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This paper investigates the drivers of cross-currency basis spreads, which were historically close to zero but have widened significantly since the start of the financial crisis. Credit and liquidity risk, as well as supply and demand have often been cited as general factors driving cross-currency basis spreads, however, these spreads may widen beyond what is normally explained by such variables. We suggest market proxies for EUR/USD basis swap spread drivers and build a multiple regression and cointegration model to explain their significance during three different historical periods of basis widening. The most important drivers of the cross-currency basis spreads appear to be short- and medium-term EU financial sector credit risk indicators, and to a slightly lesser extent, short- and medium-term US financial sector credit risk indicators. Another important driver is market volatility for the short-end basis spread, and the EUR/USD exchange rate for the medium term basis spread, and to a lesser extent, the Fed/ECB balance sheet ratio.
Cointegrated Time Series Models, Diploma thesis, MFF UK. The thesis deals with the concept of cointegration which represents appropriate tool in the analysis of nonstationary processes. Thesis concentrates on the models which are commonly used in the cointegration analysis of the time series. It describes straight connection between error-correction (EC) model and autoregressive distributed lags model (ADL). Theoretical results are applied on real data in demand for money model.