Introduction

3. Introduction 1. Introduction to Energy Trading Exchange and OTC trading Traded Contracts Settlement Fundamentals 2. Energy Contracts Time Series Specifics 3. Energy Trading: Financial and Risk Management ( ) Power Energy: Financial and Risk Management

4. Exchange and OTC Trading What does energy trading mean? Subject A is selling energy (the energy company – the producer or the trading company) + Subject B is buying energy (the energy user or the trading company) + they agree on the amount (MWh), price (EUR/MWh), delivery period, and delivery region = An energy trade (e.g. P PXE CZ BL M10-11) ( ) Introduction to Energy Trading

5. Traded Contracts ( ) Introduction to Energy Trading Traded contracts: Spot contracts day ahead: Traded today with the delivery on the following day (or the following few days when the trade takes place before a holiday o or weekend). Spot hours contracts: Traded during the current day, with delivery on the same day, even during the next hour. Futures/Forward contracts: Traded today with delivery during a specified period in the future. Options: The buyer of the option gains the right, but not the obligation, while the seller incurs the corresponding obligation to fulfill the transaction.

6. Exchange and OTC Trading Trading via exchange: Standardized contracts: Futures(standardized forward), Options, Options on futures etc. Obligation to deposit margin and settle everyday mark-to-market P/L which bears the cost of funding. Almost no counterparty/credit risk as the central counterparty/clearing house acts as the settlement guarantor. The number of power exchanges increased dramatically during the last decade ( ) Introduction to Energy Trading

7. Exchange and OTC Trading ( ) Introduction to Energy Trading

8. Exchange and OTC Trading OTC trading: Contracts are not necessarily standardized (forwards, options etc. There is no obligation to deposit a margin and settle everyday mark-to-market P/L. Counterparty risk exists in the case of OTC trading. An OTC trade can be direct between two counterparties, or via broker (Wallich Energy etc.). ( ) Introduction to Energy Trading

9. Traded Contracts – On PXE ( ) Introduction to Energy Trading

10. Settlement ( ) Introduction to Energy Trading The settlement can be: Physical: delivery of energy, payment of agreed amount Financial: payment of the difference between agreed variables The settlement of a futures contract is more complicated: * Source: Botterud, A., Bhattacharyya, A., Illic, M. (2002).: Futures and Spot Prices - An Analysis of the Scandinavian Electricity Market. 34th North American Power Symposium, 2002.

11. Fundamentals ( ) Introduction to Energy Trading

12. Fundamentals ( ) Introduction to Energy Trading * Source: www.ceps.cz

13. Fundamentals ( ) Introduction to Energy Trading * Source: www.eru.cz

14. Fundamentals ( ) Introduction to Energy Trading * Source: www.pxe.cz

15. Introduction 1. Introduction to Energy Trading 2. Energy Contracts Time Series Specifics 3. Energy Trading: Financial and Risk Management ( ) Energy Trading: Financial and Risk Management

16. Power Contracts Time Series Specifics Electricity is not an effectively storable asset. This fact has a strong influence on the time series characteristic of spot and term power contracts: Spot contracts: Power time series are more volatile than common financial time series Extreme jumps are very common (jump diffusion) Price tends to revert to the fundamental equilibrium level (mean reverting) Time series are usually seasonal Return distribution does not have the characteristics of normal distribution Forward/Futures contracts Limited storability and therefore, limited or no usage of thecost-of-carry model Low liquidity and specific liquidity characteristics – liquidity increase with decreasing time to contract maturity/delivery period. And many other specifics! ( ) Introduction to Energy Trading

17. Power Contracts Time Series Specifics ( ) Introduction to Energy Trading * Source: www.eex.com

18. Power Contracts Time Series Specifics High volatility and jumps Electricity spot day-ahead time series are very volatile with extreme jumps. Reason for this include non-storability, unexpected outages and effect of renewable sources. These facts have to be taken into consideration when we try to use stochastic model in risk management etc. The so-called Jump Diffusion Mean Reverting Model is very common: Where µ substitutes , dq represents the Poissono process where dq = 1 with the probabilityλand dq = 0 with the probability 1-λ. ( ) Introduction to Energy Trading

19. Power Contracts Time Series Specifics Cost of carry model Example: Imagine, that you know, that you will need a fuel delivery on 31.12.2011. Your supplier offers you a price for that delivery of 2 EUR per liter. Would you accept the offer? What would you consider? The spot price for the delivery tomorrow is 1,5 EUR. What else do you need to know? ( ) Introduction to Energy Trading

20. Power Contracts Time Series Specifics Example of the relationship between spot and forward contract of storable assets: ( ) Introduction to Energy Trading * Source: Reuters

21. Power Contracts Time Series Specifics Example of the relationship between spot and forward contract of non-storable asset - electricity: ( ) Introduction to Energy Trading * Source: Reuters

22. ( ) Stochastické modely v energetice Power Contracts Time Series Specifics Valuation of storable commodities forward contracts Cost of carry model Where c represents costs of the commodity carry, T is the time of forward contract maturity (delivery start), St is the spot contract price and Ft,T is the forward / futures contract price, which is traded today with maturity/delivery starting at time T. Valuation of nonstorable commodities forward contracts Equilibrium pricing Actual Price of the forward contract at time t for delivery period starting at time T(Ft,T) is given by the expected spot price of the electricity for the period T (E(ST)) and its risk premium (πt,T). Valuation of forward/futures contracts

23. Introduction 1. Introduction to Energy Trading 2. Energy Trading Specifics 3. Energy Trading: Financial and Risk Management ( ) Power Trading: Financial and Risk Management

