We estimate new indices measuring financial and economic (in)stability in Austria and in the euro area. Instead of estimating the level of (in)stability in a financial or economic system we measure the degree of predictability of (in)stability, where our methodological approach is based on the...

This paper investigates the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis. Using a broad sample of stock options traded at the American Stock Exchange and the Chicago Board Options Exchange (CBOE)...

Commodity prices co-move, but the strength of this co-movement changes over time due to structural factors, like changing energy intensity in production and consumption as well as changing composition of underlying shocks. This paper explores whether econometric models that exploit this...

In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even...

A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the jump component is persistent when forecasting the oil...

In the past decade, the popularity of realized measures and various linear models for volatility forecasting has attracted attention in the literature on the price variability of energy markets. However, results that would guide practitioners to a specific estimator and model when aiming for the...

We propose exible models for multivariate realized volatility dynamics which involve generalizations of the Box-Cox transform to the matrix case. The matrix Box-Cox model of realized covariances (MBC-RCov) is based on transformations of the covariance matrix eigenvalues, while for the Box-Cox...

We propose a dilution bias correction approach to deal with the errors-in-variables problem observed in realized volatility (RV) measures. The absolute difference between daily and monthly RV is shown to be proportional to the relative magnitude of the measurement error. Therefore, in...

Volatility forecasting has paramount importance in position sizing and risk management of CTAs. In this paper we examine the out-of-sample forecasts of widely used volatility estimators for the S&P 500 and the 10-Year US Note from a statistical and Value-at-Risk perspective. Although we do not...