The aim of this paper is to forecast (out-of-sample) the distribution of financial returns based on realized volatility measures constructed from high-frequency returns. We adopt a semi-parametric model for the distribution by assuming that the return quantiles depend on the realized measures...

We proposed a method to estimate extreme conditional quantiles by combining quantile GARCH model of Xiao and Koenker (2009) and extreme value theory (EVT) approach. We first estimate the latent volatility process using the information of intermediate quantiles. We then apply EVT to the tail...

Time series data are widely used to explore causal relationships, typically in a regression framework with lagged dependent variables. Regression-based causality tests rely on an array of functional form and distributional assumptions for valid causal inference. This paper develops a...

We provide a nontechnical review of recent nonparametric methods for estimating density and regression functions. The methods we describe make it possible for a researcher to estimate a regression function or density without having to specify in advance a particular--and hence potentially...

The nonlinear modelization has experimented a great resurgence of the hand of Chaos Theory, which shown the possibility of obtaining complex behaviors produced endogenously by the dynamics of the model, without the necessity to include exogenous random shocks. On the other hand, the importance...

The main objective of this paper is to assess how mutual information as a measure of global dependence between stock markets and macroeconomic factors can overcome some of the weaknesses of the traditional linear approaches commonly used in this context. One of the advantages of mutual...

In this paper we compare the unemployment dynamics of the US and Germany with monthly data up to 2008. With data from 1971 on the evidence is mixed when applying descriptive methods or formal unit root tests. When allowing for fractional integration, however, we find similar results to the...

This paper describes a simple yet powerful methodology to decompose asset returns sampled at high frequency into their base components (continuous, small jumps, large jumps), determine the relative magnitude of the components, and analyze the finer characteristics of these components such as the...

Stochastic variance models where the logarithmic volatility is modelled by an ARMA process and models with conditional heteroscedasticity for daily returns are studied. Volatility of monthly relative changes computed as a product of daily changes is considered and estimated from daily...

The purpose of this paper is to investigate whether shocks to out- put and employment had permanent or transitory effects during the period from 1961 to 1990 in the Federal Republic of Germany. There are a lot of parametric and non-parametric approaches which can be used for data generating...