Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of many kind of high-dimensional data. It is used in signal process- ing, mechanical ingeneering, psychometrics, and other fields under different names. It still bears the same mathematical idea: the...

We consider a difference based ridge regression estimator and a Liu type estimator of the regression parameters in the partial linear semiparametric regression model, y = Xβ + f + ε. Both estimators are analysed and compared in the sense of mean-squared error. We consider the case of...

Due to dependency of energy demand on temperature, weather derivatives enable the effective hedging of temperature related fluctuations. However, temperature varies in space and time and therefore the contingent weather derivatives also vary. The spatial derivative price distribution involves a...

In this paper we adapt a dynamic discrete choice model to examine the aggregated demand for single- and multi-year crop insurance contracts. We show that in a competitive insurance market with heterogeneous risk averse farmers, there is simultaneous demand for both insurance contracts. Moreover,...

Many industries are exposed to weather risk which they can transfer on financial markets via weather derivatives. Equilibrium models based on partial market clearing became a useful tool for pricing such kind of financial instruments. In a multi-period equilibrium pricing model agents rebalance...

Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of many kind of high-dimensional data. It is used in signal processing, mechanical engineering, psychometrics, and other fields under different names. It still bears the same mathematical idea: the...

Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of high-dimensional data. However, in many applications such as risk quantification in finance or climatology, one is interested in capturing the tail variations rather than variation around the mean. In...

Weather derivatives are contingent claims with payo based on a pre-speci ed weather index. Firms exposed to weather risk can transfer it to nancial markets via weather derivatives. We develop a utility-based model for pricing baskets of weather derivatives in over-the-counter markets under...

Weather derivatives are contingent claims with payoff based on a pre-specified weather index. Firms exposed to weather risk can transfer it to financial markets via weather derivatives. We develop a utility-based model for pricing baskets of weather derivatives under default risk on the issuer...

Due to dependency of energy demand on temperature, weather derivatives enable the effective hedging of temperature related fluctuations. However, temperature varies in space and time and therefore the contingent weather derivatives also vary. The spatial derivative price distribution involves a...