This paper derives the asymptotic distribution of nonparametric neural network estimator of the Lyapunov exponent in a noisy system proposed by Nychka et al (1992) and others. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for...

This paper derives the asymptotic distribution of the nonparametric neural network estimator of the Lyapunov exponent in a noisy system. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for testing the chaotic hypothesis based on the...

Recent studies in the empirical finance literature have reported evidence of two types of asymmetries in the joint distribution of stock returns. The Þrst is skewness in the distribution of individual stock returns, while the second is an asymmetry in the dependence between stocks: stock...

This paper shows how and when it is possible to obtain a mapping from a quarterly DSGE model to amonthly specification thatmaintains the same economic restrictions and has real coefficients. We use this technique to derive the monthly counterpart of the Gali et al (2011) model. We then augment...

This paper presents new models for aggregate UK data on mortgage possessions (foreclosures) and mortgage arrears (payment delinquencies). The innovations include the treatment of difficult to observe variations in loan quality and shifts in forbearance policy by lenders, by common latent...

Housing and pension wealth are shown to be important determinants of personal sector consumption and retirement behaviour in the UK. Housing and state pension wealth have a positive effect on consumption, while private pension wealth promotes greater savings. Greater private defined benefit...

This paper presents a Markov chain Monte Carlo algorithm for a class of multivariate diffusion models with unobserved paths. This class is of high practical interest as it includes most diffusion driven stochastic volatility models. The algorithm is based on a data augmentation scheme where the...

We address the problem of parameter estimation for diffusion driven stochastic volatility models through Markov chain Monte Carlo (MCMC). To avoid degeneracy issues we introduce an innovative reparametrisation defined through transformations that operate on the time scale of the diffusion. A...

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted on the assumption of mean squared error loss under which forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast...