2dstresstesting · 2016-07-22 · transifon+(2d+stress+test)+ bettervaluation# beerpricingofetrisks...
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2D STRESS TESTING OPTIONS AND CHALLENGES FOR SCENARIO DEVELOPMENT
2°C
OBJECTIVES
PRIMARY USERS & USE CASE
2D ALIGNMENT Misalignment of real assets with climate goals
2D STRESS TEST Resilience of porColios and financial insFtuFons to accelerated Energy TransiFon (2D stress test)
BETTER VALUATION BeMer pricing of ET risks
(assuming baseline scenario)
CLIMATE POLICY MAKERS Monitoring progress on Paris agreement
PRUDENTIAL AUTHORITIES AnFcipaFng the impact on climate acFon on financial stability
LONG TERM INVESTORS Improving long-‐term returns
1
2
3
STEP 1: TESTING REAL ASSETS ALIGNMENT
Background with wind farms and power plants
SEI METRICS PROJECT
TESTING 2D ALIGNMENT OF REAL ASSETS
Energy technology roadmap IEA 2DS
COMPARING THE ROADMAP WITH REAL ASSETS
2D porColio check Energy-‐related CO2
COMPARING ROADMAPS WITH REAL ASSETS
The por4olio exposure in 2015
6°C
2°C
4°C
COMPARING ROADMAPS WITH REAL ASSETS
Trajectory of the por4olio 2015-‐2020
6°C
2°C
4°C
COMPARING ROADMAPS WITH REAL ASSETS
2°C PATHWAY 2020
6°C
2°C
4°C
TESTING 2D ALIGNMENT FOR REAL ASSETS
CHANGES IN CAPACITY (MW)
0
1
2
3
4
5
6
7
8
9
10
2015 2020 2025
Actual plans
2°C target
0
1
2
3
4
5
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8
9
10
2015 2020 2025
Actual plans
2°C target
COAL POWER RENEWABLE POWER
Gap: 2.1 MW
Gap: 2.7 MW
EMISSIONS BEYOND BUDGET
(Kt of CO2e next 5 years)
Gap: 35.2 kt CO2
Gap: 52.2 kt CO2
INVESTMENT vs. NEEDS
($M next 5 years)
Gap: $4.1 M
Gap: $10.5 M
REVENUE GAP
($M next 5 years)
Gap: $3.3 M
Gap: $2.2 M
LINKING REAL ASSETS TO FINANCIAL PORTFOLIOS
EQUITY PORFOLIO
OWNERS
LISTED PARENT COMPANIES
STOCK TICKERS
DATA ON PHYSICAL ASSETS
FUNDS COMPARISION
-‐80%
-‐60%
-‐40%
-‐20%
0%
20%
40%
60%
80%
TOWARDS 5°C
BELOW 2°C
RENEWABLE POWER
2°C ALIGNED
PORTFOLIO ALIGNMENT ANALYSIS
5°C
2°C
SHORTCOMINGS OF 2D SCENARIOS & DATA
SHORT-‐TERM HORIZON 5-‐7 year limit on the investment outlook
0%
20%
40%
60%
80%
100%
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 % of total plann
ed add
i[on
s in
databa
se over the
next 1
0 years
Coal Gas Hydro Nuclear Renewables
LACK OF SHORT-‐TERM AMBITION IEA 2D scenarios based by design on current plans… IEA 2DS = only 50% chance to reach 2°C
-‐
50
100
150
2016 2018 2020 2022 2024
Rene
wab
le add
i[on
s (GW)
IEA 2DS
U[li[es actual plans
INDUSTRY COVERAGE • Power, Energy, Transport, Materials covered • Gap for real estate, highways, agriculture… ….
