This study analyzes rainfall weather index insurance used for forage crops, in the Province of Ontario, Canada. The first objective of the study was to examine factors affecting the willingness of farmers to pay for forage rainfall index insurance, and a survey was undertaken. Some factors found to influence farmers' willingness to pay were knowledge and attitude regarding insurance, their risk profile, and socio-economic factors. A second objective of the study was to examine basis risk reduction approaches. Basis risk is the difference between the actual loss on a farm and the index measured loss payments that are determined by weather station data. The focus was to capture changing yield and weather relationships over crop growth stages. Using farm level forage yield and daily weather station data from Ontario, a multi-trigger index was designed using weighted crop cycle optimization, and results show that basis risk was substantially reduced. / May 2016

Weather index insurance has become a popular subject in agricultural risk management. Under these policies farmers receive payments if they experience adverse weather for their crops. Spatial basis risk is the risk that weather observed at stations does not correspond to the weather experienced by the farmer. The objective of this research is to determine to what extent spatial basis risk can be impacted by the interpolation technique used to estimate weather conditions. Using forage crops from Ontario, Canada, as an example, a temperature based insurance index is developed. Seven different interpolation methods are used to estimate indemnities for forage producers. Results show that the number of weather stations in the interpolation area has a larger impact on spatial basis risk than the choice of interpolation technique. For insurers wishing to implement this type of insurance, more focus should be placed on increasing the number of available weather stations. / October 2016

Student Number : 8804388Y - MSc Dissertation - School of Computational and Applied Mathematics - Faculty of Science / This dissertation considers the pricing and hedging of contingent claims in a general semimartingale market. Initially the focus is on a complete market, where it is possible to price uniquely and hedge perfectly. In this context the two fundamental theorems of asset pricing are explored. The market is then extended to incorporate risk that cannot be hedged fully, thereby making it incomplete. Using quadratic cost criteria, optimal hedging approaches are investigated, leading to the derivations of the minimal martingale measure and the variance-optimal martingale measure. These quadratic approaches are then applied to the problem of minimizing the basis risk that arises when an option on a non-traded asset is hedged with a correlated asset. Closed-form solutions based on the Black-Scholes equation are derived and numerical results are compared with those resulting from a utility maximization approach, with encouraging results.

Life re-insurers are exposed to mortality catastrophe risk. Mortality CAT bonds are a tool that can mitigate this risk. However, a key disadvantage of this tool is the existence of population basis risk, which occurs whenever there are differences between reference and insured populations. In this thesis, we propose a method to measure population basis risk of mortality CAT bonds. We consider a fictitious mortality CAT bond based on the mortality rates of two regional populations. We first obtain mortality change indexes by calibrating the MBMM model on these two regional populations. Then we use copula-based semi-parametric models to simulate the serial dependence and interdependence structure simultaneously between two regional mortality change indexes. Finally, we analyze the hedge effectiveness of the bond, from which we are able to quantify the population basis risk. We find that population basis risk decreases under certain circumstances.

Kentucky plays a vital role in the beef supply chain. The cow/calf producers,back-grounding operations, and order buying industry are important parts of Kentucky'sagricultural economy. Basis risk is an issue that affects these groups in a negative way. Agood estimate of the expected basis must be available to make hedging efficient.Simulations were performed on Kentucky price data to determine the effectiveness ofshort hedging for Kentucky producers. A model was also used to describe some of thefactors that determine basis levels. The research revealed that it is difficult to predictbasis within an acceptable range to make short hedging with futures efficient. Eventhough short hedging reduced variability in net price, it was difficult to lock in a profit.Various options and spread strategies were presented as alternative hedging tools thatwould protect cattle producers from unexpected price declines.

