This paper investigates the response of US stock market uncertainty to monetary policy of the Federal Reserve Bank. It can be shown that monetary policy signifi cantly Granger-causes stock market confi dence. By using monthly closing prices of the V IX as a stock market uncertainty proxy and a copula-based Markov approach the stable nonlinear relation between confi dence and uncertainty is demo...

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...

Enders and Granger provide critical values to test the null hypothesis of a unit-root against the alternative of threshold adjustment. However, in obtaining their critical values, Enders and Granger did not use a consistent estimate of the threshold nor did they use a lag-augmented data generating process. This note remedies both of these problems. The power of the test statistics using the con...

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...

The present paper thoroughly explores second-best efficient allocations in an adverse selection insurance economy. We start from a natural extension of the classical model, assuming less than perfect risk perceptions. We propose first and second welfare theorems, by means of which we describe efficiencyenhancing policies. Notions of weak and strong adverse selection are promising for interpreti...