Commodity Market Forecasting - IHS Markitforecasting linked to detailed macroeconomic models Oil...
Transcript of Commodity Market Forecasting - IHS Markitforecasting linked to detailed macroeconomic models Oil...
Commodity Market ForecastingCommodity Market ForecastingWhat know and what we don’t know What know and what we don’t know
about the futureabout the futureGlobal Insights 40Global Insights 40thth AnniversaryAnniversary
22 October 200322 October 2003
31 Mt Pleasant,31 Mt Pleasant,London WC1X OAD, UKLondon WC1X OAD, UKTel: +44+20 7278 7788Tel: +44+20 7278 7788
Fax: +44+20+7278 0003Fax: +44+20+7278 0003
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Tel: +1+360 321 4707Tel: +1+360 321 4707Fax: +1+360 321 4709Fax: +1+360 321 4709
Additional offices and representatives: Additional offices and representatives: Philadephia Philadephia (Exton), (Exton), Rio de Rio de JanieroJaniero and Sydneyand Sydney
ResourceStrategies
Slide 2
ContentsContents
1) The Lessons of History
2) Commodity Markets Today
3) Key Issues for the Future
ResourceStrategies
Slide 3
There are two incompatible approaches There are two incompatible approaches to commodity price forecastingto commodity price forecasting
Fundamental Technical
• Demand is derived from economic activity
• Supply takes place in response to resource availability
• Imbalances are resolved by inventory changes which drive prices
• Used for both long-term and short-term forecasts
• All relevant market information is contained in the price
• Price trends are the key to price forecasting
• Prices forecast by purely statistical techniques and chart analysis
• Used mostly for very short-term forecasts
ResourceStrategies
Slide 4
Commodity futures prices are no Commodity futures prices are no substitute for a decent forecastsubstitute for a decent forecast
• Example: average absolute error using LME 3 month aluminum price as a forecast is $100/t
• this is 3-4 times the average absolute error of forecasts by Chase Econometrics/Resource Strategies/CRU
• “Future” price is actually today’s price for a physical delivery in the future
• This incorporates today’s market expectations• new information obviously affects expectations in the
mean time; so outcomes are not as predicted
• But: futures prices happen to be a statistically unbiased predictor of actual prices
ResourceStrategies
Slide 5
Three equally “unbiased” forecasts Three equally “unbiased” forecasts ––but one is clearly better !but one is clearly better !
Price
80
90
100
110
120
1 2 3 4 5
Forecast A Forecast B Forecast C Actual
Right direction 75%
of the time
ResourceStrategies
Slide 6
Statistical trend analysis and fundamental Statistical trend analysis and fundamental research yield similar results for copperresearch yield similar results for copper
Real Copper Price
1000
2000
3000
4000
5000
6000
7000
Jan-8
0Ja
n-81
Jan-8
2Ja
n-83
Jan-8
4Ja
n-85
Jan-8
6Ja
n-87
Jan-8
8Ja
n-89
Jan-9
0Ja
n-91
Jan-9
2Ja
n-93
Jan-9
4Ja
n-95
Jan-9
6Ja
n-97
Jan-9
8Ja
n-99
Jan-0
0Ja
n-01
Jan-0
2Ja
n-03
Statistical trend Median - LRMC
SRMC
ResourceStrategies
Slide 7
The same is true for nickelThe same is true for nickel
Real Nickel Price
0
5000
10000
15000
20000
25000
30000
Jan-8
0Ja
n-81
Jan-8
2Ja
n-83
Jan-8
4Ja
n-85
Jan-8
6Ja
n-87
Jan-8
8Ja
n-89
Jan-9
0Ja
n-91
Jan-9
2Ja
n-93
Jan-9
4Ja
n-95
Jan-9
6Ja
n-97
Jan-9
8Ja
n-99
Jan-0
0Ja
n-01
Jan-0
2Ja
n-03
Median - LRMC Statistical trend
SRMC
ResourceStrategies
Slide 8
But the aluminum trend is improbably low But the aluminum trend is improbably low due to structural shift in power marketsdue to structural shift in power markets
Real Aluminum Price
1000
1500
2000
2500
3000
3500
4000
4500
Jan-8
0Ja
n-81
Jan-8
2Ja
n-83
Jan-8
4Ja
n-85
Jan-8
6Ja
n-87
Jan-8
8Ja
n-89
Jan-9
0Ja
n-91
Jan-9
2Ja
n-93
Jan-9
4Ja
n-95
Jan-9
6Ja
n-97
Jan-9
8Ja
n-99
Jan-0
0Ja
n-01
Jan-0
2Ja
n-03
Statistical trend
Median - LRMC
SRMC
ResourceStrategies
Slide 9
Similar result in zinc, probably due to Similar result in zinc, probably due to Europe exit barriers & Chinese competitionEurope exit barriers & Chinese competition
Real Zinc Price
500
1000
1500
2000
2500
3000
Jan-8
0Ja
n-81
Jan-8
2Ja
n-83
Jan-8
4Ja
n-85
Jan-8
6Ja
n-87
Jan-8
8Ja
n-89
Jan-9
0Ja
n-91
Jan-9
2Ja
n-93
Jan-9
4Ja
n-95
Jan-9
6Ja
n-97
Jan-9
8Ja
n-99
Jan-0
0Ja
n-01
Jan-0
2Ja
n-03
Statistical trend
Median - LRMC
SRMC
ResourceStrategies
Slide 10
The really important decisions tend The really important decisions tend to require fundamental forecaststo require fundamental forecasts
• New project feasibility studies are not “bankable” without a fundamental forecast
• Long-term fundamental forecasts are required for asset valuations and for effective implementation of value based management
• Critical technical issues (definition of reserves, life of mine planning) require fundamental forecasts
