of equilibrium: Y = a + b * t + c * X
Deviation from equ.: Z = Y - a - b * t - c * X
…for the upcoming winter evenings….
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Z = 0 ⇒⇒⇒⇒ Y – c * X = a + b * t
SDE for 1st commodity:
dX = (µX + ηX * Z) * dt + σX * dWX
SDE for 2nd commodity:
dY = (µY - ηY * Z) * dt + σY * dWY
Appendix: Normal Distribution Table
Probability content from - ∞∞∞∞ to z standard deviations
…use your old (..or recent..) school books….
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standard deviations
Common percentilesfor measuring risk
68.2% = 1*standard deviation
95.4% = 2*standard deviation
…“normal distribution of Commodity costs“ ….
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What is my VAR ….what is my Value-at-Risk?
VAR is the maximum loss of MtM value on my pension fund
portfolio over a certain holding period with a certain confidence:
Holding period
P(return ≥≥≥≥ - ? %) = 95%
..use quantification as a risk measurement tool
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95%
Confidence levelMaximum loss: 9.3%
P(return ≥≥≥≥ - ? %) = 95%
Investment = € 100.000
VAR = -9,3% x € 100.000
= - € 9.300
Value-at-Risk for a “5 day” Aluminium position
Annualized Volatility 51%
* Underlying Price * 1,800 $/MT
& CHANGE theory into your practical approach...
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* Underlying Price * 1,800 $/MT
* Confidence-Multipl. * 1.645
* √ Holding Period * √ 5/250
= 168 $/MT
for 95% confidence
Value of quantified Value-at-Risk figures
A good risk methodology should answer the following questions:
�How much value can be lost in total (downside focus)?
...express the guts feeling into quantified figures...
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�How much value can be lost in total (downside focus)?
�Quantified risk for strategy A compared to strategy B (or C) ?
�How to alter your strategy given an agreed maximum loss ?
Common VAR methods
Delta-Normal:• Approximate contract values as a linear function of underlying prices
• Assume correlated Brownian Motion for underlying prices
• Calculate maximum loss based on percentile on normal return distribution
Historical Simulation:
...use Monte Carlo simulation & Co-integration...
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Historical Simulation:• Take historical sample of n-day prices changes
(e.g. during last 100 or last 1,000 trading days)
• Calculate returns of current position for historical n-day price changes
• Calculate maximum loss based on …… worst return for 99% confidence, 5th worst return for 95% confidence
Monte-Carlo Simulation:Like historical simulation, but price changes come from a price simulation
model ⇒ Rarely observed extreme price changes can be included.
Confidence levels and holding periods
The choice of the holding period and confidence level depend on the type of position, for which risk needs to be assessed. Typical VAR measures are:
• 10-day liquidation VAR with 99% confidence:
Basel II standard for risk reporting of financial institutions. It is assumed that
...and act as a professional risk manager....
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Basel II standard for risk reporting of financial institutions. It is assumed that all positions can be liquidated in 1 month time. The market risk during this liquidation period is assumed to be equivalent to holding the full position for 2 weeks (= 10 trading days).
• 1-day overnight VAR with 95% confidence:
Common standard for internal risk reporting on proprietary books. The risk measure is used to internally asses the risk of overnight positions.
….natural gas formula example….
EURcnt/M3 = x * (LSFO) + y * (GasOil) + z
LSFO and GasOil in EURLSFO and GasOil in EUR
….we are able to analyze formula contracts….
…different energy providers use different sources…..
….also in the strangest formats..….
…and isolate the “underlying” quantified volumes.
By understanding the formula behind the contract you are able to define your complete exposureto:
- Commodities- FX components
Formulas …
Energy - PetCoke, Natural Gas, Steam…..
Dredging - Maasvlakte II
Beverage - Can (metal) & Glass (energy)
Construction - Steel, Cement, Bitumen, Glass….
Treasurers: your “private gas consumption ” is linked to GasOil….
..compare history & forwards of the underlying..
