• A New Economic Framework: A DSGE Model with Cryptocurrency 

      Asimakopoulos, Stylianos; Lorusso, Marco; Ravazzolo, Francesco (CAMP Working Paper Series;07/2019, Working paper, 2019-10-12)
      This paper develops a Dynamic Stochastic General Equilibrium (DSGE) model to evaluate the economic repercussions of cryptocurrency. We assume that cryptocurrency offers an alternative currency option to government currency ...
    • 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 ...
    • Are low frequency macroeconomic variables important for high frequency electricity prices? 

      Foroni, Claudia; Ravazzolo, Francesco; Rossini, Luca (Peer reviewed; Journal article, 2023)
      Recent research finds that forecasting electricity prices is very relevant. In many applications, it might be interesting to predict daily electricity prices by using their own lags or renewable energy sources. However, ...
    • A Bayesian DSGE Approach to Modelling Cryptocurrency 

      Asimakopoulos, Stylianos; Lorusso, Marco; Ravazzolo, Francesco (CAMP Working Paper Series;09/2023, Working paper, 2023-09-21)
      We develop and estimate a DSGE model to evaluate the economic repercussions of cryptocurrency. In our model, cryptocurrency offers an alternative currency option to government currency, with endogenous supply and demand. ...
    • Commodity Futures and Forecasting Commodity Currencies 

      Ravazzolo, Francesco; Sveen, Tommy; Zahiri, Sepideh K. (CAMP Working Paper Series;7/2016, Working paper, 2016)
      This paper analyzes the extent to which information in commodity futures markets is useful for out-of-sample forecasting of commodity currencies. In the earlier literature, commodity price changes are documented to be weak ...
    • 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 ...
    • Comparing the forecasting performances of linear models for electricity prices with high RES penetration 

      Gianfreda, Angelica; Ravazzolo, Francesco; Rossini, Luca (Journal article; Peer reviewed, 2020)
      We compare alternative univariate versus multivariate models and frequentist versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, both with and without renewable ...
    • Contagion between real estate and financial markets: A Bayesian quantile-on-quantile approach 

      Caporin, Massimiliano; Gupta, Rangan; Ravazzolo, Francesco (Peer reviewed; Journal article, 2021)
      We study contagion between Real Estate Investment Trusts (REITs) and the equity market in the U.S. over four sub-samples covering January, 2003 to December, 2017, by using Bayesian nonparametric quantile-on-quantile (QQ) ...
    • Density Forecasts with MIDAS Models 

      Aastveit, Knut Are; Foroni, Claudia; Ravazzolo, Francesco (CAMP Working Paper Series;3/2014, Working paper, 2014)
      In this paper we derive a general parametric bootstrapping approach to compute density forecasts for various types of mixed-data sampling (MIDAS) regressions. We consider both classical and unrestricted MIDAS regressions ...
    • Dominant Drivers of National Inflation 

      Ditzen, Jan; Ravazzolo, Francesco (CAMP Working Paper Series;08/2022, Working paper, 2022-12-29)
      For western economies a long-forgotten phenomenon is on the horizon: rising inflation rates. We propose a novel approach christened D2ML to identify drivers of national inflation. D2ML combines machine learning for model ...
    • Fiscal Policy Regimes in Resource-Rich Economies 

      Bjørnland, Hilde C.; Casarin, Roberto; Lorusso, Marco; Ravazzolo, Francesco (CAMP Working Paper Series;13/2023, Working paper, 2023-10-21)
      We analyse fiscal policy in resource-rich economies using a novel Bayesian regime-switching panel model. The identified regimes capture pro- or countercyclical fiscal behaviour, while the switches between the regimes have ...
    • A flexible predictive density combination for large financial data sets in regular and crisis periods 

      Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco; van Dijk, Herman K. (Peer reviewed; Journal article, 2023)
      A flexible predictive density combination is introduced for large financial data sets which allows for model set incompleteness. Dimension reduction procedures that include learning allocate the large sets of predictive ...
    • Forecasting consumer confidence through semantic network analysis of online news 

      Fronzetti Colladon, Andrea; Grippa, Francesca; Guardabascio, Barbara; Costante, Gabriele; Ravazzolo, Francesco (Peer reviewed; Journal article, 2023)
      This research studies the impact of online news on social and economic consumer perceptions through semantic network analysis. Using over 1.8 million online articles on Italian media covering four years, we calculate the ...
    • 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 cryptocurrencies under model and parameter instability 

      Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco (Journal article; Peer reviewed, 2019)
      This paper studies the predictability of cryptocurrency time series. We compare several alternative univariate and multivariate models for point and density forecasting of four of the most capitalized series: Bitcoin, ...
    • Forecasting electricity prices with expert, linear, and nonlinear models 

      Billé, Anna Gloria; Gianfreda, Angelica; Del Grosso, Filippo; Ravazzolo, Francesco (Peer reviewed; Journal article, 2022)
      This paper compares several models for forecasting regional hourly day-ahead electricity prices, while accounting for fundamental drivers. Forecasts of demand, in-feed from renewable energy sources, fossil fuel prices, and ...
    • 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 ...
    • Forecasting energy commodity prices: A large global dataset sparse approach 

      Ferrari, Davide; Ravazzolo, Francesco; Vespignani, Joaquin (Journal article; Peer reviewed, 2021)
      This paper focuses on forecasting quarterly nominal global 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 ...
    • Forecasting financial markets with semantic network analysis in the COVID-19 crisis 

      Fronzetti Colladon, Andrea; Grassi, Stefano; Ravazzolo, Francesco; Violante, Francesco (Peer reviewed; Journal article, 2022)
      This paper uses a new textual data index for predicting stock market data. The index is applied to a large set of news to evaluate the importance of one or more general economic-related keywords appearing in the text. The ...
    • Forecasting GDP with global components. This time is different 

      Bjørnland, Hilde C.; Ravazzolo, Francesco; Thorsrud, Leif Anders (CAMP Working Papers Series;1/2015, Working paper, 2015)
      A long strand of literature has shown that the world has become more global. Yet, the recent Great Global Recession turned out to be hard to predict, with forecasters across the world committing large forecast errors. ...