• Industry stakeholders continue to make or buy fundamental forecasts despite their mediocre accuracy record
ResourceStrategies
Slide 11
Forecasting methods have adapted Forecasting methods have adapted to the market environmentto the market environment
Period Market Environment Forecasting Trends
First formal econometric forecasting models; classic market clearing; aggregated data
Strong demand growth, nationalization to secure economic rents, stable or rising prices
1960-1973
Highly disaggregated forecasting linked to detailed macroeconomic models
Oil crisis, severe cycles in demand and price, threat of hyper-inflation
1973-1982
Focus on supply side forecasting and understanding production costs
Reduced inflation, high interest rates, weak demand, sharp fall in prices, privatization begins
1982-1989
Hybrid forecasting techniques geared to understanding structural issues
Collapse of communism, sustained growth based on globalization and low inflation, prices still fall
1989-2001
ResourceStrategies
Slide 12
The market clearing model The market clearing model –– a a simplified versionsimplified version
Demand
Market Balance
Supply
Operating Rate
Capacity
Inventories
Production Costs
Prices
World Economy
ResourceStrategies
Slide 13
The demand side lessonsThe demand side lessons
Demand
Market Balance
Prices Capacity
• Far richer macro forecasts –but more detailed is not necessarily more accurate
• Minimal progress on understanding price elasticities
• Cost culture has weakened link between demand and investment
World Economy
ResourceStrategies
Slide 14
The supply side lessonsThe supply side lessons
Market Balance
Prices
Supply
Production Costs
Operating Rate
Capacity
• Comprehensive mine by mine, plant by plant databases
• Sophisticated understanding of cost structures
• Investment dynamics have experienced structural change
World Economy
ResourceStrategies
Slide 15
Commodity markets have Commodity markets have asymmetrical pricing dynamicsasymmetrical pricing dynamics
Condition Required Signals Price Implication
Prices rise to large premium over costs of even the highest cost producer; reflect short-run opportunity cost of the marginal consumer
All available capacity is operating but stocks are low and falling; auction market until marginal consumer defers demand
Deficit markets
Prices fall to the industry’s short-run marginal costs (SRMC)
Demand is fully satisfied and stocks are high and rising; market signals the need to cut production
Surplus markets
Prices reflect SRMC plus a premium based on future expectations; in equilibrium this equals industry long-run marginal costs (LRMC)
Demand is satisfied and producers who wish to operate are doing so; inventories are reasonable and/or trends are unclear
In between markets
ResourceStrategies
Slide 16
Prices are more often predictably below Prices are more often predictably below trend than unpredictably abovetrend than unpredictably above
Al Cu Pb Zn NiAverage of 5
MetalsMonthly DataBelow Average # 142 193 191 147 140 163 Average Deviation -12.2% -19.9% -19.4% -11.8% -18.5% -16.4% Max Deviation -28.7% -40.1% -40.0% -33.1% -43.4% -37.1%Above Average # 141 90 92 136 143 120 Average Deviation 23.3% 16.6% 22.9% 22.1% 34.2% 23.8% Max Deviation 106.7% 55.5% 122.8% 98.6% 191.7% 115.1%
Annual DataBelow Average # 11 13 15 13 12 13 Average Deviation -10.9% -22.8% -19.2% -8.7% -16.6% -15.6% Max Deviation -21.9% -35.5% -35.2% -29.8% -32.8% -31.0%Above Average # 12 10 8 10 11 10 Average Deviation 21.0% 10.9% 20.7% 23.5% 34.5% 22.1% Max Deviation 70.4% 29.6% 76.2% 68.0% 104.3% 69.7%
Metal Price Deviations from TrendJanuary 1980 to July 2003
ResourceStrategies
Slide 17
“Fan Charts” illustrate the role of “Fan Charts” illustrate the role of expectations in determining pricesexpectations in determining prices
1000
1200
1400
1600
1800
2000
2200
2400
2600
Cash 3-month
15-month
27-month
39month
54-Month
1000-10991100-11991200-12991300-13991400-14991500-15991600-16991700-17991800-18991900-19992000-20992100-21992200-22992300-
Structure of Forward Aluminum Prices Since 1989
ResourceStrategies
Slide 18
ContentsContents
1) The Lessons of History
2) Commodity Markets Today
3) Key Issues for the Future
ResourceStrategies
Slide 19
The big picture across commodity The big picture across commodity metals reflects the global economymetals reflects the global economy
• Commodity metal prices peaked between Q3 2000 and Q1 2001
• reflecting a global slowdown that predated 9/11
• The period of decline lasted 18-24 months• basically flat to recovering since mid 2002
• The recovery has been very uneven to date• well over 50% of volume growth in most metals is
coming from China
• most of the rest from other Asia and North America
• CIS has turned round, but absolute volumes are low
ResourceStrategies
