Historic market volatility has made risk management decisions by firms in the agricultural supply chain more challenging. Market risk measurement methods, such as Value-at-Risk, were developed in the financial industry to objectively measure, and thus better comprehend, market risk's effect on positions. This thesis gives a thorough background of the issues involved with risk measurement. Different scenarios were then used to demonstrate how the risk measurement method can be applied to the agricultural processing margin. In this thesis, the flour milling margin was used to demonstrate how a firm can incorporate sophisticated risk analytics into its risk management decision making process. Multiple scenarios were developed to account for different situations faced by flour millers. Ocean freight, exchange rate risk, futures price risk, basis risk and flour price risk are all included to provide examples of how market risk measurement can be beneficial to industry participants.

Public private partnerships (PPPs) are procurement models used in the provision of public infrastructures and involving private, as opposed to public, finance. The PPP model differs from the traditional public procurement model in this sense and in the unprecedented degree to which the private sector is involved. All things being equal, the rationale for choosing a PPP instead of a traditional public procurement model is if it provides a better Value for Money. As a result, a crucial issue to address is to find the key drivers of Value for Money in PPP projects and most importantly, to analyze the relationships between those key drivers and the complex notion of Value for Money. This study is based on a large overview of the literature together with contributions of informal interviews and my own opinions. Emphasis is put on the importance of risk management from financiers’ perspective and its consequences on Value for Money. The findings highlight the current problems in the Value for Money assessment that make the analysis hardly reliable. Good and bad practices in Value for Money assessment are discussed and potential solutions and guidance toward more Value for Money are provided.

This thesis explores and evaluates the forecasting application of the machine learning method Gradient Boosting Decision Trees. This method is used to forecast the demand of the online grocery market with a 7-day time horizon. The thesis was conducted in collaboration with the online grocery company Mathem. The model is applied and evaluated on three different periods representing the spring, summer and fall. The main evaluation metric is the mean absolute percentage error (MAPE), and clear differences were found depending on the predictability of the period. Apart from the model and its application to demand forecasting, the related risk was investigated. This was done by studying the Value-at-Risk and Expected Shortfall associated with discrepancies between the forecasted and actual values over the three periods. The most important conclusion of the case study at Mathem is that overestimation in the forecast is more costly in terms of monetary value than underestimating. It is also found that this is highly dependent on the cost structure of the company's operation and could therefore vary between companies. Thus, the study has contributed to understanding the applications of machine learning models in forecasting processes as well as the risks related to over/underestimating the demand of the online grocery market. / I denna uppsats utforskas och utvärderas maskininlärningsmetoden Gradient Boosting Decision Trees och dess tillämpningsområde inom prognostisering. Metoden används för att prognostisera efterfrågan på onlinehandel av dagligvaror med en 7 dagars tidshorisont. Uppsatsen gjordes i samarbete med företaget Mathem som är aktiva inom denna sektor. Modellen appliceras och utvärderas på tre olika tidsperioder som representerar våren, sommaren och hösten. Modellen själv utvärderas med avseende på måttet mean absolute percentage error (MAPE) och tydliga skillnader mellan tidsperioderna observerades relaterat till variansen i datan. Förutom modellen och dess applikation på prognostisering av efterfrågan utforskades även de relaterade riskerna. Detta genomfördes genom att studera riskmåtten Value-at-Risk och Expected Shortfall baserade på differensen mellan de prognostiserade och de faktiska värdena under dessa tre tidsperioder. Den viktiga slutsatsen som kunde dras från uppsatsen i samband med Mathem var att det, i monetära termer, är dyrare att prognostisera för högt än för lågt. En ytterligare slutsats som kan dras är att den monetära risken är mycket beroende av kostnadsstrukturen hos företaget och skulle därför kunna variera mellan olika företag. Således har denna uppsats bidragit till förståelse för användandet av maskininlärning för prognostisering samt riskerna kopplade till över- och underskattning av efterfrågan i marknaden för dagligvaruhandel online.

