Introduction to Applied Probability for Energy Risk Management

  • Nigel Da Costa Lewis
Part of the Finance and Capital Markets Series book series (FCMS)


There are many instances where those involved in energy products must make decisions under conditions of uncertainty. An oil producer must decide how much inventory to stock; a risk manger how much economic capital to set aside, and an electricity speculator when to buy or sell. In each of these cases the individuals make their decision on the basis of what they think is likely to occur; their decision is based on the probability that certain events will or will not happen. Most of us have some intuitive understanding of probability. Some people prefer to take the train to their place of work in the knowledge that a serious accident is less likely than if they drive. Others participate in high risk sports such as boxing or sailing, knowing that they are likely to face serious injury or death, but then again the likelihood of such extreme outcomes is actually quite small. Millions of individuals purchase lottery tickets even though the likelihood of wining a very large pay-out is extremely small. If we say that the probability of snow today is one-half, but tomorrow it is only one quarter, we know that snow is more likely today than tomorrow.


Probability Density Function Future Price Probability Mass Function Spot Price Discrete Random Variable 
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Further Reading

  1. Hines, W. W. and Montgomery D. C. (1980) Probability and Statistics in Engineering and Management Science. John Wiley and Sons, New York.Google Scholar
  2. Lewis, Nigel Da Costa (2003) Market Risk Modeling: Applied Statistical Methods for Practitioners. Risk Books, London.Google Scholar
  3. Lewis, Nigel Da Costa (2004) Operational Risk with Excel and VBA: Applied Statistical Methods for Risk Management. John Wiley & Sons, Inc., New York.Google Scholar

Copyright information

© Nigel Da Costa Lewis 2005

Authors and Affiliations

  • Nigel Da Costa Lewis

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