Treasurers: ……now you are able to start risk analyses
& in co-operation with procurement.. make better prepared decisions
…what if GasOil moves 100$ up …..
…what is the sensitivity to price changes….
Treasurer question : can you isolate the currency exposure…..
…YES treasurer….YOU CAN….isolate the Currency Risk…..
…as this might justifies a $ price risk….
Treasurer: should procurement buy in USD or in EUR ?
…from the basics to “cashflow-at-risk”….
…from “data” to management decisions …..
…prepared decisions decisions …..
10%
12%
14%
Strategy A versus Benchmark
0%
2%
4%
6%
8%
-€ 3.1 mln -€ 2.2 mln -€ 1.4 mln -€ 0.6 mln € 0.3 mln € 1.1 mln € 2.0 mln
…from rough data to “refined risk management”
Calculate the “expected monthly payments” …..and adjust or maintain
your strategy …..it is now a well defined & thorough calculated strategy
…including Credit Risk per counterparty…..
..calculate the “potential future exposure” (PFE) on counterparties…
…from the basics tot “cashflow-at-risk”…..
Proper Monte Carlo simulations leads to valuable insight in risks
Business areas risk limit profile
..now we can implement a risk driven approach..
A = TreasuryB = Procurement PackagingC = Procurement Energy
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Risk Manager has now created diversification for different business areas such as Treasury and Procurement over time.
Power Gas CO2FX Interest rate
� information is spread throughout subsidiaries ( decentralized )- start mapping
� difficulty of correctly quantifying the exposure- quantify natural hedges & “pass on” procedures (clauses)
� managers have different view on RM objectives- agree on earnings volatility and calculate backwards
...reasons for not having a policy...
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� managers not accountable- budgets FX-, IR- & Commodity……Risk Management
� regulated markets in the past ( gas, electricity…)- markets have changed rapidly
� impact on competitive position of the company- steep learning curve in the market
� futures, swaps and options- in line with FX and IR
� swaps are most commonly used - in line with FX and IR
� mark-to-market- liquid benchmarks have same MtM reporting functionality
...unknown product range or documentation...
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- liquid benchmarks have same MtM reporting functionality
� documentation- most financial commodity swaps fit in the “ISDA” (annex) - carbon is a physical product ( adjusted documentation) - physical power transactions documented under “EFET”
IFRS - IAS39
Cashflow hedging in compliance & in-line with company policy
� Use liquid references in your purchasing contracts
..commodity hedges and accounting....
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� Use liquid references in your purchasing contracts
� Make sure the hedge is in line with the underlying risk
� KYOS CCA runs “hedge effectiveness tests”
� Align purchasing contracts with financial opportunities
Commodity prices have fallen to lower levels so now it is time to :
� Learn the basics, educate yourselves
� Adjust and align treasury, procurement & sales
� Create a competitive advantage
..timing is good....
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�Lower your costs by combined efforts
� Balance the need for flexibility given an agreed horizon
� Install risk limits in line with companies risk appetite
� Distinguish the company from competitors
Risk Managers have an import role to play in this journey to success
� physical and volumetric details
� secure the required goods
� maintain flexibility (quality, form)
..success stories in practise....
KYOS CCA has visited many European Industrials who incorporated physical procurement & financial hedging successfully
Role Procurement Role Treasury
� financial details
� companies hedging policy
� documentation
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� maintain flexibility (quality, form)
� timing of delivery
� embed liquid benchmarks
� documentation
� quantify company risk
� manage financial risks
KYOS CCA has experience with Clients in following industries:
-Cement/Bricks -Steel -Construction -Energy (incl Waste)-Glass -Base Metals -Chemical -Beverage-Retailers -Food/sugar -Pharmaceutical -…….
Richard Cornielje
KYOS Corporate Commodity Advisory
KYOS CCA contact details
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KYOS Corporate Commodity Advisory
Lange Herenstraat 38 zwart
2011 LJ Haarlem (Netherlands)
+31 (0)6 8324 5737
www.kyos.com
