Showing 1 - 10 of 48
as well as the nature of the volatility spillovers among the US, EU and the BRIC markets has not been systematically …. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects, although tail …
Persistent link: https://www.econbiz.de/10010656018
This paper investigates whether risks associated with time-varying arrival of jumps and their effect on the dynamics of higher moments of returns are priced in the conditional mean of daily market excess returns. We find that jumps and jump dynamics are significantly related to the market equity...
Persistent link: https://www.econbiz.de/10010555039
In this paper we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated … with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically …. Its novelty is in modeling the joint, conditional, return-volatility, distribution with a infinite mixture of bivariate …
Persistent link: https://www.econbiz.de/10010555040
This paper proposes a Bayesian nonparametric modeling approach for the return distribution in multivariate GARCH models. In contrast to the parametric literature the return distribution can display general forms of asymmetry and thick tails. An infinite mixture of multivariate normals is given a...
Persistent link: https://www.econbiz.de/10010556310
We propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the...
Persistent link: https://www.econbiz.de/10011147371
In this paper we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive … models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman … filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the …
Persistent link: https://www.econbiz.de/10010540685
We develop methods for Bayesian inference in vector error correction models which are subject to a variety of switches in regime (e.g. Markov switches in regime or structural breaks). An important aspect of our approach is that we allow both the cointegrating vectors and the number of...
Persistent link: https://www.econbiz.de/10009320949
The Hodrick-Prescott (HP) method is a popular smoothing method for economic time series to get a smooth or long-term component of stationary series like growth rates. We show that the HP smoother can be viewed as a Bayesian linear model with a strong prior using differencing matrices for the...
Persistent link: https://www.econbiz.de/10009364166
The Hodrick-Prescott (HP) method is a popular smoothing method for economic time series to get a longterm component of stationary series like growth rates. The new extended HP smoothing model is applied to data-sets with an underlying metric and requires a Bayesian linear regression model with a...
Persistent link: https://www.econbiz.de/10009364167
by proposing an exponential weighted moving average model that jointly estimates volatility, skewness and kurtosis over … in the estimation of 1-day and 10-day VaR forecasts is performed in comparison with the historical simulation, filtered …
Persistent link: https://www.econbiz.de/10010551735