Copula-Based Hedge Ratios for Renewable Power Generation

Audun Nordtveit (), Kim T. Watle () and Stein-Erik Fleten
Additional contact information
Audun Nordtveit: Norwegian University of Science and Technology (NTNU)
Kim T. Watle: NTNU

Chapter Chapter 13 in Handbook of Risk Management in Energy Production and Trading, 2013, pp 313-351 from Springer

Abstract: Abstract The electricity price and production volume determine the revenue of a renewable electricity producer. Feed-in variations to power plants and high price volatility result in significant cash flow uncertainty. A copula-based Monte Carlo model is used to relate price and production volume and to find optimal hedge ratios through minimization of risk measures such as variance, hedge effectiveness, cash flow at risk, and conditional cash flow at risk. In our case study, all risk measures argue for an optimal hedge ratio between 35 and 60% of expected production. The highest risk reduction is achieved by the use of forward contracts with long time to maturity but at the expense of a low risk premium. Conversely, short-term futures and forwards only provide marginal risk reduction, but can yield attractive positive risk premiums. These findings underline the importance of distinguishing the use of derivative contracts for speculation and hedging purposes, through positions in short-term and long-term contracts, respectively.

Keywords: Cash Flow; Risk Measure; Risk Premium; Spot Price; Hedging Strategy (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4614-9035-7_13

Ordering information: This item can be ordered from
http://www.springer.com/9781461490357

DOI: 10.1007/978-1-4614-9035-7_13

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().