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This dissertation provides a comprehensive and practical analysis of basis risk in the U.S. variable annuity market and examines effective fund mapping strategies to mitigate the level of basis risk while controlling for the associated transaction costs. Variable annuities are personal savings and investment products with long-term guarantees that expose life insurers to extensive financial risks. Liabilities associated with VA guarantees are the largest liability component faced by U.S. life insurers and have raised concerns to VA providers and regulators. And the hedging performance of these guarantee liabilities is impeded by the existence of basis risk. I look into 1,892 registered VA-underlying mutual funds and two VA separate accounts to estimate the basis risk faced by U.S. VA providers at the individual fund level and the separate account level. To evaluate the degree to which basis risk can be mitigated, I consider various proxy instrument sets and assess different variable selection models. The LASSO regression is shown to be most effective at identifying the most suitable (combination of) mapping instruments that minimize basis risk, compared to other test-based and screening-based models. I supplement it with the Sure Independence Screening (SIS) procedure to further limit the number of instruments requested in the hedging strategies, and modify it by introducing the diff LASSO regression to restrict the changes in instrument allocations across rebalancing periods and, therefore, control for transaction costs. I show that VA providers can reduce their exposure to basis risk by applying data analytic techniques in their mapping process, by hedging with ETFs instead of futures contracts, and through diversification at the separate account level. Combining the traditional fund mapping method with the machine learning algorithm, the proposed portfolio mapping strategy is efficient at reducing basis risk in VA separate accounts while controlling for the tractability and transaction costs of the mapping and hedging procedure, and is practical to incorporate newly-developed VA funds, as well as the varying compositions of separate accounts. Overall, this study presents that U.S. VA providers have the ability to mitigate basis risk to a greater extent than the limited literature on this topic has suggested. / Business Administration/Risk Management and Insurance

Agriculture is one of the most weather sensitive sectors. The thesis aims to assess the efficiency of agricultural weather derivatives to reduce revenue risk in agriculture taking into consideration the growing conditions in the Czech Republic. The problem of risk management scheme in the Czech agriculture is that systemic weather risks are not covered by insurance (drought). In these cases, farmers have to rely either on their own financial reserves or ad hoc state assistance. Various combinations of weather variables, crops, regions and weather stations have been examined to design index-based weather contracts for most important crops produced in the Czech Republic. The first part of the thesis is devoted to literature review concerning risk management in agriculture. Overview of data sources is followed by assessment of risk environment of agricultural enterprises in the Czech Republic. Then, author describes the choice of crops and regions suitable for weather derivative design. The main part is devoted to method of design and valuation of weather derivatives at the regional level (burn analysis, parametric bootstrap). Finally, discussion on main findings, chances and limitations of agricultural weather derivatives is considered. The research shows the need to better differentiate public risk management support in agriculture in the Czech Republic. Regarding the efficiency of weather derivatives, it is possible to conclude that spatial (geographical) and production basis risk significantly reduce the efficiency of weather derivatives in agricultural practice.

西元二零零八年(民國九十七年)發生的全球性金融海嘯在歷史上絕對會是重要的金融事件之一，初期的徵兆點可追溯自二零零七年美國的次貸事件惡化，此次金融海嘯會在何時畫下句點，各領域的大師眾說紛紜：有人聲稱這次金融海嘯是二次世界大戰以來發生之最嚴峻的一次，將持續至少四~五年；有人說經濟大蕭條會延宕到二零一零年；樂觀的多頭大師則云今年(西元二零零九年)下半年即可嗅到景氣回春的訊息，然而在我寫這論文時，景氣蕭條的氛圍仍持續瀰漫著。雖然這篇論文並不是要探討這次歷史性金融海嘯的前因後果，但是引發我探討這篇論文主題的基差風險，卻源於美國次貸事件惡化後，金融市場反應的LIBOR 3M與LIBOR 6M間基差報價擴大現象而有所關聯。 本文針對交易室的投資組合中，在利率產品交易裡使用的浮動利率指標(Floating Rate Index)，不論是LIBOR 1M、LIBOR 3M、LIBOR 6M或LIBOR 12M，原本用來評價內含這些浮動利率指標產品的曲線(Revaluation Curve)均是由3M Swap Rate (USD LIBOR 3M)市場價格所建構而成；在納入基差因子，實際反映市場基差報價來分別建構不同浮動利率指標交易對應的不同評價曲線，比較納入基差因子前後及模擬各種基差市場價格情境下，對投資組合進行評價的損益差異，來說明忽略基差風險對投資組合的影響程度。

