This paper proposes a novel approach to the combination of conditional covariance matrix forecasts based on the use of the Generalized Method of Moments (GMM). It is shown how the procedure can be generalized to deal with large dimensional systems by means of a two-step strategy. The finite...

Population forecasts are crucial for many social, political and economic decisions. Officialpopulation projections rely in general on deterministic models which use different scenariosfor future vital rates to indicate uncertainty. However, this technique shows substantialweak points such as...

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 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...

This paper proposes a novel approach to the combination of conditional covariancematrix forecasts based on the use of the Generalized Method of Moments (GMM). Itis shown how the procedure can be generalized to deal with large dimensional systemsby means of a two-step strategy. The finite sample...

GARCH models are widely used in financial econometrics. However, we show by mean of a simple simulation example that the GARCH approach may lead to a serious model misspecification if the assumption of stationarity is violated. In particular, the well known integrated GARCH effect can be...

We propose a local adaptive multiplicative error model (MEM) accommodating time-varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

In the ideal Black-Scholes world, financial time series are assumed 1) stationary (time homogeneous) and 2) having conditionally normal distribution given the past. These two assumptions have been widely-used in many methods such as the RiskMetrics, one risk management method considered as...

According to housing investment models, house prices and replacement cost should have an equilibrating relationship. Previous empirical work - mainly based on aggregate-level data - has found only little evidence of such a relationship. By using a unique data set, covering transactions of...

GARCH models are widely used in financial econometrics. However, we show by mean of a simple simulation example that the GARCH approach may lead to a serious model misspecification if the assumption of stationarity is violated. In particular, the well known integrated GARCH effect can be...