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 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.

In this paper, we propose a new semiparametric method for GARCH model by combining the EGARCH (1,1) model and local polynomial regression. Based on the idea of two-stage estimate, a link function is estimated by the local polynomial and then the parameters are obtained via the weighted least...

This paper explores whether American Depositary Receipts (ADRs) affect the underlying local index (LD) for Japanese market, and such a phenomenon is considered as an adverse influence. Nonlinear Granger causality and Bayesian factor analysis are employed to investigate the nonlinear relationship...

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...

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...

In this paper, we evaluate the role of using consumer price index (CPI) disaggregated data to improve the accuracy of inflation forecasts. Our forecasting approach is based on extracting the factors from the subcomponents of the CPI at the highest degree of disaggregation. The data set contains...

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the...

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...

An increasing amount of empirical evidence suggests that patients with higher socioeconomic status wait less within publicly-funded hospitals to receive non-emergency (elective) surgery. Using data from Australia, we investigate the extent to which such gradient can be explained by sample...