This paper is concerned with the Bayesian analysis of stochastic volatility (SV) models with leverage. Specifically, the paper shows how the often used Kim et al. [1998. Stochastic volatility: likelihood inference and comparison with ARCH models. Review of Economic Studies 65, 361–393] method...

This paper assesses the roles of various factors influencing the volatility of crude oil prices and the possible linkage between this volatility and agricultural commodity markets. Stochastic volatility models are applied to weekly crude oil, corn and wheat futures prices from November 1998 to...

We quantify the effect of financial leverage on stock return volatility in a dynamic general equilibrium economy with debt and equity claims. The effect of financial leverage is studied both at a market and a firm level where the firm is exposed to both idiosyncratic and market risk. In a...

This paper investigates the weak form of market efficiency hypothesis over eleven Tunisian banks listed on the Tunisian Stock Exchange during the period July 2012 to June 2013. GARCH (1, 1) and its extension EGARCH (1,1) are developed in order to describe the sign and size of financial...

Incluye bibliografía ; In this paper we propose a model for monthly inflation with stochastic trend, seasonal and transitory components with QGARCH disturbances. This model distinguishes whether the long-run or short-run components are heteroscedastic. Furthermore, the uncertainty associated...

Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financial asset returns. While SV models have a number of theoretical advantages over competing variance modelling procedures they are notoriously difficult to estimate. The distinguishing feature of...

We consider the hedging of derivative securities when the price movement of the underlying asset can exhibit random jumps. Under a one factor Markovian setting, we derive a spanning relation between a long term option and a continuum of short term options. We then apply this spanning relation to...

State space alternative to autoregressive conditional heteroskedasticity models are proposed. The initial model, which is labelled the Gaussian local scale model, has a measurement density which is Gaussian, conditional on the unobservable precision. The precision is assumed to be a gamma...

This paper is concerned with simulation-based inference in generalized models of stochastic volatility defined by heavy-tailed Student-t distributions (with unknown degrees of freedom) and exogenous variables in the observation and volatility equations and a jump component in the observation...

This paper derives the exact distribution of the maximum likelihood estimator of a first-order linear autoregression with an exponential disturbance term. We also show that, even if the process is stationary, the estimator is T-consistent, where T is the sample size. In the unit root case, the...