Slide 20
Prices, however, are still well below prePrices, however, are still well below pre--recession averages recession averages –– except nickelexcept nickel
-30%
-20%
-10%
0%
10%
20%
30%
40%
Copper Lead Zinc Aluminium Nickel Tin
Average 3-month price: June 2003 vs 1993 - 2002
Special case reflecting the failure of new technology which deterred investment in late 1990s
ResourceStrategies
Slide 21
Normal (inverse) relationships between Normal (inverse) relationships between inventories and prices except for nickelinventories and prices except for nickel
LME stock and price changes, Dec ’02 – June ’03
-30%
-20%
-10%
0%
10%
20%
Zinc Aluminium Lead Copper Tin Nickel
LME stocks
LME prices
ResourceStrategies
Slide 22
CRU CRU HeatchartHeatchartTMTM
2003: Nickel hottest2003: Nickel hottest
-30%
-20%
-10%
0%
10%
20%
30%
40%
50% 75% 100% 125% 150% 175%
Stock:consumption ratio versus 15 year average
Surp
lus/
defic
it to
sto
cks
ratio
Nickel
Aluminium
Zinc
Lead
CopperTin
The “The “heatchartheatchart” shows considerable ” shows considerable divergence among metalsdivergence among metals
ResourceStrategies
Slide 23
We forecast that there will be We forecast that there will be relatively few changes in 2004relatively few changes in 2004
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
50% 75% 100% 125% 150%
Stock:consumption ratio versus 15 year average
Surp
lus/
defic
it to
sto
cks
ratio
Nickel
Aluminium
ZincLead
Copper
Tin
CRU CRU HeatchartHeatchartTMTM
2004 Forecast2004 Forecast
ResourceStrategies
Slide 24
ContentsContents
1) The Lessons of History
2) Commodity Markets Today
3) Key Issues for the Future
ResourceStrategies
Slide 25
There are four major issues that There are four major issues that we can now identifywe can now identify
• The impact of China on demand and supply
• Globalization versus protectionism
• The ability to manage the cycle and deliver shareholder value
• The impact of new technologies
ResourceStrategies
Slide 26
Chinese risk is now a critical factor in Chinese risk is now a critical factor in virtually every commodity marketvirtually every commodity market
• China accounts for 50%-70% of the annual growth in global demand (greater impact than Japan inn the 1960s)
• will coastal prosperity spread to interior China?
• when will the growth rate mature?
• China is a major producer and exporter of key commodities
• most ferroalloys, zinc, magnesium etc
• unsustainable development of power-intensive sector
• Potential exists for unexpected and severe swings in net trade balances
ResourceStrategies
Slide 27
The triumph of globalization over The triumph of globalization over protectionism is not a done dealprotectionism is not a done deal
• Steel sectors continue to be heavily protected• will be increasingly challenged by technology change in
upstream iron and steel sectors
• Non-ferrous smelting and refining is being subsidized via tariffs on imports, especially in Asia
• copying traditional Japanese practices which contribute to excess capacity bias
• Emerging problem of deindustrialization starting to affect highly efficient, competitive downstream sectors in North America
• will be a problem in Europe in next 5-10 years
ResourceStrategies
Slide 28
Good news and bad news on cyclical Good news and bad news on cyclical management potentialmanagement potential
• Industry consolidation is producing stronger and more disciplined corporate entities
• Alcoa, Alcan, Rusal etc in aluminum
• Diversified companies like Rio Tinto, BHP-Billiton, Anglo American and Xstrata in other markets
• Governments have basically exited these sectors
• Potential loss of North American swing capacity reduces overall industry supply flexibility
• devastating experience of zinc (no US swing capacity) in the current cycle
• virtually no progress in Europe towards flexible production concepts
ResourceStrategies
Slide 29
New technologies potentially trigger New technologies potentially trigger structural shifts that disrupt marketsstructural shifts that disrupt markets
• Inert anode technology in aluminum• potential drop of 25% in real cost of producing
aluminum
• Leaching of primary copper sulphide deposits• fundamental reduction in costs, scale and entry
barriers
• Similar developments in other markets• Mt Isa’s zinc technology, APL in nickel etc
• New technologies for primary iron production• Rio’s Hismelt project and its rivals threaten integration
of iron and steelmaking
ResourceStrategies
Slide 30
The challenges have escalated at least as The challenges have escalated at least as fast as the lessons have been learned!fast as the lessons have been learned!
Global and national
economic risk
Technology change
Industry management issues and challenges
Political, social and
environmental constraints
The “Renaissance Man” challenge