Weather Derivatives Research Articles

Weather rebate contracts for different risk attitudes of supply chain members

Firms that deal with weather-sensitive products are often exposed to weather risk. How a weather rebate contract can be implemented to improve the performance of a supplier-retailer supply chain is investigated. The supplier offers a weather rebate to the retailer to compensate for the loss of sales due to weather risk. Depending on certain weather conditions, the retailer receives the rebate if it orders beyond a predefined ordering quantity. Depending on its risk attitude, the supplier uses weather derivatives to minimize the downside risk. The performance of weather rebate contracts is analyzed for three cases: risk-neutral supplier and risk-averse retailer, risk-averse supplier and risk-neutral retailer, and risk-averse supplier and risk-averse retailer. Conditional Value at Risk (CVaR) is used as the risk measure. The supply chain coordination under weather risk is investigated, and the specific conditions of a weather rebate contract leading to a Pareto-improving solution for both parties are obtained. To the best of the authors’ knowledge, this is the first study that investigates the weather rebate contract incorporating the risk attitude of the firms using a cooling degree days (CDD)/heating degree days (HDD)-based rebate structure. A comparative analysis between the weather rebate and wholesale price contracts is carried out based on the actual temperature and demand data. The results show that the weather rebate contract outperforms the regular wholesale price contract in all three cases. The study also demonstrates how to use weather derivatives to improve the performance of a supply chain dealing with weather-sensitive products.

Potential use of weather derivatives in hedging aggregate viticulture yields: An analysis of the Niagara region of Canada

AbstractAlthough potentially useful for financially hedging systemic weather-related risks, weather contracts/derivatives (also referred to as parametric insurance) have not seen wide adoption in agriculture outside of applications in developing countries, frequently supported by governments and non-governmental organizations (NGOs). A significant impediment is the lack of financial firms willing to stand ready to sell weather derivatives to individual agricultural producers in the over-the-counter market who, due to the localized nature of weather, face idiosyncratic weather-related risks. In particular, the administrative and reinsurance costs of supplying relatively small contracts with specific terms to many different producers are often prohibitive. The current study considers the potential use of weather derivatives in hedging the aggregate yield/revenues of viticulture producers represented by an industry association located in the province of Ontario, Canada. We examine the sensitivity of aggregate industry yields to several relevant weather-related risks employing copula function analysis. We then consider the potential of a weather derivative in hedging the financial risk associated with cold winter temperatures, which pose the greatest risk to aggregate vinifera yields. The issue of attributing costs and payouts to individual association members remains unresolved, and several alternatives are suggested.

Risk Management Through Weather Derivatives in Agriculture Sector In Indian Context

Agriculture plays a vital role in the Indian economy, with a significant portion of the population relying on it for their livelihoods. However, the sector is highly vulnerable to weather-related risks, causing immense uncertainty and financial losses for farmers. This research article explores the potential of weather derivatives as a risk management tool for the agricultural sector in India. By analyzing the literature and drawing on various case studies, this article highlights the challenges and opportunities associated with the implementation of weather derivatives in the Indian context.

Dynamic Correlation between Weather Derivatives and Agricultural Commodity Derivatives: Evidence from the US

Dynamic Correlation between Weather Derivatives and Agricultural Commodity Derivatives: Evidence from the US

Using weather derivatives to hedge the volumetric risk of wheat crops. An experimental study to hedge temperature fluctuations using daily degree options.

