Futures Market Efficiency in the EU ETS Dr Paul Twomey Centre for - - PowerPoint PPT Presentation

futures market efficiency in the eu ets
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Futures Market Efficiency in the EU ETS Dr Paul Twomey Centre for - - PowerPoint PPT Presentation

Futures Market Efficiency in the EU ETS Dr Paul Twomey Centre for Energy and Environmental Markets (CEEM), UNSW based on work by Oliver Sartor Centre for Energy and Environmental Markets (CEEM), UNSW Outline Motivation Carbon Futures


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Dr Paul Twomey Centre for Energy and Environmental Markets (CEEM), UNSW based on work by Oliver Sartor Centre for Energy and Environmental Markets (CEEM), UNSW

Futures Market Efficiency in the EU ETS

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The potential for sustainable energy futures

Outline

Motivation Carbon Futures Market Development Methodology Summary of Results Conclusions & Possible Future Improvements

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Why care about carbon futures market efficiency?

  • Futures prices used for:

– Cost effective risk sharing and transfer (hedging) – Informed investment decision making High carbon price risk in the EU ETS market may be a significant factor in delaying low carbon investments (Neuhoff, 2007).

  • Considerable evidence that the forecast error (MSE) of

futures prices are lower than alternative price predictors in commodity and other markets.

  • Relevance for when to auction or issue permits

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The potential for sustainable energy futures

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Market Development – Phase I 2005-2007

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EU ETS Price History (Phase 1)

5 10 15 20 25 30 35 2/11/2005 4/04/2005 5/20/2005 7/07/2005 8/23/2005 10/07/2005 11/23/2005 1/10/2006 2/24/2006 4/12/2006 5/30/2006 7/14/2006 8/30/2006 10/16/2006 11/30/2006 1/18/2007 3/06/2007 4/23/2007 6/07/2007 7/24/2007 9/07/2007 10/24/2007 12/10/2007

Time (2005 - 2007) Price (Euros)

ECX Dec-06 Futures ECX Dec-05 Futures ECX Dec-07 Futures ECX Dec-08 Futures Bluenext Spot Nord Pool Dec-08 CER

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Market Development - Phase II 2008

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The potential for sustainable energy futures

EU ETS Price History (Phase 2)

5 10 15 20 25 30 35 40 1 / 3 / 2 8 1 / 1 7 / 2 8 1 / 3 1 / 2 8 2 / 1 4 / 2 8 2 / 2 8 / 2 8 3 / 1 3 / 2 8 3 / 3 1 / 2 8 4 / 1 4 / 2 8 4 / 2 8 / 2 8 5 / 1 3 / 2 8 5 / 2 7 / 2 8 6 / 1 / 2 8 6 / 2 4 / 2 8 7 / 8 / 2 8 7 / 2 2 / 2 8 8 / 5 / 2 8 8 / 1 9 / 2 8 9 / 2 / 2 8 9 / 1 6 / 2 8

Time (1/3/ - 22/9/2008) P rice (E uros)

ECX Dec-08 Futures ECX Dec-09 Futures ECX Dec-10 Futures ECX Dec-11 Futures ECX Dec-12 Futures ECX Dec-13 Futures Bluenext Spot Nord Pool Dec-08 CER

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Market Development Phases I & II

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Market Development – Contract Volumes

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The potential for sustainable energy futures

Volumes per Contract Type per Year (Non-LEBA)

200000 400000 600000 800000 1000000 1200000 1400000 S p

  • t

d e c

  • 5

d e c

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  • 7

d e c

  • 8

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  • 1

1 d e c

  • 1

2 d e c

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3 S p

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C E R s C E R

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C E R

  • 9

C E R

  • 1

C E R

  • 1

1 C E R

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2 Permit Type/Maturity Kt CO2e 2008 2007 2006 2005

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Modelling Approach

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The potential for sustainable energy futures

Two approaches: – Test cost of carry model – Granger causality tests to see whether futures lead price discovery

  • Looks at just Phase II 2008 trading from March to September.

) )( ( , t T r t t T

e S F

− −

=

δ

{ } { }

* 1 1 1

Y ,

t t t t t n n

W Z Y ε

∧ + + +

⎡ ⎤ = + ⎢ ⎥ ⎣ ⎦

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There is convergence towards the Cost of Carry predictions

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The potential for sustainable energy futures

20 25 30 35 Price (Euros) 50 100 150 Trading Day Index 2008 Bluenext Spot ECX Dec2010 Nord Pool Dec2010 LEBA Dec2010 Cost of Carry Futures Price Prediction for Dec 2010

Cost of Carry Prediction vs Reality (Dec 2010 Futures)

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The Granger Causality Tests also mostly confirm that future prices lead spot prices

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The potential for sustainable energy futures

TABLE 13: TESTS FOR GRANGER CAUSALITY FROM EUA FUTURES TO SPOT PRICES REGRESSAND Log Spot Pricet REGRESSORS Log Dec-08 Futures 1.9000 0.0564 1.4100 0.1889 Log Dec-09 Futures 1.0300 0.4141 0.8800 0.5314 Log Dec-10 Futures 3.2700 0.0011 4.6000 0.0000 Log Dec-11 Futures 1.4800 0.1607 1.6900 0.0989 Log Dec-12 Futures 0.8200 0.5850 0.9400 0.4808 #Lags per Variable 8 8 Degrees of Freedom Parameters 8 8 Observations 846 355 FULL SAMPLE (N=846) PARTIAL SAMPLE (N=355) WALD STATISTIC P-VALUE WALD STATISTIC P-VALUE

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Conclusions & Possible Improvements

The cost of carry model has clearly begun to describe carbon futures prices in Phase 2.

– Contrasting with Milunovich & Joyeux (2006)’s findings on Phase 1 – Aiming to replicate analysis with OTC data for Phase I

Combined evidence supports the assertion that EU carbon futures markets are beginning to perform a price signalling function. Clear effect of short Phase length in the trading volume data (as noted by other authors, e.g. Buchner (2007), IEA (2007)) A longer time frame and more frequent data on energy prices would definitely improve the analysis.

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The potential for sustainable energy futures