The 2006 sudden and immense downturn in U.S. House Prices sparked the 2007 global financial crisis and revived the interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting methodology that combines the Ensemble Empirical Mode...

In this paper, we review the extant mathematical and environmental economics literatures on the stochastic properties of CO2 emission allowance futures prices. We explain the main findings arising from this literature from both continuous- and jump-diffusion models. Based on the Activity...

This paper proposes a new empirical methodology for computing a cross-market volatility index – coined CMIX – based on the Factor DCC-model, implemented on volatility surprises. This approach solves both problems of treating high-dimensional data and estimating time-varying conditional...

"This paper investigates the time-varying relationship between German output and employment growth, in particular their decoupling in recent years. We estimate a correlated unobserved components model that allows for both persistent and cyclical time variation in the employment impact of GDP as...

Forecasting aggregate retail sales may improve portfolio investors’ ability to predict movements in the stock prices of the retailing chains. Therefore, this paper uses 26 (23 single and 3 combination) forecasting models to forecast South Africa’s aggregate seasonal retail sales. We use data...

This paper examines the causal relationships between the real house price index and real GDP per capita in the U.S., using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use quarterly time-series data on the real house price index and...

The choice and estimation of joint probability distribution function are key steps in portfolio optimization problem. As such distribution functions pair-copula constructions (PCC), or vine-copulae, on arbitrary R-vines are used. For the investor with exponential utility criterion the NYSE oil...

We propose a residual-based augmented Dickey-Fuller (ADF) test statistic that allows for detection of stationary cointegration within a system that may contain both I (2) and I (1) observables. The test is also consistent under the alternative of multicointegration, where first differences of...

We propose a new approach to predictive density modeling that allows for MI- DAS e¤ects in both the ?rst and second moments of the outcome and develop Gibbs sampling methods for Bayesian estimation in the presence of stochastic volatility dy- namics. When applied to quarterly U.S. GDP growth...

Our proposed local vector autoregressive (LVAR) model has time-varying parameters that allow it to be safely used in both stationary and non-stationary situations. The estimation is conducted over an interval of local homogeneity where the parameters are approximately constant. The local...