<p>Title: Corporate Strategies for Currency Risk Management</p><p>ackground:Currency fluctuations are a global phenomenon, and can affect multinational</p><p>companies directly through their cash flow, financial result and company</p><p>valuation. The exposure to currency risks might however be covered against or</p><p>‘hedged’, as it is called, by different external and internal corporate strategies.</p><p>However, some of these strategies might include a risk themselves as they can</p><p>be expensive and uncertain. It is therefore an interesting question whether if</p><p>these strategies are actually applied in practice, and if so which strategies are</p><p>favored and why.</p><p>Purpose: The purpose of this thesis is to present and explain the different external and</p><p>internal hedging techniques and to see which, or if any, strategies are favored by</p><p>large, medium-sized and small companies and for what reasons.</p><p>Method: Regarding primary data, interviews with a mostly qualitative profile have been</p><p>used to discuss the subject with respondents from six companies, diversified in</p><p>size using the classification from the European Commission. Secondary data has</p><p>been collected through literature from the university library and internet sources.</p><p>Conclusion: Large companies primarily use the strategy of forwards, since they carry high</p><p>elements of risk aversion, predictability and simplicity. For internal strategies,</p><p>large companies prefer netting. Small companies extensively use matching</p><p>because the routine is easy to establish and handle. Medium-sized companies</p><p>can use either one so much depends on the risk-aversion and cash-flow</p><p>management of the company.</p><p>Large companies continuously regard currency risk a big factor, whereas small</p><p>companies have just recently started due to the dollar depreciation. Translation</p><p>exposure should be considered a big risk regardless of the company size, if the</p><p>company is the main one in a corporate group. Finally, the subject of</p><p>currency risk management is very theoretically broad, but its appliance in</p><p>practice is very slim as only a few strategies are actually favored and frequently</p><p>used.</p>

Title: Corporate Strategies for Currency Risk Management ackground:Currency fluctuations are a global phenomenon, and can affect multinational companies directly through their cash flow, financial result and company valuation. The exposure to currency risks might however be covered against or ‘hedged’, as it is called, by different external and internal corporate strategies. However, some of these strategies might include a risk themselves as they can be expensive and uncertain. It is therefore an interesting question whether if these strategies are actually applied in practice, and if so which strategies are favored and why. Purpose: The purpose of this thesis is to present and explain the different external and internal hedging techniques and to see which, or if any, strategies are favored by large, medium-sized and small companies and for what reasons. Method: Regarding primary data, interviews with a mostly qualitative profile have been used to discuss the subject with respondents from six companies, diversified in size using the classification from the European Commission. Secondary data has been collected through literature from the university library and internet sources. Conclusion: Large companies primarily use the strategy of forwards, since they carry high elements of risk aversion, predictability and simplicity. For internal strategies, large companies prefer netting. Small companies extensively use matching because the routine is easy to establish and handle. Medium-sized companies can use either one so much depends on the risk-aversion and cash-flow management of the company. Large companies continuously regard currency risk a big factor, whereas small companies have just recently started due to the dollar depreciation. Translation exposure should be considered a big risk regardless of the company size, if the company is the main one in a corporate group. Finally, the subject of currency risk management is very theoretically broad, but its appliance in practice is very slim as only a few strategies are actually favored and frequently used.

In this thesis we address problems associated with financial modelling from a Bayesian point of view. Specifically, we look at the problem of calibrating financial models, measuring the model uncertainty of a claim and choosing an optimal hedging strategy. Throughout the study, the local volatility model is used as a working example to clarify the proposed methods. This thesis assumes a prior probability density for the unknown parameter in a model we try to calibrate. The prior probability density regularises the ill-posedness of the calibration problem. Further observations of market prices are used to update this prior, using Bayes law, and give a posterior probability density for the unknown model parameter. Resulting Bayes estimators are shown to be consistent for finite-dimensional model parameters. The posterior density is then used to compute the Bayesian model average price. In tests on local volatility models it is shown that this price is closer than the prices of comparable calibration methods to the price given by the true model. The second part of the thesis focuses on quantifying model uncertainty. Using the framework for market risk measures we propose axioms for new classes of model uncertainty measures. Similar to the market risk case, we prove representation theorems for coherent and convex model uncertainty measures. Example measures from the latter class are provided using the Bayesian posterior. These are used to value the model uncertainty for a range of financial contracts priced in the local volatility model. In the final part of the thesis we propose a method for selecting the model, from a set of candidate models, that optimises the hedging of a specified financial contract. In particular we choose the model whose corresponding price and hedge optimises some hedging performance indicator. The selection problem is solved using Bayesian loss functions to encapsulate the loss from using one model to price and hedge when the true model is a different model. Linkages are made with convex model uncertainty measures and traditional utility functions. Numerical experiments on a stochastic volatility model and the local volatility model show that the Bayesian strategy can outperform traditional strategies, especially for exotic options.

