In this work, we make use of the shifting-mean autoregressive model which is a flexible univariate nonstationary model. It is suitable for describing characteristic features in inflation series as well as for medium-term forecasting. With this model we decompose the inflation process into a...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

Recent research has focused on modelling asset prices by Itô semimartingales. In such a modelling framework, the quadratic variation consists of a continuous and a jump component. This paper is about inference on the jump part of the quadratic variation, which can be estimated by the difference...

This paper presents some limit theorems for certain functionals of moving averages of semimartingales plus noise, which are observed at high frequency. Our method generalizes the pre-averaging approach (see [13],[11]) and provides consistent estimates for various characteristics of general...

This paper studies the effect of time–inhomogeneous jumps and leverage type effects on realised variance calculations when the logarithmic asset price is given by a Lévy–driven stochastic volatility model. In such a model, the realised variance is an inconsistent estimator of the integrated...

We consider a new class of estimators for volatility functionals in the setting of frequently observed Itô diffusions which are disturbed by i.i.d. noise. These statistics extend the approach of pre-averaging as a general method for the estimation of the integrated volatility in the presence of...

In this paper we extend the CKLS one factor short rate model to include extreme value nonlinear mean reversion. Similarly to a recent stock market study, we include the smallest short rate during the previous year in the mean equation. We investigate the US and five other major markets (Canada,...

Forecasting using factor models based on large data sets have received ample attention due to the models’ ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly...

We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...

Low birthweight outcomes are associated with large social and economic costs, and therefore the possible determinants of low birthweight are of great interest. One such determinant which has received considerable attention is maternal smoking. From an economic perspective this is in part due to...