La era digital ha ocasionado que el comprador peruano migre hacia el e-commerce. Sin embargo, percibe ciertos riesgos los cuales influencian en su intención de adquirir algún producto por esta vía. Asimismo, estos riesgos varían de acuerdo a la categoría. Por ello, la presente trabajo estudiará los riesgos percibidos con respecto a la categoría maquillaje, debido a que investigaciones anteriores no han estudiado esta categoría, por lo cual se cubrirá esta deficiencia de conocimiento en el e-commerce. Las variables elegidas son el riesgo financiero, de privacidad, de producto, de conveniencia, compra y post-compra. Para poder comprobar las hipótesis se realizó una investigación mixta. Por un lado, en cuanto al estudio cualitativo, se realizaron 2 focus group a mujeres de 20 a 32 años que compren frecuentemente maquillaje por en canal online, y se realizaron 3 entrevistas a profundidad a expertos en el tema. Por otro lado, con respecto al estudio cuantitativo, se realizaron 250 cuestionarios al público en estudio. Finalmente, para comprobar las hipótesis planteadas, se realizó un análisis de regresión lineal múltiple entre la variable de intención de compra y los riesgos percibidos en su conjunto. Posteriormente, se obtuvo que las variables que influencian en la intención de compra son el riesgo de conveniencia y de producto. / The digital age has caused the Peruvian buyer to migrate to electronic commerce. However, he perceives certain risks which influence his intention to purchase a product through this channel. Similarly, these risks related to the category agreement. Therefore, the present work studying the perceived risks regarding the makeup category, due to previous research that has not studied this category, so this knowledge deficiency in e-commerce will be covered. The variables chosen are financial, privacy, product, convenience, purchase and post-purchase risk. In order to evaluate the hypotheses, a mixed investigation was carried out. On the one hand, regarding the qualitative study, 2 focus groups were used on women between 20 and 32 years of age who make up makeup by online channel, and 3 in-depth interviews were conducted with experts on the subject. On the other hand, regarding the quantitative study, 250 questionnaires were analyzed to the study public. Finally, to verify the hypotheses raised, a multiple linear regression analysis was performed between the purchase intention variable and the risks perceived as a whole. Subsequently, it is expected that the variables that influence the purchase intention are the convenience and product risk. / Trabajo de investigación

Ägarlägenheter är en upplåtelseform som bygger på tredimensionell fastighetsindelning. Denmöjliggjordes i svensk lagstiftning år 2009 med syftet att bidra till en mångfaldig bostadsmarknad,samt erbjuda fastighetsägaren större frihet att förfoga över den egna bostaden. Upplåtelseformen ärvanlig utomlands, men har inte fått något större genomslag i Sverige. I dagsläget präglas den svenska ekonomin av inflation och snabba räntehöjningar. Denna rapportundersöker därför hur ekonomisk nedgång påverkar olika aktörers inställning till ägarlägenheter. Föratt kunna dra slutsatser kring detta identifieras faktorer som kan påverka den ekonomiska risken förbanker, privatpersoner och byggherrar, samt hur riskerna kan motverkas genom juridiska åtgärder.Med ekonomisk risk menas i denna rapport värdeutvecklingen på marknadens objekt, det vill sägarisken för minskad eller utebliven avkastning kopplat till lönsamhet. Resultatet bygger på intervju- och litteraturstudier. Slutsatsen som dras är att det kan identifieras fleramöjliga riskfaktorer som påverkar lönsamheten för aktörerna. Informationsbrist bland marknadensaktörer leder bland annat till begränsad efterfrågan, och därmed lägre lönsamhet för byggherrar.Finansieringsmöjligheterna för köp och byggnation av ägarlägenheter är också begränsade, vilketidentifieras som en risk för privatpersoner och byggherrar som riskerar sämre lånevillkor. Bristfälligakrav på en ekonomisk underhållsplan för samfällighetsföreningar utgör en risk för banker ochprivatpersoner då det blir svårt att förutspå framtida utgifter. Studien kommer därför fram till attytterligare lagkrav på ekonomiska underhållsplaner bör införas. För att minska ekonomiska risker medägarlägenheter identifieras även behov av lagstiftning som möjliggör ombildning av det befintligabostadsbeståndet till ägarlägenheter. Dessutom bör det ställas krav på kommuner att nyttjamarkanvisning i större omfattning, för att gynna upplåtelseformen. Slutligen dras slutsatsen att dagensekonomiska nedgång kan leda till att aktörerna ställer sig mer positiva till ägarlägenheter. Detta tillföljd av att höjda räntor synliggör risker med andra upplåtelseformer och gör hushållen merriskmedvetna. Utifrån detta är det möjligt att den ekonomiska nedgången resulterar i att ägarlägenheterökar i popularitet. / Condominium ownership (sv. ägarlägenheter), is a model based on three-dimensional propertydivision, where the apartments are regarded as property units and are owned individually.The concept was introduced in Swedish law in 2009. The purpose was to contribute to a diversehousing market and offer the owner, in principle, freedom to dispose of his own home. Thecondominium ownership model is common internationally but has not had any major impact inSweden. Today, the Swedish economy is characterized by inflation and rapidly increasing interest rates.Therefore, this report aims to examine how economic instability affects the attitude of various actorstoward condominium ownership. To conclude, factors are identified that can affect the financial riskfor banks, individuals, and developers, as well as how these can be counteracted by legal measures. Inthis report, economic risk is measured as volatility and profitability. The study concludes that several possible risk factors can be identified that affect profitability when itcomes to investing in condominium ownership apartments. Lack of information leads, among otherthings, to limited demand and thus lower profitability for real estate developers. The financingpossibilities for purchasing and constructing condominium ownership apartments are also limited,which is identified as a risk for customers and developers who risk higher interest rates. Inadequaterequirements for a financial maintenance plan pose a risk for banks and individuals as it becomesdifficult to predict future expenses. The study, therefore, identifies a need for additional legalrequirements on financial maintenance plans to be introduced. To reduce financial risks, a need forlegislation is also identified that enables the conversion of the existing housing stock intocondominium ownership apartments. In addition, there should be a requirement that municipalities useland instructions in a more efficient way to favor the condominium ownership model. Finally, it isconcluded that today's economic instability can lead to actors taking a more positive view ofcondominium ownership. This results from increased interest rates making risks with other housingalternatives visible and making households more aware of the risks. Based on this, the economicdownturn may result in the condominium ownership model increasing in popularity.

