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Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach
(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
(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
(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
(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 Implied Volatility Returns for At-The-Money Currency Options Using Machine Learning
(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
(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
(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
(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 rental rates for Norwegian commercial real estate
(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
(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
(Journal article, 2020) -
Foreign acquisitions : the end of the Norwegian IT industry?
(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?
(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
(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
(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 ... -
Foreign operation mode flexibility: tradeoffs and managerial responses
(Peer reviewed; Journal article, 2021)Firms’ ability to change foreign operation modes appears highly desirable in an increasingly volatile and unpredictable global environment. We propose and discuss mode flexibility as a management capability, with the aim ... -
Foreign operations and modes diversity: A study of Norwegian oil field services
(Master thesis, 2017)This study takes a critical look at both how firms configure their foreign operations in the global market place; and the rational for and impediments behind the dynamics of mode configurations. The data analysis draws ... -
Foreign shocks
(CAMP Working Papers Series;11/2015, Working paper, 2015)How and to what extent are small open economies affected by international shocks? I develop and estimate a medium scale DSGE model that addresses both questions. The model incorporates i) international markets for firm-to-firm ... -
Foreign Shocks in an Estimated Multi-Sector Model
(CAMP Working Paper Series;4/2014, Working paper, 2014)How are macroeconomic fluctuations in open economies affected by international business cycles? To shed some light on this question, I develop and estimate a medium scale DSGE model for a small open economy. The model ... -
Foreign versus domestic buy-outs: evidence from returns of private equity
(Master thesis, 2019)This study investigates the differences between foreign- and domestic private equity investments and identifies that factors explain these differences. We used a unique dataset acquired from Bloomberg, analyzing 700 deals ...