لقد اصبح التغير المناخي واحد من اقوى الخطب والاحاديث في العالم فالارتفاع في درجات الحرارة والذي يعزى الى المستويات المتصاعدة من اوكسيدات الكربون كذلك تزايد التقلب في مستويات تساقط الامطار افضى وسيفضي الى توليفة متزايدة التنوع من التاثيرات السلبية مناخياً واقتصادياً واجتماعياً وبيولوجياً، وبذلك فان تأثير الطقس على الأنشطة التجارية يبدو هائلاً وخطيراً وهو يختلف باختلاف النشاط التجاري والموقع وحجم ومستوى التغير الحاصل في المتغيرات المناخية. في القطاع الزراعي(محل اهتمام هذه الدراسة) ، يمكن أن تحدث التقلب في درجات الحرارة على حجم السلع الاساسية المنتجة على مستوى البلد،ناهيك عن تأثيرها بالتبعية على نوعية وجودة هذه السلع وبالتالي اسعارها ليس فقط محلياً انما دولياً. هذه المخاطرة الحجمية اثقلت كاهل المتعرضين لها سواء اكانو افراداً ام مؤسسات ام دول واصبح لزاماً البحث عن اداة تساهم جزئياً او كلياً في معالجة هذه المشكلة فكانت مشتقات الطقس هي السبيل المقترح لذلك. تشمل المخاطر التي تغطيها مشتقات الطقس التأثير العكسي المحتمل للطقس على التكاليف والإيرادات والتدفقات النقدية المتوقعة.
 مشتقات الطقس ادوات مبتكرة حديثة غاية في الروعة لتسليع الجو ، اي لتحويل متغيرات الارصدة الجوية الى سلعة قابلة للتداول في الاسواق وبين المتعاملين بيعاًوشراء. وهي تشكل قمة الابداع في فكر الهندسة المالية المعاصر. لذا تحاول هذه الدراسة طرح واختيار انجح الاستراتيجيات التي من الممكن اعتمادها للتخلص او للتقليل من تأثير المخاطرة الحجمية للسلع الاساسية . فكرة هذا الاسلوب قائمة على فكرة تقليل مخاطر الطقس التي تؤدي الى نقص غلة المحصول وذلك من خلال اعداد هندسات مالية محتملة طبقاً لقواعد واجراءات علمية رياضية دقيقة، تستهدف بناء استراتيجيات تداول قائمة على خيارات مستقبليات الطقس غايتها الاساس هي تحويط المخاطرة الحجمية للسلع الاساسية المختارة(القمح ) المتولدة بسبب التقلبات في متغيرات الطقس المدروسة(درجات الحرارة) .
 ولغرض تحقيق غايات هذه الدراسة فقد تم جمع بيانات درجات الحرارة للدول المدروسة(العراق والولايات المتحدة) للمدة( 2006-2020). وباستعمال عدد من الاساليب المالية والرياضية والاحصائية وخلصت الدراسة للعديد من الاستنتاجات ولعل من اهمها ان بالامكان التخلص من الاثار المحتملة لتقلبات الطقس في حجم انتاج السلع الاساسية وذلك باستعمال خيارات مستقبليات الطقس وان التحوط عبر هذه الادوات هو افضل بكثير من عدم التحوط على الاطلاق . وتوصلت الدراسة لعدد من التوصيات من اهمها ضرورة اللجوء الى اسواق مشتقات الطقس الدولية،كخطوة اولئ، وذلك لتحويط القلب في احتياجات العراق من محصولي القمح والرز والناشئة من تقلبات الطقس في العراق وفي الدول المصدرة لتلك السلع وذلك عبر استراتيجيات التحوط المتقاطع واقامة سوق لمشتقات الطقس في العراق، كخطوة ثانية بعد استكمال جميع الاشتراطات الضرورية والكافية لاتمام ذلك لما لذلك من اهمية بالغة في تنفيذ استراتيجيات ادارة مخاطرة الطقس التي تواجهها مختلف القطاعات الاقتصادية بالبلد.

Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power

Since the future output of wind power generation is uncertain due to weather conditions, there is an increasing need to manage the risks associated with wind power businesses, which have been increasingly implemented in recent years. This study introduces multiple weather derivatives of wind speed and temperature and examines their effectiveness in reducing (hedging) the fluctuation risk of future cash flows attributed to wind power generation. Given the diversification of hedgers and hedging needs, we propose new standardized derivatives with higher-order monomial payoff functions, such as “wind speed cubic derivatives” and “wind speed and temperature cross-derivatives,” to minimize the cash flow variance and develop a market-trading scheme to practically use these derivatives in wind power businesses. In particular, while demonstrating the importance of standardizing weather derivatives regarding market liquidity and efficiency, we propose a strategy to narrow down the required number (or volume) of traded instruments and improve trading efficiency by utilizing the least absolute shrinkage and selection operator (LASSO) regression. Empirical analysis reveals that higher-order, multivariate standardized derivatives can not only enhance the out-of-sample hedge effect but also help reduce trading volume. The results suggest that diversification of hedging instruments increases transaction flexibility and helps wind power generators find more efficient portfolios, which can be generalized to risk management practices in other businesses.

A Stochastic Weather Model for Drought Derivatives in Arid Regions: A Case Study in Qatar

In this paper, we propose a stochastic weather model consisting of temperature, humidity, and precipitation, which is used to calculate a reconnaissance drought index (RDI) in Qatar. The temperature and humidity models include stochastic differential equations and utilize an adjusted Ornstein–Uhlenbeck (O–U) process. For the precipitation model, a first-order Markov chain is used to differentiate between wet and dry days and the precipitation amount on wet days is determined by a probability distribution. Five different probability distributions were statistically tested to obtain an appropriate precipitation amount. The evapotranspiration used in the RDI calculation incorporates crop coefficient values, depends on the growth stages of the crops, and provides a crop-specific and more realistic representation of the drought conditions. Five different evapotranspiration formulations were investigated in order to obtain the most accurate RDI values. The calculated RDI was used to assess the intensity of drought in Doha, Qatar, and could be used for the pricing of financial drought derivatives, a form of weather derivative. These derivatives could be used by agricultural producers to hedge against the economic effects of droughts.

A blockchain-based platform for trading weather derivatives

This study investigated the technical and economic viability of hedging electricity consumption using weather derivatives and smart contracts. For this purpose, we priced call options to hedge against excess of temperature for 5 Brazilian cities. We also developed a distributed autonomous application (DApp) using smart contracts, which allows individuals to negotiate these financial instruments. Our findings suggest that blockchain technology can be useful in providing a low-cost infrastructure to develop financial instruments to hedge weather-related losses. The cost of providing this platform has been estimated to be less than 300 USD. The price of options has been estimated under 50 USD. This is particularly useful for electricity consumers and small businesses in poor countries. In addition, this study provides a comprehensive guide for the development of financial solutions using smart contracts to mitigate climate change impacts.

Role of Financial Innovation in Achieving Economic Sustainability: A Review Study

Financial innovation accelerates the economic sustainability of firms by enhancing financial markets’ productivity, accelerating capital development, improving financial services, and creating more effective financial intermediation. This article, therefore, highlights the possible economic performance associated with applying different methods of financial innovation. Employing a desk study methodology, this paper discusses the effectiveness of financial innovation techniques in enhancing firms’ economic sustainability performance theoretically. In doing so, this review paper provides policymakers and practitioners with several insights into the efficiency of such strategies for businesses’ sustainable economic growth. Abstract: Economic Sustainability, Exchanged-traded funds, Financial innovation, Hedge funds, private equity, weather derivative.