Copulas as a description of joint probability distributions is today common when modeling financial risk. The optimal mass transport problem also describes dependence structures, although it is not well explored. This thesis explores the dependence structures of the entropy regularized optimal mass transport problem. The basic copula properties are replicated for the optimal mass transport problem. The estimation of the parameters of the optimal mass transport problem is attempted using a maximum likelihood analogy, but only successful when observing the general tendencies on a grid of the parameters. / Copulas som en beskrivning av simultanfördelning är idag en vanlig modell för finansiell risk. Optimala masstransport problemet beskriver också simultant beroende mellan fördelningar, även om det är mindre undersökt. Denna uppsats undersöker beroendestrukturer av det entropiregulariserade optimala masstransport problemet. De basala egenskaperna hos copulas är replikerade för det optimala masstransport problemet. Ett försök att skatta parametrarna i det optimala masstransport problemet görs med en maximum-likelihood liknande metod, men är endast framgångsrik i att uppsakata de generella tendenserna på en grid av parametrarna.

This dissertation examines the challenges associated with disruptions in supply chain financing and the railway transportation network. The study is divided into six chapters: In Chapter 1, we introduce the core problems under investigation. Chapter 2 investigates supply chain financing, emphasizing trade credit and bank credit—two predominant external financing mechanisms. Given the inherent uncertainties in demand, interest rates, and supplier credit ratings, this chapter introduces a stochastic programming model accounting for demand uncertainty. Subsequently, a robust optimization program is applied, whose complexity demands a specialized solution methodology. By analyzing a case study centered around a prominent U.S. retailer, the research reveals key insights into decision-making processes related to financing, the effects of bargaining power on portfolio mix and profits, and the relative importance of interest rate uncertainties over supplier credit ratings. Chapter 3 introduces a game-theoretical model designed to hedge financing risks in supply chains, with a focus on the application of insurance for both trade and bank credits. To support the design of effective supply chain finance contracts, three distinct contracts are developed, aiming to synchronize both financial and material flows within the supply chain. A significant feature of this chapter is the data-driven approach employed to address the potential bankruptcy risks that can arise from borrowing loans. Alongside this, a novel solution algorithm is introduced to solve the proposed non-convex models. A case study involving Ford Motor Company and a Chicago-based retailer enriches the research with real-world context. The findings offer several managerial insights: the strategic advantages of different insurance services vary based on the risk attitudes and profit margins of participants. For example, when a retailer operates with a lower profit margin, the use of Trade Credit Insurance (TCI) is recommended in conjunction with a risk-seeking retailer, while a risk-averse retailer might diminish the benefits of TCI. Conversely, with high profit margin retailers, the adoption of Payment Protection Insurance (PPI) is advised under all conditions. In Chapter 4, a game-theoretical model for risk mitigation within railway transportation is introduced. This model addresses random disruptions by employing strategies like repair, re-routing, third-party services, and leasing capacity from competing rail companies. Through a U.S. case study, the efficacy of these strategies is examined, with renting railcars emerging as a particularly potent approach to enhance resilience and reduce third-party expenses. The research further suggests that negotiations extending delivery dates can significantly diminish post-disruption costs. Finally, Chapter 5 summarizes the primary contributions of this research, laying the groundwork for prospective studies in this domain. / Thesis / Doctor of Philosophy (PhD)

