Business cycles, the ups and downs observed somewhat simultaneously in numerous macroeconomic variables in an economy and often measured using real GDP, are important and, despite much economic research, still incom- pletely understood. Dating the business cycle has always been of interest in macroeconomic research. The dating might help to find the causes of a recession and this understanding could help to prevent or limit the duration of recessions in the future. A non-stationary, non-parametric smoothing- technique is proposed here to make business cycles simpler to analyse and interpret. The method is applied to the Euro area and to the Swedish econ- omy. For the Euro area the method finds two deeper and two milder reces- sions and one stagnation period since 1970. The dating is close to that of the CEPR. The same method is then used to date recessions in Sweden for the period 1969-2006. Four recessions were found. One research area of interest related to the dating of business cycles is forecasting of an upcoming recession. If an upcoming recession is detected, monetary policy could respond and avoid an output gap or a fall in inflation. We use a probit model to examine the in-sample performance of various financial variables as a predictor of Swedish recessions. The results show that the slope of the yield curve appears to perform better than other variables, but also that the spread is not a reliable indicator for detecting recessions in Sweden since there are many false warnings.