882 resultados para Risk Management Agency


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This thesis examines the suitability of VaR in foreign exchange rate risk management from the perspective of a European investor. The suitability of four different VaR models is evaluated in respect to have insight if VaR is a valuable tool in managing foreign exchange rate risk. The models evaluated are historical method, historical bootstrap method, variance-covariance method and Monte Carlo simulation. The data evaluated are divided into emerging and developed market currencies to have more intriguing analysis. The foreign exchange rate data in this thesis is from 31st January 2000 to 30th April 2014. The results show that the previously mentioned VaR models performance in foreign exchange risk management is not to be considered as a single tool in foreign exchange rate risk management. The variance-covariance method and Monte Carlo simulation performs poorest in both currency portfolios. Both historical methods performed better but should also be considered as an additional tool along with other more sophisticated analysis tools. A comparative study of VaR estimates and forward prices is also included in the thesis. The study reveals that regardless of the expensive hedging cost of emerging market currencies the risk captured by VaR is more expensive and thus FX forward hedging is recommended

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Growing awareness in corporate responsibility and issues related to sustainability is seen to increase innovativeness in a company as well as in its supply chain. The stakeholders’ awareness on sustainability has increased, and they demand the companies to identify sustainability risks and adapt procedures for mitigating them. The purpose of this thesis is to examine how risks are managed in sustainable supply chain. Definition of sustainability risks and risk management procedures construct the framework of the study. It is done through an empirical study conducted on 95 Finnish companies operating in the manufacturing industry. The data is acquired via an online questionnaire. The research has been conducted as a quantitative study utilizing the methods of statistical analysis, such as correlation analysis and factor analysis. The essential results of this thesis are identified risk-procedure connections, and the importance of different risks and procedures in the respondent companies.

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This thesis reveals the topic of reputational risk management as a key element for business continuity and value maximization. The purpose of the work is to investigate reputational risk from the side of its definition, management (including legal requirements on this risk category) and measurement and to analyse reputational risk’s impact on business continuity and value maximization. To be able to do this, different respective articles, reports of financial institutions are gathered and constructive summaries and analysis are made. In order to deeply investigate the impact of reputational risk on business continuity and value maximization, it was chosen to study it from three aspects: 1) check the impact of stock valuation of 7 companies that experienced reputational catastrophe / risk, 2) analyse a case study on disagreements in management of reputational risk among case companies and impact on their respective performance, and 3) conduct a survey of financial sector companies in Liechtenstein to see how reputational risk management works in practice. The findings of the research showed a significant impact of reputation decadence on company’s value and trading volume, and showed crucial importance of post-crisis management for the company’s financial performance. The results of the qualitative research based on survey proved that companies consider reputational risk management as a one of the key elements for their business continuity and value maximization.

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Emerging markets of Northern Africa and Turkey provide growth opportunities for logistics service companies in the middle of low growth environment of European Union. The purpose of this research is to explore and analyze the risk factors in container shipping industry and third party logistics (3PL) services. The research empirically examined the risk factors, which are related within the interaction between these two parties in emerging markets of Mediterranean area. The previous studies have provided a valuable insight into the operational risks faced by container shipping industries. However, most of these studies have focused on one or several operational risk factors from a single point of view, and no studies have inclusively examined the possible operational risks faced in the container shipping industry from dual perspective of 3PL provider and its customers. A questionnaire has been deployed to collect related data; and the impacts of the risks were then be assessed and ranked using the method of risk mapping. Respondents were located in Turkey, Algeria, Tunisia, and Libya. Research presents the most important risk factors identified, and compares them between 3PL provider and its customers. The research also provide some risk mitigation strategies for the key risk factors, and tried to figure out a common risk picture, which guides the managers in both sides to have a better decisions and as a result, improve the performance of the container shipping operations. Challenge during project execution time was that customers identified vast amount of more risks than what was the case with logistics service operator.

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Development of risk management practices became significant part of transportation companies’ strategy. Evolution from insurance management into enterprise risk management (ERM) led to development of risk management tools and methods. The purpose of this thesis is to design technique for evaluation of risk management practices of national transportation companies. The empirical research is made on the example of Russian and Finnish transportation companies. The required data was conducted with a help of survey. The result of the thesis is designed technique for risk management practices evaluation that allows to compare practices of different countries and organizations with different characteristics. The Master thesis has novelty in theoretical and practical contribution. It was designed new technique based on realization of the method of APIS. Moreover, it has practical implication as managers can utilize this method for comparison of practices between different countries, different organization and even different units within particular organization.

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Rapport de recherche

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Les quatre principales activités de la gestion de risque thérapeutique comportent l’identification, l’évaluation, la minimisation, et la communication du risque. Ce mémoire aborde les problématiques liées à l’identification et à la minimisation du risque par la réalisation de deux études dont les objectifs sont de: 1) Développer et valider un outil de « data mining » pour la détection des signaux à partir des banques de données de soins de santé du Québec; 2) Effectuer une revue systématique afin de caractériser les interventions de minimisation de risque (IMR) ayant été implantées. L’outil de détection de signaux repose sur la méthode analytique du quotient séquentiel de probabilité (MaxSPRT) en utilisant des données de médicaments délivrés et de soins médicaux recueillis dans une cohorte rétrospective de 87 389 personnes âgées vivant à domicile et membres du régime d’assurance maladie du Québec entre les années 2000 et 2009. Quatre associations « médicament-événement indésirable (EI) » connues et deux contrôles « négatifs » ont été utilisés. La revue systématique a été faite à partir d’une revue de la littérature ainsi que des sites web de six principales agences réglementaires. La nature des RMIs ont été décrites et des lacunes de leur implémentation ont été soulevées. La méthode analytique a mené à la détection de signaux dans l'une des quatre combinaisons médicament-EI. Les principales contributions sont: a) Le premier outil de détection de signaux à partir des banques de données administratives canadiennes; b) Contributions méthodologiques par la prise en compte de l'effet de déplétion des sujets à risque et le contrôle pour l'état de santé du patient. La revue a identifié 119 IMRs dans la littérature et 1,112 IMRs dans les sites web des agences réglementaires. La revue a démontré qu’il existe une augmentation des IMRs depuis l’introduction des guides réglementaires en 2005 mais leur efficacité demeure peu démontrée.

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This research was undertaken with an objective of studying software development project risk, risk management, project outcomes and their inter-relationship in the Indian context. Validated instruments were used to measure risk, risk management and project outcome in software development projects undertaken in India. A second order factor model was developed for risk with five first order factors. Risk management was also identified as a second order construct with four first order factors. These structures were validated using confirmatory factor analysis. Variation in risk across categories of select organization / project characteristics was studied through a series of one way ANOVA tests. Regression model was developed for each of the risk factors by linking it to risk management factors and project /organization characteristics. Similarly regression models were developed for the project outcome measures linking them to risk factors. Integrated models linking risk factors, risk management factors and project outcome measures were tested through structural equation modeling. Quality of the software developed was seen to have a positive relationship with risk management and negative relationship with risk. The other outcome variables, namely time overrun and cost over run, had strong positive relationship with risk. Risk management did not have direct effect on overrun variables. Risk was seen to be acting as an intervening variable between risk management and overrun variables.

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Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub-optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out-of-sample forecasting performance of various linear and GARCH-type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decisionmaking.