Blar i NHH Brage på tittel
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Predicting takeover targets on Oslo stock exchange : an extension to the prediction literature on the Norwegian M&A market
(Master thesis, 2021)The purpose of this research is to extend the previous literature on prediction of takeover targets on Oslo Stock Exchange. We aim to improve the prediction model developed by Khan and Myrholt (2018) by introducing new ... -
Predicting bankruptcy for norwegian firms : a study of Altman’s Z´´-model using alternative ratios
(Master thesis, 2017)In this thesis, we study whether modern accounting ratios based on deductive reasoning and modern financial statements are superior to older, conventional ratios. The focus of this study is to evaluate to what extent ... -
Predicting corporate bond returns in the US bond market via machine learning
(Master thesis, 2022)We perform a comparative analysis of two machine learning methods to predict corporate bond return in the US bond market. In contrast to previous studies, we find that the most influential variables are associated with ... -
Predicting Credit Card Delinquency: A Fundamental Model of Cardholder Financial Behavior
(Doctoral thesis, 2019-11)This thesis proposes a model of credit card customer delinquency based on theoretical advancements in financial decision-making. As follows, this thesis has two main research purposes. First, credit card delinquency is ... -
Predicting default in the Norwegian High Yield bond market : a study of defaults in the years 2006-2013
(Master thesis, 2013)This thesis studies determinants of defaults experienced in the Norwegian High Yield bond market from 2006 to 2013. This is done by finding defaulted issuers from the bonds registered in the Norwegian Trustees database ... -
Predicting defaults in the automotive credit Industry : an empircial study using machine learning techniques predicting loan defaults
(Master thesis, 2020)This master thesis explore the potential of Machine Learning techniques in predicting default of vehicle loan applicants. Usually, banks or other financial institutions utilize the Logistic Regression algorithm to support ... -
Predicting financial distress in Norway : using logistic regression and random forest models
(Master thesis, 2019)Financial distress can be a highly costly and disruptive event, both on the level of the firm as well as for the society. Models to predict financial distress for this reason have been beneficial. In this thesis, we aim ... -
Predicting housing prices with machine learning : a macroeconomic analysis of the Norwegian housing market
(Master thesis, 2020)This thesis explores the applicability of machine learning in macroeconomic housing price predictions in Norway. We apply three machine learning models Elastic Net, Random Forest and Neural Network on historical time-time ... -
Predicting Norwegian takeover targets : an empirical analysis of the Norwegian M&A market
(Master thesis, 2018)The prediction of takeover targets has been covered in several studies. However, it tends to be the same major stock exchanges that are subject to analysis. Based on 153 Norwegian public targets from 1995 to 2012, ... -
Predicting patent litigation : a comprehensive comparison of machine learning algorithm performance in predicting patent litigation
(Master thesis, 2020)Patents are designed to act as an incentive for innovation by awarding exclusive property rights to the inventor. And as such, patents are one of the main driving forces behind innovation, and ultimately economic growth ... -
Predicting private equity enterprise multiples using coarsened exact matching
(Master thesis, 2021)This thesis investigates if it is possible to predict accurate and unbiased Net Asset Values for private equity (PE) portfolio companies using multiple valuation. The study is motivated by PE research that has found that ... -
Predicting Private Equity Fund Performance with Machine Learning
(Master thesis, 2022)This paper has the objective of applying machine learning models to predict the performance of private equity funds, to allow for more effective fund selection for investors in the private markets. Prior research has ... -
Predicting salmon futures returns : an empirical study from 2007 to 2019
(Master thesis, 2019)In order to investigate the factors that influence the return of salmon futures, we construct a fully hedged, passive, front month rolling portfolio of long positions in these contracts. We show that the excess return ... -
Predicting shipping defaults : an empirical study of the driving forces of default in the shipping industry
(Master thesis, 2020)This study empirically investigates the driving forces of default at the time of issue in the shipping industry. By developing a logit model based on a sample of 64 shipping bonds and loans, it is shown that the most ... -
Predicting spreads in the Nordic high yield bond market : a study of credit pricing in the years 2000-2012
(Master thesis, 2015)The main objective of this thesis is to identify and measure explanatory factors of observed credit spreads in the Nordic corporate high yield bond market in the period 2000 – 2012. From literature on credit pricing, we ... -
Predicting success in early-stage venture capital investment
(Master thesis, 2019)In this thesis, I examine predictors of early-stage success (ESS) for early-stage venture capital (ESVC) investments, observable at the point of initial investment. I use a self-collected sample of 30 Norwegian portfolio ... -
Predicting the impact of academic articles on marketing research: Using machine learning to predict highly cited marketing articles
(Master thesis, 2022)The citation count of an academic article is of great importance to researchers and readers. Due to the large increase in the publication of academic articles every year, it may be difficult to recognize the articles ... -
Prediction of Stock Market Volatility Utilizing Sentiment from News and Social Media Texts : A study on the practical implementation of sentiment analysis and deep learning models for predicting day-ahead volatility
(Master thesis, 2022)This thesis studies the impact of sentiment on the prediction of volatility for 100 of the largest stocks in the S&P500 index. The purpose is to find out if sentiment can improve the forecast of day-ahead volatility ... -
Predictive modelling of customer claims across multiple insurance policies : an empirical study of how individual customer insurance data can be used to assess customer risk across multiple insurance products by employing machine learning and advanced ensemble techniques
(Master thesis, 2020)In this master thesis, we have analysed how individual insurance customer data can be used to assess customer risk across multiple insurance policies. Our dataset contains 63 variables about the characteristics of each ... -
Predictive power of AIS on marine insurance : a demonstration of how activity level and operational patterns of the merchant fleet can be used to predict P&I insurance claims using machine learning
(Master thesis, 2018)Digitalisation is making a growing appearance across all sectors, and traditional P&I insurance is no exception. Marine insurance is said to be several years behind traditional land-based insurance when it comes to ...