Estimating Commodity Term Structure Volatilities

Roncoroni, Andréa; Brik, Rachid Id; Cummins, Mark

doi:10.1002/9781119011590.ch12

Cited by 3 publications

(5 citation statements)

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“…These considerations, which represent an innovative aspect of our study, are only in relation to volumetric risk management (Roncoroni et al [9]), thus neglecting the market risk associated with electricity price volatility, allowing us to conclude that the hedging operation of our industrial portfolio provides substantial benefits in terms of the worst-case scenario, for which the application of weather derivatives certainly helps to dampen losses arising from unfavorable weather events.…”

Section: Discussionmentioning

confidence: 99%

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Hedging Wind Power Risk Exposure through Weather Derivatives

2022

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We introduce the industrial portfolio of a wind farm of a hypothetical company and its valuation consistent with the financial market. Next, we propose a static risk management policy originating from hedging against volumetric risk due to drops in wind intensity and we discuss the consequences. The hedging effectiveness firstly requires adequate modeling calibration and an extensive knowledge of these atypical financial (commodity) markets. In this hedging experiment, we find significant benefits for weather-sensitive companies, which can lead to new business opportunities. We provide a new financial econometrics approach to derive weather risk exposure in a typical wind farm. Our results show how accurate risk management can have a real benefit on corporate revenues. Specifically, we apply the spot market price simulation (SMaPS) model for the spot price of electricity. The parameters are calibrated using the prices of the French day-ahead market, and the historical series of the total hourly load is used as the final consumption. Next, we analyze wind speed and its relationship with electricity spot prices. As our main contribution, we demonstrate the effects of a hypothetical hedging strategy with collar options implemented against volumetric risk to satisfy demand at a specific time. Regarding the hedged portfolio, we observe that the “worst value” increases considerably while the earnings-at-risk (EaR) decreases. We consider only volumetric risk management, thus neglecting the market risk associated with electricity price volatility, allowing us to conclude that the hedging operation of our industrial portfolio provides substantial benefits in terms of the worst-case scenario.

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Section: Discussionmentioning

confidence: 99%

“…The multiple applications of weather derivatives have been extensively studied in the existing literature. Alexandridis and Zapranis [6], Burger et al [7], Jewson and Brix [8], and Roncoroni et al [9] present the general applications of weather derivatives along with a description of the main pricing techniques.…”

Section: Introductionmentioning

confidence: 99%

Hedging Wind Power Risk Exposure through Weather Derivatives

2022

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“…With this notation, we introduce the following hedging problem with respect to the daily revenue as min f Var Rm − f Ŝm , Pm , Ŵm s.t. f Ŝm , Pm , Ŵm = 0 (10) where f is a payoff function of the derivative contract and is optimized under the zero-mean condition. Based on a similar argument to that of solving (1), the optimization problem in (10) may be solved by constructing suitable regression equations.…”

Section: Daily Hedging Modelsmentioning

confidence: 99%

“…The first equation is a linear regression equation, whereas the second may be solved as a GAM to minimize the residual sum of squares with a penalty on smoothness. Then, we obtain linear hedging and spline hedging strategies to solve the optimal hedging problem for the daily setting defined in (10).…”

Section: Daily Hedging Modelsmentioning

confidence: 99%

“…In particular, weather derivatives are extremely useful for hedging energy market-related risks, and in recent years, there have been a large number of applications in both practical and research contexts [6]. Moreover, pricing methods and specific applications of weather derivatives are presented in several pieces of literature [7][8][9][10], where previous studies have been mainly related to weather derivatives on a single underlying index such as temperature [11][12][13][14][15][16], but also solar radiation/irradiation [17,18] and rainfall [19]. In the context of wind power businesses, the recent increase in hedging needs, coupled with the increased demand for wind power to achieve decarbonization goals, has led to recent studies on wind derivatives.…”

Section: Introductionmentioning

confidence: 99%

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Construction of Mixed Derivatives Strategy for Wind Power Producers

Yamada

Matsumoto

2023

Energies

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Due to the inherent uncertainty of wind conditions as well as the price unpredictability in the competitive electricity market, wind power producers are exposed to the risk of concurrent fluctuations in both price and volume. Therefore, it is imperative to develop strategies to effectively stabilize their revenues, or cash flows, when trading wind power output in the electricity market. In light of this context, we present a novel endeavor to construct multivariate derivatives for mitigating the risk of fluctuating cash flows that are associated with trading wind power generation in electricity markets. Our approach involves leveraging nonparametric techniques to identify optimal payoff structures or compute the positions of derivatives with fine granularity, utilizing multiple underlying indexes including spot electricity price, area-wide wind power production index, and local wind conditions. These derivatives, referred to as mixed derivatives, offer advantages in terms of hedge effectiveness and contracting efficiency. Notably, we develop a methodology to enhance the hedge effects by modeling multivariate functions of wind speed and wind direction, incorporating periodicity constraints on wind direction via tensor product spline functions. By conducting an empirical analysis using data from Japan, we elucidate the extent to which the hedge effectiveness is improved by constructing mixed derivatives from various perspectives. Furthermore, we compare the hedge performance between high-granular (hourly) and low-granular (daily) formulations, revealing the advantages of utilizing a high-granular hedging approach.

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Real Options in Energy: A Guided Analysis of the Operations Literature

Nadarajah

Secomandi

2021

SSRN Journal

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Estimating Commodity Term Structure Volatilities

Cited by 3 publications

References 5 publications

Hedging Wind Power Risk Exposure through Weather Derivatives

Hedging Wind Power Risk Exposure through Weather Derivatives

Construction of Mixed Derivatives Strategy for Wind Power Producers

Real Options in Energy: A Guided Analysis of the Operations Literature

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