STEP 2: STRESS TESTING FINANCIAL ASSETS
Background with stock market curve and Wall street skyline
ET RISK PROJECT
TRANSLATING 2D ROADMAPS INTO FINANCIAL PARAMETERS
MORE
LESS
OUTCOMES IN THE 2D ROADMAP RESULTS FROM THE 2D STRESS TEST
IMPACT ON CASH FLOWS
PARAMETERS OF A 2D STRESS SCENARIO
TAX ON FUELS
FUEL EFFICIENCY STANDARD
NEGOTIATED AGREEMENT ON FLEET EFFICIENCY
TAX ON VEHICLES
CONGESTION CHARGES
TRANSLATING 2D ROADMAPS INTO FINANCIAL PARAMETERS
What does it look like? Example of the 2D stress test scenario under development in ET Risk project => building blocks of a scenario
Output Technology
Modal shin
-‐ Changes in consumpFon paMerns (Total volume of cars reduces)
-‐ Total volume product sold
Technology shin -‐ Shin from coal to renewable power -‐ Shin from ICE engines to EVs
-‐ Change in market share of product
Non-‐convenGonal (Company specific)
Legal
LiFgaFon due to poor reporFng of risks of climate change of the company
-‐ LiFgaFon against energy and fossil fuel companies by shareholders for failing to report risks of climate change
-‐ €/case
LiFgaFon due to damage to the environment
-‐ LiFgaFon against individual companies by groups or individuals for negaFve impacts of climate change
-‐ €
ReputaFon
Improved/destroyed reputaFon of companies and investor funds
-‐ ReputaFon loss due to investments in companies causing environmental damage
-‐ € lost in revenue
Market Market signals
Commodity prices excluding taxes and subsidies
-‐ Coal, oil, gas and electricity prices
-‐ €/BOE -‐ €/kWh
Technology costs -‐ Costs of incremental innovaFons (E.g. solar PV)
-‐ Costs of disrupFve innovaFons (E.g. BaMeries, CCS)
-‐ €/unit
Level 1 Category of risk factor
Level 2 Category of risk factor
Risk factor Examples Metric
Policy
Gov. Fiscal measures
Carbon price -‐ Carbon tax -‐ Cap-‐and-‐trade
-‐ €/ton CO
Technology taxes -‐ Import duFes on green/brown technologies -‐ Fuel or resource tax
-‐ €/item
Subsidies/rebates -‐ Tax rebate -‐ Feed in tariff
-‐ €/volume of good
Regulatory instruments
Technology supply regulaFon -‐ Renewable porColio standard (RPS) -‐ Best Available Technology mandate
Technology mandate
Technology pricing regulaFon -‐ Technology price floor -‐ Technology price ceiling
-‐ € min or max of specific products
Technology/emissions standard -‐ Power plant emissions standard -‐ Vehicle emissions standard
-‐ tCO2/t product -‐ gCO2/km
Energy efficiency standard -‐ Energy efficiency standard on producFon plants
-‐ kWh/t product
Output
Policy
Market
'Non-‐convenFonal'
Other macro trends
• ProducFon volumes • Fuel / technology volumes
• Regulatory costs • Regulatory constraints
• Commodity prices / costs • Technology costs
• Legal costs • ReputaFonal costs
• GDP / inflaFon • Other disrupFve shocks
KEY CHALLENGES OF SCENARIO DEVELOPMENT
ARBITRARY CHOICES Burden sharing, winning techs, level of…
LINKING TO OTHER MACRO TRENDS DisrupFve impact of AI, assumpFon on macro-‐economic trends
LIKELIHOOD Combining ambiFon (2D) and credibility
STEP 3: ADOPTION BY FINANCIAL ANALYSTS
Background with trading floor
TRAGEDY OF THE HORIZON
CHALLENGE#1: RISK CONCENTRATE ON LONG TERM
16
Electric U[li[es NPV (cash flow by period)
Natural coal capacity re[rements (by age)
IEA 450 Scenario re[rements
2015-‐2020 2020-‐2025 2025-‐2030 2030-‐2035 2035-‐2040 Post 2040
ReGrement gap
Analysis gap Equity research analyst
Real economy Gme horizon
Analysts horizon
CHALLENGE#1: RISK CONCENTRATE ON LONG TERM
17
0%
5%
10%
15%
20%
25%
30%
35%
1 2 3 4 5 6 7 8 9 10 11
Percen
tage of R
espo
nses
Consumer Discre[onary Consumer Staples Energy
Health Care Industrials Informa[on Technology
Materials Telecommunica[on Services U[li[es
Bloomberg issues a survey to equity research analysts on earnings es8mates. The responses listed in their database tail off a=er 5 years of forecasts, with 74% of analyst responses coming in the first three years and 94% coming in the first 5 years.
CHALLENGE#1: POTENTIAL TECHNICAL RESPONSES
Example: Kepler-‐Cheuvreux… Example: CO-‐Firm, Barclays
Cement companies in Germany
Example: Academic literature
CHALLENGE#2: LACK OF DEMAND FOR LONG TERM ANALYSIS
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0
50
100
150
200
250
300
10,0
5,0
3,3
2,5
2,0
1,7
1,4
1,3
1,1
1,0
0,9
0,8
0,8
0,7
0,7
0,6
0,6
0,6
0,5
0,5
Num
ber o
f Fun
ds
Poriolio Turnover Period ( Years)
Poriolio Turnover of Long-‐Only Mutual Fund Managers (Source: 2dii and Mercer, Forthcoming)
Turnover AUM % of Total
Average
Poriolio turnover of long-‐only mutual fund managers (Source: 2dii, Mercer & The Genera[on Founda[on, Forthcoming)
100% annual p
orColio
turnover implies a
Fme
horizon of 1 ye
ar.
NYSE Average Holding Period for stocks, 1940-‐2005 (Source: Haldane, 2010)
CHALLENGE#2: POTENTIAL RESPONSES
VOLUNTARY • Group of long-‐term investors ready to pay for long-‐term risk analysis • Public sector RfP for long-‐term risk analysis (Germany)
MANDATORY • Mandatory climate risk disclosure for financial insFtuFons (France -‐ Investors) • Stress tests by prudenFal authoriFes (France – Banks)
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