24. Financial and Risk management Characteristic features of the issues related to energy trading and connected with financial and risk management reveal plenty of questions which have to be solved by: energy companies’ management consultants academics etc. The following slides present some examples of such issues. ( ) Introduction to Energy Trading

25. Financial and Risk management Storability and supply + transmission management Electricity cannot be economically stored. However, the load (demand for power) cannot be predicted with 100 % certainty. A generator can not be turned off or turned on in a second. Furthermore, we have to calculate with the start up and shut down costs. How we should manage the supply? How we should manage the transmission and the balance in the transmission system? The market with so-called purchased services exists. ( ) Introduction to Energy Trading

26. Financial and Risk management Storability and term contracts valuation As it was presented above, there is no clear connectionbetween the electricity spot price and the forward price. The cost of carry model cannot be applied, as the storability of electricity is not very common. The question of term contracts valuation arises: What should the real value of the forward/futures contracts be? Is equilibrium pricing the best model to explain the value of forward/futures contracts? ( ) Introduction to Energy Trading

27. Financial and Risk management Forecasting – different deterministic factors than those, known from finance The analysis of fundamental factors which determine the value of shares, bonds, FX rates, interest rates, etc. have been the center of attention for the last several decades. However, power is traded and the fundamental factors of its value have to be examined as well. Forecasting of load (demand) value and its determinants is still a very important issue. Should we use Standard and well known tools such regression and correlation analysis etc? Such tools, as fuzzy logic, neural networks or other? ( ) Introduction to Energy Trading

28. Financial and Risk management Costs allocation The energy for final customers is usually bought from the electricity wholesale market. Some portion could be bought as a base load month contract and some as a day-ahead spot contract. Costs should be somehow reallocated between the final customers. The problem is that customers can turn on or turn off an electric device at any time and it is hard to identify who consumed electricity bought at a lower or higher price. This is an interesting management and risk management issue. ( ) Introduction to Energy Trading

29. Financial and Risk management Risk management issues Electricity time series characteristics, and trading business itself, reveal several risk management issues which have to be solved within each company: Calculation of Value at Risk figures (model development and calibration) Monitoring of risk management exposures (sensitivity analysis, stress testing, position limits monitoring etc.). Counterparty/credit risk management, modeling of the future potential exposure etc. ( ) Introduction to Energy Trading

30. Financial and Risk management Long term investments The investment into an energy generator device is usually very long term. However future electricity prices are very uncertain, and might change dramatically. In the long term period, the political changes might be very influential and unpredictable. These facts open issues of particular parameters forecasting project financing business model set up ( ) Introduction to Power Trading

31. Financial and Risk management Transmission Electricity is usually produced in a few large generators and has to be transfered to final consumers through a transmission system. How effective can the transmission be; how significant are the losses? Imagine a European integrated electricity market; is that possible? What is market coupling? ( ) Introduction to Energy Trading

32. Financial and Risk management Thanks for your attention ( ) Introduction to Energy Trading

33. References ARLT, J., M., ARLTOVÁ, M.: Ekonomické časové řady. Grada Publishing, Praha, 2007. BARAN, J.: Analýza a porovnání různých modelů pro Value at Risk na nelineárním portfoliu. Katedra pravděpodobnosti a matematické statistiky, 2009. CARTEA, A., MARCELO, G.F.: Pricing in Elektricity Markets: a mean reverting jump diffusion model with seasonality. University of London, 2005 CULOT, M., GOFFIN, V., LAWFORD,S. a kol: An Affine Jump Diffusion Model for Electricity. Electrabel SA, 2006. CRAINE, R., LOCHSTOER L., SYRTVEIT, K.: Estimation of a Stochastic-Volatility Jump-Diffusion Model. University of California at Berkley, 2000. ČULÍK, M., VALECKÝ, J.: Non-linear Modelling of Electricity Price: Self Exciting Threshold Auto-Regressive Approach. Mezinárodní konference Finanční řízení podniků a finančních institucí, Ostrava, 2009. DIXIT, A.K., PINDYCK R.S.: Investment Under Uncertainty, Princeton University Press, Princeton, NJ, 1994 EMBRECHTS, P., MCNEAIL, A., STRAUMANN, D.: Correlation: Pitfalls and Alternatives. ETH Zentrum, Zurich, 1999. GARCIA FRANCO, J.C.: Maximum likelihood estimation of mean reverting process. HORNÍK, T., DRAHOVZAL, O.: Nová rizika v energetice – velkoobchodní trh s elektřinou. Ekonomika a Management, Praha, 2008. ( ) Introduction to Energy Trading

34. References LYZANETS, N., SENCHYNA, M.: Comparing different Value-at-Risk models for hedge funds. University of Lausanne, 2005. LYZANETS, N., SENCHYNA, M.: Comparing different Value-at-Risk models for hedge funds. University of Lausanne, 2005. MEYER-BRANDIS, T.,TANKOV, P.: Multi-factor jump-diffusion models of elektricity prices. Europlace Institute of Finance, 2006. PAPEŽ, M.: Verifikace VaR modelu – back testing PAPEŽ, M.: Stochastické modelování úrokových sazeb RUEDIGER, K., SCHINDLMAYR G., REIK, H. B.: A Two-Factor Model for the Electricity Forward Market. Universtat Karlsruhe, Karlsruhe, 2005 ECC margining. Leipzig: ECC, AG, 2010. Trading Rules. Praha: Power Exchange Central Europe, a.s., 2010 www.pxe.cz http://en.wikipedia.org/wiki/Credit_score http://en.wikipedia.org/wiki/Credit_rating ( ) Introduction to Energy Trading