Hedging Volumetric Risks of Solar Power Producers Using Weather Derivative Smart Contracts on a Blockchain Marketplace

The vulnerability of solar power producers to sunshine fluctuations exposes them to the volumetric risk that future electricity generation may deviate from predicted generation. Weather derivatives have recently emerged as a tool for hedging the volumetric risks of these power producers. However, the state-of-the-art instruments have several shortcomings, contributing to their limited application in the industry. Therefore, novel solar radiation-based weather derivative smart contract arrangements on a blockchain marketplace are proposed to address some of the main limitations of traditional instruments. In this regard, the cash flow of solar generators is modelled to assess the weather elements causing its stochasticity. Using this information, novel smart contract arrangements on a blockchain marketplace with solar radiation days as the underlying weather index are developed and analytically valued. Thereafter, a suite of novel smart contract autonomous mechanisms compelling contracting parties to behave rationally and maintain an enduring arrangement is presented. Finally, a trading strategy based on the developed smart contract arrangements is proposed to minimize the power producers’ volatility risk. Results emanating from notional simulations indicate that the proposed approach could be more suitable for hedging the volumetric risks of solar power producers than traditional instruments.

Analytical View of Pricing Weather and Freight Derivatives: 1950–2020

A weather derivative is financial instrument that companies or individuals use to hedge against the risk of weather-related losses. Freight derivatives value is derived from the future levels of freight rates, like a dry bulk-a category of cargo stowed in bulk, consisting of grain, cotton, coal, etc., carrying rates, and oil tanker rates. Numerous empirical studies exist on weather and freight derivatives and their pricing models such as Indifference Pricing Approach, Arbitrage Pricing Model, Financial Pricing model, Benchmark Pricing Approach, Fair Pricing Approach, Actuarial Pricing, Consumer Based Pricing Method, and Index Modeling. This paper aims to address issues relating to the functioning of weather and freight derivatives. This paper also focuses on the studies published on weather and freight derivatives’ pricing models during the last seven decades (i.e., 1950–2020). Objectives: (1) To understand the vital issues relating to models of weather and freight derivatives. (2) To compare pricing models of weather and freight derivatives during the last seven decades (i.e., 1950–2020).

A Study on Weather Risk Management Disclosure Practices in Power Generation and Transmission Companies in India

The goal of this study is to assess how well Indian power generation and transmission firms’ disclosure their exposure to weather risks in their annual reports. The analyses utilised the textual content analysis approach and hand-collected data from annual reports of firms. Ten power generating and transmission firms that are listed on the NSE are considered in the research. These firms' primary line of work is the production and distribution of electricity from various energy sources, including coal, biomass, wind, hydro, and biogas. For the study, the annual reports from 2010–11 to 2019–2020 were collected and analyzed. It is found that the majority of firms, including those that dealt with currencies, commodities, financial, and interest rates, reported using derivatives. No information is provided in the annual report about the management or reduction of weather-related risk, and no weather derivative methods or management techniques are employed. Keywords: Weather risk, disclosure, derivatives, power generation, hedge

Modeling and Designing of Rainfall Derivative Contract in India

There has been a prolonged discussion on the use of rainfall derivatives in the Indian conditions. The use of rainfall derivative instruments that could empower the ecosystem of trading and absorbing rainfall risk. The study adopted a unique approach of designing the rainfall indexation based on proposed metrics which is DRD/ERD index, this could be used as building blocks for designing rainfall derivatives similar to HDDs/CDDs underlying temperature derivatives. DRD/ERD values are computed for 36 meteorological subdivisions of India. The basic rainfall future contract structure is defined and analyse how it can reduce the rainfall risk. Like CAT bonds and weather derivatives, rainfall derivatives constitute potentially a distinct asset class and hence could be an added arsenal in the hands of investors for enriching their portfolios.

Hedging Wind Power Risk Exposure through Weather Derivatives

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.

