Now showing items 2049-2068 of 6416

    • 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. ...
    • Forecasting Global Energy Commodity Prices: A Systematic Approach to Forecast Combination 

      Eliassen, Peder; Aag, Ruben (Master thesis, 2024)
      We investigate the accuracy of different forecasts of the global real price of oil and natural gas, on a monthly basis. In particular, we investigate whether combinations of forecasts including newer models are more ...
    • Forecasting Implied Volatility Returns for At-The-Money Currency Options Using Machine Learning 

      Kanavin, Philip Sigurd Risgaard; Hvalbye, William Gunnholt (Master thesis, 2023)
      This paper explores the use of machine learning models to predict what characteristics affect illiquidity in stocks using historical data. The paper uses thirteen different regressions, exploring the effects of 43 ...
    • Forecasting Norwegian Mainland Gross Domestic Product - Using Deep Learning Algorithms 

      Bentsen, Simen; Telkhigov, Akhmed (Master thesis, 2022)
      Gross domestic product is a measure of overall economic activity. It is therefore regarded as one of the most important summary factors for understanding the economic state of a country. Hence, an accurate prediction of ...
    • Forecasting Norwegian Mainland Gross Domestic Product : Using Deep Learning Algorithms 

      Bentsen, Simen; Telkhigov, Akhmed (Master thesis, 2022)
      Gross domestic product is a measure of overall economic activity. It is therefore regarded as one of the most important summary factors for understanding the economic state of a country. Hence, an accurate prediction of ...
    • Forecasting Realized Volatility with Earnings Announcements and Overnight Returns 

      Stadsvik, Sander André Pilskog; Ås, Emil Andre (Master thesis, 2023)
      In our study, we forecast realized volatility utilizing a large panel of stocks from the S&P 500, with the inclusion of overnight returns and earnings announcements. Our comparative analysis employs both the heterogeneous ...
    • Forecasting regional GDPs: a comparison with spatial dynamic panel data models 

      Billé, Anna Gloria; Tomelleri, Alessio; Ravazzolo, Francesco (Peer reviewed; Journal article, 2023)
      The monitoring of the regional (provincial) economic situation is of particular importance due to the high level of heterogeneity and interdependences among different territories. Although econometric models allow for ...
    • Forecasting rental rates for Norwegian commercial real estate 

      Styrvold, Håkon; Nereng, Ketil (Master thesis, 2012-05-14)
      This study seeks to identify key determinants of rents of commercial real estate in Oslo and formulate econometric models capable of describing and predicting their movements. Such a model will improve the precision of ...
    • Forecasting the U.S. Treasury Yield Curve using Targeted Diffusion Indices 

      Piene, Fredrik Bergh; Vedvik, Jan Ove (Master thesis, 2020)
      We investigate possible empirical linkages between variation in the U.S. Treasury yield curve and several measures of economic and financial activity by the methodology targeted diffusion index forecasting. First, we ...
    • Forecasting: An Essential Introduction 

      Thorsrud, Leif Anders (Journal article, 2020)
    • Foreign acquisitions : the end of the Norwegian IT industry? 

      Bjerkeli, David; Klauer, Morten Maurer (Master thesis, 2014-02-11)
      When Norwegian IT companies are sold out of the country it often results in a debate regarding the effects it might have on the industry. There are both skeptics and those that endorse these acquisitions, but to our ...
    • Foreign aid strategies: China taking over? 

      Welle-Strand, Anne; Kjøllesdal, Kristian (Journal article; Peer reviewed, 2010)
      Over the past decade China has emerged as an important source of foreign aid for African countries. Providing aid on terms of its own choosing, China challenges the current foreign aid paradigm in four main ways: ...
    • Foreign Direct Investment and Host Country Industry Development: Insights from Africa 

      Nguyen, Tung Duy; Hestvedt, Christoffer Berg (Master thesis, 2020)
      Based upon African countries and their level of industry development, this study analyzes the impact of host country industry development (HCID) on the survival of FDI. The study consists of a dataset with 1146 observations ...
    • Foreign Direct Investment: A Study of the African Determinants 

      Rosenvinge, Hedvig Marie Scholz; Skavern, Sondre (Master thesis, 2019)
      This thesis explores the determinants of foreign direct investment (FDI) to Sub- Saharan Africa (SSA) compared to other developing regions, with an emphasis on risk. Estimation results from cross-section regressions using ...