A new type of momentum based on the signs of past returns is introduced. This momentum is driven primarily by sign dependence, which is positively related to average return and negatively related to return volatility. An empirical application using a universe of commodity and financial futures...

We consider the issue of Block Bootstrap methods in processes that exhibit strong dependence. The main difficulty is to transform the series in such way that implementation of these techniques can provide an accurate approximation to the true distribution of the test statistic under...

A two-stage forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step, we perform the multi-step ahead forecasts...

The cyclical properties of the annual growth of the Baltic Dry Index (BDI) and their implications for short-to-medium term forecasting performance are investigated. We show that the BDI has a cyclical pattern which has been stable except for a period after the 2007 crisis. This pattern has...

This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area economies. The results indicate that the Automatic Leading...

We propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the...

We propose a novel way to assess information processing in a complex environment of market fragmentation. We take a different angle from the price discovery literature, and investigate information processing in the stochastic process driving stock's volatility (volatility discovery). We show...

A reversal pattern in the time series context from 12 to 24 months after the formation of trend following signals is observed in a universe of 55 liquid futures instruments. We find that instruments with sell signals in the trend following portfolio (i.e. "losers") contribute to this type of...

A two step forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step, we perform the multi-step ahead forecasts for...

This paper aims at providing a primer on the use of big data in macroeconomic nowcasting and early estimation. We discuss: (i) a typology of big data characteristics relevant for macroeconomic nowcasting and early estimates, (ii) methods for features extraction from unstructured big data to...