The main objective of the paper is to test whether post-earnings announcement drift (PEAD) is a consequence of the presence of self-attribution bias in investors’ expectations, regarding permanent earnings. This is the first study to examine empirically this issue, in the sample of Athens...

Implied volatility index of the S&P500 is considered as a dependent variable in a fractionally integrated ARMA model, whereas volatility measures based on interday and intraday datasets are considered as explanatory variables. The next trading day’s implied volatility forecasts provide...

Autoregressive Conditional Heteroscedasticity (ARCH) models have successfully been applied in order to predict asset return volatility. Predicting volatility is of great importance in pricing financial derivatives, selecting portfolios, measuring and managing investment risk more accurately. In...

In statistical modeling contexts, the use of one-step-ahead prediction errors for testing hypotheses on the forecasting ability of an assumed model has been widely considered (see, e.g. Xekalaki et al. (2003, in Stochastic Musings, J.Panaretos (ed.), Laurence Erlbaum), Degiannakis and Xekalaki...

A number of ARCH models are considered in the framework of evaluating the performance of a method for model selection based on a standardized prediction error criterion (SPEC). According to this method, the ARCH model with the lowest sum of squared standardized forecasting errors is selected for...

In statistical modelling contexts, the use of one-step-ahead prediction errors for testing hypotheses on the forecasting ability of an assumed model has been widely considered. Quite often, the testing procedure requires independence in a sequence of recursive standardized prediction errors,...

The EC Directive on financial instruments markets 2004 (MiFID) has introduced a number of order and trade publication obligations imposed on organised exchanges, alternative trading systems (ATS), and the class of broker dealers that execute transactions in shares internally. This article...

In statistical modeling contexts, the use of one-step-ahead prediction errors for testing hypotheses on the forecasting ability of an assumed model has been widely considered (see, e.g., Xekalaki et al. (2003, in Stochastic Musings, J.Panaretos (ed.), Laurence Erlbaum), Degiannakis and Xekalaki...

We evaluate the economic usefulness of oil price forecasts by means of conditional forecasting of five US macroeconomic indicators. First, we forecast oil prices using a mixed sampling frequency framework, where oil prices are driven by information available at high-frequency; and subsequently...