• A New Monthly Indicator of Global Real Economic Activity 

      Ravazzolo, Francesco; Vespignani, Joaquin L. (CAMP Working Papers Series;2/2015, Working paper, 2015)
      In modelling macroeconomic time series, often a monthly indicator of global real economic activity is used. We propose a new indicator, named World steel production, and compare it to other existing indicators, precisely ...
    • Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration 

      Gianfreda, Angelica; Ravazzolo, Francesco; Rossini, Luca (CAMP Working Paper Series;2, Working paper, 2018-01)
      This paper compares alternative univariate versus multivariate models, probabilistic versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, with and without ...
    • Does forecast combination improve Norges Bank inflation forecasts? 

      Bjørnland, Hilde C.; Gerdrup, Karsten; Jore, Anne Sofie; Smith, Christie; Thorsrud, Leif Anders (CAMAR Working Paper Series;2/2010, Working paper, 2010)
      We develop a system that provides model-based forecasts for inflation in Norway. We recursively evaluate quasi out-of-sample forecasts from a large suite of models from 1999 to 2009. The performance of the models are then ...
    • Forecasting Cryptocurrencies Financial Time Series 

      Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco (CAMP Working Paper Series;5, Working paper, 2018-03)
      This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, ...
    • Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach 

      Ferrari, Davide; Ravazzolo, Francesco; Vespignani, Joaquin (CAMP Working Paper Series;11/2019, Working paper, 2019-12)
      This paper focuses on forecasting quarterly energy prices of commodities, such as oil, gas and coal, using the Global VAR dataset proposed by Mohaddes and Raissi (2018). This dataset includes a number of potentially ...
    • Large Time-Varying Volatility Models for Electricity Prices 

      Gianfreda, Angelica; Ravazzolo, Francesco; Rossini, Luca (CAMP Working Paper Series;05/2020, Working paper, 2020-07-02)
      We study the importance of time-varying volatility in modelling hourly electricity prices when fundamental drivers are included in the estimation. This allows us to contribute to the literature of large Bayesian VARs by ...
    • News media vs. FRED-MD for macroeconomic forecasting 

      Ellingsen, Jon; Larsen, Vegard H.; Thorsrud, Leif Anders (CAMP Working Paper Series;08/2020, Working paper, 2020-10-08)
      Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer ...
    • Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts 

      Krüger, Fabian; Clark, Todd E.; Ravazzolo, Francesco (CAMP Working Paper Series;8/2015, Working paper, 2015)
      This paper shows entropic tilting to be a flexible and powerful tool for combining mediumterm forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting ...