Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility. Employing German DAX-index retu...

In Markov-switching regression models, we use Kullback–Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. Specifically, we derive a new information criterion, Markov switching criterion (MSC), which is an estimate of KL divergence. MSC imposes an appropriate penalty to mitigate the overretention of states in the Markov chai...

In this paper Efficient Importance Sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as we...

This paper presents a novel characterization of continuous time processes that captures the primary idiosyncratic features of many financial time series. We extend the analysis of unit root behaviors to incorporate series that have continuous sampling, but do so in such a way that the overall series does not tend towards explosive paths, as is implied by many unit root setups. In doing so, we e...

The outcome of popular unit root tests depends heavily on the initial condition, i.e. on the difference between the initial observation and the deterministic component. In some applications it is difficult to rule out small or large values of the initial condition a priori, so this dependence can be quite difficult to deal with in practice. We explore a number of methods for constructing unit r...

Disputes about econometric methodology partly reflect a lack of evidence on alternative approaches. We reconsider econometric model selection from a computer-automation perspective, focusing on general-to-specific reductions, embodied in PcGets. Starting from a general congruent model, standard testing procedures eliminate statistically-insignificant variables, with diagnostic tests checking th...

We study the returns to investing in VIX futures and VIX Exchange Traded Notes (ETNs). We document a substantial negative return premium for both ETNs and the futures. For example, the a constant maturity portfolio of one-month VIX futures loses about 30% per year over our sample period (2006-2013). We propose an equilibrium model to explain these negative returns. In this model, increases in v...

A trivariate vector autoregression time series process, based on a present-value land price model, is used to decompose Iowa farmland prices into fundamental and non-fundamental components. A recent study, by Falk and Lee (1998), found that non-fundamental shocks are an important source of volatility in farmland prices and it was interpreted that these price movements were due to fads not specu...

This paper investigates whether the degree of predictability can be explained by existing asset pricing models, and provides two theoretical upper bounds on the R-square of the regression of stock returns on predictors for given classes of models of interest. Empirically, we find that the predictive R-square is significantly larger than the upper bounds permitted by well known asset pricing mod...

This paper analyses revisions of Swiss current account data, taking into account the actual data revision process and the implied types of revisions. In addition we investigate whether the first release of current account data can be improved upon by the use of survey results as gathered by the KOF Swiss Economic Institute, ETH Zurich. An answer in the affirmative indicates that it is possible ...