We show the statistical properties of the most important cryptocurrencies, of which Bitcoin is the most prominent example. We characterize their exchange rates versus the US Dollar by fitting parametric distributions to them. It is shown that returns are clearly non-normal, with standard...

In a broad class of sticky price models the non-neutrality of nominal shocks is encoded by a simple sufficient statistic: the ratio of the kurtosis of the size-distribution of price changes over the frequency of price changes. We test this theoretical prediction using data for a large number of...

We construct new indicators of the imbalance between demand and supply for the Canadian economy by using natural language processing techniques to analyze earnings calls of publicly listed firms. The results show that the text-based indicators are highly correlated with official inflation data...

The preparations for the introduction of the euro in 1999 involved the need for a new set of statistics for the euro area. Since then, significant progress has been made with regard to the coverage, timeliness and accuracy of these statistics. The reliability of the first releases - i.e. their...

The preparations for the introduction of the euro in 1999 involved the need for a new set of statistics for the euro area. Since then, significant progress has been made with regard to the coverage, timeliness and accuracy of these statistics. The reliability of the first releases - i.e. their...

Mostly used estimators of Hurst exponent for detection of long-range dependence are biased by presence of short-range dependence in the underlying time series. We present confidence intervals estimates for rescaled range and modified rescaled range. We show that the difference in expected values...

In this paper, we empirically assess the predictive accuracy of a large group of models based on the use of principle components and other shrinkage methods, including Bayesian model averaging and various bagging, boosting, LASSO and related methods Our results suggest that model averaging does...

We provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous-time jump diffusion models traditionally used in asset pricing finance. Our approach builds directly on recently developed realized variation measures...

The aim of this paper is to derive the main factors that separate cryptocurrencies from the classical assets, by using various classification techniques applied to the daily time series of log-returns. In this sense, a daily time series of asset returns (either cryptocurrencies or classical...