It is widely known that conditional covariances of asset returns change over time. Researchers doing empirical work have adopted many strategies for accommodatingcon-ditional heteroskedasticity. Among the popular strategies are: (a) chopping the available data into short blocks of time and assuming homoskedasticity within the blocks, (b) performing one-sided rolling regressions, in which only d...

We study the validity of Zipf’s Law in a data set of Chinese city sizes. Previous investigations are restricted to log-log rank-size regression for a fixed sample. In contrast, we use rolling sample regression methods in which the sample is changing with the truncation point. The intuition is that if the distribution is Pareto with a coefficient one (Zipf’s law holds), rolling sample regression...

Structural change is a major source of forecast failure. Immediately after a break, forecasting problems are particularly severe due to a lack of information about the new data generation process. Techniques exist for monitoring for structural change in real time, but the optimal post-break strategy is unexplored. We consider two approaches. First, monitoring for change and then combining forec...

This paper has provided "out of sample" evidence of stock returns predictability in Tehran Stock Exchange. 68 qualified companies over the period from 2002 to 2015 were selected and for five different "forms of returns", five superior predictive models have been designed by applying "General to specific" approach of modeling technique. Then "out of sample" analysis, based on rolling regressions...

We examine how to forecast after a recent break. We consider monitoring for change and then combining forecasts from models that do and do not use data before the change; and robust methods, namely rolling regressions, forecast averaging over different windows and exponentially weighted moving average (EWMA) forecasting. We derive analytical results for the performance of the robust methods rel...

This paper investigates the relationship between electricity demand and temperature in the European Union. We address this issue by means of a panel threshold regression model on 15 European countries over the last two decades. Our results confirm the non linearity of the link between electricity consumption and temperature found in more limited geographical areas in previous studies. By distin...

Two regression methods can be interpreted as based on Gini's mean difference (GMD). One relies on a weighted average of slopes defined between adjacent observations and the other is based on minimization of the GMD of the errors. The properties of the former approach are investigated in a multiple regression framework. These estimators have representations that resemble the OLS estimators, and ...