ANN-Time Varying GARCH Model: Simulations and Application in Modelling Temperature for Weather Derivatives

ANN-Time Varying GARCH Model: Simulations and Application in Modelling Temperature for Weather Derivatives

Methods for risk premium: Application for agriculture companies in Czech Republic

In business valuation, alternative cost of equity plays an important role considering the risk related to investment. Even a slight change in cost of equity can significantly affect the resulting business value. However, in the Czech Republic, risk premium has not been adequately addressed in terms of methodology. The objective of the paper is to explore the application of selected methods in calculating risk premium, and to select or modify existing methodology for the calculation of risk premium used in agricultural companies. For the purposes of determining the alternative cost of equity, three methods are selected: build up model, CAPM, and Fama and French Three Factor model; internal data of a family farm XY are used. Beta coefficient is calculated on the basis of the input data, and the results of the individual methods are compared. Based on the data of companies operating in the Czech market, the performed analysis suggests that the Build Up model is suitable for expressing alternative cost of equity. The agriculture sector is very specific, as agricultural companies are the first to be affected by the climate change. A follow-up study could be focused on the analysis and prediction of the impacts of climate change, with possible emphasis on the importance of weather derivatives for agriculture companies.

Introduction to weather derivatives

AbstractThe weather is one of the factors that may have an impact on the countries' economies. There are two main hedging ways against unexpected weather conditions: weather derivatives and weather insurances. During the last two decades, companies started to use weather derivatives against weather issues, especially in the energy and agriculture sectors. Starting from weather derivatives' first launch, their transaction volumes at the exchange and over‐the‐counter markets have increased. In addition to the increasing dependency of the economies on the weather, providing the weather derivative contracts with a reasonable premium amount is another reason which helps to have this positive trend. Since weather derivatives have similar parameters and rules with classical financial derivatives, it is possible to use the same pricing approaches for financial and weather derivatives. Monte–Carlo simulation, based on random number generation, is one of the existing methods of pricing derivative contracts. A difference between simulated values and really occurred data is the base point of the expected payoff or price of the contract. The current article introduces weather derivatives and shows two different approaches to their pricing, where one of them requires deeper statistical analysis. Adding the statistical analysis into the consideration, defining the relation between each data value, helps to provide better estimation and less volatility. Having less volatility can provide more accurate estimations and reasonable prices that are affordable and desired by the companies.This article is categorized under: Energy Systems Economics > Economics and Policy Energy Systems Economics > Systems and Infrastructure

Weedy Finance: Weather Insurance and Parametric Life on Unstable Grounds

Based in the agrarian worlds of commercial sesame farming in northern Paraguay, where insurance companies are now selling weather derivatives to poor farmers, this article tracks financial practices that depend less on the healthy crops and more on the weeds that thrive among the profitable plants. Parametric insurance operates like a derivative and is triggered by certain weather conditions, which raises questions about the limits of survivability for human-crop relations. I sketch out a series of concerns about weeds as an entry point and helpful heuristic for multiple overlapping kinds of speculation in a multispecies, capitalist, and troubled landscape. By gridding the world to a limited set of expedient parameters, what generative social and human grounds do we lose in the process? A speculative anthropological imaginary might posit “weedy finance” as a critical standpoint and set of political claims for casting climate-based finance as one of the lively systems that can and should be intentionally and selectively weeded out.

A Stochastic Harmonic Oscillator Temperature Model for the Valuation of Weather Derivatives

Stochastic processes are employed in this paper to capture the evolution of daily mean temperatures, with the goal of pricing temperature-based weather options. A stochastic harmonic oscillator model is proposed for the temperature dynamics and results of numerical simulations and parameter estimation are presented. The temperature model is used to price a one-month call option and a sensitivity analysis is undertaken to examine how call option prices are affected when the model parameters are varied.

A methodology for temperature option pricing in the equatorial regions

Weather derivatives are financial instruments that can be used by organizations or individuals to hedge risks associated with adverse weather conditions. Weather conditions can directly decrease profits by affecting the volume of sales or costs. This paper develops a methodology for temperature option pricing in equatorial regions. In this approach, temperature is forecast by combining deterministic and stochastic models. We find that forecasting daily temperature with a model that combines a truncated third-order Fourier series with a mean reversion stochastic process proves the most accurate for pricing the options. The methodology is calibrated with data gathered in Bogotá, Colombia, using Monte Carlo simulations.