A new innovations state space modeling framework, incorporating Box-Cox transformations, Fourier series with time varying coefficients and ARMA error correction, is introduced for forecasting complex seasonal time series that cannot be handled using existing forecasting models. Such complex time...

This paper aims to develop new methods for statistical inference in a class of stochastic volatility models for financial data based on non-Gaussian Ornstein-Uhlenbeck (OU) processes. Our approach uses indirect inference methods: First, a quasi-likelihood for the actual data is estimated. This...

The main goal of this paper is to examine the relationship between macroeconomic shocks and yield curve movements in Hungary. To this end, we apply a Nelson-Siegel type dynamic yield curve model, where changes of the yield curve are driven by two latent factors and some key macro variables that...

A univariate first order stochastic cycle can be represented as an element of a bivariate first order vector autoregressive process, or VAR(1), where the transition matrix is associated with a Givens rotation. From the geometrical viewpoint, the kernel of the cyclical dynamics is described by a...

A key ingredient of many particle filters is the use of the sampling importance resampling algorithm (SIR), which transforms a sample of weighted draws from a prior distribution into equally weighted draws from a posterior distribution.  We give a novel analysis of the SIR algorithm and analyse...

This paper shows how to estimate forecast uncertainty about future short-term interest rates by combining a time-varying Taylor rule with an unobserved components model of economic fundamentals. Using this model I separate interest rate uncertainty into economically meaningful components that...

In this paper we use a state-space model with Markov-switching to detect speculative bubbles in stock-price data. Our two innovations are (1) to adapt this technology to the state-space representation of a well-known present-value stock-price model, and (2) to estimate the model via...

A new version of the local scale model of Shephard (1994) is presented. Its features are identically distributed evolution equation disturbances, the incorporation of in-the-mean effects, and the incorporation of variance regressors. A Bayesian posterior simulator and an exact simulation...

The main goal of this paper is to examine the relationship between macroeconomic shocks and yield curve movements in Hungary. To this end, we apply a Nelson-Siegel type dynamic yield curve model, where changes of the yield curve are driven by two latent factors and some key macro variables that...

In this paper, we formulate a statistical model of inflation that combines data on survey expectations and the inflation target set by central banks.. Our model produces inflation forecasts that are aligned with survey expectations, thereby integrating the predictive power of the survey...