This paper focuses on modelling environment changes in a way that allows to price weather derivatives in a flexible and efficient way. Applications and importance of climate and weather contracts extends beyond financial markets and hedging as they can be used as complementary tools for risk assessment. In addition, option-based approach toward resource management can offer very special insights on rareevents and allow to reuse derivative pricing methods to improve natural resources management. To demonstrate this general concept, we use Monte Carlo and stochastic modelling of temperatures to evaluate weather options. Research results are accompanied by R and Python code.
Management decisions are typically meant to be making a lasting impact, or at least bringing us one step closer to a long-term goal. Yet there are situations where it is hard to link decisions made and results achieved. The problem gets more complex when comparing different backgrounds, as management quality is often assessed either in specific organizational context (Ghoshal and Bartlett, 1994; Coggburn and Schneider, 2003) or in a finite number of case-studies. These methods have been successfully used for a long time in corporate environment (Gong et al., 2018) and for public sector decisions (Eller et al., 2018), but their application is not as easy when facing problems that are affected by multiple economy-wide factors, and/or by variables that are not directly observable. We study the long term impact on management decisions in environmental management by using market information on different instruments used to manage and control environmental pollution and risk. The core reason for choosing this approach is that market data is able to account for economic reasons and capture changes that go beyond the scope of an individual corporation or a public agency.
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