Electricity load pattern hedging with static forward strategies

Näsäkkälä, Erkka; Keppo, Jussi

doi:10.1108/03074350510769721

Cited by 23 publications

(28 citation statements)

References 31 publications

(30 reference statements)

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“…For the companies utilizing a method based on historic 15 The zero correlation between price and production volume is subject to some dispute. A negative correlation between volume and electricity prices prices lowers the incentives for hedging as this relationship acts as a natural hedge while the converse is true for a positive correlation (Näsäkkälä and Keppo, 2005). We find that both relationships are plausible.…”

Section: Risk Exposurementioning

confidence: 54%

Selective hedging in hydro-based electricity companies

2013

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We analyze risk management trends in electricity commodity markets using the production and transaction data and written hedging policies of 12 Norwegian hydropower companies. The scope of our analysis is the hedging of physical electricity production using the power derivatives available at NASDAQ OMX Commodities. In their hedging policy, these companies either use a Cashflow at Risk (C-FaR) approach or a hedge ratio approach, or follow no explicitly stated approach. We find that the derivative cashflows constitute substantial profits for these companies. Furthermore, hedging contributes to reducing the C-FaR for 10 of the companies. These findings are surprising considering that we expect hedging to yield zero expected profit and to smooth the earnings function. Overall, our findings reveal that a practice of incorporating market views in hedging decisions is widespread in the sample companies, as both sanctioned in their written hedging policy and as indicated by the substantial hedging profits.

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Section: Risk Exposurementioning

confidence: 54%

Selective hedging in hydro-based electricity companies

2013

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“…On the other hand, while it is relatively simple to hedge price risks for a specific quantity, such hedging, due to the lack of effective market instrument that would enable such hedging, becomes difficult when the demand quantity is uncertain, i.e., volumetric risk are involved. In this paper, the hedger's approach of dealing with quantity risk is to postpone the hedging time in order to get better quantity estimates (see [4]). …”

Section: Introductionmentioning

confidence: 99%

Static Hedging with Uncertain Quantity and Departure from the Cost-of-Carry Valuation

Liu

Wang

2006

Acta Mathematicae Applicatae Sinica, English Series

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In this paper, we are concerned with the optimal hedge ratio under quantity risk as well as discrepancies between the futures market price and its theoretical valuation according to the cost-of-carry model.Assuming a geometric Brownian motion for forecasting process, we model mispricing as a specific noise component in the dynamics of futures market prices, based on which the optimal hedging strategy is calculated.Finally, we illustrate optimal strategy and its properties by numerical examples.

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“…Less dynamic, but not quite static, is the two-stage stochastic programming approach, as explained in Conejo et al (2008). On the other hand, Näsäkkälä and Keppo (2005) use a static hedging strategy with forward contracts. This strategy is derived by minimizing the variance of the portfolio at the horizon, ie, it is assumed that the risk-adjusted expected value of the portfolio is maximized when the portfolio variance is minimized.…”

Section: Introductionmentioning

confidence: 99%