Pricing of electricity futures with modified Schwartz and ... · Pricing of electricity futures...

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Pricing of electricityfutures with modified

Schwartz and Smith two factormodel

Maria KholopovaUniversity of Twente

Plan of presentation• Motivation• Schwartz and Smith model for commodity

futures pricing and modifications of the modelfor electricity

• Calibration issues• Results• Further research• Questions and discussions

Future prices EEX

15,00

20,00

25,00

30,00

35,00

40,00

45,00

50,00

55,00

01.07.2002

01.08.2002

01.09.2002

01.10.2002

01.11.2002

01.12.2002

01.01.2003

01.02.2003

01.03.2003

01.04.2003

01.05.2003

01.06.2003

01.07.2003

01.08.2003

01.09.2003

01.10.2003

01.11.2003

01.12.2003

01.01.2004

01.02.2004

01.03.2004

01.04.2004

01.05.2004

01.06.2004

01.07.2004

01.08.2004

01.09.2004

01.10.2004

01.11.2004

01.12.2004

Jul-2002

Aug-2002

Sep-2002

Oct-2002

Nov-2002

Dec-2002

Jan-2003

Feb-2003

Mar-2003

Apr-2003

May-2003

Jun-2003

Jul-2003

Aug-2003

Sep-2003

Oct-2003

Nov-2003

Dec-2003

Jan-2004

Feb-2004

Mar-2004

Apr-2004

May-2004

Jun-2004

Jul-2004

Aug-2004

Sep-2004

Oct-2004

Nov-2004

Dec-2004

Jan-2005

Feb-2005

Mar-2005

Apr-2005

May-2005

Jun-2005

Possible approaches to futures modeling

• Derive future prices from the spot example: Schwartz and Smith two-factor model

• Model future dynamics directly example: Heath-Jarrow-Morton (HJM) approach

Electricity futures• Delivery over month/quarter and over a year• Overlapping delivery periods• Average spot price is used for reference

price of the future contract• Two possibilities

1. Model fixed-delivery futures F(t,T) and deriveelectricity futures F(t,T0,T)

2. Model directly electricity futures F(t,T0,T)

Schwartz and Smith model forcommodity futures

t T0 T

Calibration

• Simple estimation of the parameters leads tounrealistic sets of parameters which are alsodepended on starting values and boundaries forparameters estimation.

• Example:

0.670.020.010.290.08-0.563.99

! !" !" !" !" !µ !