Thesis (Ph. D.)--Stanford University, 2001. / Includes bibliographical references (leaves 119-121).

Cette thèse porte sur la modélisation, la prévision et la couverture du risque de contagion financière. Après une présentation générale des fondements théoriques et des mécanismes de propagation relatifs à la contagion financière, nous introduisons une modélisation fondée sur les modèles de cointégration non linéaire et de causalité non linéaire dans lesquels, les variables et le terme d’erreur du modèle à correction d’erreur obéissent à la dynamique de processus auto-régressifs à changement de régime de type TAR et M-TAR pour capter l’effet de contagion. Une extension de cette modélisation au cadre de prévision probabiliste conditionnelle a été faite par la suite à travers les réseaux de croyance Bayésienne pour renforcer le pouvoir prédictif. Ensuite, nous montrons comment une institution financière peut couvrir son portefeuille contre ce type de risque par de nouvelles approches. Nous proposons pour cela, une stratégie de couverture purement statique dans une perspective règlementaire à l’aide de modèles génératifs de type Vines-copula, une stratégie de couverture semi-statique fondée sur la budgétisation des risques et une stratégie de couverture dynamique à partir des processus de diffusion à sauts mutualisés. Ces nouvelles modélisations sont testées empiriquement sur un ensemble d’indices boursiers. / This Ph.D thesis focuses on modeling, forecasting and hedging financial contagion. After an overview of the theoretical foundations and spread mechanism relating to financial contagion, we introduce modeling based on nonlinear cointegration and non-linear causality models in which the variables and the error term in the correction model error obey at the dynamics of autoregressive regime change process of type TAR and M-TAR to catch the contagion effect. An extension of this model to conditional probabilistic forecasting framework was done through Bayesian belief networks, to enhance the predictive power. Then we show how a financial institution can hedge its portfolio against this risk by new specifications. Therefore, we offer a purely static hedging strategy in a regulatory perspective using generative models Vines-copula, a semi-static hedging strategy based on risk budgeting and dynamic hedging strategy based on mutually exciting jumps diffusion process. These new models are tested empirically on set of market indices.

Master’s thesis deals with analysis of specific business transactions, where company exchange-rate risks happen. On the basis of findings, the thesis includes the proposals of treasury instruments for exchange-rate loss minimalization.

Using a sample of 141 U.S. small-cap industrial firms, I examine the firm characteristics that influence its use of foreign exchange derivatives to hedge exchange rate risk. Companies in the industrial sector produce goods and services that are used for the production of another final product. The performance of this sector is closely correlated to the level of demand from the final consumer. I find firm size, the amount of foreign sales, and firm liquidity influence the firm's decision to use foreign exchange derivatives to hedge exchange rate risk. For those firms that hedge exchange rate risk using derivatives, a second test examines the firm characteristics that influence the extent of its hedging activities. I find the extent of hedging is influenced by the amount of foreign sales, the amount of foreign assets, and the number of foreign subsidiaries the firm operates. A final test examines whether certain firm characteristics influence its decision to use options as part of its hedging operations. I find no evidence that the firm characteristics examined herein influence that decision.

This doctoral thesis widely analyses the process of investment decision-making. In its individual parts, it researches models used for planning, analysing and evaluation of investments projects, but also models used for final decision about realization of the investment. Investing activity is present in world economic cycle in all it’s phases. Capital sources used for financing if the investment projects are scarce and must be handled with care. For this reason, there are many supportive methodologies and models employed in managing of the investments as well as instruments developed to miti-gate the potential project risks. However, even utilization of these instruments and models can’t guarantee the expected results. There are uncertainties, errors and in-accuracies in the process that can thwart investment decisions. The aim of the thesis is to analyse the investment decision-making process (from the initial idea to the realization of the investment project) and to identify the main un-certainties – factors influencing the success / error rate of models for investment project planning as well as the decision on their realization. The main outcome of the thesis is an overview of these factors and recommenda-tions on how to work with these factors and make the process as effective as possi-ble. Another output is an analysis and recommendations for the use of financing sources and mix of the instruments that should be used to mitigate the potential impact of risks that are connected to all investment projects.