Wetter stellt für die Landwirtschaft einen Hauptunsicherheitsfaktor dar. Angesichts der Kli-maveränderung gilt es als wahrscheinlich, dass Wetterschwankungen und die Häufigkeit extremer Wetterereignisse in Zukunft zunehmen werden. Vor diesem Hintergrund spielt die Entwicklung von Wetterrisikomanagementinstrumenten eine wichtige Rolle zur Einkom-mensstabilisierung in der Landwirtschaft sowohl in entwickelten Volkswirtschaften als auch in Entwicklungsländern. Seit Mitte der neunziger Jahre werden auf Finanzmärkten sogenannte Wetterderivate angebo-ten, die den Austausch von Wetterrisiken zwischen Marktteilnehmern ermöglichen. Zielsetzung der vorliegenden Arbeits ist es, die Einsatzmöglichkeiten von Wetterderivaten in der Landwirtschaft zu untersuchen. Dazu sind verschiedene methodische Vorarbeiten zu leisten. Erstens, wird ein statistisches Modell benötigt, das die Unsicherheit des betrachteten Wetterereignisses (z.B. Temperatur oder Niederschlag) beschreibt. Zweitens, muss der Zusammenhang zwischen Wetter und landwirtschaftlicher Produkti-on abgebildet werden. Drittens, schließlich bedarf es eines theoretischen Modells, um das Wetterderivat zu bepreisen. Liegen die genannten Modellkomponenten vor, kann die Hedgingeffektivität eines Wetterde-rivats aus Sicht eines landwirtschaftlichen Produzenten bestimmt werden. Dies geschieht in der vorliegenden Arbeit beispielhaft für Getreideproduzenten in Deutschland. Es zeigt sich, dass die Hedgigeffektivität und damit die Zahlungsbereitschaft für Wetterderivate produkt- und regionsspezifisch ist. Angesichts eines ausgeprägten Basisrisikos ist es unwahrscheinlich, dass Wetterderivate in Deutschland eine breite Anwendung durch Landwirte erfahren werden. Ihr Anwendungspotenzial bei landwirtschaftlichen Versicherern und Rückversicheren er-scheint dagegen höher, da diese mit Hilfe von Wetterderivaten einen Teil ihres systematischen Risikos aus landwirtschaftlichen Ertragsversicherungen auf den Kapitalmarkt transferieren können. / Weather is a major factor of uncertainty for agriculture. The effects of climate change means that it is likely that in the future there will be increased fluctuations in weather patterns and extreme meteorological events will become more regular. In this context, the development of weather risk management instruments plays an important role in the stabilising of incomes in the agricultural sector, both in developed economies as well as in developing countries. Since the mid-nineties, so-called weather derivatives have been emerged on the market which enables participants in the market to exchange weather risks. This work aims to investigate the implementation possibilities of weather derivatives in agriculture. A range of methodological preliminary investigations will be carried out. First of all it is necessary to find a statistical model which describes the uncertainty of observed weather events (e.g. temperature or precipitation). Secondly, the relationship between weather and agricultural production needs to be mapped. Thirdly, a theoretical model needs to be devised which is capable of pricing the weather derivatives. The hedging effectiveness of a weather derivative can be determined from the point of view of an agricultural producer using the model components described above. This study will use the example of grain producers in Germany. It will demonstrate that hedging effectiveness and with it willingness to pay for weather derivatives depends on the product and region. A pronounced basis risk means that it is unlikely that weather derivatives will be widely used by farmers in Germany. Their application potential for agricultural insurers and reinsurers, however, seems greater, since they can use weather derivatives to transfer a part of their systematic risk from agricultural income insurance onto the capital market.