Transcript Case Study: Quality Management, Document Management, and

VERBUND-Austrian Power Trading
Modelling Electricity Prices
Dipl.-Ing. Dr. Josef H. Bogensperger
Head of Risk Management
VERBUND – Austrian Power Trading AG
Welcome, may we introduce ourselves
VERBUND is ...
► ... the largest producer and distributor of electrical energy in Austria
► ... the operator of the super-regional high-voltage grid of Austria with
important connections to the neighbour countries in Central Europe
► ... one of the biggest Austrian listed companies
► ... the most eco-friendly electricity generator in the European Union
► ... one of the most modern electricity companies in Europe
► ... a successful player at the European electricity market
Dr. Josef Bogensperger
17. Juli 2015
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VERBUND Key Figures 2005: Numbers
►
►
►
►
Sales revenue
EBIT
Free Cash Flow
Moody´s Rating
2,51 bn €
526,5 mln €
597,3 mln €
A1
► Electricity sales
► Generation
►Hydro
►Thermal
57,282 GWh
29,011 GWh
24,788 GWh
4,223 GWh
► Employees
Share Chart
2,436
Shareholding Structure
51 %
22 %
27 %
Republic of
Austria
Free Float
Institutional
Investors
Dr. Josef Bogensperger
17. Juli 2015
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VERBUND Key Figures 2005: Volumes
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VERBUND-Austrian Power Trading AG


Energy Turnover: (APT trades in the name and on behalf of VERBUND)
2004: 86 TWh (69% international, 79% thereof in Germany)
Products:
APT & APT Subsidiaries
Physical Energy,
APT Target Markets
Energy Derivatives,
APT New Markets
Proofs of Origin,
Emission-Certificates

Target Groups:
Retail, Wholesale,
Big (Industrial) End users

Employees:
120

Owner:
100% Verbund
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VERBUND Organizational Chart
VERBUND HOLDING
VERBUNDAustrian Power
Grid AG
VERBUND Italia
Energia
POWEO
VERBUNDAustrian Hydro
Power AG
VERBUND-Austrian
Thermal Power
GmbH & Co. KG
VERBUNDAustrian Power
Trading AG
VERBUNDAustrian Power
Sales GmbH
APT SK
APT CZ
Energie Klagenfurt GmbH
APT Hungária
APT Energa Hellas
VERBUNDBeteiligungsgmbH
APT Slovenija
VERBUNDManagement
Service GmbH
Dr. Josef Bogensperger
APT Deutschland
17. Juli 2015
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Table of Contents

Price forward curve (PFC)

Hourly price forward curve (HPFC)

Simulation Results

Scenario Backtesting
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Specification of firm schedule
 Fixed schedule: The customer defines an hourly fixed schedule,
every deviation will be charged extra by actual prices
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Hourly curve needs a two component model
“Historical”
factors
Market
data
yearly,
quarterly
PFC
1st component
Dr. Josef Bogensperger
17. Juli 2015
Stochastic
spot prices
monthly
PFC
hourly
PFC
Pricing
2nd component
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Price forward curve (PFC)
price
month products
year products
quarter products
balance of month (BOM)
time
now
load data of structured products is hourly → we need hourly prices
Dr. Josef Bogensperger
17. Juli 2015
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Price forward curve (PFC)
 Prices for future delivery at various points in time
 Granularity of observable products reduces over time
 Reflects the actual market opinion
 Emerge from traded standard products
(month/quarter/year, base/peak)
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Price forward curve (PFC)
 We use all historical data from the European Energy
Exchange (EEX) as model input.
Assume the following price processes for historical data of future
products:
Year:............................ Yi (t), i {2002, , 2012}
Quarter in year (i):........ Qk,i (t), k {1, , 4}
Month in quarter (k):..... M j,k (t), j {1, ,3}
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1st component: receive monthly PFC
historical factors
 y,q 
1

 Qk,i  t  Yi  t 
q,m 
t
1

M t
t
j,k
Qk  t 
Yi  T y,q
quarterly PFC
Ql  T  q,m
monthly PFC
Yi  T 
Qk  T 
Ql  T 
M j (T)
actual market data
  0,...,T
Dr. Josef Bogensperger

17. Juli 2015
includes specific times of history
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Another method to receive quarterly PFC
 Assuming that the following correlation is high
 Q  t  Q k,i 1  t  
corr  k,i
,
 Y  t  Y  t  
i 1
 i

→ we can use actual quotes for the estimation of  y,q
Dr. Josef Bogensperger
17. Juli 2015
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Arbitrage free monthly forward curve (MPFC)
 Monthly prices have to be arbitrage free compared to quarterly and
yearly prices, therefore:
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yi Yi (t)   m j,i M j,i (t)
j1
i, j …year i, month j in year i
yi , m j,i …Number of hours
Yi (t), M j,i (t) …prices at t
 Settlement prices are arbitrage free, intraday prices in general not
→ be careful using actual quotes, get them first arbitrage free
Dr. Josef Bogensperger
17. Juli 2015
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2nd component: receive HPFC
 Spot price simulation: Sampling method
Cluster similar historical data: season, weekend, holidays,…
Random selection of a historic day of a corresponding class

→ we get a sample H1, j ,

, H n j , j of hourly prices for month j
Get hours arbitrage free: For example, shift all hourly prices till
nj
M jm j   Hk, j is fulfilled.
k 1
Dr. Josef Bogensperger
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2nd component: receive HPFC
Possible improvement
Modelling spot prices as stochastic process on a daily basis using
 Jump Diffusion or
 Regime Switching
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How to display results
short
long
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How to display results
Price distribution for
1000 possible scenarios
If quarters do not quote,
we look at the
summer/winter spread of
the scenarios
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Back testing models
 Back testing is the validation of the underlying simulation
 Regarding HPFC in APT back testing is solved using a database
 Historical and simulated price data are fed into a database
 Historical prices since the start up of the certain power exchange
 Simulation prices HPFC for 1000 scenarios
 Possibility of selection criteria on specific periods of time to find similarities
 Graphical query results indicate strengths and weaknesses of a model
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Back testing models
Comparison of historical and simulated prices for every Wednesday, 7-10pm
Probability
0,16
Simulation
0,14
History
0,12
0,1
0,08
0,06
0,04
0,02
5
4,
8
4,
6
4,
4
4,
2
4
3,
8
3,
6
3,
4
3,
2
3
2,
8
2,
6
2,
4
2,
2
2
1,
8
1,
6
1,
4
1,
2
1
0,
8
0,
6
0,
4
0,
2
0
0
Scaled prices based on monthly means
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Thank you
for your attention!
Dipl.-Ing. Dr. Josef H. Bogensperger
VERBUND-Austrian Power Trading AG
Tel.
Mob.
Fax.
email
Dr. Josef Bogensperger
17. Juli 2015
+43 (0) 50313-53020
+43 664 243 58 34
+43 (0) 50313-153020
[email protected]
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