Intraday data of 26 German stocks are used to investigate whether the information contained in trading volume and number of trades as well as in various specifications of overnight returns can improve one-step-ahead volatility forecasts. For this purpose, a HAR model of the realized range...

The purpose of this study is to analyze the interrelationships among the Taiwanese, Japanese and Korean TFT-LCD panel industry stock market indexes by applying a trivariate FIEC-FIGARCH model. The empirical results confirm that the FIEC-FIGARCH model can be used to capture long memory behavior...

Many previous analyses of inflation have used either long memory or nonlinear time series models. This paper suggests a simple adaptive modification of the basic ARFIMA model, which uses a flexible Fourier form to allow for a time varying intercept. Simulation evidence suggests that the model...

This study investigates the relationship between U.S. state housing prices and overall U.S. housing prices as well as the relationship among state housing prices using fractional integration and cointegration techniques. The results based on parametric and semiparametric estimators reveal that...

The study provides evidence in favor of the price range as a proxy estimator of volatility in financial time series, in the cases that either intra-day datasets are unavailable or they are available at a low sampling frequency.

This paper examines the dynamics of volatility transmission between EU emission allowances (EUA) and oil markets using a range-based volatility measure. We propose a multivariate conditional autoregressive range model with bivariate lognormal distribution to capture volatility dynamics and...

We employ a large dataset of physical inventory data on 21 different commodities for the period 1993–2011 to empirically analyze the behavior of commodity prices and their volatility as predicted by the theory of storage. We examine two main issues. First, we analyze the relationship between...

In order to shed new light on the influence of volume and economic fundamentals on the long-run volatility of the Chinese stock market we follow the methodology introduced by Engle et al. (2009) and Engle and Rangel (2008) to account for the effects of macro fundamentals, and augment it with...

We examine both in-sample and out-of-sample predictability of South African stock return using macroeconomic variables. We base our analysis on a predictive regression framework, using monthly data covering the in-sample period between 1990:01 and 1996:12, and the out-of sample period commencing...

This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both in-sample and out-of-sample tests applied to daily returns of the Johannesburg Stock Exchange (JSE) All Share Index from 07/02/1995 to 08/25/2010. We find evidence of structural...