This thesis focuses on solving financial crisis throught foreign exchange swaps. Facilities, which provided help to Banks around the world called swap lines. These facilities introduced U.S. Federal Reserve (Fed) in late 2007. The swap lines were one of the many liquidity programs that Fed conducted in order to provide liquidity to the global banking system. Using indicator 3M Libor -- OIS spread, which informs about the problems in the interbank markets, is studied the impact of these swap facilities to the global banking system. It was found, that impact of swap lines were positive, but not because of announcement effect. Swap lines had positive impact only after an enormous increase in the volume of U.S. dollars in transactions. In other part of thesis is estimated revenue and expenses for the Fed. Revenues are campared with the data in the annual report. Revenues are estimated as a sum of all the interest payments in all banks, which dollars from the swap lines "spilled" into their jurisdictions. Costs are estimated as a opportunity costs.

A large part of the foreign exchange market concerns the trading of FX swaps. While entering a position in a FX swap does not cost any money, banks earn money on FX swaps when their customers cross the bid/ask spread, creating a perceived transaction costs for the swaps. To hedge the risks of their customer positions, banks enter new positions in FX swaps with other banks, crossing the same bid/ask spread. Traditional hedging methods does not take perceived transaction costs into account when determining hedge positions, resulting in greater portfolio losses than necessary for the banks. Therefore, the topic of hedging while taking transaction costs into account could be of great value. When valuing FX swaps and estimating risk factors in a FX environment, term structures need to be estimated for pricing the instruments. The estimation of term structures can be done using several ap- proaches, among them bootstrapping and interpolating the curve or parameterizing the curve, assuming it to be described by a functional form. These traditional methods of term structure measurement has the downside of being unstable and fluctuating greatly over time because of different local optimas each day, or result in very large pricing errors due to certain instruments needing to be excluded from the term structure measurement. These attributes result in capturing extra, unnecessary volatility in the curves which does not model the true risk, consequently estimating the risk factors wrongly when risk management and hedging needs to be done. The estimation of good quality term structures which are stable over time and result in low pricing errors are therefore of great interest to study. In this thesis, a FX swap portfolio is hedged using a Stochastic Programming (SP) model developed by Blomvall and Hagenbj ̈ork (2020). For the valuation of FX swaps in the portfolio and the generation of risk factors for the model, term structures were estimated using a multiple yield curve framework of Blomvall and Ndengo (2013), which penalizes pricing errors and use regularization functions to produce smooth curves. For both the term structure measurement method and the hedging method, a critical part affecting the per- formance of the methods lies in choosing good parameter values, which is what has been the main purpose of this study. The results show that good quality term structures can be estimated using the multiple yield curve frame- work if good parameter choices are made. The resulting curves fulfill the criteria of being stable over time while also keeping the price errors out-of-sample small. A portfolio hedged using a SP-model with certain chosen parameter values and also using the good quality term structures estimated is shown to eliminate a great deal of risk compared to an unhedged portfolio. When compared with a traditional hedging model called the Boxes model, the SP-model gains value from taking perceived transaction costs into account and thus manages to hedge the risks less costly than the Boxes model does.

The global foreign exchange (FX) market is one of the world's largest financial markets and a significant part of this market concerns the trading of FX swaps. For banks and other financial institutions, it is of great interest to model these swaps as accurately as possible, as this could improve their risk management. Numerous methods exist for modeling FX swaps, but it is not always clear if one model is superior to another. The purpose of this thesis is therefore to analyze, evaluate and compare different models that represent the stochastic processes in the FX swap market. To accomplish this, the thesis employs the reality model evaluation methodology developed by \citet{Blom_fx_pdf}. With this methodology, likelihood values for an out-of-sample period can be determined for a model, thereby enabling a statistical comparison to ascertain which model more accurately reflects the true distribution. This thesis will compare two models for FX swap prices: an interest rate model and a PIP-model. The PIP-model is constructed by determining a multivariate distribution based on in-sample observations of pips. The likelihood values for the out-of-sample observations can therefore be determined directly. The interest rate model, on the other hand, will be implemented using Blomvall's reality model evaluation in order to determine the likelihood values. It is constructed by evaluating risk factors of the FX swaps, rather than historical pips. The risk factors evaluated in this thesis are forward curves, the spot price and spikes in the supply and demand curve at certain dates. The results show that the interest rate model better represents the true distribution of FX swaps compared to the PIP-model. The statistical test of the out-of-sample likelihood values shows that the probability of the interest rate model outperforming the PIP-model is approximately 100 \%. Additionally, the result suggests that an implementation of the interest rate model using a Student's t-distribution is more advantageous than using a normal distribution, a conclusion also supported by a statistical test. Moreover, the effectiveness of Blomvall's reality model evaluation in determining likelihood values is confirmed, thus enabling the statistical comparison of different models.