Integrating Information, Misinformation and Desire: Improved Weather-Risk Management for the Energy Sector

2016 ◽  
pp. 289-296 ◽  
Author(s):  
Leonard A. Smith
Keyword(s):  
Risk Management ◽  
Energy Sector ◽  
Weather Risk ◽  
Weather Risk Management

scholarly journals Weather Risk Management in Energy Sector: The Polish Case

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 945
Author(s):  
Monika Wieczorek-Kosmala
Keyword(s):  
Risk Management ◽  
Energy Sector ◽  
Annual Reports ◽  
Research Approach ◽  
Weather Derivatives ◽  
Weather Risk ◽  
The Cost ◽  
Energy Companies ◽  
Weather Risk Management ◽  
The Impact

The energy sector is perceived as one of the most exposed sectors to the consequences of weather risk both directly (damages of its infrastructure) and indirectly (frictions to the energy supply–demand balance). The main aim of this paper is to provide an insight into the impact of weather risk on economic activity of companies operating in the energy sector in Poland. The empirical objective is to examine whether energy companies: (i) identify their relevant weather risk exposures; (ii) evaluate the impact of weather risk in the cost-revenues dimension; and (iii) implement weather risk management tools, in this case—weather derivatives. In a methodical context, this study relies on a unique research approach and derives from works that examine companies’ risk disclosures in annual reports, by applying textual content analysis. The results indicate that Polish energy companies recognize the impact of weather risk on their performance, also in the cost-revenues dimension. However, although the reported weather risk management methods were diversified, the examined companies did not use weather derivatives to hedge their weather risk exposures. In the overall dimension, the companies leading with the perception and management of weather risk were diversified regarding performance and market size.

THE WEATHER RISK MANAGEMENT INDUSTRY'S CLIMATE FORECAST AND DATA NEEDS

2002 ◽  
Vol 83 (8) ◽  
pp. 1193-1198 ◽  
Author(s):  
Richard J. Murnane ◽  
Michael Crowe ◽  
Allan Eustis ◽  
Susan Howard ◽  
Judy Koepsell ◽  
...  
Keyword(s):  
Risk Management ◽  
Climate Forecast ◽  
Weather Risk ◽  
Weather Risk Management

scholarly journals An Internet-Based Tool for Weather Risk Management

2008 ◽  
Vol 37 (1) ◽  
pp. 63-78 ◽  
Author(s):  
Calum G. Turvey ◽  
Michael Norton
Keyword(s):  
New York ◽  
Risk Management ◽  
Computer Program ◽  
Agricultural Production ◽  
Well Being ◽  
The United States ◽  
Web Based ◽  
Weather Risk ◽  
Weather Risk Management ◽  
Weather Insurance

This paper introduces a web-based computer program designed to evaluate weather risk management and weather insurance in the United States. The paper outlines the economics of weather risk in terms of agricultural production and household well-being; defines weather risk in terms of intensity, duration, and frequency; and illustrates the computer program use by comparing heat and precipitation risks at Ardmore, Oklahoma, and Ithaca, New York.

Weather Derivatives and Weather Risk Management

2005 ◽  
Vol 8 (1) ◽  
pp. 127-140 ◽  
Author(s):  
Patrick L. Brockett ◽  
Mulong Wang ◽  
Chuanhou Yang
Keyword(s):  
Risk Management ◽  
Weather Derivatives ◽  
Weather Risk ◽  
Weather Risk Management

A credibility-based yield forecasting model for crop reinsurance pricing and weather risk management

2019 ◽  
Vol 79 (1) ◽  
pp. 2-26 ◽  
Author(s):  
Wenjun Zhu ◽  
Lysa Porth ◽  
Ken Seng Tan
Keyword(s):  
Risk Management ◽  
Closed Form ◽  
Crop Yield ◽  
Forecasting Model ◽  
Content Type ◽  
Credibility Estimator ◽  
Weather Risk ◽  
Yield Forecasting ◽  
Crop Yield Forecasting ◽  
Weather Risk Management

Purpose The purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed form reinsurance pricing formulas. A yield restatement approach to account for changing crop mix through time is also demonstrated. Design/methodology/approach The new crop yield forecasting model is empirically analyzed based on detailed farm-level data from Manitoba, Canada, covering 216 crop varieties from 19,238 farms from 1996 to 2011. As well, corresponding weather data from 30 stations, including daily temperature and precipitation, are considered. Algorithms that combine screening regression, cross-validation and principal component analysis are evaluated for the purpose of achieving efficient dimension reduction and model selection. Findings The results show that the new yield forecasting model provides significant improvements over the classical regression model, both in terms of in-sample and out-of-sample forecasting abilities. Research limitations/implications The empirical analysis is limited to data from the province of Manitoba, Canada, and other regions may show different results. Practical implications This research is useful from a risk management perspective for insurers and reinsurers, and the framework may also be used to develop improved weather risk management strategies to help manage adverse weather events. Originality/value This is the first paper to integrate a credibility estimator for crop yield forecasting, and develop a closed form reinsurance pricing formula.

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