This paper aims to enrich the understanding and modelling strategies for cryptocurrency markets by investigating major cryptocurrencies´ returns determinants and forecast their returns. To handle model uncertainty when modelling cryptocurrencies, we conduct model selection for an autoregressive...

The accuracy of variance prediction depends on both the specification and the accuracy of parameter estimation. To predict stock return variance in a large and ever-changing universe, this paper proposes to replace the classic time-series dynamics specification per each name with a...

In this paper, we make multi-step forecasts of the annual growth rates of the real GRP for each of the 31 Chinese provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly account for spatial dependence between the GRP growth rates. In addition, the...

This paper analyzes the role played by financial assets, direct real estate, and the Fama and French factors in explaining EREIT returns and examines the usefulness of these variables in forecasting returns. Four models are analyzed and their predictive potential is assessed by comparing three...

We analyze the impacts of alternative submarket definitions when predicting house prices in a mass appraisal context, using both ordinary least squares (OLS) and geostatistical techniques. For this purpose, we use over 13,000 housing transactions for Louisville, Kentucky. We use districts...

In this paper, we make multi-step forecasts of the monthly growth rates of the prices and rents for flats in 26 largest German cities. Given the small time dimension, the forecasts are done in a panel-data format. In addition, we use panel models that account for spatial dependence between the...

Because of heterogeneity across regions, economic policy measures are increasingly targeted at the regional level. As a result, the need for economic forecasts at a sub-national level is rapidly increasing. The data available to compute regional forecasts is usually based on a pseudo-panel that...

In this paper, we evaluate the forecasting ability of 115 indicators to predict the housing prices and rents in 71 German cities. Above all, we are interested in whether the local business confidence indicators can allow substantially improving the forecasts, given the local nature of the...

In this paper, we evaluate the forecasting ability of 145 indicators and ten types of forecast combination schemes to predict housing prices and rents in 71 German cities. We are interested in whether local business confidence indicators facilitate substantial improvements of the forecasts,...

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle...