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Purpose: To examine how various share buyback types affect the immediate stock returns of financial institutions in a cross-country comparison following the COVID-19 pandemic. Methodology: Panel data regression with fixed and random effects models, analyzing stock returns on announcement dates. Control variables include buyback value, market capitalization, and leverage ratio. Theoretical perspec

Since Sweden's historic decision to join NATO in 2022, much attention has been given to the political decision-making process. However, less attention has focused on external influences in the non-political policy analysis. This thesis purpose has therefore been to investigate how Washington-based think tanks contributed to Sweden’s security policy analysis during the NATO accession process be

This thesis investigates whether firms that hedge, specifically against interest rate, currency, or commodity risks, experience a lower cost of capital compared to non-hedging firms. It further explores the firm-specific conditions under which hedging is most effective in reducing financing costs. We develop a custom Python-based model that integrates regular expressions, Natural Language Processi

Purpose: The purpose of this thesis is to investigate the effects of the announcement and implementation of the EU’s Corporate Sustainability Reporting Directive (CSRD) on ESG scores and individual pillar scores of firms. Furthermore, this thesis investigates the impact of firm ESG scores on firm performance. Methodology: This thesis uses Difference-in-Differences and Regression Discontinuity De

This thesis investigates the economic and operational consequences of price-responsive operation of a large-scale alkaline electrolyzer producing hydrogen for fossil-free steel production. A time-resolved linear optimization model was implemented in Python, describing the interaction between a 740 MW electrolyzer (37 units of 20 MW), a hydrogen storage and a constant hydrogen demand. Three operati

Research Aim This thesis explores the role of user-generated content (UGC) in destination marketing, specifically focusing on Harbin, China. It aims to understand how UGC on social media, particularly Douyin, influences Harbin's destination image and the motivations behind content creation. Methodology A mixed-method approach was employed, combining netnography and semi-structured interviews.

With future technologies and Industry 4.0, the need for robust and accurate positioning to optimize productivity and industrial operations increases. The previous positioning methods using triangulation or angle-of-arrival are not good enough, especially not for clutter-dense factories with poor line-of-sight conditions. For this thesis project, a convolutional neural network model was trained t