August 2004 month forward

25

27

29

31

33

35

37

39

02/02/2

004

02/03/2

004

02/04/2

004

02/05/2

004

02/06/2

004

02/07/2

004

02/08/2

004

modelled

August

2004

data

August

2004

January 2005 month forward

25

27

29

31

33

35

37

01/07/2

002

01/08/2

002

01/09/2

002

01/10/2

002

01/11/2

002

01/12/2

002

modelled

January

2005

data

January

2005

October 2003 quarter forward

20

22

24

26

28

30

32

34

36

38

01/07/2

002

01/09/2

002

01/11/2

002

01/01/2

003

01/03/2

003

01/05/2

003

01/07/2

003

01/09/2

003

modelled

october

2003

data

october

2003

April 2004 quarter forward

20

21

22

23

24

25

26

27

28

29

30

01/07/2

002

01/09/2

002

01/11/2

002

01/01/2

003

01/03/2

003

01/05/2

003

01/07/2

003

01/09/2

003

modelled

April

2004

data April

2004

January 2005 year forward

20

21

22

23

24

25

26

27

28

29

30

01/07/2002

01/08/2002

01/09/2002

01/10/2002

01/11/2002

01/12/2002

01/01/2003

01/02/2003

modelled

January

2005

data

January

2005

January 2006 year forward

20

22

24

26

28

30

32

01/07/2002

01/08/2002

01/09/2002

01/10/2002

01/11/2002

01/12/2002

01/01/2003

01/02/2003

modelled

January

2006

data

January

2005

State variables and logarithm of spot price

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.50

1/0

7/2

00

2

01

/09

/20

02

01

/11

/20

02

01

/01

/20

03

01

/03

/20

03

01

/05

/20

03

01

/07

/20

03

01

/09

/20

03

01

/11

/20

03

01

/01

/20

04

01

/03

/20

04

01

/05

/20

04

01

/07

/20

04

01

/09

/20

04

01

/11

/20

04

short term deviations

equilibrium level

log S

Modelled spot

20

25

30

35

40

45

50

55

60

01/07/2002

01/09/2002

01/11/2002

01/01/2003

01/03/2003

01/05/2003

01/07/2003

01/09/2003

01/11/2003

01/01/2004

01/03/2004

01/05/2004

01/07/2004

01/09/2004

01/11/2004

modelled

spot

!"#$%&'()"*)

+,-,./

+,-,.

+,-,0/

+,-,0

+,-,1/

+,-,1

+,-,,/

,

1 0, .2 /3 44 25 11/ 1.6 1/. 140 121 01, 002 063 054 035 .,/ .06 .6. .50

'"#$

Calibration

• Now we first estimate from spot data(=0.427)

• Example:

0.700.060.040.340.580.600.43

! !" !" !" !" !µ !

!

January 2003 month forward

20

21

22

23

24

25

26

27

28

29

01/07/2002

01/08/2002

01/09/2002

01/10/2002

01/11/2002

01/12/2002

01/01/2003

modelled

January

2003

data

January

2003

January 2005 month forward

25

27

29

31

33

35

37

30/06/2004

30/07/2004

30/08/2004

30/09/2004

30/10/2004

30/11/2004

30/12/2004

modelled

January

2005

data

January

2005

October 2003 quarter forward

20

22

24

26

28

30

32

34

36

01/07/2

002

01/09/2

002

01/11/2

002

01/01/2

003

01/03/2

003

01/05/2

003

01/07/2

003

01/09/2

003

modelled

october

2003

data

october

2003

January 2006 quarter forward

30

31

32

33

34

35

36

31/03/2004

31/05/2004

31/07/2004

30/09/2004

30/11/2004

modelled

January

2006

data

January

2006

January 2005 year forward

20

22

24

26

28

30

32

34

36

38

01/07/2002

01/11/2002

01/03/2003

01/07/2003

01/11/2003

01/03/2004

01/07/2004

01/11/2004

modelled

January

2005

data

January

2005

January 2006 year forward

20

22

24

26

28

30

32

34

36

38

30/12/2002

30/03/2003

30/06/2003

30/09/2003

30/12/2003

30/03/2004

30/06/2004

30/09/2004

30/12/2004

modelled

January

2006

data

January

2005

State variables and logarithm of spot price

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.50

1/0

7/2

00

2

01

/09

/20

02

01

/11

/20

02

01

/01

/20

03

01

/03

/20

03

01

/05

/20

03

01

/07

/20

03

01

/09

/20

03

01

/11

/20

03

01

/01

/20

04

01

/03

/20

04

01

/05

/20

04

01

/07

/20

04

01

/09

/20

04

01

/11

/20

04

short term deviations

equilibrium level

log S

Modelled spot

20

25

30

35

40

45

50

55

6001/07/2002

01/09/2002

01/11/2002

01/01/2003

01/03/2003

01/05/2003

01/07/2003

01/09/2003

01/11/2003

01/01/2004

01/03/2004

01/05/2004

01/07/2004

01/09/2004

01/11/2004

modelled

spot

!"#$%&'()"*)

+

+,++-

+,++.

+,++/

+,++0

+,++1

+,++2

- .+ /3 14 55 32 --1 -/0 -1/ -5. -3- .-+ ..3 .04 .25 .42 /+1 /.0 /0/ /2.

'"#$

Forward curve 30.06.2004

25.0000

27.0000

29.0000

31.0000

33.0000

35.0000

37.0000

39.0000

41.0000

1 91 181 271 361 451 541 631 721 811 901 991 1081

model

curve

market

data

Further research• Optimize estimation of model parameters:

some parameters could be estimated a priory.• Estimation of model parameters using

different approach: for example simplecalibration with minimizing squared errors(fitting to monthly futures)

• Forecasting• Option pricing

Questions?

Suggestions?