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 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 paper proposes a data driven adaptive model selection strategy. The selection crite- rion measures economic exante forecasting content by means of trading implied cash flows. Empirical evidence suggests that the proposed strategy is neither exposed to selection bias nor to the risk of...

Weather influences our daily lives and choices and has an enormous impact on cooperate revenues and earnings. Weather derivatives differ from most derivatives in that the underlying weather cannot be traded and their market is relatively illiquid. The weather derivative market is therefore...

Weather derivatives (WD) are different from most financial derivatives because the underlying weather cannot be traded and therefore cannot be replicated by other financial instruments. The market price of risk (MPR) is an important parameter of the associated equivalent martingale measures used...

Forecasting based pricing of Weather Derivatives (WDs) is a new approach in valuation of contingent claims on nontradable underlyings. Standard techniques are based on historical weather data. Forward-looking information such as meteorological forecasts or the implied market price of risk (MPR)...

Recently the topic of global warming has become very popular. The literature has concentrated its attention on the evidence of such effect, either by detecting regime shifts or change points in time series. The majority of these methods are designed to find shifts in mean, but only few can do...

Electricity load forecasts are an integral part of many decision-making processes in the electricity market. However, most literature on electricity load forecasting concentrates on deterministic forecasts, neglecting possibly important information about uncertainty. A more complete picture of...

We analyze a consistent two-factor model for pricing temperature derivatives that incorporates the forward looking information available in the market by specifying a model for the dynamics of the complete meteorological forecast curve. The two-factor model is a generalization of the...

In this paper we investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact...