Weather inuences our daily lives and choices and has an enormous impact on corporate revenues andearnings. Weather derivatives dier from most derivatives in that the underlying weather cannot be tradedand their market is relatively illiquid. The weather derivative market is therefore incomplete....

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

The study of natural catastrophe models plays an important role in the prevention and mitigation of disasters. After the occurrence of a natural disaster, the reconstruction can be financed with catastrophe bonds (CAT bonds) or reinsurance. This paper examines the calibration of a real...

In this study we forecast the term structure of FIBOR/EURIBOR swap rates by means of recursive vector autoregressive (VAR) models. In advance, a principal components analysis (PCA) is adopted to reduce the dimensionality of the term structure. To evaluate ex–ante forecasting performance for...

The paper proposes a data driven adaptive model selection strategy. The selection criterionmeasures economic ex-ante forecasting content by means of trading implied cash flows.Empirical evidence suggests that the proposed strategy is neither exposed to selection biasnor to the risk of choosing...