The Central Bank Inflation Bias in the Presence of Asymmetric Preferences and Non-Normal Shocks

We investigate the nature of the inflation bias in a model that exhibits asymmetries in preferences and non–normality in shocks but simplifies to the classic Barro-Gordon problem as a special case. The inflation bias is shown to depend on the trade-off between preference, structural and the scale and shape parameters of the model.

Co-volatility and correlation clustering : a multivariate correlated ARCH framework

We present a new, full multivariate framework for modelling the evolution of conditional correlation between financial asset returns. Our approach assumes that a vector of asset returns is shocked by a vector innovation process the covariance matrix of which is timedependent. We then employ an appropriate Cholesky decomposition of the asset covariance matrix which, when transformed using a Spherical decomposition allows for the modelling of conditional variances and correlations. The resulting asset covariance matrix is guaranteed to be positive definite at each point in time. We follow Christodoulakis and Satchell (2001) in designing conditionally autoregressive stochastic processes for the correlation coefficients and present analytical results for their distribution properties. Our approach allows for explicit out-of-sample forecasting of conditional correlations and generates a number of observed stylised facts such as time-varying correlations, persistence and correlation clustering, co-movement between correlation coefficients, correlation and volatility as well as between volatility processes (co-volatility). We also study analytically the co-movement between the elements of the asset covariance matrix which are shown to depend on their persistence parameters. We provide empirical evidence on a trivariate model using monthly data from Dow Jones Industrial, Nasdaq Composite and the 3-month US Treasury Bill yield which supports our theoretical arguments

Sharp style analysis in the MSCI sector portfolios: a Monte Carlo integration approach

We examine a decision-theoretic Bayesian framework for the estimation of Sharpe Style portfolio weights of the MSCI sector returns. Following van Dijk and Kloek (1980) an appropriately defined prior density of style weights can incorporate non-negativity and other constraints. We use factor-mimicking portfolios as proxies to global style factors such as Value, Growth, Debt and Size. Our computational approach is based on Monte Carlo Integration (MCI) of Kloek and van Dijk (1978) for the estimation of the posterior moments and distribution of portfolio weights. MCI provides a number of advantages, such as a flexible choice of prior distributions, improved numerical accuracy of the estimated parameters, the use of inequality restrictions in prior distributions and exact inference procedures. Our empirical findings suggest that, contrary to existing evidence, style factors do explain the MSCI sector portfolio returns for the particular sample period. Further, non-negativity constraints on portfolio weights were found to be binding in all cases

Labour Market Dynamics in Greek Regions: a Bayesian Markov Chain Approach Using Proportions Data

This paper focuses on Greek labour market dynamics at a regional base, which comprises of 16 provinces, as defined by NUTS levels 1 and 2 (Eurostat, 2008), using Markov Chains for proportions data for the first time in the literature. We apply a Bayesian approach, which employs a Monte Carlo Integration procedure that uncovers the entire empirical posterior distribution of transition probabilities from full employment to part employment, unemployment and economically unregistered unemployment and vice a versa. Our results show that there are disparities in the transition probabilities across regions, implying that the convergence of the Greek labour market at a regional base is far from being considered as completed. However, some common patterns are observed as regions in the south of the country exhibit similar transition probabilities between different states of the labour marketGreek Regions, Employment, Unemployment, Markov Chains

Exact Elliptical Distributions for Models of Conditionally Random Financial Volatility

Assuming the time series of random returns to be jointly elliptical, we derive a relationship between its conditional variance and the probability density function of the conditioning set. In the case that such a relationship is linear in a quadratic form for of the conditioning variables, we show that the probability density function of the conditioning variables is multivariate t. This result is then applied to models of conditionally random volatility and used to derive exact results for the GARCH(p,q) class of processes previously thought to be intractable.Elliptical Distributions, Financial Asset Returns, Conditional Volatility, GARCH

Return Attribution Analysis of the UK Insurance Portfolios

We examine the attribution of premium growth rates for the five main insurance sectors of the United Kingdom for the period 1969-2005; in particular, Property, Motor, Pecuniary, Health & Accident, and Liability. In each sector, the growth rates of aggregate insurance premiums are viewed as portfolio returns which we attribute to a number of factors such as realized and expected losses and expenses, their uncertainty and market power, using the Sharpe (1988, 1992) Style Analysis. Our estimation method differs from the standard least squares practice which does not provide confidence intervals for style betas and adopts a Bayesian approach, resulting in a robust estimate of the entire empirical distribution of each beta coefficients for the full sample. We also perform a rolling analysis of robust estimation for a window of seven overlapping samples. Our empirical findings show that there are some main differences across industries as far as the weights attributed to the underlying factors. Rolling regressions assist us to identify the variability of these weights over time, but also across industries

Macro economy, stock market and oil prices: Do meaningful relationships exist among their cyclical fluctuations?

This paper examines the relationship among consumer price index, industrial production, stock market and oil prices in Greece. Initially we use a unified statistical framework (cointegration and VECM) to study the data in levels. We then employ a multivariate VAR model to examine the relationship between the cyclical components of our series. The period of the study is from 1996:1 – 2008:6. Findings suggest that oil prices and the stock market exercise a positive effect on the Greek CPI, in the long run. Cyclical components analysis suggests that oil prices exercise significant negative influence to the stock market. In addition, oil prices are negatively influencing CPI, at a significant level. However, we find no effect of oil prices on industrial production and CPI. Finally, no relationship can be documented between the industrial production and stock market for the Greek market. The findings of this study are of a particular interest and importance to policy makers, financial managers, financial analysts and investors dealing with the Greek economy and the Greek stock market

Central Corneal Thickness in Patients With Neovascular Age-Related Macular Degeneration

Purpose: To compare the central corneal thickness (CCT) measurements of patients with neovascular age-related macular degeneration (AMD) and control subjects. Methods: The CCT value (measured with ultrasound corneal pachymetry) of 130 eyes (130 patients, 1 eye from each patient) with neovascular AMD (AMD group) and 98 eyes (98 patients, 1 eye from each patient) of similar age, sex, and eye's axial length healthy control subjects (normal group) was compared. Results: The mean age (AMD group: 69.1 years vs. control group: 69.5 years, P = 0.81), sex (AMD group: 77 women, 59% vs. control group: 59 women, 60%, P = 0.77), and eye's axial length (AMD group: 25.05-mm vs. control group: 24.61-mm, P = 0.38) of patients with neovascular AMD and healthy control subjects were comparable. There were no statistically significant differences in the mean CCT measurements in the neovascular AMD group in comparison with the control group (549.44 vs. 544.35 mm, P = 0.11). Conclusions: CCT measurements do not differ in patients with neovascular AMD compared with healthy control subjects