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This study investigates the relationship between financial literacy and financial risk tolerance among finance students at the University of Jayewardenepura in Sri Lanka, a  developing country. The research focuses on understanding how financial literacy influences financial risk tolerance within this specific student population. The majority of students exhibit similar levels of financial literacy and financial risk tolerance, with notable variations in financial knowledge compared to other dimensions of financial literacy such as financial attitude and financial behaviour. Correlation analysis reveals a strong positive relationship between financial literacy and financial risk tolerance, with financial knowledge showing a particularly strong association. Financial attitude and financial behaviour show moderate correlations with risk tolerance. Regression analysis indicates that financial attitude is the most influencing factor affecting financial risk tolerance.Furthermore, controlling variables like age, gender, and year of study does not significantly impact financial literacy levels among the participants. When comparing with previous studies, it shows that financial literacy and financial risk tolerance are crucial regardless of a country's development status and both types of nations showing a positive link between them. While developed countries often focus on gender's role in finance, developing onestend to minimize its significance by highlighting the need for strategies to enhance financialliteracy in each country. Thus, this study provides valuable understanding about thedynamics of financial literacy and risk tolerance among university students in Sri Lanka bycontributing to the existing literature on financial education and decision-making behaviours.

This thesis aims to analyze some of the available methods that aid in risk estimation based on econometric models, as well as to propose some new ones. Some of the questions that are expected to be answered include which distribution to choose to obtain better risk estimates for series with abnormal behaviours, how to determine whether the distribution in parametric conditional models is a Student’s t, and how to assess whether an asset’s risk helps predict the risk of another asset. In Chapter 1, we estimate several cryptocurrencies’ Expected Shortfall using different error distributions and GARCH-type models for conditional variance. ur goal is to examine which distributions perform better and to check which component of the specification plays a more crucial role in estimating Expected Shortfall. The performance of the estimations is conducted using a backtesting technique with a rolling-window approach. Results show that, in the case of Bitcoin, it is important to use a distribution with at least two parameters that control its shape and an extension of the GARCH model, whether it be the NGARCH or the CGARCH model. On the other hand, other smaller cryptocurrencies yield good enough risk predictions with the Student’s t distribution and a GARCH model. The fact that the main measures of financial risk are focused on the tail of the distribution of returns highlights the importance of the choice of an appropriate distribution model. Chapter 2 develops a procedure for consistently testing the specification of a Student’s t distribution for the innovations of a dynamic model. This contributes to the existing literature by providing a test for Student’s t distributions in conditional mean and variance models with a parameter-free test statistic and, thus, a known asymptotic distribution, avoiding the use of more computationally costly resampling techniques such as bootstrapping. The specific expressions needed for the computation of the test statistic are obtained by adapting the generic test of Bai (2003), which is based on the Khmaladze (1988) transformation of the model residuals. Finally, in Chapter 3, the concept of Granger causality in Expected Shortfall (ES) is introduced, along with a testing procedure to detect this type of predictive relationship between return series. Granger causality in Expected Shortfall is here defined as the predictive ability of tail values of a series over future tail values of another series on average. This definition may help in analyzing whether past values of an asset in extreme risk affect future extreme risk values of another asset. The main contribution of this chapter is a test for detecting this type of causality, based on the test for Granger causality in VaR by Hong et al. (2009). An empirical application on financial institutions from different industries (banking, insurance, and diversified financials) is presented to analyze the risk spillovers in the US financial market. The contribution of this thesis to the field of financial econometrics focuses on the market risk of financial assets, both in its modeling through the metric known as Expected Shortfall suggested in the Basel III Accords and in its utility beyond capital requirements. The results highlight the importance of a good specification of the chosen distribution model for risk estimation - especially in high-risk assets such as cryptocurrencies - and a test is proposed to verify if the conditional distribution in parametric models used for risk predictions is or is not a Student’s t distribution. Finally, a Granger causality test in Expected Shortfall is proposed, which allows for studying risk propagation in tails of return distributions. The proposed test can be used to investigate interconnections within and between markets as a complement when evaluating systemic risk. Other potential applications include improving Expected Shortfall forecasts by including causing variables as regressors in estimations, studying the inclusion of certain asset pairs in the same portfolio based on how they interact in the riskiest situations, or constructing networks of extreme risk propagation. / Esta tesis doctoral ha sido financiada mediante una ayuda FPU por el Ministerio de Educación, Cultura y Deporte (FPU17/06227).